Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: Application to a smoking cessation trial

PubMed Central

Siddique, Juned; Harel, Ofer; Crespi, Catherine M.; Hedeker, Donald

2014-01-01

The true missing data mechanism is never known in practice. We present a method for generating multiple imputations for binary variables that formally incorporates missing data mechanism uncertainty. Imputations are generated from a distribution of imputation models rather than a single model, with the distribution reflecting subjective notions of missing data mechanism uncertainty. Parameter estimates and standard errors are obtained using rules for nested multiple imputation. Using simulation, we investigate the impact of missing data mechanism uncertainty on post-imputation inferences and show that incorporating this uncertainty can increase the coverage of parameter estimates. We apply our method to a longitudinal smoking cessation trial where nonignorably missing data were a concern. Our method provides a simple approach for formalizing subjective notions regarding nonresponse and can be implemented using existing imputation software. PMID:24634315

A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.

PubMed

Ambler, Gareth; Omar, Rumana Z; Royston, Patrick

2007-06-01

Risk models that aim to predict the future course and outcome of disease processes are increasingly used in health research, and it is important that they are accurate and reliable. Most of these risk models are fitted using routinely collected data in hospitals or general practices. Clinical outcomes such as short-term mortality will be near-complete, but many of the predictors may have missing values. A common approach to dealing with this is to perform a complete-case analysis. However, this may lead to overfitted models and biased estimates if entire patient subgroups are excluded. The aim of this paper is to investigate a number of methods for imputing missing data to evaluate their effect on risk model estimation and the reliability of the predictions. Multiple imputation methods, including hotdecking and multiple imputation by chained equations (MICE), were investigated along with several single imputation methods. A large national cardiac surgery database was used to create simulated yet realistic datasets. The results suggest that complete case analysis may produce unreliable risk predictions and should be avoided. Conditional mean imputation performed well in our scenario, but may not be appropriate if using variable selection methods. MICE was amongst the best performing multiple imputation methods with regards to the quality of the predictions. Additionally, it produced the least biased estimates, with good coverage, and hence is recommended for use in practice.

The True Ultracool Binary Fraction Using Spectral Binaries

NASA Astrophysics Data System (ADS)

Bardalez Gagliuffi, Daniella; Burgasser, Adam J.; Schmidt, Sarah J.; Gagné, Jonathan; Faherty, Jacqueline K.; Cruz, Kelle; Gelino, Chris

2018-01-01

Brown dwarfs bridge the gap between stars and giant planets. While the essential mechanisms governing their formation are not well constrained, binary statistics are a direct outcome of the formation process, and thus provide a means to test formation theories. Observational constraints on the brown dwarf binary fraction place it at 10 ‑ 20%, dominated by imaging studies (85% of systems) with the most common separation at 4 AU. This coincides with the resolution limit of state-of-the-art imaging techniques, suggesting that the binary fraction is underestimated. We have developed a separation-independent method to identify and characterize tightly-separated (< 5 AU) binary systems of brown dwarfs as spectral binaries by identifying traces of methane in the spectra of late-M and early-L dwarfs. Imaging follow-up of 17 spectral binaries yielded 3 (18%) resolved systems, corroborating the observed binary fraction, but 5 (29%) known binaries were missed, reinforcing the hypothesis that the short-separation systems are undercounted. In order to find the true binary fraction of brown dwarfs, we have compiled a volume-limited, spectroscopic sample of M7-L5 dwarfs and searched for T dwarf companions. In the 25 pc volume, 4 candidates were found, three of which are already confirmed, leading to a spectral binary fraction of 0.95 ± 0.50%, albeit for a specific combination of spectral types. To extract the true binary fraction and determine the biases of the spectral binary method, we have produced a binary population simulation based on different assumptions of the mass function, age distribution, evolutionary models and mass ratio distribution. Applying the correction fraction resulting from this method to the observed spectral binary fraction yields a true binary fraction of 27 ± 4%, which is roughly within 1σ of the binary fraction obtained from high resolution imaging studies, radial velocity and astrometric monitoring. This method can be extended to identify giant planet companions to young brown dwarfs.

Stochastic model search with binary outcomes for genome-wide association studies.

PubMed

Russu, Alberto; Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-06-01

The spread of case-control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model.

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

PubMed

Chan, Jennifer S K

2016-05-01

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stochastic model search with binary outcomes for genome-wide association studies

PubMed Central

Malovini, Alberto; Puca, Annibale A; Bellazzi, Riccardo

2012-01-01

Objective The spread of case–control genome-wide association studies (GWASs) has stimulated the development of new variable selection methods and predictive models. We introduce a novel Bayesian model search algorithm, Binary Outcome Stochastic Search (BOSS), which addresses the model selection problem when the number of predictors far exceeds the number of binary responses. Materials and methods Our method is based on a latent variable model that links the observed outcomes to the underlying genetic variables. A Markov Chain Monte Carlo approach is used for model search and to evaluate the posterior probability of each predictor. Results BOSS is compared with three established methods (stepwise regression, logistic lasso, and elastic net) in a simulated benchmark. Two real case studies are also investigated: a GWAS on the genetic bases of longevity, and the type 2 diabetes study from the Wellcome Trust Case Control Consortium. Simulations show that BOSS achieves higher precisions than the reference methods while preserving good recall rates. In both experimental studies, BOSS successfully detects genetic polymorphisms previously reported to be associated with the analyzed phenotypes. Discussion BOSS outperforms the other methods in terms of F-measure on simulated data. In the two real studies, BOSS successfully detects biologically relevant features, some of which are missed by univariate analysis and the three reference techniques. Conclusion The proposed algorithm is an advance in the methodology for model selection with a large number of features. Our simulated and experimental results showed that BOSS proves effective in detecting relevant markers while providing a parsimonious model. PMID:22534080

An archival analysis of stall warning system effectiveness during airborne icing encounters

NASA Astrophysics Data System (ADS)

Maris, John Michael

An archival study was conducted to determine the influence of stall warning system performance on aircrew decision-making outcomes during airborne icing encounters. A Conservative Icing Response Bias (CIRB) model was developed to explain the historical variability in aircrew performance in the face of airframe icing. The model combined Bayes' Theorem with Signal Detection Theory (SDT) concepts to yield testable predictions that were evaluated using a Binary Logistic Regression (BLR) multivariate technique applied to two archives: the NASA Aviation Safety Reporting System (ASRS) incident database, and the National Transportation Safety Board (NTSB) accident databases, both covering the period January 1, 1988 to October 2, 2015. The CIRB model predicted that aircrew would experience more incorrect response outcomes in the face of missed stall warnings than with stall warning False Alarms. These predicted outcomes were observed at high significance levels in the final sample of 132 NASA/NTSB cases. The CIRB model had high sensitivity and specificity, and explained 71.5% (Nagelkerke R2) of the variance of aircrew decision-making outcomes during the icing encounters. The reliability and validity metrics derived from this study suggest indicate that the findings are generalizable to the population of U.S. registered turbine-powered aircraft. These findings suggest that icing-related stall events could be reduced if the incidence of stall warning Misses could be minimized. Observed stall warning Misses stemmed from three principal causes: aerodynamic icing effects, which reduced the stall angle-of-attack (AoA) to below the stall warning calibration threshold; tail stalls, which are not monitored by contemporary protection systems; and icing-induced system issues (such as frozen pitot tubes), which compromised stall warning system effectiveness and airframe envelope protections. Each of these sources of missed stall warnings could be addressed by Aerodynamic Performance Monitoring (APM) systems that directly measure the boundary layer airflow adjacent to the affected aerodynamic surfaces, independent of other aircraft stall protection, air data, and AoA systems. In addition to investigating APM systems, measures should also be taken to include the CIRB phenomenon in aircrew training to better prepare crews to cope with airborne icing encounters. The SDT/BLR technique would allow the forecast gains from these improved systems and training processes to be evaluated objectively and quantitatively. The SDT/BLR model developed for this study has broad application outside the realm of airborne icing. The SDT technique has been extensively validated by prior research, and the BLR is a very robust multivariate technique. Combined, they could be applied to evaluate high order constructs (such as stall awareness for this study), in complex and dynamic environments. The union of SDT and BLR reduces the modeling complexities for each variable into the four binary SDT categories of Hit, Miss, False Alarm, and Correct Rejection, which is the optimum format for the BLR. Despite this reductionist approach to complex situations, the method has demonstrated very high statistical and practical significance, as well as excellent predictive power, when applied to the airborne icing scenario.

Binary pulsar evolution: unveiled links and new species

NASA Astrophysics Data System (ADS)

Possenti, Andrea

2013-03-01

In the last years a series of blind and/or targeted pulsar searches led to almost triple the number of known binary pulsars in the galactic field with respect to a decade ago. The focus will be on few outliers, which are emerging from the average properties of the enlarged binary pulsar population. Some of them may represent the long sought missing links between two kinds of neutron star binaries, while others could represent the stereotype of new groups of binaries, resulting from an evolutionary path which is more exotic than those considered until recently. In particular, a new class of binaries, which can be dubbed Ultra Low Mass Binary Pulsars (ULMBPs), is emerging from recent data.

High statistical heterogeneity is more frequent in meta-analysis of continuous than binary outcomes.

PubMed

Alba, Ana C; Alexander, Paul E; Chang, Joanne; MacIsaac, John; DeFry, Samantha; Guyatt, Gordon H

2016-02-01

We compared the distribution of heterogeneity in meta-analyses of binary and continuous outcomes. We searched citations in MEDLINE and Cochrane databases for meta-analyses of randomized trials published in 2012 that reported a measure of heterogeneity of either binary or continuous outcomes. Two reviewers independently performed eligibility screening and data abstraction. We evaluated the distribution of I(2) in meta-analyses of binary and continuous outcomes and explored hypotheses explaining the difference in distributions. After full-text screening, we selected 671 meta-analyses evaluating 557 binary and 352 continuous outcomes. Heterogeneity as assessed by I(2) proved higher in continuous than in binary outcomes: the proportion of continuous and binary outcomes reporting an I(2) of 0% was 34% vs. 52%, respectively, and reporting an I(2) of 60-100% was 39% vs. 14%. In continuous but not binary outcomes, I(2) increased with larger number of studies included in a meta-analysis. Increased precision and sample size do not explain the larger I(2) found in meta-analyses of continuous outcomes with a larger number of studies. Meta-analyses evaluating continuous outcomes showed substantially higher I(2) than meta-analyses of binary outcomes. Results suggest differing standards for interpreting I(2) in continuous vs. binary outcomes may be appropriate. Copyright © 2016 Elsevier Inc. All rights reserved.

Suicides by persons reported as missing prior to death: a retrospective cohort study

PubMed Central

Sveticic, Jerneja; Too, Lay San

2012-01-01

Objective A first study to compare suicides by missing persons with other suicide cases. Design Retrospective cohort study for the period 1994–2007. Geographical location Queensland, Australia. Population 194 suicides by missing persons and 7545 other suicides were identified through the Queensland Suicide Register and the National Coroners Information System. Main outcome measure χ2 statistics and binary logistic regression were used to identify distinct characteristics of suicides by missing persons. Results Compared with other suicide cases, missing persons significantly more often died by motor vehicle exhaust gas toxicity (23.7% vs 16.4%; χ2=7.32, p<0.01), jumping from height (6.7% vs 3.2%; χ2=7.08, p<0.01) or drowning (8.2% vs 1.8%; χ2=39.53, p<0.01), but less frequently by hanging (29.4% vs 39.9%; χ2=8.82, p<0.01). They were most frequently located in natural outdoors locations (58.2% vs 11.1%; χ2=388.25, p<0.01). Persons gone missing were less likely to have lived alone at time of death (OR 0.45, 95% CI 0.26 to 0.76), yet more likely to be institutionalised (OR 3.12, 95% CI 1.28 to 7.64). They were less likely to have been physically ill (OR 0.64, 95% CI 0.43 to 0.95) or have a history of problematic consumptions of alcohol (OR 0.52, 95% CI 0.31 to 0.87). In comparison to other suicide cases, missing persons more often communicated their suicidal intent prior to death (OR 1.58, 95% CI 1.13 to 2.22). Conclusions Suicides by missing persons show several distinct characteristics in comparisons to other suicides. The findings have implications for development of suicide prevention strategies focusing on early identification and interventions targeting this group. In particular, it may offer assistance to police in designing risk assessment procedures and subsequent investigations of missing persons. PMID:22454187

A comparison of multiple imputation methods for incomplete longitudinal binary data.

PubMed

Yamaguchi, Yusuke; Misumi, Toshihiro; Maruo, Kazushi

2018-01-01

Longitudinal binary data are commonly encountered in clinical trials. Multiple imputation is an approach for getting a valid estimation of treatment effects under an assumption of missing at random mechanism. Although there are a variety of multiple imputation methods for the longitudinal binary data, a limited number of researches have reported on relative performances of the methods. Moreover, when focusing on the treatment effect throughout a period that has often been used in clinical evaluations of specific disease areas, no definite investigations comparing the methods have been available. We conducted an extensive simulation study to examine comparative performances of six multiple imputation methods available in the SAS MI procedure for longitudinal binary data, where two endpoints of responder rates at a specified time point and throughout a period were assessed. The simulation study suggested that results from naive approaches of a single imputation with non-responders and a complete case analysis could be very sensitive against missing data. The multiple imputation methods using a monotone method and a full conditional specification with a logistic regression imputation model were recommended for obtaining unbiased and robust estimations of the treatment effect. The methods were illustrated with data from a mental health research.

Considerations of multiple imputation approaches for handling missing data in clinical trials.

PubMed

Quan, Hui; Qi, Li; Luo, Xiaodong; Darchy, Loic

2018-07-01

Missing data exist in all clinical trials and missing data issue is a very serious issue in terms of the interpretability of the trial results. There is no universally applicable solution for all missing data problems. Methods used for handling missing data issue depend on the circumstances particularly the assumptions on missing data mechanisms. In recent years, if the missing at random mechanism cannot be assumed, conservative approaches such as the control-based and returning to baseline multiple imputation approaches are applied for dealing with the missing data issues. In this paper, we focus on the variability in data analysis of these approaches. As demonstrated by examples, the choice of the variability can impact the conclusion of the analysis. Besides the methods for continuous endpoints, we also discuss methods for binary and time to event endpoints as well as consideration for non-inferiority assessment. Copyright © 2018. Published by Elsevier Inc.

PHYSICS OF ECLIPSING BINARIES. II. TOWARD THE INCREASED MODEL FIDELITY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prša, A.; Conroy, K. E.; Horvat, M.

The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures, and luminosities), yet the models are not capable of reproducing observed data well, either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but weremore » not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs; http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light travel time effects, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes the photon-weighted mode, the enhanced limb darkening treatment, the better reflection treatment, and Doppler boosting. Here we present the concepts on which PHOEBE is built and proofs of concept that demonstrate the increased model fidelity.« less

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Reporting and handling missing outcome data in mental health: a systematic review of Cochrane systematic reviews and meta-analyses.

PubMed

Spineli, Loukia M; Pandis, Nikolaos; Salanti, Georgia

2015-06-01

The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal. Copyright © 2014 John Wiley & Sons, Ltd.

OGLE-2017-BLG-1130: The First Binary Gravitational Microlens Detected from Spitzer Only

NASA Astrophysics Data System (ADS)

Wang, Tianshu; Calchi Novati, S.; Udalski, A.; Gould, A.; Mao, Shude; Zang, W.; Beichman, C.; Bryden, G.; Carey, S.; Gaudi, B. S.; Henderson, C. B.; Shvartzvald, Y.; Yee, J. C.; Spitzer Team; Mróz, P.; Poleski, R.; Skowron, J.; Szymański, M. K.; Soszyński, I.; Kozłowski, S.; Pietrukowicz, P.; Ulaczyk, K.; Pawlak, M.; OGLE Collaboration; Albrow, M. D.; Chung, S.-J.; Han, C.; Hwang, K.-H.; Jung, Y. K.; Ryu, Y.-H.; Shin, I.-G.; Zhu, W.; Cha, S.-M.; Kim, D.-J.; Kim, H.-W.; Kim, S.-L.; Lee, C.-U.; Lee, D.-J.; Lee, Y.; Park, B.-G.; Pogge, R. W.; KMTNet Collaboration

2018-06-01

We analyze the binary gravitational microlensing event OGLE-2017-BLG-1130 (mass ratio q ∼ 0.45), the first published case in which the binary anomaly was detected only by the Spitzer Space Telescope. This event provides strong evidence that some binary signals can be missed by observations from the ground alone but detected by Spitzer. We therefore invert the normal procedure, first finding the lens parameters by fitting the space-based data and then measuring the microlensing parallax using ground-based observations. We also show that the normal four-fold space-based degeneracy in the single-lens case can become a weak eight-fold degeneracy in binary-lens events. Although this degeneracy is resolved in event OGLE-2017-BLG-1130, it might persist in other events.

[Near miss outcomes in gambling games].

PubMed

Pecsenye, Zsuzsa; Kurucz, Gyozo

2017-01-01

Games of chance operate with an intermittent reinforcement schedule in which the number of games takes the player to win differ in each turn thus they can not predict when the next positive reinforcement arrives. The near miss outcome (close to winning but actually a losing outcome) can be interpreted as a secondary (built in) reinforcement within variable ratio reinforcement schedule that presumably contribute to the development and maintanance of gambling addiction. The aim of this publication would be to introduce near miss outcomes and to summarize and critically analyze literature connected to this issue.We searched internet datebases using word "near miss" and analyse articles focusing on gambling games. Based on numerous authors' results a near miss rate set at around 30% increases the desire to continue playing among gamblers and players who have no former gambling experience as well. Some studies have demonstrated that this effect might be related to the extent the player has the situation under control during the gambling session. The hypothetical inhibiting effect of a 45% near miss ratio has not yet been proven. Neurobiological researches show middle-cerebral activity during near miss outcomes furthermore similar physiological patterns have been discovered following a near miss and winning outcomes. Regarding the connection between intrapsychic variables (cognitive and personality factors) and near misses there are very few studies. The fact that different authors interpret near miss outcomes differently even when studying the same game leads to problems in interpreting their results. It follows from the foregoing empirical results that near miss outcomes contribute to the development and maintanance of pathological gambling but we have little information on the factors implementing this effect.

The Candy Crush Sweet Tooth: How 'Near-misses' in Candy Crush Increase Frustration, and the Urge to Continue Gameplay.

PubMed

Larche, Chanel J; Musielak, Natalia; Dixon, Mike J

2017-06-01

Like many gambling games, the exceedingly popular and lucrative smartphone game "Candy Crush" features near-miss outcomes. In slot machines, a near-miss involves getting two of the needed three high-paying symbols on the pay-line (i.e., just missing the big win). In Candy Crush, the game signals when you just miss getting to the next level by one or two moves. Because near-misses in gambling games have consistently been shown to invigorate play despite being frustrating outcomes, the goal of the present study was to examine whether such near-misses trigger increases in player arousal, frustration and urge to continue play in Candy Crush. Sixty avid Candy Crush players were recruited to play the game for 30 min while having their Heart Rate, Skin Conductance Level, subjective arousal, frustration and urge to play recorded for three types of outcomes: wins (where they level up), losses (where they don't come close to levelling up), and near-misses (where they just miss levelling up). Near-misses were more arousing than losses as indexed by increased heart rate and greater subjective arousal. Near-misses were also subjectively rated as the most frustrating of all outcomes. Most importantly, of any type of outcome, near-misses triggered the most substantial urge to continue play. These findings suggest that near-misses in Candy Crush play a role in player commitment to the game, and may contribute to players playing longer than intended.

A repeated measures model for analysis of continuous outcomes in sequential parallel comparison design studies.

PubMed

Doros, Gheorghe; Pencina, Michael; Rybin, Denis; Meisner, Allison; Fava, Maurizio

2013-07-20

Previous authors have proposed the sequential parallel comparison design (SPCD) to address the issue of high placebo response rate in clinical trials. The original use of SPCD focused on binary outcomes, but recent use has since been extended to continuous outcomes that arise more naturally in many fields, including psychiatry. Analytic methods proposed to date for analysis of SPCD trial continuous data included methods based on seemingly unrelated regression and ordinary least squares. Here, we propose a repeated measures linear model that uses all outcome data collected in the trial and accounts for data that are missing at random. An appropriate contrast formulated after the model has been fit can be used to test the primary hypothesis of no difference in treatment effects between study arms. Our extensive simulations show that when compared with the other methods, our approach preserves the type I error even for small sample sizes and offers adequate power and the smallest mean squared error under a wide variety of assumptions. We recommend consideration of our approach for analysis of data coming from SPCD trials. Copyright © 2013 John Wiley & Sons, Ltd.

Observation of Stronger-than-Binary Correlations with Entangled Photonic Qutrits

NASA Astrophysics Data System (ADS)

Hu, Xiao-Min; Liu, Bi-Heng; Guo, Yu; Xiang, Guo-Yong; Huang, Yun-Feng; Li, Chuan-Feng; Guo, Guang-Can; Kleinmann, Matthias; Vértesi, Tamás; Cabello, Adán

2018-05-01

We present the first experimental confirmation of the quantum-mechanical prediction of stronger-than-binary correlations. These are correlations that cannot be explained under the assumption that the occurrence of a particular outcome of an n ≥3 -outcome measurement is due to a two-step process in which, in the first step, some classical mechanism precludes n -2 of the outcomes and, in the second step, a binary measurement generates the outcome. Our experiment uses pairs of photonic qutrits distributed between two laboratories, where randomly chosen three-outcome measurements are performed. We report a violation by 9.3 standard deviations of the optimal inequality for nonsignaling binary correlations.

The Orientation of Eta Carinae and the Powering Mechanism of Intermediate-luminosity Optical Transients (ILOTS)

NASA Astrophysics Data System (ADS)

Kashi, Amit; Soker, Noam

2018-05-01

Contrary to recent claims, we argue that the orientation of the massive binary system Eta Carinae is such that the secondary star is closer to us at periastron passage, and it is on the far side during most of the time of the eccentric orbit. The binary orientation we dispute is based on problematic interpretations of recent observations. Among these are the radial velocity of the absorption component of He I P-Cyg lines, of the He II λ4686 emission line, and of the Br γ line emitted by clumps close to the binary system. We also base our orientation on observations of asymmetric molecular clumps that were recently observed by ALMA around the binary system, and were claimed to compose a torus with a missing segment. The orientation has implications for the modeling of the binary interaction during the nineteenth century Great Eruption (GE) of Eta Carinae that occurred close to periastron passage. The orientation where the secondary is closer to us at periastron leads us to suggest that the mass-missing side of the molecular clumps is a result of accretion onto the secondary star during periastron passage when the clumps were ejected, probably during the GE. The secondary star accreted a few solar masses during the GE and the energy from the accretion process consists of the majority of the GE energy. This in turn strengthens the more general model according to which many intermediate-luminosity optical transients (ILOTS) are powered by accretion onto a secondary star.

Gravitational waves from binary supermassive black holes missing in pulsar observations.

PubMed

Shannon, R M; Ravi, V; Lentati, L T; Lasky, P D; Hobbs, G; Kerr, M; Manchester, R N; Coles, W A; Levin, Y; Bailes, M; Bhat, N D R; Burke-Spolaor, S; Dai, S; Keith, M J; Osłowski, S; Reardon, D J; van Straten, W; Toomey, L; Wang, J-B; Wen, L; Wyithe, J S B; Zhu, X-J

2015-09-25

Gravitational waves are expected to be radiated by supermassive black hole binaries formed during galaxy mergers. A stochastic superposition of gravitational waves from all such binary systems would modulate the arrival times of pulses from radio pulsars. Using observations of millisecond pulsars obtained with the Parkes radio telescope, we constrained the characteristic amplitude of this background, A(c,yr), to be <1.0 × 10(-15) with 95% confidence. This limit excludes predicted ranges for A(c,yr) from current models with 91 to 99.7% probability. We conclude that binary evolution is either stalled or dramatically accelerated by galactic-center environments and that higher-cadence and shorter-wavelength observations would be more sensitive to gravitational waves. Copyright © 2015, American Association for the Advancement of Science.

Missed doses of oral antihyperglycemic medications in US adults with type 2 diabetes mellitus: prevalence and self-reported reasons.

PubMed

Vietri, Jeffrey T; Wlodarczyk, Catherine S; Lorenzo, Rose; Rajpathak, Swapnil

2016-09-01

Adherence to antihyperglycemic medication is thought to be suboptimal, but the proportion of patients missing doses, the number of doses missed, and reasons for missing are not well described. This survey was conducted to estimate the prevalence of and reasons for missed doses of oral antihyperglycemic medications among US adults with type 2 diabetes mellitus, and to explore associations between missed doses and health outcomes. The study was a cross-sectional patient survey. Respondents were contacted via a commercial survey panel and completed an on-line questionnaire via the Internet. Respondents provided information about their use of oral antihyperglycemic medications including doses missed in the prior 4 weeks, personal characteristics, and health outcomes. Weights were calculated to project the prevalence to the US adult population with type 2 diabetes mellitus. Outcomes were compared according to number of doses missed in the past 4 weeks using bivariate statistics and generalized linear models. Approximately 30% of adult patients with type 2 diabetes mellitus reported missing or reducing ≥1 dose of oral antihyperglycemic medication in the prior 4 weeks. Accidental missing was more commonly reported than purposeful skipping, with forgetting the most commonly reported reason. The timing of missed doses suggested respondents had also forgotten about doses missed, so the prevalence of missed doses is likely higher than reported. Outcomes were poorer among those who reported missing three or more doses in the prior 4 weeks. A substantial number of US adults with type 2 diabetes mellitus miss doses of their oral antihyperglycemic medications.

Missing data frequency and correlates in two randomized surgical trials for urinary incontinence in women.

PubMed

Brubaker, Linda; Litman, Heather J; Kim, Hae-Young; Zimmern, Philippe; Dyer, Keisha; Kusek, John W; Richter, Holly E; Stoddard, Anne

2015-08-01

Missing data is frequently observed in clinical trials; high rates of missing data may jeopardize trial outcome validity. We determined the rates of missing data over time, by type of data collected and compared demographic and clinical factors associated with missing data among women who participated in two large randomized clinical trials of surgery for stress urinary incontinence, the Stress Incontinence Surgical Treatment Efficacy Trial (SISTEr) and the Trial of Midurethral Sling (TOMUS). The proportions of subjects who attended and missed each follow-up visit were calculated. The chi-squared test, Fisher's exact test and t test were used to compare women with and without missing data, as well as the completeness of the data for each component of the composite primary outcome. Data completeness for the primary outcome computation in the TOMUS trial (62.3%) was nearly double that in the SISTEr trial (35.7%). The follow-up visit attendance rate decreased over time. A higher proportion of subjects attended all follow-up visits in the TOMUS trial and overall there were fewer missing data for the period that included the primary outcome assessment at 12 months. The highest levels of complete data for the composite outcome variables were for the symptoms questionnaire (SISTEr 100 %, TOMUS 99.8%) and the urinary stress test (SISTEr 96.1%, TOMUS 96.7%). In both studies, the pad test was associated with the lowest levels of complete data (SISTEr 85.1%, TOMUS 88.3%) and approximately one in ten subjects had incomplete voiding diaries at the time of primary outcome assessment. Generally, in both studies, a higher proportion of younger subjects had missing data. This analysis lacked a patient perspective as to the reasons for missing data that could have provided additional information on subject burden, motivations for adherence and study design. In addition, we were unable to compare the effects of the different primary outcome assessment time-points in an identically designed trial. Missing visits and data increased with time. Questionnaire data and physical outcome data (urinary stress test) that could be assessed during a visit were least prone to missing data, whereas data for variables that required subject effort while away from the research team (pad test, voiding diary) were more likely to be missing. Older subjects were more likely to provide complete data.

Does Missed Care in Isolated Rural Hospitals Matter?

PubMed

Smith, Jessica G

2018-06-01

Missed care is associated with adverse outcomes such as patient falls and decreased nurse job satisfaction. Although studied in populations of interest such as neonates, children, and heart failure patients, there are no studies about missed care in rural hospitals. Reducing care omissions in rural hospitals might help improve rural patient outcomes and ensure that rural hospitals can remain open in an era of hospital reimbursement dependent on care outcomes, such as through value-based purchasing. Understanding the extent of missed nursing care and its implications for rural populations might provide crucial information to alert rural hospital administrators and nurses about the incidence and influence of missed care on health outcomes. Focusing on missed care within rural hospitals and other rural health care settings is important to address the specific health needs of aging rural U.S. residents who are isolated from high-volume, urban health care facilities.

Probability genotype imputation method and integrated weighted lasso for QTL identification.

PubMed

Demetrashvili, Nino; Van den Heuvel, Edwin R; Wit, Ernst C

2013-12-30

Many QTL studies have two common features: (1) often there is missing marker information, (2) among many markers involved in the biological process only a few are causal. In statistics, the second issue falls under the headings "sparsity" and "causal inference". The goal of this work is to develop a two-step statistical methodology for QTL mapping for markers with binary genotypes. The first step introduces a novel imputation method for missing genotypes. Outcomes of the proposed imputation method are probabilities which serve as weights to the second step, namely in weighted lasso. The sparse phenotype inference is employed to select a set of predictive markers for the trait of interest. Simulation studies validate the proposed methodology under a wide range of realistic settings. Furthermore, the methodology outperforms alternative imputation and variable selection methods in such studies. The methodology was applied to an Arabidopsis experiment, containing 69 markers for 165 recombinant inbred lines of a F8 generation. The results confirm previously identified regions, however several new markers are also found. On the basis of the inferred ROC behavior these markers show good potential for being real, especially for the germination trait Gmax. Our imputation method shows higher accuracy in terms of sensitivity and specificity compared to alternative imputation method. Also, the proposed weighted lasso outperforms commonly practiced multiple regression as well as the traditional lasso and adaptive lasso with three weighting schemes. This means that under realistic missing data settings this methodology can be used for QTL identification.

Prognostic indicators of poor short-term outcome of physiotherapy intervention in women with stress urinary incontinence.

PubMed

Hendriks, Erik J M; Kessels, Alfons G H; de Vet, Henrica C W; Bernards, Arnold T M; de Bie, Rob A

2010-03-01

To identify prognostic indicators independently associated with poor outcome of physiotherapy intervention in women with primary or recurrent stress urinary incontinence (stress UI). A prospective cohort study was performed in physiotherapy practices in primary care to identify prognostic indicators 12 weeks after initiation of physiotherapy intervention. Patients were referred by general practitioners or urogynecologists. Risk factors for stress UI were examined as potential prognostic indicators of poor outcome. The primary outcomes were defined as poor outcome on the binary Leakage Severity scale (LS scale) and the binary global perceived effectiveness (GPE) score. Two hundred sixty-seven women, with a mean age of 47.7 (SD = 8.3), with stress UI for at least 6 months were included. At 12 weeks, 43% and 59% of the women were considered recovered on the binary LS scale and the binary GPE score, respectively. Prognostic indicators associated with poor outcome included 11 indicators based on the binary LS scale and 8 based on the binary GPE score. The prognostic indicators shared by both models show that poor recovery was associated with women with severe stress UI, POP-Q stage > II, poor outcome of physiotherapy intervention for a previous UI episode, prolonged second stage of labor, BMI > 30, high psychological distress, and poor physical health. This study provides robust evidence of clinically meaningful prognostic indicators of poor short-term outcome. These findings need to be confirmed by replication studies. (c) 2009 Wiley-Liss, Inc.

Systematic reviews do not adequately report or address missing outcome data in their analyses: a methodological survey.

PubMed

Kahale, Lara A; Diab, Batoul; Brignardello-Petersen, Romina; Agarwal, Arnav; Mustafa, Reem A; Kwong, Joey; Neumann, Ignacio; Li, Ling; Lopes, Luciane Cruz; Briel, Matthias; Busse, Jason W; Iorio, Alfonso; Vandvik, Per Olav; Alexander, Paul Elias; Guyatt, Gordon; Akl, Elie A

2018-07-01

To describe how systematic review authors report and address categories of participants with potential missing outcome data of trial participants. Methodological survey of systematic reviews reporting a group-level meta-analysis. We included a random sample of 50 Cochrane and 50 non-Cochrane systematic reviews. Of these, 25 reported in their methods section a plan to consider at least one of the 10 categories of missing outcome data; 42 reported in their results, data for at least one category of missing data. The most reported category in the methods and results sections was "unexplained loss to follow-up" (n = 34 in methods section and n = 6 in the results section). Only 19 reported a method to handle missing data in their primary analyses, which was most often complete case analysis. Few reviews (n = 9) reported in the methods section conducting sensitivity analysis to judge risk of bias associated with missing outcome data at the level of the meta-analysis; and only five of them presented the results of these analyses in the results section. Most systematic reviews do not explicitly report sufficient information on categories of trial participants with potential missing outcome data or address missing data in their primary analyses. Copyright © 2018 Elsevier Inc. All rights reserved.

Increased Urge to Gamble Following Near-Miss Outcomes May Drive Purchasing Behaviour in Scratch Card Gambling.

PubMed

Stange, Madison; Graydon, Candice; Dixon, Mike J

2017-09-01

Previous research into scratch card gambling has highlighted the effects of these games on players' arousal and affective states. Specifically, near-miss outcomes in scratch cards (uncovering 2 of 3 needed jackpot symbols) have been associated with high levels of physiological and subjective arousal and negative emotional evaluations, including increased frustration. We sought to extend this research by examining whether near-misses prompted increases in gambling urge, and the subsequent purchasing of additional scratch cards. Participants played two scratch cards with varying outcomes with half of the sample experiencing a near-miss for the jackpot prize, and the other half experiencing a regular loss. Players rated their urge to continue gambling after each game outcome, and following the initial playing phase, were then able to use their winnings to purchase additional cards. Our results indicated that near-misses increased the urge to gamble significantly more than regular losses, and urge to gamble in the near-miss group was significantly correlated with purchasing at least one additional card. Although some players in the loss group purchased another card, there was no correlation between urge to gamble and purchasing in this group. Additionally, participants in the near-miss group who purchased additional cards reported higher levels of urge than those who did not purchase more cards. This was not true for the loss group: participants who experienced solely losing outcomes reported similar levels of urge regardless of whether or not they purchased more scratch cards. Despite near-misses' objective status as monetary losses, the increased urge that follows near-miss outcomes may translate into further scratch card gambling for a subset of individuals .

A systematic review and development of a classification framework for factors associated with missing patient-reported outcome data.

PubMed

Palmer, Michael J; Mercieca-Bebber, Rebecca; King, Madeleine; Calvert, Melanie; Richardson, Harriet; Brundage, Michael

2018-02-01

Missing patient-reported outcome data can lead to biased results, to loss of power to detect between-treatment differences, and to research waste. Awareness of factors may help researchers reduce missing patient-reported outcome data through study design and trial processes. The aim was to construct a Classification Framework of factors associated with missing patient-reported outcome data in the context of comparative studies. The first step in this process was informed by a systematic review. Two databases (MEDLINE and CINAHL) were searched from inception to March 2015 for English articles. Inclusion criteria were (a) relevant to patient-reported outcomes, (b) discussed missing data or compliance in prospective medical studies, and (c) examined predictors or causes of missing data, including reasons identified in actual trial datasets and reported on cover sheets. Two reviewers independently screened titles and abstracts. Discrepancies were discussed with the research team prior to finalizing the list of eligible papers. In completing the systematic review, four particular challenges to synthesizing the extracted information were identified. To address these challenges, operational principles were established by consensus to guide the development of the Classification Framework. A total of 6027 records were screened. In all, 100 papers were eligible and included in the review. Of these, 57% focused on cancer, 23% did not specify disease, and 20% reported for patients with a variety of non-cancer conditions. In total, 40% of the papers offered a descriptive analysis of possible factors associated with missing data, but some papers used other methods. In total, 663 excerpts of text (units), each describing a factor associated with missing patient-reported outcome data, were extracted verbatim. Redundant units were identified and sequestered. Similar units were grouped, and an iterative process of consensus among the investigators was used to reduce these units to a list of factors that met the guiding principles. The list was organized on a framework, using an iterative consensus-based process. The resultant Classification Framework is a summary of the factors associated with missing patient-reported outcome data described in the literature. It consists of 5 components (instrument, participant, centre, staff, and study) and 46 categories, each with one or more sub-categories or examples. A systematic review of the literature revealed 46 unique categories of factors associated with missing patient-reported outcome data, organized into 5 main component groups. The Classification Framework may assist researchers to improve the design of new randomized clinical trials and to implement procedures to reduce missing patient-reported outcome data. Further research using the Classification Framework to inform quantitative analyses of missing patient-reported outcome data in existing clinical trials and to inform qualitative inquiry of research staff is planned.

What impact does nursing care left undone have on patient outcomes? Review of the literature.

PubMed

Recio-Saucedo, Alejandra; Dall'Ora, Chiara; Maruotti, Antonello; Ball, Jane; Briggs, Jim; Meredith, Paul; Redfern, Oliver C; Kovacs, Caroline; Prytherch, David; Smith, Gary B; Griffiths, Peter

2018-06-01

Systematic review of the impact of missed nursing care on outcomes in adults, on acute hospital wards and in nursing homes. A considerable body of evidence supports the hypothesis that lower levels of registered nurses on duty increase the likelihood of patients dying on hospital wards, and the risk of many aspects of care being either delayed or left undone (missed). However, the direct consequence of missed care remains unclear. Systematic review. We searched Medline (via Ovid), CINAHL (EBSCOhost) and Scopus for studies examining the association of missed nursing care and at least one patient outcome. Studies regarding registered nurses, healthcare assistants/support workers/nurses' aides were retained. Only adult settings were included. Because of the nature of the review, qualitative studies, editorials, letters and commentaries were excluded. PRISMA guidelines were followed in reporting the review. Fourteen studies reported associations between missed care and patient outcomes. Some studies were secondary analyses of a large parent study. Most of the studies used nurse or patient reports to capture outcomes, with some using administrative data. Four studies found significantly decreased patient satisfaction associated with missed care. Seven studies reported associations with one or more patient outcomes including medication errors, urinary tract infections, patient falls, pressure ulcers, critical incidents, quality of care and patient readmissions. Three studies investigated whether there was a link between missed care and mortality and from these results no clear associations emerged. The review shows the modest evidence base of studies exploring missed care and patient outcomes generated mostly from nurse and patient self-reported data. To support the assertion that nurse staffing levels and skill mix are associated with adverse outcomes as a result of missed care, more research that uses objective staffing and outcome measures is required. Although nurses may exercise judgements in rationing care in the face of pressure, there are nonetheless adverse consequences for patients (ranging from poor experience of care to increased risk of infection, readmissions and complications due to critical incidents from undetected physiological deterioration). Hospitals should pay attention to nurses' reports of missed care and consider routine monitoring as a quality and safety indicator. © 2017 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Analysis of Longitudinal Outcome Data with Missing Values in Total Knee Arthroplasty.

PubMed

Kang, Yeon Gwi; Lee, Jang Taek; Kang, Jong Yeal; Kim, Ga Hye; Kim, Tae Kyun

2016-01-01

We sought to determine the influence of missing data on the statistical results, and to determine which statistical method is most appropriate for the analysis of longitudinal outcome data of TKA with missing values among repeated measures ANOVA, generalized estimating equation (GEE) and mixed effects model repeated measures (MMRM). Data sets with missing values were generated with different proportion of missing data, sample size and missing-data generation mechanism. Each data set was analyzed with three statistical methods. The influence of missing data was greater with higher proportion of missing data and smaller sample size. MMRM tended to show least changes in the statistics. When missing values were generated by 'missing not at random' mechanism, no statistical methods could fully avoid deviations in the results. Copyright © 2016 Elsevier Inc. All rights reserved.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

NASA Astrophysics Data System (ADS)

Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.

2018-04-01

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

Statistical analysis and handling of missing data in cluster randomized trials: a systematic review.

PubMed

Fiero, Mallorie H; Huang, Shuang; Oren, Eyal; Bell, Melanie L

2016-02-09

Cluster randomized trials (CRTs) randomize participants in groups, rather than as individuals and are key tools used to assess interventions in health research where treatment contamination is likely or if individual randomization is not feasible. Two potential major pitfalls exist regarding CRTs, namely handling missing data and not accounting for clustering in the primary analysis. The aim of this review was to evaluate approaches for handling missing data and statistical analysis with respect to the primary outcome in CRTs. We systematically searched for CRTs published between August 2013 and July 2014 using PubMed, Web of Science, and PsycINFO. For each trial, two independent reviewers assessed the extent of the missing data and method(s) used for handling missing data in the primary and sensitivity analyses. We evaluated the primary analysis and determined whether it was at the cluster or individual level. Of the 86 included CRTs, 80 (93%) trials reported some missing outcome data. Of those reporting missing data, the median percent of individuals with a missing outcome was 19% (range 0.5 to 90%). The most common way to handle missing data in the primary analysis was complete case analysis (44, 55%), whereas 18 (22%) used mixed models, six (8%) used single imputation, four (5%) used unweighted generalized estimating equations, and two (2%) used multiple imputation. Fourteen (16%) trials reported a sensitivity analysis for missing data, but most assumed the same missing data mechanism as in the primary analysis. Overall, 67 (78%) trials accounted for clustering in the primary analysis. High rates of missing outcome data are present in the majority of CRTs, yet handling missing data in practice remains suboptimal. Researchers and applied statisticians should carry out appropriate missing data methods, which are valid under plausible assumptions in order to increase statistical power in trials and reduce the possibility of bias. Sensitivity analysis should be performed, with weakened assumptions regarding the missing data mechanism to explore the robustness of results reported in the primary analysis.

On the Counterfactual Nature of Gambling Near-misses: An Experimental Study.

PubMed

Wu, Yin; van Dijk, Eric; Li, Hong; Aitken, Michael; Clark, Luke

2017-10-01

Research on gambling near-misses has shown that objectively equivalent outcomes can yield divergent emotional and motivational responses. The subjective processing of gambling outcomes is affected substantially by close but non-obtained outcomes (i.e. counterfactuals). In the current paper, we investigate how different types of near-misses influence self-perceived luck and subsequent betting behavior in a wheel-of-fortune task. We investigate the counterfactual mechanism of these effects by testing the relationship with a second task measuring regret/relief processing. Across two experiments (Experiment 1, n  = 51; Experiment 2, n  = 104), we demonstrate that near-wins (neutral outcomes that are close to a jackpot) decreased self-perceived luck, whereas near-losses (neutral outcomes that are close to a major penalty) increased luck ratings. The effects of near-misses varied by near-miss position (i.e. whether the spinner stopped just short of, or passed through, the counterfactual outcome), consistent with established distinctions between upward versus downward, and additive versus subtractive, counterfactual thinking. In Experiment 1, individuals who showed stronger counterfactual processing on the regret/relief task were more responsive to near-wins and near-losses on the wheel-of-fortune task. The effect of near-miss position was attenuated when the anticipatory phase (i.e. the spin and deceleration) was removed in Experiment 2. Further differences were observed within the objective gains and losses, between "clear" and "narrow" outcomes. Taken together, these results help substantiate the counterfactual mechanism of near-misses. © 2017 The Authors Journal of Behavioral Decision Making Published by John Wiley & Sons Ltd.

On the Counterfactual Nature of Gambling Near‐misses: An Experimental Study

PubMed Central

van Dijk, Eric; Li, Hong; Aitken, Michael; Clark, Luke

2017-01-01

Abstract Research on gambling near‐misses has shown that objectively equivalent outcomes can yield divergent emotional and motivational responses. The subjective processing of gambling outcomes is affected substantially by close but non‐obtained outcomes (i.e. counterfactuals). In the current paper, we investigate how different types of near‐misses influence self‐perceived luck and subsequent betting behavior in a wheel‐of‐fortune task. We investigate the counterfactual mechanism of these effects by testing the relationship with a second task measuring regret/relief processing. Across two experiments (Experiment 1, n = 51; Experiment 2, n = 104), we demonstrate that near‐wins (neutral outcomes that are close to a jackpot) decreased self‐perceived luck, whereas near‐losses (neutral outcomes that are close to a major penalty) increased luck ratings. The effects of near‐misses varied by near‐miss position (i.e. whether the spinner stopped just short of, or passed through, the counterfactual outcome), consistent with established distinctions between upward versus downward, and additive versus subtractive, counterfactual thinking. In Experiment 1, individuals who showed stronger counterfactual processing on the regret/relief task were more responsive to near‐wins and near‐losses on the wheel‐of‐fortune task. The effect of near‐miss position was attenuated when the anticipatory phase (i.e. the spin and deceleration) was removed in Experiment 2. Further differences were observed within the objective gains and losses, between “clear” and “narrow” outcomes. Taken together, these results help substantiate the counterfactual mechanism of near‐misses. © 2017 The Authors Journal of Behavioral Decision Making Published by John Wiley & Sons Ltd. PMID:29081596

A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study.

PubMed

Liu, Danping; Yeung, Edwina H; McLain, Alexander C; Xie, Yunlong; Buck Louis, Germaine M; Sundaram, Rajeshwari

2017-09-01

Imperfect follow-up in longitudinal studies commonly leads to missing outcome data that can potentially bias the inference when the missingness is nonignorable; that is, the propensity of missingness depends on missing values in the data. In the Upstate KIDS Study, we seek to determine if the missingness of child development outcomes is nonignorable, and how a simple model assuming ignorable missingness would compare with more complicated models for a nonignorable mechanism. To correct for nonignorable missingness, the shared random effects model (SREM) jointly models the outcome and the missing mechanism. However, the computational complexity and lack of software packages has limited its practical applications. This paper proposes a novel two-step approach to handle nonignorable missing outcomes in generalized linear mixed models. We first analyse the missing mechanism with a generalized linear mixed model and predict values of the random effects; then, the outcome model is fitted adjusting for the predicted random effects to account for heterogeneity in the missingness propensity. Extensive simulation studies suggest that the proposed method is a reliable approximation to SREM, with a much faster computation. The nonignorability of missing data in the Upstate KIDS Study is estimated to be mild to moderate, and the analyses using the two-step approach or SREM are similar to the model assuming ignorable missingness. The two-step approach is a computationally straightforward method that can be conducted as sensitivity analyses in longitudinal studies to examine violations to the ignorable missingness assumption and the implications relative to health outcomes. © 2017 John Wiley & Sons Ltd.

Missing data reconstruction using Gaussian mixture models for fingerprint images

NASA Astrophysics Data System (ADS)

Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

2016-05-01

Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

Evaluating Failures and near Misses in Human Spaceflight History for Lessons for Future Human Spaceflight

NASA Technical Reports Server (NTRS)

Barr, Stephanie

2010-01-01

Studies done in the past have drawn on lessons learned with regard to human loss-of-life events. However, an examination of near-fatal accidents can be equally useful, not only in detecting causes, both proximate and systemic, but also for determining what factors averted disaster, what design decisions and/or operator actions prevented catastrophe. Binary pass/fail launch history is often used for risk, but this also has limitations. A program with a number of near misses can look more reliable than a consistently healthy program with a single out-of-family failure. Augmenting reliability evaluations with this near miss data can provide insight and expand on the limitations of a strictly pass/fail evaluation. This paper intends to show how near-miss lessons learned can provide crucial data for any new human spaceflight programs that are interested in sending man into space

Evaluating Failures and Near Misses in Human Spaceflight History for Lessons for Future Human Spaceflight

NASA Astrophysics Data System (ADS)

Barr, Stephanie

2010-09-01

Studies done in the past have drawn on lessons learned with regard to human loss-of-life events. However, an examination of near-fatal accidents can be equally useful, not only in detecting causes, both proximate and systemic, but also for determining what factors averted disaster, what design decisions and/or operator actions prevented catastrophe. Binary pass/fail launch history is often used for risk, but this also has limitations. A program with a number of near misses can look more reliable than a consistently healthy program with a single out-of-family failure. Augmenting reliability evaluations with this near miss data can provide insight and expand on the limitations of a strictly pass/fail evaluation. This paper intends to show how near-miss lessons learned can provide crucial data for any new human spaceflight programs that are interested in sending man into space.

Evidence for network evolution in an arabidopsis interactome map

USDA-ARS?s Scientific Manuscript database

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the pl...

The Handling of Missing Binary Data in Language Research

ERIC Educational Resources Information Center

Pichette, François; Béland, Sébastien; Jolani, Shahab; Lesniewska, Justyna

2015-01-01

Researchers are frequently confronted with unanswered questions or items on their questionnaires and tests, due to factors such as item difficulty, lack of testing time, or participant distraction. This paper first presents results from a poll confirming previous claims (Rietveld & van Hout, 2006; Schafer & Graham, 2002) that data…

Attrition Bias Related to Missing Outcome Data: A Longitudinal Simulation Study.

PubMed

Lewin, Antoine; Brondeel, Ruben; Benmarhnia, Tarik; Thomas, Frédérique; Chaix, Basile

2018-01-01

Most longitudinal studies do not address potential selection biases due to selective attrition. Using empirical data and simulating additional attrition, we investigated the effectiveness of common approaches to handle missing outcome data from attrition in the association between individual education level and change in body mass index (BMI). Using data from the two waves of the French RECORD Cohort Study (N = 7,172), we first examined how inverse probability weighting (IPW) and multiple imputation handled missing outcome data from attrition in the observed data (stage 1). Second, simulating additional missing data in BMI at follow-up under various missing-at-random scenarios, we quantified the impact of attrition and assessed how multiple imputation performed compared to complete case analysis and to a perfectly specified IPW model as a gold standard (stage 2). With the observed data in stage 1, we found an inverse association between individual education and change in BMI, with complete case analysis, as well as with IPW and multiple imputation. When we simulated additional attrition under a missing-at-random pattern (stage 2), the bias increased with the magnitude of selective attrition, and multiple imputation was useless to address it. Our simulations revealed that selective attrition in the outcome heavily biased the association of interest. The present article contributes to raising awareness that for missing outcome data, multiple imputation does not do better than complete case analysis. More effort is thus needed during the design phase to understand attrition mechanisms by collecting information on the reasons for dropout.

High Resolution Imaging of Very Low Mass Spectral Binaries: Three Resolved Systems and Detection of Orbital Motion in an L/T Transition Binary

NASA Astrophysics Data System (ADS)

Bardalez Gagliuffi, Daniella C.; Gelino, Christopher R.; Burgasser, Adam J.

2015-11-01

We present high resolution Laser Guide Star Adaptive Optics imaging of 43 late-M, L and T dwarf systems with Keck/NIRC2. These include 17 spectral binary candidates, systems whose spectra suggest the presence of a T dwarf secondary. We resolve three systems: 2MASS J1341-3052, SDSS J1511+0607 and SDSS J2052-1609 the first two are resolved for the first time. All three have projected separations <8 AU and estimated periods of 14-80 years. We also report a preliminary orbit determination for SDSS J2052-1609 based on six epochs of resolved astrometry between 2005 and 2010. Among the 14 unresolved spectral binaries, 5 systems were confirmed binaries but remained unresolved, implying a minimum binary fraction of {47}-11+12% for this sample. Our inability to resolve most of the spectral binaries, including the confirmed binaries, supports the hypothesis that a large fraction of very low mass systems have relatively small separations and are missed with direct imaging. Some of the data presented herein were obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W.M. Keck Foundation.

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed Central

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group. PMID:28034175

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

A Statistical Model for Misreported Binary Outcomes in Clustered RCTs of Education Interventions

ERIC Educational Resources Information Center

Schochet, Peter Z.

2013-01-01

In education randomized control trials (RCTs), the misreporting of student outcome data could lead to biased estimates of average treatment effects (ATEs) and their standard errors. This article discusses a statistical model that adjusts for misreported binary outcomes for two-level, school-based RCTs, where it is assumed that misreporting could…

A State Change In The Missing Link Binary Pulsar System Psr J1023+0038

DOE PAGES

Stappers, B. W.; Archibald, A. M.; Hessels, J. W. T.; ...

2014-07-01

We present radio, X-ray, and γ-ray observations which reveal that the binary millisecond pulsar / low-mass X-ray binary transition system PSR J1023+0038 has undergone a transformation in state. Whereas until recently the system harbored a bright millisecond radio pulsar, the radio pulsations at frequencies between 300 to 5000MHz have now become undetectable. Concurrent with this radio disappearance, the γ-ray flux of the system has quintupled. We conclude that, though the radio pulsar is currently not detectable, the pulsar mechanism is still active and the pulsar wind, as well as a newly formed accretion disk, are together providing the necessary conditionsmore » to create the γ-ray increase. The system is the first example of a transient, compact, low-mass γ-ray binary and will continue to provide an exceptional test bed for better understanding the formation of millisecond pulsars as well as accretion onto neutron stars in general.« less

A unifying framework for marginalized random intercept models of correlated binary outcomes

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian M.

2013-01-01

We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood-based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized random intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts. PMID:25342871

Stochastic Template Bank for Gravitational Wave Searches for Precessing Neutron Star-Black Hole Coalescence Events

NASA Technical Reports Server (NTRS)

Indik, Nathaniel; Haris, K.; Dal Canton, Tito; Fehrmann, Henning; Krishnan, Badri; Lundgren, Andrew; Nielsen, Alex B.; Pai, Archana

2017-01-01

Gravitational wave searches to date have largely focused on non-precessing systems. Including precession effects greatly increases the number of templates to be searched over. This leads to a corresponding increase in the computational cost and can increase the false alarm rate of a realistic search. On the other hand, there might be astrophysical systems that are entirely missed by non-precessing searches. In this paper we consider the problem of constructing a template bank using stochastic methods for neutron star-black hole binaries allowing for precession, but with the restrictions that the total angular momentum of the binary is pointing toward the detector and that the neutron star spin is negligible relative to that of the black hole. We quantify the number of templates required for the search, and we explicitly construct the template bank. We show that despite the large number of templates, stochastic methods can be adapted to solve the problem. We quantify the parameter space region over which the non-precessing search might miss signals.

Sensitivity analysis for missing dichotomous outcome data in multi-visit randomized clinical trial with randomization-based covariance adjustment.

PubMed

Li, Siying; Koch, Gary G; Preisser, John S; Lam, Diana; Sanchez-Kam, Matilde

2017-01-01

Dichotomous endpoints in clinical trials have only two possible outcomes, either directly or via categorization of an ordinal or continuous observation. It is common to have missing data for one or more visits during a multi-visit study. This paper presents a closed form method for sensitivity analysis of a randomized multi-visit clinical trial that possibly has missing not at random (MNAR) dichotomous data. Counts of missing data are redistributed to the favorable and unfavorable outcomes mathematically to address possibly informative missing data. Adjusted proportion estimates and their closed form covariance matrix estimates are provided. Treatment comparisons over time are addressed with Mantel-Haenszel adjustment for a stratification factor and/or randomization-based adjustment for baseline covariables. The application of such sensitivity analyses is illustrated with an example. An appendix outlines an extension of the methodology to ordinal endpoints.

Missing data on body mass index in a breast cancer register: how is it associated with patient characteristics and clinical outcomes?

PubMed

Tin Tin, Sandar; Elwood, J Mark; Lawrenson, Ross; Campbell, Ian

2017-03-03

To assess the completeness of data on body mass index (BMI) in a regional breast cancer register, and its association with patient characteristics and clinical outcomes. This analysis used the data from the Waikato Breast Cancer Register and involved all women who were diagnosed with primary breast cancer in the Waikato District Health Board Region between January 2000 and June 2014. Patients with recorded BMI were compared with those with missing data in terms of demographics, disease factors and treatment factors. Cox regression modelling was performed, and hazards of specific outcomes associated with missing data on BMI were assessed. Of the 3,536 patients included in this analysis, 27.4% had missing data on BMI. Missing data was more frequent in older patients, rural dwellers, patients with comorbidities, screen detected patients, patients with early stage or low grade cancer and hormone receptor positive patients, but was minimal in patients who received chemotherapy. Patients with missing data were less likely to experience loco-regional recurrence (although not significant), metastasis and breast cancer specific mortality, but more likely to experience death from other causes even after demographic, disease and treatment factors were adjusted. Height or weight or both were not recorded for more than one quarter of the patients. Missing data was differential by specific patient characteristics and clinical outcomes.

Metastatic Spine Tumor Surgery: A Comparative Study of Minimally Invasive Approach Using Percutaneous Pedicle Screws Fixation Versus Open Approach.

PubMed

Kumar, Naresh; Malhotra, Rishi; Maharajan, Karthikeyan; Zaw, Aye S; Wu, Pang Hung; Makandura, Milindu C; Po Liu, Gabriel Ka; Thambiah, Joseph; Wong, Hee-Kit

2017-10-01

Prospective cohort study. Minimally invasive spinal surgery (MISS) has been gaining recognition in patients with metastatic spine disease (MSD). The advantages are reduction in blood loss, hospital stay, and postoperative morbidity. Most of the studies were case series with very few comparing the outcomes of MISS to open approaches. To evaluate and compare the clinical and perioperative outcomes of MISS versus open approach in patients with symptomatic MSD, who underwent posterior spinal stabilization and/or decompression. Our study included 45 MSD patients; 27 managed by MISS and 18 by open approach. All patients had MSD presenting with symptoms of neurological deficit, spinal instability, or both. Preoperative, intraoperative, and postoperative data were collected for comparison of the 2 approaches. All patients were followed up until the end of study period (maximum up to 4 years from time of surgery) or till their demise. The clinical outcome measures were pain control, neurological and functional status, whereas perioperative outcomes were blood loss, operative time, length of hospital stay, and time taken to initiate radiotherapy/chemotherapy after index surgery. Majority of patients in both groups showed improvement in pain, neurological status, independent ambulation, and ECOG score in the postoperative period with no significant differences between the 2 groups. There was a significant reduction in intraoperative blood loss (621 mL less, P<0.001) in the MISS group. The average time to initiate radiotherapy after surgery was 13 days (range, 12-16 d) in MISS and 24 days (range, 16-40 d) in the open group. This difference was statistically significant (P<0.001). Operative time and duration of hospital stay were also favorable in the MISS group, although the differences were not significant. MISS is comparable with open approach demonstrating similar improvements in clinical outcomes, that is pain control, neurological and functional status. MISS approaches have also shown promising results due to lesser intraoperative blood loss and allowing earlier radiotherapy/chemotherapy.

Mapping integration of midwives across the United States: Impact on access, equity, and outcomes

PubMed Central

Stoll, Kathrin; MacDorman, Marian; Declercq, Eugene; Cramer, Renee; Cheyney, Melissa; Fisher, Timothy; Butt, Emma; Yang, Y. Tony; Powell Kennedy, Holly

2018-01-01

Poor coordination of care across providers and birth settings has been associated with adverse maternal-newborn outcomes. Research suggests that integration of midwives into regional health systems is a key determinant of optimal maternal-newborn outcomes, yet, to date, the characteristics of an integrated system have not been described, nor linked to health disparities. Methods Our multidisciplinary team examined published regulatory data to inform a 50-state database describing the environment for midwifery practice and interprofessional collaboration. Items (110) detailed differences across jurisdictions in scope of practice, autonomy, governance, and prescriptive authority; as well as restrictions that can affect patient safety, quality, and access to maternity providers across birth settings. A nationwide survey of state regulatory experts (n = 92) verified the ‘on the ground’ relevance, importance, and realities of local interpretation of these state laws. Using a modified Delphi process, we selected 50/110 key items to include in a weighted, composite Midwifery Integration Scoring (MISS) system. Higher scores indicate greater integration of midwives across all settings. We ranked states by MISS scores; and, using reliable indicators in the CDC-Vital Statistics Database, we calculated correlation coefficients between MISS scores and maternal-newborn outcomes by state, as well as state density of midwives and place of birth. We conducted hierarchical linear regression analysis to control for confounding effects of race. Results MISS scores ranged from lowest at 17 (North Carolina) to highest at 61 (Washington), out of 100 points. Higher MISS scores were associated with significantly higher rates of spontaneous vaginal delivery, vaginal birth after cesarean, and breastfeeding, and significantly lower rates of cesarean, preterm birth, low birth weight infants, and neonatal death. MISS scores also correlated with density of midwives and access to care across birth settings. Significant differences in newborn outcomes accounted for by MISS scores persisted after controlling for proportion of African American births in each state. Conclusion The MISS scoring system assesses the level of integration of midwives and evaluates regional access to high quality maternity care. In the United States, higher MISS Scores were associated with significantly higher rates of physiologic birth, less obstetric interventions, and fewer adverse neonatal outcomes. PMID:29466389

EVERY INTERACTING DOUBLE WHITE DWARF BINARY MAY MERGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Ken J.

2015-05-20

Interacting double white dwarf (WD) binaries can give rise to a wide variety of astrophysical outcomes ranging from faint thermonuclear and Type Ia supernovae to the formation of neutron stars and stably accreting AM Canum Venaticorum systems. One key factor affecting the final outcome is whether mass transfer remains dynamically stable or instead diverges, leading to the tidal disruption of the donor and the merger of the binary. It is typically thought that for low ratios of the donor mass to the accretor mass, mass transfer remains stable, especially if accretion occurs via a disk. In this Letter, we examinemore » low mass ratio double WD binaries and find that the initial phase of hydrogen-rich mass transfer leads to a classical nova-like outburst on the accretor. Dynamical friction within the expanding nova shell shrinks the orbit and causes the mass transfer rate to increase dramatically above the accretor's Eddington limit, possibly resulting in a binary merger. If the binary survives the first hydrogen-rich nova outbursts, dynamical friction within the subsequent helium-powered nova shells pushes the system even more strongly toward merger. While further calculations are necessary to confirm this outcome for the entire range of binaries previously thought to be dynamically stable, it appears likely that most, if not all, interacting double WD binaries will merge during the course of their evolution.« less

On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials*

PubMed Central

Brummel, Sean S.; Gillen, Daniel L.

2014-01-01

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement. PMID:25540717

Rasch-family models are more valuable than score-based approaches for analysing longitudinal patient-reported outcomes with missing data.

PubMed

de Bock, Élodie; Hardouin, Jean-Benoit; Blanchin, Myriam; Le Neel, Tanguy; Kubis, Gildas; Bonnaud-Antignac, Angélique; Dantan, Étienne; Sébille, Véronique

2016-10-01

The objective was to compare classical test theory and Rasch-family models derived from item response theory for the analysis of longitudinal patient-reported outcomes data with possibly informative intermittent missing items. A simulation study was performed in order to assess and compare the performance of classical test theory and Rasch model in terms of bias, control of the type I error and power of the test of time effect. The type I error was controlled for classical test theory and Rasch model whether data were complete or some items were missing. Both methods were unbiased and displayed similar power with complete data. When items were missing, Rasch model remained unbiased and displayed higher power than classical test theory. Rasch model performed better than the classical test theory approach regarding the analysis of longitudinal patient-reported outcomes with possibly informative intermittent missing items mainly for power. This study highlights the interest of Rasch-based models in clinical research and epidemiology for the analysis of incomplete patient-reported outcomes data. © The Author(s) 2013.

An approximate generalized linear model with random effects for informative missing data.

PubMed

Follmann, D; Wu, M

1995-03-01

This paper develops a class of models to deal with missing data from longitudinal studies. We assume that separate models for the primary response and missingness (e.g., number of missed visits) are linked by a common random parameter. Such models have been developed in the econometrics (Heckman, 1979, Econometrica 47, 153-161) and biostatistics (Wu and Carroll, 1988, Biometrics 44, 175-188) literature for a Gaussian primary response. We allow the primary response, conditional on the random parameter, to follow a generalized linear model and approximate the generalized linear model by conditioning on the data that describes missingness. The resultant approximation is a mixed generalized linear model with possibly heterogeneous random effects. An example is given to illustrate the approximate approach, and simulations are performed to critique the adequacy of the approximation for repeated binary data.

2SLS versus 2SRI: Appropriate methods for rare outcomes and/or rare exposures.

PubMed

Basu, Anirban; Coe, Norma B; Chapman, Cole G

2018-06-01

This study used Monte Carlo simulations to examine the ability of the two-stage least squares (2SLS) estimator and two-stage residual inclusion (2SRI) estimators with varying forms of residuals to estimate the local average and population average treatment effect parameters in models with binary outcome, endogenous binary treatment, and single binary instrument. The rarity of the outcome and the treatment was varied across simulation scenarios. Results showed that 2SLS generated consistent estimates of the local average treatment effects (LATE) and biased estimates of the average treatment effects (ATE) across all scenarios. 2SRI approaches, in general, produced biased estimates of both LATE and ATE under all scenarios. 2SRI using generalized residuals minimized the bias in ATE estimates. Use of 2SLS and 2SRI is illustrated in an empirical application estimating the effects of long-term care insurance on a variety of binary health care utilization outcomes among the near-elderly using the Health and Retirement Study. Copyright © 2018 John Wiley & Sons, Ltd.

Prevalence of maternal near miss and community-based risk factors in Central Uganda.

PubMed

Nansubuga, Elizabeth; Ayiga, Natal; Moyer, Cheryl A

2016-11-01

To examine the prevalence of maternal near-miss (MNM) and its associated risk factors in a community setting in Central Uganda. A cross-sectional research design employing multi-stage sampling collected data from women aged 15-49 years in Rakai, Uganda, who had been pregnant in the 3years preceding the survey, conducted between August 10 and December 31, 2013. Additionally, in-depth interviews were conducted. WHO-based disease and management criteria were used to identify MNM. Binary logistic regression was used to predict MNM risk factors. Content analysis was performed for qualitative data. Survey data were collected from 1557 women and 40 in-depth interviews were conducted. The MNM prevalence was 287.7 per 1000 pregnancies; the majority of MNMs resulted from hemorrhage. Unwanted pregnancies, a history of MNM, primipara, pregnancy danger signs, Banyakore ethnicity, and a partner who had completed primary education only were associated with increased odds of MNM (all P<0.05). MNM morbidity is a significant burden in Central Uganda. The present study demonstrated higher MNM rates compared with studies employing organ-failure MNM-diagnostic criteria. These findings illustrate the need to look beyond mortality statistics when assessing maternal health outcomes. Concerted efforts to increase supervised deliveries, access to emergency obstetric care, and access to contraceptives are warranted. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Comparing object recognition from binary and bipolar edge images for visual prostheses.

PubMed

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2016-11-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition.

Propensity score analysis with partially observed covariates: How should multiple imputation be used?

PubMed

Leyrat, Clémence; Seaman, Shaun R; White, Ian R; Douglas, Ian; Smeeth, Liam; Kim, Joseph; Resche-Rigon, Matthieu; Carpenter, James R; Williamson, Elizabeth J

2017-01-01

Inverse probability of treatment weighting is a popular propensity score-based approach to estimate marginal treatment effects in observational studies at risk of confounding bias. A major issue when estimating the propensity score is the presence of partially observed covariates. Multiple imputation is a natural approach to handle missing data on covariates: covariates are imputed and a propensity score analysis is performed in each imputed dataset to estimate the treatment effect. The treatment effect estimates from each imputed dataset are then combined to obtain an overall estimate. We call this method MIte. However, an alternative approach has been proposed, in which the propensity scores are combined across the imputed datasets (MIps). Therefore, there are remaining uncertainties about how to implement multiple imputation for propensity score analysis: (a) should we apply Rubin's rules to the inverse probability of treatment weighting treatment effect estimates or to the propensity score estimates themselves? (b) does the outcome have to be included in the imputation model? (c) how should we estimate the variance of the inverse probability of treatment weighting estimator after multiple imputation? We studied the consistency and balancing properties of the MIte and MIps estimators and performed a simulation study to empirically assess their performance for the analysis of a binary outcome. We also compared the performance of these methods to complete case analysis and the missingness pattern approach, which uses a different propensity score model for each pattern of missingness, and a third multiple imputation approach in which the propensity score parameters are combined rather than the propensity scores themselves (MIpar). Under a missing at random mechanism, complete case and missingness pattern analyses were biased in most cases for estimating the marginal treatment effect, whereas multiple imputation approaches were approximately unbiased as long as the outcome was included in the imputation model. Only MIte was unbiased in all the studied scenarios and Rubin's rules provided good variance estimates for MIte. The propensity score estimated in the MIte approach showed good balancing properties. In conclusion, when using multiple imputation in the inverse probability of treatment weighting context, MIte with the outcome included in the imputation model is the preferred approach.

Sickness absence of LU train drivers after track incidents.

PubMed

Chavda, S

2016-10-01

Track incidents including near misses and those causing injury or death are a psychological hazard for train operators. No study has directly investigated how train operators are affected depending on track incident outcome and few studies have investigated the impact of near misses. To compare sickness absence (SA) of London Underground train operators following track incidents categorized by outcome, including near misses. This was an observational study using historical data of track incidents from April 2008 to October 2013. Track incidents were divided into four categories according to outcome (near miss on platform, near miss on track, significant injury and fatality). Additional information on age, gender and previous relevant history was collected. A total of 685 track incidents were analysed. There was a significant difference in SA taken after near misses ('no injury') incidents compared with significant injury and fatality ('injury') incidents (P < 0.001). There was also a significant difference in SA in train operators involved in a fatality incident compared with significant injury incidents (P < 0.05). SA in train operators following a track incident increases in line with the severity of the incident in terms of outcome. Fatal track incidents caused the highest level of SA followed by significant injury incidents. Near misses also caused substantial levels of SA. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

The effect of missing KIR ligands, activating KIR genotype and haplotype on the outcome of T-cell-replete hematopoietic stem cell transplantation from HLA-identical siblings in Thai patients.

PubMed

Khanuntong, S; Kuptawintu, P; Upaisilpsathaporn, K; Poolchareon, A; Bunworasate, U; Hirankarn, N

2016-06-01

This study was a retrospective analysis of Thai patients undergoing T-replete hematopoietic stem cell transplant from human leukocyte antigen (HLA)-identical sibling donors. We investigated 66 patients, including 40 patients with acute myeloid leukemia (AML), 12 patients with acute lymphoblastic leukemia and 14 patients with chronic myeloid leukemia. Killer cell immunoglobulin-like receptor (KIR) genes and HLA ligands were typed by polymerase chain reaction-sequence specific oligonucleotide probes. We analyzed the effect of the number of missing KIR ligands (Bw4, C1 and C2) on clinical outcomes. A beneficial effect of missing KIR ligand was not observed in both univariate and multivariate analysis. When we analyzed the effect of specific missing KIR ligand on clinical outcomes, there was a trend that patients with missing A11 ligand had lower relapse rate (P = 0.076). Therefore, we also conducted the analysis by including the group with missing KIR ligands of Bw4, C1, C2 and A11. Patients with two or more than two missing KIR ligands had a trend for better clinical outcome including reduced relapse (P = 055) and statistically significant in terms of reduced acute graft-vs-host disease (aGVHD) rate (P = 0.013). In multivariate analysis, patients with two or more than two missing KIR ligands had a statistically significant better clinical outcome in terms of reduced aGVHD rate (HR = 0.155, 95%CI = 0.040-0.605, P = 0.007). The association between clinical outcome with KIR haplotypes, centromeric B haplotype and activating KIR was not observed here. Although the sample size in this study is rather limited, these data can later be subjected to meta-analysis to help reach the conclusion of the usefulness of this additional promising KIR genotyping in various hematopoietic stem cell transplantation types. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Flexible link functions in nonparametric binary regression with Gaussian process priors.

PubMed

Li, Dan; Wang, Xia; Lin, Lizhen; Dey, Dipak K

2016-09-01

In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. © 2015, The International Biometric Society.

Flexible Link Functions in Nonparametric Binary Regression with Gaussian Process Priors

PubMed Central

Li, Dan; Lin, Lizhen; Dey, Dipak K.

2015-01-01

Summary In many scientific fields, it is a common practice to collect a sequence of 0-1 binary responses from a subject across time, space, or a collection of covariates. Researchers are interested in finding out how the expected binary outcome is related to covariates, and aim at better prediction in the future 0-1 outcomes. Gaussian processes have been widely used to model nonlinear systems; in particular to model the latent structure in a binary regression model allowing nonlinear functional relationship between covariates and the expectation of binary outcomes. A critical issue in modeling binary response data is the appropriate choice of link functions. Commonly adopted link functions such as probit or logit links have fixed skewness and lack the flexibility to allow the data to determine the degree of the skewness. To address this limitation, we propose a flexible binary regression model which combines a generalized extreme value link function with a Gaussian process prior on the latent structure. Bayesian computation is employed in model estimation. Posterior consistency of the resulting posterior distribution is demonstrated. The flexibility and gains of the proposed model are illustrated through detailed simulation studies and two real data examples. Empirical results show that the proposed model outperforms a set of alternative models, which only have either a Gaussian process prior on the latent regression function or a Dirichlet prior on the link function. PMID:26686333

Missed losses loom larger than missed gains: Electrodermal reactivity to decision choices and outcomes in a gambling task.

PubMed

Wu, Yin; Van Dijk, Eric; Aitken, Mike; Clark, Luke

2016-04-01

Loss aversion is a defining characteristic of prospect theory, whereby responses are stronger to losses than to equivalently sized gains (Kahneman & Tversky Econometrica, 47, 263-291, 1979). By monitoring electrodermal activity (EDA) during a gambling task, in this study we examined physiological activity during risky decisions, as well as to both obtained (e.g., gains and losses) and counterfactual (e.g., narrowly missed gains and losses) outcomes. During the bet selection phase, EDA increased linearly with bet size, highlighting the role of somatic signals in decision-making under uncertainty in a task without any learning requirement. Outcome-related EDA scaled with the magnitudes of monetary wins and losses, and losses had a stronger impact on EDA than did equivalently sized wins. Narrowly missed wins (i.e., near-wins) and narrowly missed losses (i.e., near-losses) also evoked EDA responses, and the change of EDA as a function of the size of the missed outcome was modestly greater for near-losses than for near-wins, suggesting that near-losses have more impact on subjective value than do near-wins. Across individuals, the slope for choice-related EDA (as a function of bet size) correlated with the slope for outcome-related EDA as a function of both the obtained and counterfactual outcome magnitudes, and these correlations were stronger for loss and near-loss conditions than for win and near-win conditions. Taken together, these asymmetrical EDA patterns to objective wins and losses, as well as to near-wins and near-losses, provide a psychophysiological instantiation of the value function curve in prospect theory, which is steeper in the negative than in the positive domain.

Using linked educational attainment data to reduce bias due to missing outcome data in estimates of the association between the duration of breastfeeding and IQ at 15 years.

PubMed

Cornish, Rosie P; Tilling, Kate; Boyd, Andy; Davies, Amy; Macleod, John

2015-06-01

Most epidemiological studies have missing information, leading to reduced power and potential bias. Estimates of exposure-outcome associations will generally be biased if the outcome variable is missing not at random (MNAR). Linkage to administrative data containing a proxy for the missing study outcome allows assessment of whether this outcome is MNAR and the evaluation of bias. We examined this in relation to the association between infant breastfeeding and IQ at 15 years, where a proxy for IQ was available through linkage to school attainment data. Subjects were those who enrolled in the Avon Longitudinal Study of Parents and Children in 1990-91 (n = 13 795), of whom 5023 had IQ measured at age 15. For those with missing IQ, 7030 (79%) had information on educational attainment at age 16 obtained through linkage to the National Pupil Database. The association between duration of breastfeeding and IQ was estimated using a complete case analysis, multiple imputation and inverse probability-of-missingness weighting; these estimates were then compared with those derived from analyses informed by the linkage. IQ at 15 was MNAR-individuals with higher attainment were less likely to have missing IQ data, even after adjusting for socio-demographic factors. All the approaches underestimated the association between breastfeeding and IQ compared with analyses informed by linkage. Linkage to administrative data containing a proxy for the outcome variable allows the MNAR assumption to be tested and more efficient analyses to be performed. Under certain circumstances, this may produce unbiased results. © The Author 2015. Published by Oxford University Press on behalf of the International Epidemiological Association.

The current practice of handling and reporting missing outcome data in eight widely used PROMs in RCT publications: a review of the current literature.

PubMed

Rombach, Ines; Rivero-Arias, Oliver; Gray, Alastair M; Jenkinson, Crispin; Burke, Órlaith

2016-07-01

Patient-reported outcome measures (PROMs) are designed to assess patients' perceived health states or health-related quality of life. However, PROMs are susceptible to missing data, which can affect the validity of conclusions from randomised controlled trials (RCTs). This review aims to assess current practice in the handling, analysis and reporting of missing PROMs outcome data in RCTs compared to contemporary methodology and guidance. This structured review of the literature includes RCTs with a minimum of 50 participants per arm. Studies using the EQ-5D-3L, EORTC QLQ-C30, SF-12 and SF-36 were included if published in 2013; those using the less commonly implemented HUI, OHS, OKS and PDQ were included if published between 2009 and 2013. The review included 237 records (4-76 per relevant PROM). Complete case analysis and single imputation were commonly used in 33 and 15 % of publications, respectively. Multiple imputation was reported for 9 % of the PROMs reviewed. The majority of publications (93 %) failed to describe the assumed missing data mechanism, while low numbers of papers reported methods to minimise missing data (23 %), performed sensitivity analyses (22 %) or discussed the potential influence of missing data on results (16 %). Considerable discrepancy exists between approved methodology and current practice in handling, analysis and reporting of missing PROMs outcome data in RCTs. Greater awareness is needed for the potential biases introduced by inappropriate handling of missing data, as well as the importance of sensitivity analysis and clear reporting to enable appropriate assessments of treatment effects and conclusions from RCTs.

Definition, reporting, and interpretation of composite outcomes in clinical trials: systematic review

PubMed Central

Cordoba, Gloria; Schwartz, Lisa; Woloshin, Steven; Bae, Harold

2010-01-01

Objective To study how composite outcomes, which have combined several components into a single measure, are defined, reported, and interpreted. Design Systematic review of parallel group randomised clinical trials published in 2008 reporting a binary composite outcome. Two independent observers extracted the data using a standardised data sheet, and two other observers, blinded to the results, selected the most important component. Results Of 40 included trials, 29 (73%) were about cardiovascular topics and 24 (60%) were entirely or partly industry funded. Composite outcomes had a median of three components (range 2–9). Death or cardiovascular death was the most important component in 33 trials (83%). Only one trial provided a good rationale for the choice of components. We judged that the components were not of similar importance in 28 trials (70%); in 20 of these, death was combined with hospital admission. Other major problems were change in the definition of the composite outcome between the abstract, methods, and results sections (13 trials); missing, ambiguous, or uninterpretable data (9 trials); and post hoc construction of composite outcomes (4 trials). Only 24 trials (60%) provided reliable estimates for both the composite and its components, and only six trials (15%) had components of similar, or possibly similar, clinical importance and provided reliable estimates. In 11 of 16 trials with a statistically significant composite, the abstract conclusion falsely implied that the effect applied also to the most important component. Conclusions The use of composite outcomes in trials is problematic. Components are often unreasonably combined, inconsistently defined, and inadequately reported. These problems will leave many readers confused, often with an exaggerated perception of how well interventions work. PMID:20719825

Definition, reporting, and interpretation of composite outcomes in clinical trials: systematic review.

PubMed

Cordoba, Gloria; Schwartz, Lisa; Woloshin, Steven; Bae, Harold; Gøtzsche, Peter C

2010-08-18

To study how composite outcomes, which have combined several components into a single measure, are defined, reported, and interpreted. Systematic review of parallel group randomised clinical trials published in 2008 reporting a binary composite outcome. Two independent observers extracted the data using a standardised data sheet, and two other observers, blinded to the results, selected the most important component. Of 40 included trials, 29 (73%) were about cardiovascular topics and 24 (60%) were entirely or partly industry funded. Composite outcomes had a median of three components (range 2-9). Death or cardiovascular death was the most important component in 33 trials (83%). Only one trial provided a good rationale for the choice of components. We judged that the components were not of similar importance in 28 trials (70%); in 20 of these, death was combined with hospital admission. Other major problems were change in the definition of the composite outcome between the abstract, methods, and results sections (13 trials); missing, ambiguous, or uninterpretable data (9 trials); and post hoc construction of composite outcomes (4 trials). Only 24 trials (60%) provided reliable estimates for both the composite and its components, and only six trials (15%) had components of similar, or possibly similar, clinical importance and provided reliable estimates. In 11 of 16 trials with a statistically significant composite, the abstract conclusion falsely implied that the effect applied also to the most important component. The use of composite outcomes in trials is problematic. Components are often unreasonably combined, inconsistently defined, and inadequately reported. These problems will leave many readers confused, often with an exaggerated perception of how well interventions work.

Treatment of missing data in follow-up studies of randomised controlled trials: A systematic review of the literature.

PubMed

Sullivan, Thomas R; Yelland, Lisa N; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-08-01

After completion of a randomised controlled trial, an extended follow-up period may be initiated to learn about longer term impacts of the intervention. Since extended follow-up studies often involve additional eligibility restrictions and consent processes for participation, and a longer duration of follow-up entails a greater risk of participant attrition, missing data can be a considerable threat in this setting. As a potential source of bias, it is critical that missing data are appropriately handled in the statistical analysis, yet little is known about the treatment of missing data in extended follow-up studies. The aims of this review were to summarise the extent of missing data in extended follow-up studies and the use of statistical approaches to address this potentially serious problem. We performed a systematic literature search in PubMed to identify extended follow-up studies published from January to June 2015. Studies were eligible for inclusion if the original randomised controlled trial results were also published and if the main objective of extended follow-up was to compare the original randomised groups. We recorded information on the extent of missing data and the approach used to treat missing data in the statistical analysis of the primary outcome of the extended follow-up study. Of the 81 studies included in the review, 36 (44%) reported additional eligibility restrictions and 24 (30%) consent processes for entry into extended follow-up. Data were collected at a median of 7 years after randomisation. Excluding 28 studies with a time to event primary outcome, 51/53 studies (96%) reported missing data on the primary outcome. The median percentage of randomised participants with complete data on the primary outcome was just 66% in these studies. The most common statistical approach to address missing data was complete case analysis (51% of studies), while likelihood-based analyses were also well represented (25%). Sensitivity analyses around the missing data mechanism were rarely performed (25% of studies), and when they were, they often involved unrealistic assumptions about the mechanism. Despite missing data being a serious problem in extended follow-up studies, statistical approaches to addressing missing data were often inadequate. We recommend researchers clearly specify all sources of missing data in follow-up studies and use statistical methods that are valid under a plausible assumption about the missing data mechanism. Sensitivity analyses should also be undertaken to assess the robustness of findings to assumptions about the missing data mechanism.

Bayesian inference for joint modelling of longitudinal continuous, binary and ordinal events.

PubMed

Li, Qiuju; Pan, Jianxin; Belcher, John

2016-12-01

In medical studies, repeated measurements of continuous, binary and ordinal outcomes are routinely collected from the same patient. Instead of modelling each outcome separately, in this study we propose to jointly model the trivariate longitudinal responses, so as to take account of the inherent association between the different outcomes and thus improve statistical inferences. This work is motivated by a large cohort study in the North West of England, involving trivariate responses from each patient: Body Mass Index, Depression (Yes/No) ascertained with cut-off score not less than 8 at the Hospital Anxiety and Depression Scale, and Pain Interference generated from the Medical Outcomes Study 36-item short-form health survey with values returned on an ordinal scale 1-5. There are some well-established methods for combined continuous and binary, or even continuous and ordinal responses, but little work was done on the joint analysis of continuous, binary and ordinal responses. We propose conditional joint random-effects models, which take into account the inherent association between the continuous, binary and ordinal outcomes. Bayesian analysis methods are used to make statistical inferences. Simulation studies show that, by jointly modelling the trivariate outcomes, standard deviations of the estimates of parameters in the models are smaller and much more stable, leading to more efficient parameter estimates and reliable statistical inferences. In the real data analysis, the proposed joint analysis yields a much smaller deviance information criterion value than the separate analysis, and shows other good statistical properties too. © The Author(s) 2014.

A review of the handling of missing longitudinal outcome data in clinical trials

PubMed Central

2014-01-01

The aim of this review was to establish the frequency with which trials take into account missingness, and to discover what methods trialists use for adjustment in randomised controlled trials with longitudinal measurements. Failing to address the problems that can arise from missing outcome data can result in misleading conclusions. Missing data should be addressed as a means of a sensitivity analysis of the complete case analysis results. One hundred publications of randomised controlled trials with longitudinal measurements were selected randomly from trial publications from the years 2005 to 2012. Information was extracted from these trials, including whether reasons for dropout were reported, what methods were used for handing the missing data, whether there was any explanation of the methods for missing data handling, and whether a statistician was involved in the analysis. The main focus of the review was on missing data post dropout rather than missing interim data. Of all the papers in the study, 9 (9%) had no missing data. More than half of the papers included in the study failed to make any attempt to explain the reasons for their choice of missing data handling method. Of the papers with clear missing data handling methods, 44 papers (50%) used adequate methods of missing data handling, whereas 30 (34%) of the papers used missing data methods which may not have been appropriate. In the remaining 17 papers (19%), it was difficult to assess the validity of the methods used. An imputation method was used in 18 papers (20%). Multiple imputation methods were introduced in 1987 and are an efficient way of accounting for missing data in general, and yet only 4 papers used these methods. Out of the 18 papers which used imputation, only 7 displayed the results as a sensitivity analysis of the complete case analysis results. 61% of the papers that used an imputation explained the reasons for their chosen method. Just under a third of the papers made no reference to reasons for missing outcome data. There was little consistency in reporting of missing data within longitudinal trials. PMID:24947664

Comparison of minimally invasive spine surgery using intraoperative computed tomography integrated navigation, fluoroscopy, and conventional open surgery for lumbar spondylolisthesis: a prospective registry-based cohort study.

PubMed

Wu, Meng-Huang; Dubey, Navneet Kumar; Li, Yen-Yao; Lee, Ching-Yu; Cheng, Chin-Chang; Shi, Chung-Sheng; Huang, Tsung-Jen

2017-08-01

To date, the surgical approaches for the treatment of lumbar spondylolisthesis by transforaminal lumbar interbody fusion (TLIF) using minimally invasive spine surgery assisted with intraoperative computed tomography image-integrated navigation (MISS-iCT), fluoroscopy (MISS-FS), and conventional open surgery (OS) are debatable. This study compared TLIF using MISS-iCT, MISS-FS, and OS for treatment of one-level lumbar spondylolisthesis. This is a prospective, registry-based cohort study that compared surgical approaches for patients who underwent surgical treatment for one-level lumbar spondylolisthesis. One hundred twenty-four patients from January 2010 to March 2012 in a medical center were recruited. The outcome measures were clinical assessments, including Short-Form 12, visual analog scale (VAS), Oswestry Disability Index, Core Outcome Measurement Index, and patient satisfaction, and blood loss, hospital stay, operation time, postoperative pedicle screw accuracy, and superior-level facet violation. All surgeries were performed by two senior surgeons together. Ninety-nine patients (40M, 59F) who had at least 2 years' follow-up were divided into three groups according to the operation methods: MISS-iCT (N=24), MISS-FS (N=23), and OS (N=52) groups. Charts and surgical records along with postoperative CT images were assessed. MISS-iCT and MISS-FS demonstrated a significantly lowered blood loss and hospital stay compared with OS group (p<.01). Operation time was significantly lower in the MISS-iCT and OS groups compared with the MISS-FS group (p=.002). Postoperatively, VAS scores at 1 year and 2 years were significantly improved in the MISS-iCT and MISS-FS groups compared with the OS groups. No significant difference in the number of pedicle screw breach (>2 mm) was found. However, a lower superior-level facet violation rate was observed in the MISS-iCT and OS groups (p=.049). MISS-iCT TLIF demonstrated reduced operation time, blood loss, superior-level facet violation, hospital stay, and improved functional outcomes compared with the MISS-FS and OS approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Empirical evidence about inconsistency among studies in a pair‐wise meta‐analysis

PubMed Central

Turner, Rebecca M.; Higgins, Julian P. T.

2015-01-01

This paper investigates how inconsistency (as measured by the I2 statistic) among studies in a meta‐analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta‐analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta‐analyses were obtained, which can inform priors for between‐study variance. Inconsistency estimates were highest on average for binary outcome meta‐analyses of risk differences and continuous outcome meta‐analyses. For a planned binary outcome meta‐analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta‐analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta‐analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta‐analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. PMID:26679486

A prospective evaluation of missed injuries in trauma patients, before and after formalising the trauma tertiary survey.

PubMed

Keijzers, Gerben B; Campbell, Don; Hooper, Jeffrey; Bost, Nerolie; Crilly, Julia; Steele, Michael Craig; Del Mar, Chris; Geeraedts, Leo M G

2014-01-01

This study prospectively evaluated in-hospital and postdischarge missed injury rates in admitted trauma patients, before and after the formalisation of a trauma tertiary survey (TTS) procedure. Prospective before-and-after cohort study. TTS were formalised in a single regional level II trauma hospital in November 2009. All multitrauma patients admitted between March-October 2009 (preformalisation of TTS) and December 2009-September 2010 (post-) were assessed for missed injury, classified into three types: Type I, in-hospital, (injury missed at initial assessment, detected within 24 h); Type II, in-hospital (detected in hospital after 24 h, missed at initial assessment and by TTS); Type III, postdischarge (detected after hospital discharge). Secondary outcome measures included TTS performance rates and functional outcomes at 1 and 6 months. A total of 487 trauma patients were included (pre-: n = 235; post-: n = 252). In-hospital missed injury rate (Types I and II combined) was similar for both groups (3.8 vs. 4.8 %, P = 0.61), as were postdischarge missed injury rates (Type III) at 1 month (13.7 vs. 11.5 %, P = 0.43), and 6 months (3.8 vs. 3.3 %, P = 0.84) after discharge. TTS performance was substantially higher in the post-group (27 vs. 42 %, P < 0.001). Functional outcomes for both cohorts were similar at 1 and 6 months follow-up. This is the first study to evaluate missed injury rates after hospital discharge and demonstrated cumulative missed injury rates >15 %. Some of these injuries were clinically relevant. Although TTS performance was significantly improved by formalising the process (from 27 to 42 %), this did not decrease missed injury rates.

Cyclists' Anger As Determinant of Near Misses Involving Different Road Users.

PubMed

Marín Puchades, Víctor; Prati, Gabriele; Rondinella, Gianni; De Angelis, Marco; Fassina, Filippo; Fraboni, Federico; Pietrantoni, Luca

2017-01-01

Road anger constitutes one of the determinant factors related to safety outcomes (e.g., accidents, near misses). Although cyclists are considered vulnerable road users due to their relatively high rate of fatalities in traffic, previous research has solely focused on car drivers, and no study has yet investigated the effect of anger on cyclists' safety outcomes. The present research aims to investigate, for the first time, the effects of cycling anger toward different types of road users on near misses involving such road users and near misses in general. Using a daily diary web-based questionnaire, we collected data about daily trips, bicycle use, near misses experienced, cyclist's anger and demographic information from 254 Spanish cyclists. Poisson regression was used to assess the association of cycling anger with near misses, which is a count variable. No relationship was found between general cycling anger and near misses occurrence. Anger toward specific road users had different effects on the probability of near misses with different road users. Anger toward the interaction with car drivers increased the probability of near misses involving cyclists and pedestrians. Anger toward interaction with pedestrians was associated with higher probability of near misses with pedestrians. Anger toward cyclists exerted no effect on the probability of near misses with any road user (i.e., car drivers, cyclists or pedestrians), whereas anger toward the interactions with the police had a diminishing effect on the occurrence of near misses' involving all types of road users. The present study demonstrated that the effect of road anger on safety outcomes among cyclists is different from that of motorists. Moreover, the target of anger played an important role on safety both for the cyclist and the specific road users. Possible explanations for these differences are based on the difference in status and power with motorists, as well as on the potential displaced aggression produced by the fear of retaliation by motorized vehicle users.

Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study

PubMed Central

Sescousse, Guillaume; Yu, Hongbo; Clark, Luke; Li, Hong

2018-01-01

Increased cognitive distortions (i.e. biased processing of chance, probability and skill) are a key psychopathological process in disordered gambling. The present study investigated state and trait aspects of cognitive distortions in 22 individuals with Internet Gaming Disorder (IGD) and 22 healthy controls. Participants completed the Gambling Related Cognitions Scale as a trait measure of cognitive distortions, and played a slot machine task delivering wins, near-misses and full-misses. Ratings of pleasure (“liking”) and motivation to play (“wanting”) were taken following the different outcomes, and gambling persistence was measured after a mandatory phase. IGD was associated with elevated trait cognitive distortions, in particular skill-oriented cognitions. On the slot machine task, the IGD group showed increased “wanting” ratings compared with control participants, while the two groups did not differ regarding their “liking” of the game. The IGD group displayed increased persistence on the slot machine task. Near-miss outcomes did not elicit stronger motivation to play compared to full-miss outcomes overall, and there was no group difference on this measure. However, a near-miss position effect was observed, such that near-misses stopping before the payline were rated as more motivating than near-misses that stopped after the payline, and this differentiation was attenuated in the IGD group, suggesting possible counterfactual thinking deficits in this group. These data provide preliminary evidence for increased incentive motivation and cognitive distortions in IGD, at least in the context of a chance-based gambling environment. PMID:29346434

Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study.

PubMed

Wu, Yin; Sescousse, Guillaume; Yu, Hongbo; Clark, Luke; Li, Hong

2018-01-01

Increased cognitive distortions (i.e. biased processing of chance, probability and skill) are a key psychopathological process in disordered gambling. The present study investigated state and trait aspects of cognitive distortions in 22 individuals with Internet Gaming Disorder (IGD) and 22 healthy controls. Participants completed the Gambling Related Cognitions Scale as a trait measure of cognitive distortions, and played a slot machine task delivering wins, near-misses and full-misses. Ratings of pleasure ("liking") and motivation to play ("wanting") were taken following the different outcomes, and gambling persistence was measured after a mandatory phase. IGD was associated with elevated trait cognitive distortions, in particular skill-oriented cognitions. On the slot machine task, the IGD group showed increased "wanting" ratings compared with control participants, while the two groups did not differ regarding their "liking" of the game. The IGD group displayed increased persistence on the slot machine task. Near-miss outcomes did not elicit stronger motivation to play compared to full-miss outcomes overall, and there was no group difference on this measure. However, a near-miss position effect was observed, such that near-misses stopping before the payline were rated as more motivating than near-misses that stopped after the payline, and this differentiation was attenuated in the IGD group, suggesting possible counterfactual thinking deficits in this group. These data provide preliminary evidence for increased incentive motivation and cognitive distortions in IGD, at least in the context of a chance-based gambling environment.

The Influence of Tardy Classmates on Students' Socio-Emotional Outcomes

ERIC Educational Resources Information Center

Gottfried, Michael A.

2014-01-01

Background/Context: Researchers, policymakers, and practitioners undoubtedly concur that missing school deteriorates student outcomes. And yet, in evaluating the deleterious effects of missing in-school time, empirical research has almost exclusively focused on absences, and the scant amount of empirical literature on tardiness has focused on…

Causal analysis of ordinal treatments and binary outcomes under truncation by death.

PubMed

Wang, Linbo; Richardson, Thomas S; Zhou, Xiao-Hua

2017-06-01

It is common that in multi-arm randomized trials, the outcome of interest is "truncated by death," meaning that it is only observed or well-defined conditioning on an intermediate outcome. In this case, in addition to pairwise contrasts, the joint inference for all treatment arms is also of interest. Under a monotonicity assumption we present methods for both pairwise and joint causal analyses of ordinal treatments and binary outcomes in presence of truncation by death. We illustrate via examples the appropriateness of our assumptions in different scientific contexts.

Missing Not at Random Models for Latent Growth Curve Analyses

ERIC Educational Resources Information Center

Enders, Craig K.

2011-01-01

The past decade has seen a noticeable shift in missing data handling techniques that assume a missing at random (MAR) mechanism, where the propensity for missing data on an outcome is related to other analysis variables. Although MAR is often reasonable, there are situations where this assumption is unlikely to hold, leading to biased parameter…

A model for incomplete longitudinal multivariate ordinal data.

PubMed

Liu, Li C

2008-12-30

In studies where multiple outcome items are repeatedly measured over time, missing data often occur. A longitudinal item response theory model is proposed for analysis of multivariate ordinal outcomes that are repeatedly measured. Under the MAR assumption, this model accommodates missing data at any level (missing item at any time point and/or missing time point). It allows for multiple random subject effects and the estimation of item discrimination parameters for the multiple outcome items. The covariates in the model can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is described utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher-scoring solution, which provides standard errors for all model parameters, is used. A data set from a longitudinal prevention study is used to motivate the application of the proposed model. In this study, multiple ordinal items of health behavior are repeatedly measured over time. Because of a planned missing design, subjects answered only two-third of all items at a given point. Copyright 2008 John Wiley & Sons, Ltd.

The dynamical mass of a classical Cepheid variable star in an eclipsing binary system.

PubMed

Pietrzyński, G; Thompson, I B; Gieren, W; Graczyk, D; Bono, G; Udalski, A; Soszyński, I; Minniti, D; Pilecki, B

2010-11-25

Stellar pulsation theory provides a means of determining the masses of pulsating classical Cepheid supergiants-it is the pulsation that causes their luminosity to vary. Such pulsational masses are found to be smaller than the masses derived from stellar evolution theory: this is the Cepheid mass discrepancy problem, for which a solution is missing. An independent, accurate dynamical mass determination for a classical Cepheid variable star (as opposed to type-II Cepheids, low-mass stars with a very different evolutionary history) in a binary system is needed in order to determine which is correct. The accuracy of previous efforts to establish a dynamical Cepheid mass from Galactic single-lined non-eclipsing binaries was typically about 15-30% (refs 6, 7), which is not good enough to resolve the mass discrepancy problem. In spite of many observational efforts, no firm detection of a classical Cepheid in an eclipsing double-lined binary has hitherto been reported. Here we report the discovery of a classical Cepheid in a well detached, double-lined eclipsing binary in the Large Magellanic Cloud. We determine the mass to a precision of 1% and show that it agrees with its pulsation mass, providing strong evidence that pulsation theory correctly and precisely predicts the masses of classical Cepheids.

Comparing object recognition from binary and bipolar edge images for visual prostheses

PubMed Central

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2017-01-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

Addressing the Challenges of Obtaining Functional Outcomes in Traumatic Brain Injury Research: Missing Data Patterns, Timing of Follow-Up, and Three Prognostic Models

PubMed Central

Morrison, Laurie J.; Devlin, Sean M.; Bulger, Eileen M.; Brasel, Karen J.; Sheehan, Kellie; Minei, Joseph P.; Kerby, Jeffrey D.; Tisherman, Samuel A.; Rizoli, Sandro; Karmy-Jones, Riyad; van Heest, Rardi; Newgard, Craig D.

2014-01-01

Abstract Traumatic brain injury (TBI) is common and debilitating. Randomized trials of interventions for TBI ideally assess effectiveness by using long-term functional neurological outcomes, but such outcomes are difficult to obtain and costly. If there is little change between functional status at hospital discharge versus 6 months, then shorter-term outcomes may be adequate for use in future clinical trials. Using data from a previously published multi-center, randomized, placebo-controlled TBI clinical trial, we evaluated patterns of missing outcome data, changes in functional status between hospital discharge and 6 months, and three prognostic models to predict long-term functional outcome from covariates available at hospital discharge (functional measures, demographics, and injury characteristics). The Resuscitation Outcomes Consortium Hypertonic Saline trial enrolled 1282 TBI patients, obtaining the primary outcome of 6-month Glasgow Outcome Score Extended (GOSE) for 85% of patients, but missing the primary outcome for the remaining 15%. Patients with missing outcomes had less-severe injuries, higher neurological function at discharge (GOSE), and shorter hospital stays than patients whose GOSE was obtained. Of 1066 (83%) patients whose GOSE was obtained both at hospital discharge and at 6-months, 71% of patients had the same dichotomized functional status (severe disability/death vs. moderate/no disability) after 6 months as at discharge, 28% had an improved functional status, and 1% had worsened. Performance was excellent (C-statistic between 0.88 and 0.91) for all three prognostic models and calibration adequate for two models (p values, 0.22 and 0.85). Our results suggest that multiple imputation of the standard 6-month GOSE may be reasonable in TBI research when the primary outcome cannot be obtained through other means. PMID:24552494

Addressing the challenges of obtaining functional outcomes in traumatic brain injury research: missing data patterns, timing of follow-up, and three prognostic models.

PubMed

Zelnick, Leila R; Morrison, Laurie J; Devlin, Sean M; Bulger, Eileen M; Brasel, Karen J; Sheehan, Kellie; Minei, Joseph P; Kerby, Jeffrey D; Tisherman, Samuel A; Rizoli, Sandro; Karmy-Jones, Riyad; van Heest, Rardi; Newgard, Craig D

2014-06-01

Traumatic brain injury (TBI) is common and debilitating. Randomized trials of interventions for TBI ideally assess effectiveness by using long-term functional neurological outcomes, but such outcomes are difficult to obtain and costly. If there is little change between functional status at hospital discharge versus 6 months, then shorter-term outcomes may be adequate for use in future clinical trials. Using data from a previously published multi-center, randomized, placebo-controlled TBI clinical trial, we evaluated patterns of missing outcome data, changes in functional status between hospital discharge and 6 months, and three prognostic models to predict long-term functional outcome from covariates available at hospital discharge (functional measures, demographics, and injury characteristics). The Resuscitation Outcomes Consortium Hypertonic Saline trial enrolled 1282 TBI patients, obtaining the primary outcome of 6-month Glasgow Outcome Score Extended (GOSE) for 85% of patients, but missing the primary outcome for the remaining 15%. Patients with missing outcomes had less-severe injuries, higher neurological function at discharge (GOSE), and shorter hospital stays than patients whose GOSE was obtained. Of 1066 (83%) patients whose GOSE was obtained both at hospital discharge and at 6-months, 71% of patients had the same dichotomized functional status (severe disability/death vs. moderate/no disability) after 6 months as at discharge, 28% had an improved functional status, and 1% had worsened. Performance was excellent (C-statistic between 0.88 and 0.91) for all three prognostic models and calibration adequate for two models (p values, 0.22 and 0.85). Our results suggest that multiple imputation of the standard 6-month GOSE may be reasonable in TBI research when the primary outcome cannot be obtained through other means.

Sociodemographic profile and predictors of outpatient clinic attendance among HIV-positive patients initiating antiretroviral therapy in Selangor, Malaysia.

PubMed

Abdulrahman, Surajudeen Abiola; Rampal, Lekhraj; Othman, Norlijah; Ibrahim, Faisal; Hayati, Kadir Shahar; Radhakrishnan, Anuradha P

2017-01-01

Inconsistent literature evidence suggests that sociodemographic, economic, and system- and patient-related factors are associated with clinic attendance among the HIV-positive population receiving antiretroviral therapy (ART) around the world. We examined the factors that predict outpatient clinic attendance among a cohort of HIV-positive patients initiating ART in Selangor, Malaysia. This cross-sectional study analyzed secondary data on outpatient clinic attendance and sociodemographic, economic, psychosocial, and patient-related factors among 242 adult Malaysian patients initiating ART in Selangor, Malaysia. Study cohort was enrolled in a parent randomized controlled trial (RCT) in Hospital Sungai Buloh Malaysia between January and December 2014, during which peer counseling, medication, and clinic appointment reminders were provided to the intervention group through short message service (SMS) and telephone calls for 24 consecutive weeks. Data on outpatient clinic attendance were extracted from the hospital electronic medical records system, while other patient-level data were extracted from pre-validated Adult AIDS Clinical Trial Group (AACTG) adherence questionnaires in which primary data were collected. Outpatient clinic attendance was categorized into binary outcome - regular attendee and defaulter categories - based on the number of missed scheduled outpatient clinic appointments within a 6-month period. Multivariate regression models were fitted to examine predictors of outpatient clinic attendance using SPSS version 22 and R software. A total of 224 (93%) patients who completed 6-month assessment were included in the model. Out of those, 42 (18.7%) defaulted scheduled clinic attendance at least once. Missed appointments were significantly more prevalent among females (n=10, 37.0%), rural residents (n=10, 38.5%), and bisexual respondents (n=8, 47.1%). Multivariate binary logistic regression analysis showed that Indian ethnicity (adjusted odds ratio [AOR] =0.235; 95% CI [0.063-0.869]; P =0.030) and heterosexual orientation (AOR =4.199; 95% CI [1.040-16.957]; P =0.044) were significant predictors of outpatient clinic attendance among HIV-positive patients receiving ART in Malaysia. Ethnicity and sexual orientation of Malaysian patients may play a significant role in their level of adherence to scheduled clinic appointments. These factors should be considered during collaborative adherence strategy planning at ART initiation.

Empirical evidence about inconsistency among studies in a pair-wise meta-analysis.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; Higgins, Julian P T

2016-12-01

This paper investigates how inconsistency (as measured by the I 2 statistic) among studies in a meta-analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta-analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta-analyses were obtained, which can inform priors for between-study variance. Inconsistency estimates were highest on average for binary outcome meta-analyses of risk differences and continuous outcome meta-analyses. For a planned binary outcome meta-analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta-analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta-analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta-analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

Suspended Education in Massachusetts: Using Days of Lost Instruction Due to Suspension to Evaluate Our Schools

ERIC Educational Resources Information Center

Losen, Daniel J.; Sun, Wei-Ling; Keith, Michael A., II

2017-01-01

Missed instruction can have a devastating impact on educational outcomes. Some reasons for missed instruction are beyond the control of schools and districts: some students miss school due to mental or physical illness or injury, and transportation problems sometimes are to blame. One major reason for missed instruction that schools can directly…

A Framework for Designing Cluster Randomized Trials with Binary Outcomes

ERIC Educational Resources Information Center

Spybrook, Jessaca; Martinez, Andres

2011-01-01

The purpose of this paper is to provide a frame work for approaching a power analysis for a CRT (cluster randomized trial) with a binary outcome. The authors suggest a framework in the context of a simple CRT and then extend it to a blocked design, or a multi-site cluster randomized trial (MSCRT). The framework is based on proportions, an…

Fetal and neonatal deaths of children of patients classified as near miss.

PubMed

Nardello, Daniele Marin; Guimarães, Alzira Maria D Avila Nery; Barreto, Ikaro Daniel de Carvalho; Gurgel, Ricardo Queiroz; Ribeiro, Eleonora Ramos de Oliveira; Gois, Cristiane Franca Lisboa

2017-01-01

identify the epidemiological aspects of early fetal and neonatal deaths in children of patients classified with near miss and the factors associated with this outcome. a cross-sectional study of 79 women identified with near miss and their newborns. The variables were analyzed using Fisher's exact test. Risk factors were estimated based on unadjusted and adjusted odds ratios, and by means of multiple correspondence analysis, with significance for p <0.05. hypertensive disorders totaled 40.5%; Of these, 58.3% had adverse fetal and neonatal outcome. The newborns admitted to the Neonatal Intensive Care Unit proved to be significant for the outcome (70.8%), gestational age <32 weeks (41.6%), birth weight <2500 (66.7%), neonatal asphyxia (50%) and early respiratory discomfort (72.2%). prematurity, neonatal asphyxia, and early respiratory distress were significant characteristics for the outcome among newborns.

Optimal simultaneous superpositioning of multiple structures with missing data.

PubMed

Theobald, Douglas L; Steindel, Phillip A

2012-08-01

Superpositioning is an essential technique in structural biology that facilitates the comparison and analysis of conformational differences among topologically similar structures. Performing a superposition requires a one-to-one correspondence, or alignment, of the point sets in the different structures. However, in practice, some points are usually 'missing' from several structures, for example, when the alignment contains gaps. Current superposition methods deal with missing data simply by superpositioning a subset of points that are shared among all the structures. This practice is inefficient, as it ignores important data, and it fails to satisfy the common least-squares criterion. In the extreme, disregarding missing positions prohibits the calculation of a superposition altogether. Here, we present a general solution for determining an optimal superposition when some of the data are missing. We use the expectation-maximization algorithm, a classic statistical technique for dealing with incomplete data, to find both maximum-likelihood solutions and the optimal least-squares solution as a special case. The methods presented here are implemented in THESEUS 2.0, a program for superpositioning macromolecular structures. ANSI C source code and selected compiled binaries for various computing platforms are freely available under the GNU open source license from http://www.theseus3d.org. dtheobald@brandeis.edu Supplementary data are available at Bioinformatics online.

Standards should be applied in the prevention and handling of missing data for patient-centered outcomes research: a systematic review and expert consensus.

PubMed

Li, Tianjing; Hutfless, Susan; Scharfstein, Daniel O; Daniels, Michael J; Hogan, Joseph W; Little, Roderick J A; Roy, Jason A; Law, Andrew H; Dickersin, Kay

2014-01-01

To recommend methodological standards in the prevention and handling of missing data for primary patient-centered outcomes research (PCOR). We searched National Library of Medicine Bookshelf and Catalog as well as regulatory agencies' and organizations' Web sites in January 2012 for guidance documents that had formal recommendations regarding missing data. We extracted the characteristics of included guidance documents and recommendations. Using a two-round modified Delphi survey, a multidisciplinary panel proposed mandatory standards on the prevention and handling of missing data for PCOR. We identified 1,790 records and assessed 30 as having relevant recommendations. We proposed 10 standards as mandatory, covering three domains. First, the single best approach is to prospectively prevent missing data occurrence. Second, use of valid statistical methods that properly reflect multiple sources of uncertainty is critical when analyzing missing data. Third, transparent and thorough reporting of missing data allows readers to judge the validity of the findings. We urge researchers to adopt rigorous methodology and promote good science by applying best practices to the prevention and handling of missing data. Developing guidance on the prevention and handling of missing data for observational studies and studies that use existing records is a priority for future research. Copyright © 2014 Elsevier Inc. All rights reserved.

Multivariate Bayesian analysis of Gaussian, right censored Gaussian, ordered categorical and binary traits using Gibbs sampling

PubMed Central

Korsgaard, Inge Riis; Lund, Mogens Sandø; Sorensen, Daniel; Gianola, Daniel; Madsen, Per; Jensen, Just

2003-01-01

A fully Bayesian analysis using Gibbs sampling and data augmentation in a multivariate model of Gaussian, right censored, and grouped Gaussian traits is described. The grouped Gaussian traits are either ordered categorical traits (with more than two categories) or binary traits, where the grouping is determined via thresholds on the underlying Gaussian scale, the liability scale. Allowances are made for unequal models, unknown covariance matrices and missing data. Having outlined the theory, strategies for implementation are reviewed. These include joint sampling of location parameters; efficient sampling from the fully conditional posterior distribution of augmented data, a multivariate truncated normal distribution; and sampling from the conditional inverse Wishart distribution, the fully conditional posterior distribution of the residual covariance matrix. Finally, a simulated dataset was analysed to illustrate the methodology. This paper concentrates on a model where residuals associated with liabilities of the binary traits are assumed to be independent. A Bayesian analysis using Gibbs sampling is outlined for the model where this assumption is relaxed. PMID:12633531

No cataclysmic variables missing: higher merger rate brings into agreement observed and predicted space densities

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Schreiber, Matthias R.; Zorotovic, Mónica; Iłkiewicz, Krystian; Hurley, Jarrod R.; Giersz, Mirek; Lagos, Felipe

2018-06-01

The predicted and observed space density of cataclysmic variables (CVs) have been for a long time discrepant by at least an order of magnitude. The standard model of CV evolution predicts that the vast majority of CVs should be period bouncers, whose space density has been recently measured to be ρ ≲ 2 × 10-5 pc-3. We performed population synthesis of CVs using an updated version of the Binary Stellar Evolution (BSE) code for single and binary star evolution. We find that the recently suggested empirical prescription of consequential angular momentum loss (CAML) brings into agreement predicted and observed space densities of CVs and period bouncers. To progress with our understanding of CV evolution it is crucial to understand the physical mechanism behind empirical CAML. Our changes to the BSE code are also provided in details, which will allow the community to accurately model mass transfer in interacting binaries in which degenerate objects accrete from low-mass main-sequence donor stars.

Monitoring the quality of cardiac surgery based on three or more surgical outcomes using a new variable life-adjusted display.

PubMed

Gan, Fah Fatt; Tang, Xu; Zhu, Yexin; Lim, Puay Weng

2017-06-01

The traditional variable life-adjusted display (VLAD) is a graphical display of the difference between expected and actual cumulative deaths. The VLAD assumes binary outcomes: death within 30 days of an operation or survival beyond 30 days. Full recovery and bedridden for life, for example, are considered the same outcome. This binary classification results in a great loss of information. Although there are many grades of survival, the binary outcomes are commonly used to classify surgical outcomes. Consequently, quality monitoring procedures are developed based on binary outcomes. With a more refined set of outcomes, the sensitivities of these procedures can be expected to improve. A likelihood ratio method is used to define a penalty-reward scoring system based on three or more surgical outcomes for the new VLAD. The likelihood ratio statistic W is based on testing the odds ratio of cumulative probabilities of recovery R. Two methods of implementing the new VLAD are proposed. We accumulate the statistic W-W¯R to estimate the performance of a surgeon where W¯R is the average of the W's of a historical data set. The accumulated sum will be zero based on the historical data set. This ensures that if a new VLAD is plotted for a future surgeon of performance similar to this average performance, the plot will exhibit a horizontal trend. For illustration of the new VLAD, we consider 3-outcome surgical results: death within 30 days, partial and full recoveries. In our first illustration, we show the effect of partial recoveries on surgical results of a surgeon. In our second and third illustrations, the surgical results of two surgeons are compared using both the traditional VLAD based on binary-outcome data and the new VLAD based on 3-outcome data. A reversal in relative performance of surgeons is observed when the new VLAD is used. In our final illustration, we display the surgical results of four surgeons using the new VLAD based completely on 3-outcome data. Full recovery and bedridden for life are two completely different outcomes. There is a great loss of information when different grades of 'successful' operations are naively classified as survival. When surgical outcomes are classified more accurately into more than two categories, the resulting new VLAD will reveal more accurately and fairly the surgical results. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

The Primordial Binary Fraction in Trumpler 14: Frequency and Multiplicity Parameters

NASA Astrophysics Data System (ADS)

Sabbi, Elena

2017-08-01

This is an astrometric proposal designed to identify and characterize the properties of medium- and long-period (orbital periods ranging from 1.8 to 100 years) visual binaries in the mass range between 4 and 20 Mo in the young compact cluster Trumpler 14 in the Carina Nebula. We aim to probe the virtually unexplored population of intermediate- and high-mass binaries that will experience a Roche-lobe overflow during their post-main-sequence evolution. These binaries are of particular interest because they are expected to be the progenitors of supernovae Type Ia, b, and c, X-ray binaries, double neutron stars and double black holes. Multiplicity properties of young stars can be further used to constrain the outcome of the star-formation process and hence distinguish between various formation scenarios. The medium- and long-period binaries (P> 0.5 yr) are hard to detect and expensive to characterize with traditional ground-based spectroscopy. Knowledge of their orbital properties is however crucial to properly estimate the overall fraction of OB stars whose evolution is affected by binary interaction and to predict the outcome of such interaction. Because of the well characterized PSF of WFC3/UVIS and its temporal stability, HST is the only facility able to characterize the properties of OB-type medium-period binaries in Tr14, and Tr14 is the only nearby high-density OB-type young cluster.

Systematic review of the quality of prognosis studies in systemic lupus erythematosus.

PubMed

Lim, Lily S H; Lee, Senq J; Feldman, Brian M; Gladman, Dafna D; Pullenayegum, Eleanor; Uleryk, Elizabeth; Silverman, Earl D

2014-10-01

Prognosis studies examine outcomes and/or seek to identify predictors or factors associated with outcomes. Many prognostic factors have been identified in systemic lupus erythematosus (SLE), but few have been consistently found across studies. We hypothesized that this is due to a lack of rigor of study designs. This study aimed to systematically assess the methodologic quality of prognosis studies in SLE. A search of prognosis studies in SLE was performed using MEDLINE and Embase, from January 1990 to June 2011. A representative sample of 150 articles was selected using a random number generator and assessed by 2 reviewers. Each study was assessed by a risk of bias tool according to 6 domains: study participation, study attrition, measurement of prognostic factors, measurement of outcomes, measurement/adjustment for confounders, and appropriateness of statistical analysis. Information about missing data was also collected. A cohort design was used in 71% of studies. High risk of bias was found in 65% of studies for confounders, 57% for study participation, 56% for attrition, 36% for statistical analyses, 20% for prognostic factors, and 18% for outcome. Missing covariate or outcome information was present in half of the studies. Only 6 studies discussed reasons for missing data and 2 imputed missing data. Lack of rigorous study design, especially in addressing confounding, study participation and attrition, and inadequately handled missing data, has limited the quality of prognosis studies in SLE. Future prognosis studies should be designed with consideration of these factors to improve methodologic rigor. Copyright © 2014 by the American College of Rheumatology.

Transfusion Indication Threshold Reduction (TITRe2) randomized controlled trial in cardiac surgery: statistical analysis plan.

PubMed

Pike, Katie; Nash, Rachel L; Murphy, Gavin J; Reeves, Barnaby C; Rogers, Chris A

2015-02-22

The Transfusion Indication Threshold Reduction (TITRe2) trial is the largest randomized controlled trial to date to compare red blood cell transfusion strategies following cardiac surgery. This update presents the statistical analysis plan, detailing how the study will be analyzed and presented. The statistical analysis plan has been written following recommendations from the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, prior to database lock and the final analysis of trial data. Outlined analyses are in line with the Consolidated Standards of Reporting Trials (CONSORT). The study aims to randomize 2000 patients from 17 UK centres. Patients are randomized to either a restrictive (transfuse if haemoglobin concentration <7.5 g/dl) or liberal (transfuse if haemoglobin concentration <9 g/dl) transfusion strategy. The primary outcome is a binary composite outcome of any serious infectious or ischaemic event in the first 3 months following randomization. The statistical analysis plan details how non-adherence with the intervention, withdrawals from the study, and the study population will be derived and dealt with in the analysis. The planned analyses of the trial primary and secondary outcome measures are described in detail, including approaches taken to deal with multiple testing, model assumptions not being met and missing data. Details of planned subgroup and sensitivity analyses and pre-specified ancillary analyses are given, along with potential issues that have been identified with such analyses and possible approaches to overcome such issues. ISRCTN70923932 .

Corrigendum to "Matrix-algebra-based calculations of the time evolution of the binary spin-bath model for magnetization transfer" [J. Magn. Reson. 230 (2013) 88-97

NASA Astrophysics Data System (ADS)

Müller, Dirk K.; Pampel, André; Möller, Harald E.

2015-12-01

In the print version of this article initially published, reference to a funding source was missing. The following information should be added to the Acknowledgements section: This work was funded (in part) by the Helmholtz Alliance ICEMED-Imaging and Curing Environmental Metabolic Diseases, through the Initiative and Networking Fund of the Helmholtz Association.

Connecting traces of galaxy evolution: the missing core mass-morphological fine structure relation

NASA Astrophysics Data System (ADS)

Bonfini, P.; Bitsakis, T.; Zezas, A.; Duc, P.-A.; Iodice, E.; González-Martín, O.; Bruzual, G.; González Sanoja, A. J.

2018-01-01

Deep exposure imaging of early-type galaxies (ETGs) are revealing the second-order complexity of these objects, which have been long considered uniform, dispersion-supported spheroidals. `Fine structure' features (e.g. ripples, plumes, tidal tails, rings) as well as depleted stellar cores (i.e. central light deficits) characterize a number of massive ETG galaxies, and can be interpreted as the result of galaxy-galaxy interactions. We discuss how the time-scale for the evolution of cores and fine structures are comparable, and hence it is expected that they develop in parallel after the major interaction event which shaped the ETG. Using archival data, we compare the `depleted stellar mass' (i.e. the mass missing from the depleted stellar core) against the prominence of the fine structure features, and observe that they correlate inversely. This result confirms our expectation that, while the supermassive black hole (SMBH) binary (constituted by the SMBHs of the merger progenitors) excavates the core via three-body interactions, the gravitational potential of the newborn galaxy relaxes, and the fine structures fade below detection levels. We expect the inverse correlation to hold at least within the first Gyr from the merger which created the SMBH binary; after then, the fine structure evolves independently.

Reporting and Handling Missing Outcome Data in Mental Health: A Systematic Review of Cochrane Systematic Reviews and Meta-Analyses

ERIC Educational Resources Information Center

Spineli, Loukia M.; Pandis, Nikolaos; Salanti, Georgia

2015-01-01

Objectives: The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. Methods: Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by…

Effects of Missing Data Methods in SEM under Conditions of Incomplete and Nonnormal Data

ERIC Educational Resources Information Center

Li, Jian; Lomax, Richard G.

2017-01-01

Using Monte Carlo simulations, this research examined the performance of four missing data methods in SEM under different multivariate distributional conditions. The effects of four independent variables (sample size, missing proportion, distribution shape, and factor loading magnitude) were investigated on six outcome variables: convergence rate,…

Multiple imputation for assessment of exposures to drinking water contaminants: evaluation with the Atrazine Monitoring Program.

PubMed

Jones, Rachael M; Stayner, Leslie T; Demirtas, Hakan

2014-10-01

Drinking water may contain pollutants that harm human health. The frequency of pollutant monitoring may occur quarterly, annually, or less frequently, depending upon the pollutant, the pollutant concentration, and community water system. However, birth and other health outcomes are associated with narrow time-windows of exposure. Infrequent monitoring impedes linkage between water quality and health outcomes for epidemiological analyses. To evaluate the performance of multiple imputation to fill in water quality values between measurements in community water systems (CWSs). The multiple imputation method was implemented in a simulated setting using data from the Atrazine Monitoring Program (AMP, 2006-2009 in five Midwestern states). Values were deleted from the AMP data to leave one measurement per month. Four patterns reflecting drinking water monitoring regulations were used to delete months of data in each CWS: three patterns were missing at random and one pattern was missing not at random. Synthetic health outcome data were created using a linear and a Poisson exposure-response relationship with five levels of hypothesized association, respectively. The multiple imputation method was evaluated by comparing the exposure-response relationships estimated based on multiply imputed data with the hypothesized association. The four patterns deleted 65-92% months of atrazine observations in AMP data. Even with these high rates of missing information, our procedure was able to recover most of the missing information when the synthetic health outcome was included for missing at random patterns and for missing not at random patterns with low-to-moderate exposure-response relationships. Multiple imputation appears to be an effective method for filling in water quality values between measurements. Copyright © 2014 Elsevier Inc. All rights reserved.

Does a missed obstetric anal sphincter injury at time of delivery affect short-term functional outcome?

PubMed

Ramage, L; Yen, C; Qiu, S; Simillis, C; Kontovounisios, C; Tan, E; Tekkis, P

2018-01-01

Introduction This study aimed to ascertain whether missed obstetric anal sphincter injury at delivery had worse functional and quality of life outcomes than primary repair immediately following delivery. Materials and methods Two to one propensity matching was undertaken of patients presenting to a tertiary pelvic floor unit with ultrasound evidence of missed obstetric anal sphincter injury within 24 months of delivery with patients who underwent primary repair at the time of delivery by parity, grade of injury and time to assessment. Outcomes compared included Birmingham Bowel, Bladder and Urinary Symptom Questionnaire (BBUSQ), Wexner Incontinence Score, Short Form-36, Pelvic Organ Prolapse/Urinary Incontinence Sexual Questionnaire and anorectal physiology results. Results Thirty-two missed anal sphincter injuries were matched two to one with sixty-two patients who underwent primary repair of an anal sphincter defect. Mean time to follow-up was 9.31 ± 6.79 months. Patients with a missed anal sphincter injury had suffered more incontinence, as seen in higher the Birmingham Bowel, Bladder and Urinary Symptom Questionnaire (BBUSQ; 30.56% ± 14.41% vs. 19.75% ± 15.65%, P = 0.002) and Wexner scores (6.00 ± 3.76 vs. 3.67 ± 4.06, P = 0.009). They also had a worse BBUSQ urinary domain score (28.25% ± 14.9% vs. 17.01 ± 13.87%, P = 0.001) and worse physical functioning as measured by the Short Form-36 questionnaire (P = 0.045). There were no differences in other outcomes compared, including anorectal physiology and sexual function. Discussion In the short-term, patients with a missed obstetric anal sphincter injury had significantly worse faecal incontinence and urinary function scores, however quality of life and sexual function were largely comparable between groups. Conclusions Longer-term follow-up is needed to assess the effects of missed obstetric anal sphincter injury over time.

Amplified Striatal Responses to Near-Miss Outcomes in Pathological Gamblers

PubMed Central

Sescousse, Guillaume; Janssen, Lieneke K; Hashemi, Mahur M; Timmer, Monique H M; Geurts, Dirk E M; ter Huurne, Niels P; Clark, Luke; Cools, Roshan

2016-01-01

Near-misses in gambling games are losing events that come close to a win. Near-misses were previously shown to recruit reward-related brain regions including the ventral striatum, and to invigorate gambling behavior, supposedly by fostering an illusion of control. Given that pathological gamblers are particularly vulnerable to such cognitive illusions, their persistent gambling behavior might result from an amplified striatal sensitivity to near-misses. In addition, animal studies have shown that behavioral responses to near-miss-like events are sensitive to dopamine, but this dopaminergic influence has not been tested in humans. To investigate these hypotheses, we recruited 22 pathological gamblers and 22 healthy controls who played a slot machine task delivering wins, near-misses and full-misses, inside an fMRI scanner. Each participant played the task twice, once under placebo and once under a dopamine D2 receptor antagonist (sulpiride 400 mg), in a double-blind, counter-balanced design. Participants were asked about their motivation to continue gambling throughout the task. Across all participants, near-misses elicited higher motivation to continue gambling and increased striatal responses compared with full-misses. Crucially, pathological gamblers showed amplified striatal responses to near-misses compared with controls. These group differences were not observed following win outcomes. In contrast to our hypothesis, sulpiride did not induce any reliable modulation of brain responses to near-misses. Together, our results demonstrate that pathological gamblers have amplified brain responses to near-misses, which likely contribute to their persistent gambling behavior. However, there is no evidence that these responses are influenced by dopamine. These results have implications for treatment and gambling regulation. PMID:27006113

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

A sensitivity analysis for missing outcomes due to truncation by death under the matched-pairs design.

PubMed

Imai, Kosuke; Jiang, Zhichao

2018-04-29

The matched-pairs design enables researchers to efficiently infer causal effects from randomized experiments. In this paper, we exploit the key feature of the matched-pairs design and develop a sensitivity analysis for missing outcomes due to truncation by death, in which the outcomes of interest (e.g., quality of life measures) are not even well defined for some units (e.g., deceased patients). Our key idea is that if 2 nearly identical observations are paired prior to the randomization of the treatment, the missingness of one unit's outcome is informative about the potential missingness of the other unit's outcome under an alternative treatment condition. We consider the average treatment effect among always-observed pairs (ATOP) whose units exhibit no missing outcome regardless of their treatment status. The naive estimator based on available pairs is unbiased for the ATOP if 2 units of the same pair are identical in terms of their missingness patterns. The proposed sensitivity analysis characterizes how the bounds of the ATOP widen as the degree of the within-pair similarity decreases. We further extend the methodology to the matched-pairs design in observational studies. Our simulation studies show that informative bounds can be obtained under some scenarios when the proportion of missing data is not too large. The proposed methodology is also applied to the randomized evaluation of the Mexican universal health insurance program. An open-source software package is available for implementing the proposed research. Copyright © 2018 John Wiley & Sons, Ltd.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

The Structure and Composition Statistics of 6A Binary and Ternary Crystalline Materials.

PubMed

Hever, Alon; Oses, Corey; Curtarolo, Stefano; Levy, Ohad; Natan, Amir

2018-01-16

The fundamental principles underlying the arrangement of elements into solid compounds with an enormous variety of crystal structures are still largely unknown. This study presents a general overview of the structure types appearing in an important subset of the solid compounds, i.e., binary and ternary compounds of the 6A column oxides, sulfides and selenides. It contains an analysis of these compounds, including the prevalence of various structure types, their symmetry properties, compositions, stoichiometries and unit cell sizes. It is found that these compound families include preferred stoichiometries and structure types that may reflect both their specific chemistry and research bias in the available empirical data. Identification of nonoverlapping gaps and missing stoichiometries in these structure populations may be used as guidance in the search for new materials.

Incomplete fuzzy data processing systems using artificial neural network

NASA Technical Reports Server (NTRS)

Patyra, Marek J.

1992-01-01

In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

The presence of missing data is a limitation of large datasets, including the National Surgical Quality Improvement Program (NSQIP). In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias. Multiple imputation, a statistically rigorous approach that approximates missing data and preserves sample size, may be an improvement over complete case analysis. The present study aims to evaluate the impact of using multiple imputation in comparison with complete case analysis for assessing the associations between preoperative laboratory values and adverse outcomes following anterior cervical discectomy and fusion (ACDF) procedures. This is a retrospective review of prospectively collected data. Patients undergoing one-level ACDF were identified in NSQIP 2012-2015. Perioperative adverse outcome variables assessed included the occurrence of any adverse event, severe adverse events, and hospital readmission. Missing preoperative albumin and hematocrit values were handled using complete case analysis and multiple imputation. These preoperative laboratory levels were then tested for associations with 30-day postoperative outcomes using logistic regression. A total of 11,999 patients were included. Of this cohort, 63.5% of patients had missing preoperative albumin and 9.9% had missing preoperative hematocrit. When using complete case analysis, only 4,311 patients were studied. The removed patients were significantly younger, healthier, of a common body mass index, and male. Logistic regression analysis failed to identify either preoperative hypoalbuminemia or preoperative anemia as significantly associated with adverse outcomes. When employing multiple imputation, all 11,999 patients were included. Preoperative hypoalbuminemia was significantly associated with the occurrence of any adverse event and severe adverse events. Preoperative anemia was significantly associated with the occurrence of any adverse event, severe adverse events, and hospital readmission. Multiple imputation is a rigorous statistical procedure that is being increasingly used to address missing values in large datasets. Using this technique for ACDF avoided the loss of cases that may have affected the representativeness and power of the study and led to different results than complete case analysis. Multiple imputation should be considered for future spine studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiple imputation methods for bivariate outcomes in cluster randomised trials.

PubMed

DiazOrdaz, K; Kenward, M G; Gomes, M; Grieve, R

2016-09-10

Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single-level multiple imputation that ignores the clustering, multiple imputation with a fixed effect for each cluster and multilevel multiple imputation. We contrasted the alternative approaches to handling missing data in a cost-effectiveness analysis that uses data from a cluster randomised trial to evaluate an exercise intervention for care home residents. We then conducted a simulation study to assess the performance of these approaches on bivariate continuous outcomes, in terms of confidence interval coverage and empirical bias in the estimated treatment effects. Missing-at-random clustered data scenarios were simulated following a full-factorial design. Across all the missing data mechanisms considered, the multiple imputation methods provided estimators with negligible bias, while complete case analysis resulted in biased treatment effect estimates in scenarios where the randomised treatment arm was associated with missingness. Confidence interval coverage was generally in excess of nominal levels (up to 99.8%) following fixed-effects multiple imputation and too low following single-level multiple imputation. Multilevel multiple imputation led to coverage levels of approximately 95% throughout. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions.

PubMed

Tay, Richard

2016-03-01

The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated. Copyright © 2015 Elsevier Ltd. All rights reserved.

A note about high blood pressure in childhood

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Simão, Carla

2017-06-01

In medical, behavioral and social sciences it is usual to get a binary outcome. In the present work is collected information where some of the outcomes are binary variables (1='yes'/ 0='no'). In [14] a preliminary study about the caregivers perception of pediatric hypertension was introduced. An experimental questionnaire was designed to be answered by the caregivers of routine pediatric consultation attendees in the Santa Maria's hospital (HSM). The collected data was statistically analyzed, where a descriptive analysis and a predictive model were performed. Significant relations between some socio-demographic variables and the assessed knowledge were obtained. In [14] can be found a statistical data analysis using partial questionnaire's information. The present article completes the statistical approach estimating a model for relevant remaining questions of questionnaire by Generalized Linear Models (GLM). Exploring the binary outcome issue, we intend to extend this approach using Generalized Linear Mixed Models (GLMM), but the process is still ongoing.

Maternal near miss and death among women with severe hypertensive disorders: a Brazilian multicenter surveillance study.

PubMed

Zanette, Elvira; Parpinelli, Mary Angela; Surita, Fernanda Garanhani; Costa, Maria Laura; Haddad, Samira Maerrawi; Sousa, Maria Helena; E Silva, Joao Luiz Pinto; Souza, Joao Paulo; Cecatti, Jose Guilherme

2014-01-16

Hypertensive disorders represent the major cause of maternal morbidity in middle income countries. The main objective of this study was to identify the prevalence and factors associated with severe maternal outcomes in women with severe hypertensive disorders. This was a cross-sectional, multicenter study, including 6706 women with severe hypertensive disorder from 27 maternity hospitals in Brazil. A prospective surveillance of severe maternal morbidity with data collected from medical charts and entered into OpenClinica®, an online system, over a one-year period (2009 to 2010). Women with severe preeclampsia, severe hypertension, eclampsia and HELLP syndrome were included in the study. They were grouped according to outcome in near miss, maternal death and potentially life-threatening condition. Prevalence ratios and 95% confidence intervals adjusted for cluster effect for maternal and perinatal variables and delays in receiving obstetric care were calculated as risk estimates of maternal complications having a severe maternal outcome (near miss or death). Poisson multiple regression analysis was also performed. Severe hypertensive disorders were the main cause of severe maternal morbidity (6706/9555); the prevalence of near miss was 4.2 cases per 1000 live births, there were 8.3 cases of Near Miss to 1 Maternal Death and the mortality index was 10.7% (case fatality). Early onset of the disease and postpartum hemorrhage were independent variables associated with severe maternal outcomes, in addition to acute pulmonary edema, previous heart disease and delays in receiving secondary and tertiary care. In women with severe hypertensive disorders, the current study identified situations independently associated with a severe maternal outcome, which could be modified by interventions in obstetric care and in the healthcare system. Furthermore, the study showed the feasibility of a hospital system for surveillance of severe maternal morbidity.

Strategies for Dealing with Missing Accelerometer Data.

PubMed

Stephens, Samantha; Beyene, Joseph; Tremblay, Mark S; Faulkner, Guy; Pullnayegum, Eleanor; Feldman, Brian M

2018-05-01

Missing data is a universal research problem that can affect studies examining the relationship between physical activity measured with accelerometers and health outcomes. Statistical techniques are available to deal with missing data; however, available techniques have not been synthesized. A scoping review was conducted to summarize the advantages and disadvantages of identified methods of dealing with missing data from accelerometers. Missing data poses a threat to the validity and interpretation of trials using physical activity data from accelerometry. Imputation using multiple imputation techniques is recommended to deal with missing data and improve the validity and interpretation of studies using accelerometry. Copyright © 2018 Elsevier Inc. All rights reserved.

Suicides by persons reported as missing prior to death: a retrospective cohort study.

PubMed

Sveticic, Jerneja; Too, Lay San; De Leo, Diego

2012-01-01

A first study to compare suicides by missing persons with other suicide cases. Retrospective cohort study for the period 1994-2007. GEOGRAPHICAL LOCATION: Queensland, Australia. 194 suicides by missing persons and 7545 other suicides were identified through the Queensland Suicide Register and the National Coroners Information System. χ(2) statistics and binary logistic regression were used to identify distinct characteristics of suicides by missing persons. Compared with other suicide cases, missing persons significantly more often died by motor vehicle exhaust gas toxicity (23.7% vs 16.4%; χ(2)=7.32, p<0.01), jumping from height (6.7% vs 3.2%; χ(2)=7.08, p<0.01) or drowning (8.2% vs 1.8%; χ(2)=39.53, p<0.01), but less frequently by hanging (29.4% vs 39.9%; χ(2)=8.82, p<0.01). They were most frequently located in natural outdoors locations (58.2% vs 11.1%; χ(2)=388.25, p<0.01). Persons gone missing were less likely to have lived alone at time of death (OR 0.45, 95% CI 0.26 to 0.76), yet more likely to be institutionalised (OR 3.12, 95% CI 1.28 to 7.64). They were less likely to have been physically ill (OR 0.64, 95% CI 0.43 to 0.95) or have a history of problematic consumptions of alcohol (OR 0.52, 95% CI 0.31 to 0.87). In comparison to other suicide cases, missing persons more often communicated their suicidal intent prior to death (OR 1.58, 95% CI 1.13 to 2.22). Suicides by missing persons show several distinct characteristics in comparisons to other suicides. The findings have implications for development of suicide prevention strategies focusing on early identification and interventions targeting this group. In particular, it may offer assistance to police in designing risk assessment procedures and subsequent investigations of missing persons.

Reporting and dealing with missing quality of life data in RCTs: has the picture changed in the last decade?

PubMed

Fielding, S; Ogbuagu, A; Sivasubramaniam, S; MacLennan, G; Ramsay, C R

2016-12-01

Missing data are a major problem in the analysis of data from randomised trials affecting power and potentially producing biased treatment effects. Specifically focussing on quality of life outcomes, we aimed to report the amount of missing data, whether imputation was used and what methods and was the missing mechanism discussed from four leading medical journals and compare the picture to our previous review nearly a decade ago. A random selection (50 %) of all RCTS published during 2013-2014 in BMJ, JAMA, Lancet and NEJM was obtained. RCTs reported in research letters, cluster RCTs, non-randomised designs, review articles and meta-analysis were excluded. We included 87 RCTs in the review of which 35 % the amount of missing primary QoL data was unclear, 31 (36 %) used imputation. Only 23 % discussed the missing data mechanism. Nearly half used complete case analysis. Reporting was more unclear for secondary QoL outcomes. Compared to the previous review, multiple imputation was used more prominently but mainly in sensitivity analysis. Inadequate reporting and handling of missing QoL data in RCTs are still an issue. There is a large gap between statistical methods research relating to missing data and the use of the methods in applications. A sensitivity analysis should be undertaken to explore the sensitivity of the main results to different missing data assumptions. Medical journals can help to improve the situation by requiring higher standards of reporting and analytical methods to deal with missing data, and by issuing guidance to authors on expected standard.

Missing Data in the Field of Otorhinolaryngology and Head & Neck Surgery: Need for Improvement.

PubMed

Netten, Anouk P; Dekker, Friedo W; Rieffe, Carolien; Soede, Wim; Briaire, Jeroen J; Frijns, Johan H M

Clinical studies are often facing missing data. Data can be missing for various reasons, for example, patients moved, certain measurements are only administered in high-risk groups, and patients are unable to attend clinic because of their health status. There are various ways to handle these missing data (e.g., complete cases analyses, mean substitution). Each of these techniques potentially influences both the analyses and the results of a study. The first aim of this structured review was to analyze how often researchers in the field of otorhinolaryngology/head & neck surgery report missing data. The second aim was to systematically describe how researchers handle missing data in their analyses. The third aim was to provide a solution on how to deal with missing data by means of the multiple imputation technique. With this review, we aim to contribute to a higher quality of reporting in otorhinolaryngology research. Clinical studies among the 398 most recently published research articles in three major journals in the field of otorhinolaryngology/head & neck surgery were analyzed based on how researchers reported and handled missing data. Of the 316 clinical studies, 85 studies reported some form of missing data. Of those 85, only a small number (12 studies, 3.8%) actively handled the missingness in their data. The majority of researchers exclude incomplete cases, which results in biased outcomes and a drop in statistical power. Within otorhinolaryngology research, missing data are largely ignored and underreported, and consequently, handled inadequately. This has major impact on the results and conclusions drawn from this research. Based on the outcomes of this review, we provide solutions on how to deal with missing data. To illustrate, we clarify the use of multiple imputation techniques, which recently became widely available in standard statistical programs.

Implicit Valuation of the Near-Miss is Dependent on Outcome Context.

PubMed

Banks, Parker J; Tata, Matthew S; Bennett, Patrick J; Sekuler, Allison B; Gruber, Aaron J

2018-03-01

Gambling studies have described a "near-miss effect" wherein the experience of almost winning increases gambling persistence. The near-miss has been proposed to inflate the value of preceding actions through its perceptual similarity to wins. We demonstrate here, however, that it acts as a conditioned stimulus to positively or negatively influence valuation, dependent on reward expectation and cognitive engagement. When subjects are asked to choose between two simulated slot machines, near-misses increase valuation of machines with a low payout rate, whereas they decrease valuation of high payout machines. This contextual effect impairs decisions and persists regardless of manipulations to outcome feedback or financial incentive provided for good performance. It is consistent with proposals that near-misses cause frustration when wins are expected, and we propose that it increases choice stochasticity and overrides avoidance of low-valued options. Intriguingly, the near-miss effect disappears when subjects are required to explicitly value machines by placing bets, rather than choosing between them. We propose that this task increases cognitive engagement and recruits participation of brain regions involved in cognitive processing, causing inhibition of otherwise dominant systems of decision-making. Our results reveal that only implicit, rather than explicit strategies of decision-making are affected by near-misses, and that the brain can fluidly shift between these strategies according to task demands.

Accretion dynamics in pre-main sequence binaries

NASA Astrophysics Data System (ADS)

Tofflemire, B.; Mathieu, R.; Herczeg, G.; Ardila, D.; Akeson, R.; Ciardi, D.; Johns-Krull, C.

Binary stars are a common outcome of star formation. Orbital resonances, especially in short-period systems, are capable of reshaping the distribution and flows of circumstellar material. Simulations of the binary-disk interaction predict a dynamically cleared gap around the central binary, accompanied by periodic ``pulsed'' accretion events that are driven by orbital motion. To place observational constraints on the binary-disk interaction, we have conducted a long-term monitoring program tracing the time-variable accretion behavior of 9 short-period binaries. In this proceeding we present two results from our campaign: 1) the detection of periodic pulsed accretion events in DQ Tau and TWA 3A, and 2) evidence that the TWA 3A primary is the dominant accretor in the system.

Likelihoods for fixed rank nomination networks

PubMed Central

HOFF, PETER; FOSDICK, BAILEY; VOLFOVSKY, ALEX; STOVEL, KATHERINE

2014-01-01

Many studies that gather social network data use survey methods that lead to censored, missing, or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence of other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare Bayesian parameter estimates obtained from a likelihood for complete binary networks with those obtained from likelihoods that are derived from the FRN scheme, and therefore accommodate the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, particularly for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design. PMID:25110586

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

PubMed

Cunningham, Corbin A; Drew, Trafton; Wolfe, Jeremy M

2017-02-01

In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.

Is the perceived placebo effect comparable between adults and children? A meta-regression analysis.

PubMed

Janiaud, Perrine; Cornu, Catherine; Lajoinie, Audrey; Djemli, Amina; Cucherat, Michel; Kassai, Behrouz

2017-01-01

A potential larger perceived placebo effect in children compared with adults could influence the detection of the treatment effect and the extrapolation of the treatment benefit from adults to children. This study aims to explore this potential difference, using a meta-epidemiological approach. A systematic review of the literature was done to identify trials included in meta-analyses evaluating a drug intervention with separate data for adults and children. The standardized mean change and the proportion of responders (binary outcomes) were used to calculate the perceived placebo effect. A meta-regression analysis was conducted to test for the difference between adults and children of the perceived placebo effect. For binary outcomes, the perceived placebo effect was significantly more favorable in children compared with adults (β = 0.13; P = 0.001). Parallel group trials (β = -1.83; P < 0.001), subjective outcomes (β = -0.76; P < 0.001), and the disease type significantly influenced the perceived placebo effect. The perceived placebo effect is different between adults and children for binary outcomes. This difference seems to be influenced by the design, the disease, and outcomes. Calibration of new studies for children should consider cautiously the placebo effect in children.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review

PubMed Central

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Stockler, Martin R; King, Madeleine T

2016-01-01

Objectives Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. Data sources MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. Eligibility criteria English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. Methods 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. Results 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. Conclusions The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. PMID:27311907

What to Do when Data Are Missing in Group Randomized Controlled Trials. NCEE 2009-0049

ERIC Educational Resources Information Center

Puma, Michael J.; Olsen, Robert B.; Bell, Stephen H.; Price, Cristofer

2009-01-01

This NCEE Technical Methods report examines how to address the problem of missing data in the analysis of data in Randomized Controlled Trials (RCTs) of educational interventions, with a particular focus on the common educational situation in which groups of students such as entire classrooms or schools are randomized. Missing outcome data are a…

Sensitivity subgroup analysis based on single-center vs. multi-center trial status when interpreting meta-analyses pooled estimates: the logical way forward.

PubMed

Alexander, Paul E; Bonner, Ashley J; Agarwal, Arnav; Li, Shelly-Anne; Hariharan, Abishek; Izhar, Zain; Bhatnagar, Neera; Alba, Carolina; Akl, Elie A; Fei, Yutong; Guyatt, Gordon H; Beyene, Joseph

2016-06-01

Prior studies regarding whether single-center trial estimates are larger than multi-center are equivocal. We examined the extent to which single-center trials yield systematically larger effects than multi-center trials. We searched the 119 core clinical journals and the Cochrane Database of Systematic Reviews for meta-analyses (MAs) of randomized controlled trials (RCTs) published during 2012. In this meta-epidemiologic study, for binary variables, we computed the pooled ratio of ORs (RORs), and for continuous outcomes mean difference in standardized mean differences (SMDs), we conducted weighted random-effects meta-regression and random-effects MA modeling. Our primary analyses were restricted to MAs that included at least five RCTs and in which at least 25% of the studies used each of single trial center (SC) and more trial center (MC) designs. We identified 81 MAs for the odds ratio (OR) and 43 for the SMD outcome measures. Based on our analytic plan, our primary analysis (core) is based on 25 MAs/241 RCTs (binary outcome) and 18 MAs/173 RCTs (continuous outcome). Based on the core analysis, we found no difference in magnitude of effect between SC and MC for binary outcomes [RORs: 1.02; 95% confidence interval (CI): 0.83, 1.24; I(2) 20.2%]. Effect sizes were systematically larger for SC than MC for the continuous outcome measure (mean difference in SMDs: -0.13; 95% CI: -0.21, -0.05; I(2) 0%). Our results do not support prior findings of larger effects in SC than MC trials addressing binary outcomes but show a very similar small increase in effect in SC than MC trials addressing continuous outcomes. Authors of systematic reviews would be wise to include all trials irrespective of SC vs. MC design and address SC vs. MC status as a possible explanation of heterogeneity (and consider sensitivity analyses). Copyright © 2015 Elsevier Inc. All rights reserved.

Understanding repeated non-attendance in health services: a pilot analysis of administrative data and full study protocol for a national retrospective cohort.

PubMed

Williamson, Andrea E; Ellis, David A; Wilson, Philip; McQueenie, Ross; McConnachie, Alex

2017-02-14

Understanding the causes of low engagement in healthcare is a pre-requisite for improving health services' contribution to tackling health inequalities. Low engagement includes missing healthcare appointments. Serially (having a pattern of) missing general practice (GP) appointments may provide a risk marker for vulnerability and poorer health outcomes. A proof of concept pilot using GP appointment data and a focus group with GPs informed the development of missed appointment categories: patients can be classified based on the number of appointments missed each year. The full study, using a retrospective cohort design, will link routine health service and education data to determine the relationship between GP appointment attendance, health outcomes, healthcare usage, preventive health activity and social circumstances taking a life course approach and using data from the whole journey in the National Health Service (NHS) healthcare. 172 practices will be recruited (∼900 000 patients) across Scotland. The statistical analysis will focus on 2 key areas: factors that predict patients who serially miss appointments, and serial missed appointments as a predictor of future patient outcomes. Regression models will help understand how missed appointment patterns are associated with patient and practice characteristics. We shall identify key factors associated with serial missed appointments and potential interactions that might predict them. The results of the project will inform debates concerning how best to reduce non-attendance and increase patient engagement within healthcare systems. Significant non-academic beneficiaries include governments, policymakers and medical practitioners. Results will be disseminated via a combination of academic outputs (papers, conferences), social media and through collaborative public health/policy fora. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Socioeconomic status and outcomes after sport-related concussion: a preliminary investigation.

PubMed

Zuckerman, Scott L; Zalneraitis, Brian Holt; Totten, Douglas J; Rubel, Kolin E; Kuhn, Andrew W; Yengo-Kahn, Aaron M; Bonfield, Christopher M; Sills, Allen K; Solomon, Gary S

2017-06-01

OBJECTIVE A significant proportion of patients experience long-term symptoms after sport-related concussion (SRC), and several factors have been associated with this protracted recovery. Limited data exist on the role of socioeconomic status (SES) on SRC outcomes. The objective in this study was to conduct a preliminary investigation to determine the effect of SES on outcomes after SRC in student-athletes treated at a regional sports concussion center. METHODS A retrospective cohort study of 282 middle school, high school, and collegiate student-athletes was conducted. An attempt was made to contact all patients seen at a comprehensive SRC center between January 2012 and May 2015 for in-depth interviews. Subsequent demographic data were collected. The SES was defined as follows: cost of living percentile, median income percentile, percentage of college graduates, percentage of homeowners, county type, and insurance status. Outcomes after SRC were defined as follows: days of symptom duration, days of missed school, and days of missed practice. Statistically controlled covariates included sex, race, age, body mass index, concussion history, neuropsychiatric history, and type of sport. RESULTS A total of 282 student-athletes consented and were studied. The median age was 15.8 years (range 11.6-22.2 years) and 61.4% of student-athletes were male. A previous concussion was incurred by 34.0% of student-athletes. Football was the most common sport (32.3%), followed by soccer (16.3%), and basketball (15.6%). The median symptom duration was 21 days (range 1-365 days); the median missed school days was 2 (range 0-90 days); and median for days of missed practice was 10 (range 0-150 days). After multivariate Cox regression analysis, no relationship between any of the 6 SES variables and symptom duration or missed practice was seen. However, individuals with private insurance had more missed days of school than those with public insurance (hazard ratio 0.46, 95% CI 0.26-0.83, p = 0.009). CONCLUSIONS In a preliminary study of middle school, high school, and collegiate student-athletes, SES had no impact on the outcomes of symptom duration and missed practice. However, for individuals with private insurance, the return to school was slower than for those with public insurance. This pilot study reveals the complex relationship between SES and SRC recovery, which demands further study with more accurate and validated assessments of SES.

Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

PubMed

Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

2018-03-01

This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

The Effect of a Brief Acceptance and Commitment Therapy Intervention on the Near-Miss Effect in Problem Gamblers

ERIC Educational Resources Information Center

Nastally, Becky L.; Dixon, Mark R.

2012-01-01

In the current study, 3 participants with a history of problem gambling were exposed to computerized slot machine play consisting of outcomes that depicted wins, losses, and near misses (2 out of 3 identical slot machine symbols). Participants were asked to rate each type of outcome in terms of its closeness to a win on a scale of 1 to 10 before…

Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms.

PubMed

Shahinfar, Saleh; Page, David; Guenther, Jerry; Cabrera, Victor; Fricke, Paul; Weigel, Kent

2014-02-01

When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most effective explanatory variables in predicting pregnancy outcome. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

New Insights into Handling Missing Values in Environmental Epidemiological Studies

PubMed Central

Roda, Célina; Nicolis, Ioannis; Momas, Isabelle; Guihenneuc, Chantal

2014-01-01

Missing data are unavoidable in environmental epidemiologic surveys. The aim of this study was to compare methods for handling large amounts of missing values: omission of missing values, single and multiple imputations (through linear regression or partial least squares regression), and a fully Bayesian approach. These methods were applied to the PARIS birth cohort, where indoor domestic pollutant measurements were performed in a random sample of babies' dwellings. A simulation study was conducted to assess performances of different approaches with a high proportion of missing values (from 50% to 95%). Different simulation scenarios were carried out, controlling the true value of the association (odds ratio of 1.0, 1.2, and 1.4), and varying the health outcome prevalence. When a large amount of data is missing, omitting these missing data reduced statistical power and inflated standard errors, which affected the significance of the association. Single imputation underestimated the variability, and considerably increased risk of type I error. All approaches were conservative, except the Bayesian joint model. In the case of a common health outcome, the fully Bayesian approach is the most efficient approach (low root mean square error, reasonable type I error, and high statistical power). Nevertheless for a less prevalent event, the type I error is increased and the statistical power is reduced. The estimated posterior distribution of the OR is useful to refine the conclusion. Among the methods handling missing values, no approach is absolutely the best but when usual approaches (e.g. single imputation) are not sufficient, joint modelling approach of missing process and health association is more efficient when large amounts of data are missing. PMID:25226278

Growth Modeling with Non-Ignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial

PubMed Central

Muthén, Bengt; Asparouhov, Tihomir; Hunter, Aimee; Leuchter, Andrew

2011-01-01

This paper uses a general latent variable framework to study a series of models for non-ignorable missingness due to dropout. Non-ignorable missing data modeling acknowledges that missingness may depend on not only covariates and observed outcomes at previous time points as with the standard missing at random (MAR) assumption, but also on latent variables such as values that would have been observed (missing outcomes), developmental trends (growth factors), and qualitatively different types of development (latent trajectory classes). These alternative predictors of missing data can be explored in a general latent variable framework using the Mplus program. A flexible new model uses an extended pattern-mixture approach where missingness is a function of latent dropout classes in combination with growth mixture modeling using latent trajectory classes. A new selection model allows not only an influence of the outcomes on missingness, but allows this influence to vary across latent trajectory classes. Recommendations are given for choosing models. The missing data models are applied to longitudinal data from STAR*D, the largest antidepressant clinical trial in the U.S. to date. Despite the importance of this trial, STAR*D growth model analyses using non-ignorable missing data techniques have not been explored until now. The STAR*D data are shown to feature distinct trajectory classes, including a low class corresponding to substantial improvement in depression, a minority class with a U-shaped curve corresponding to transient improvement, and a high class corresponding to no improvement. The analyses provide a new way to assess drug efficiency in the presence of dropout. PMID:21381817

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

FORMATION AND EVOLUTION OF GALACTIC INTERMEDIATE/LOW-MASS X-RAY BINARIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Yong; Li, Xiang-Dong, E-mail: lixd@nju.edu.cn

2015-08-10

We investigate the formation and evolutionary sequences of Galactic intermediate- and low-mass X-ray binaries (I/LMXBs) by combining binary population synthesis (BPS) and detailed stellar evolutionary calculations. Using an updated BPS code we compute the evolution of massive binaries that leads to the formation of incipient I/LMXBs and present their distribution in the initial donor mass versus initial orbital period diagram. We then follow the evolution of the I/LMXBs until the formation of binary millisecond pulsars (BMSPs). We find that the birthrate of the I/LMXB population is in the range of 9 × 10{sup −6}–3.4 × 10{sup −5} yr{sup −1}, compatiblemore » with that of BMSPs that are thought to descend from I/LMXBs. We show that during the evolution of I/LMXBs they are likely to be observed as relatively compact binaries with orbital periods ≲1 day and donor masses ≲0.3M{sub ⊙}. The resultant BMSPs have orbital periods ranging from less than 1 day to a few hundred days. These features are consistent with observations of LMXBs and BMSPs. We also confirm the discrepancies between theoretical predictions and observations mentioned in the literature, that is, the theoretical average mass transfer rates (∼10{sup −10} M{sub ⊙} yr{sup −1}) of LMXBs are considerably lower than observed, and the number of BMSPs with orbital periods ∼0.1–10 days is severely underestimated. These discrepancies imply that something is missing in the modeling of LMXBs, which is likely to be related to the mechanisms of the orbital angular momentum loss.« less

Estimating Mass Parameters of Doubly Synchronous Binary Asteroids

NASA Astrophysics Data System (ADS)

Davis, Alex; Scheeres, Daniel J.

2017-10-01

The non-spherical mass distributions of binary asteroid systems lead to coupled mutual gravitational forces and torques. Observations of the coupled attitude and orbital dynamics can be leveraged to provide information about the mass parameters of the binary system. The full 3-dimensional motion has 9 degrees of freedom, and coupled dynamics require the use of numerical investigation only. In the current study we simplify the system to a planar ellipsoid-ellipsoid binary system in a doubly synchronous orbit. Three modes are identified for the system, which has 4 degrees of freedom, with one degree of freedom corresponding to an ignorable coordinate. The three modes correspond to the three major librational modes of the system when it is in a doubly synchronous orbit. The linearized periods of each mode are a function of the mass parameters of the two asteroids, enabling measurement of these parameters based on observations of the librational motion. Here we implement estimation techniques to evaluate the capabilities of this mass measurement method. We apply this methodology to the Trojan binary asteroid system 617 Patroclus and Menoetius (1906 VY), the final flyby target of the recently announced LUCY Discovery mission. This system is of interest because a stellar occultation campaign of the Patroclus and Menoetius system has suggested that the asteroids are similarly sized oblate ellipsoids moving in a doubly-synchronous orbit, making the system an ideal test for this investigation. A number of missed observations during the campaign also suggested the possibility of a crater on the southern limb of Menoetius, the presence of which could be evaluated by our mass estimation method. This presentation will review the methodology and potential accuracy of our approach in addition to evaluating how the dynamical coupling can be used to help understand light curve and stellar occultation observations for librating binary systems.

Parent health literacy and adherence-related outcomes in children with epilepsy.

PubMed

Paschal, Angelia M; Mitchell, Qshequilla P; Wilroy, Jereme D; Hawley, Suzanne R; Mitchell, Jermaine B

2016-03-01

The relationship between parent health literacy and adherence to treatment in children with epilepsy has not been fully explored. The purpose of this study was to determine whether parent health literacy and other variables predicted factors associated with adherence, such as missed medication doses, missed medical appointments, and seizure frequency, in children with epilepsy between 1 and 12 years old. It was hypothesized that parents with adequate parent health literacy would report fewer missed doses, missed appointments, and seizure occurrences. Using a nonexperimental, cross-sectional study design, interviews were conducted with 146 parents and guardians of children with epilepsy who resided in rural communities. Univariate analyses, including ANOVA, and multiple linear regressions were conducted. Results indicated that parent health literacy was the strongest predictor of two of the adherence-related factors. Higher health literacy scores were associated with fewer missed medication doses and seizure occurrences. However, health literacy was not associated with missed medical appointments. Among other study variables, higher household income was also predictive of fewer missed doses. The study findings suggest that inadequate health literacy among parents may serve as an independent risk factor for adherence-related outcomes among children with epilepsy. Further research, as well as effective, targeted parent health literacy strategies used to improve epilepsy management and care in children, is recommended. Copyright © 2015 Elsevier Inc. All rights reserved.

Subjective Prior Distributions for Modeling Longitudinal Continuous Outcomes with Non-Ignorable Dropout

PubMed Central

Paddock, Susan M.; Ebener, Patricia

2010-01-01

Substance abuse treatment research is complicated by the pervasive problem of non-ignorable missing data – i.e., the occurrence of the missing data is related to the unobserved outcomes. Missing data frequently arise due to early client departure from treatment. Pattern-mixture models (PMMs) are often employed in such situations to jointly model the outcome and the missing data mechanism. PMMs require non-testable assumptions to identify model parameters. Several approaches to parameter identification have therefore been explored for longitudinal modeling of continuous outcomes, and informative priors have been developed in other contexts. In this paper, we describe an expert interview conducted with five substance abuse treatment clinical experts who have familiarity with the Therapeutic Community modality of substance abuse treatment and with treatment process scores collected using the Dimensions of Change Instrument. The goal of the interviews was to obtain expert opinion about the rate of change in continuous client-level treatment process scores for clients who leave before completing two assessments and whose rate of change (slope) in treatment process scores is unidentified by the data. We find that the experts’ opinions differed dramatically from widely-utilized assumptions used to identify parameters in the PMM. Further, subjective prior assessment allows one to properly address the uncertainty inherent in the subjective decisions required to identify parameters in the PMM and to measure their effect on conclusions drawn from the analysis. PMID:19012279

Clinical and Microbiologic Characteristics of Clostridium difficile Infection Caused by Binary Toxin Producing Strain in Korea.

PubMed

Kim, Jieun; Seo, Mi-Ran; Kang, Jung Oak; Choi, Tae Yeal; Pai, Hyunjoo

2013-06-01

Binary toxin-producing Clostridium difficile infections (CDI) are known to be more severe and to cause higher case fatality rates than those by binary toxin-negative isolates. There has been few data of binary toxin-producing CDI in Korea. Objective of the study is to characterize clinical and microbiological trait of CDI cause by binary-toxin producing isolates in Korea. From September 2008 through January 2010, clinical characteristics, medication history and treatment outcome of all the CDI patients were collected prospectively. Toxin characterization, PCR ribotyping and antibiotic susceptibility were performed with the stool isolates of C. difficile. During the period, CDI caused by 11binary toxin-producing isolates and 105 toxin A & toxin B-positive binary toxin-negative isolates were identified. Comparing the disease severity and clinical findings between two groups, leukocytosis and mucoid stool were more frequently observed in patients with binary toxin-positive isolates (OR: 5.2, 95% CI: 1.1 to 25.4, P = 0.043; OR: 7.6, 95% CI: 1.6 to 35.6, P = 0.010, respectively), but clinical outcome of 2 groups did not show any difference. For the risk factors for acquisition of binary toxin-positive isolates, previous use of glycopeptides was the significant risk factor (OR: 6.2, 95% CI: 1.4 to 28.6, P = 0.019), but use of probiotics worked as an inhibitory factor (OR: 0.1, 95% CI: 0.0 to 0.8; P = 0.026). PCR ribotypes of binary toxinproducing C. difficile showed variable patterns: ribotype 130, 4 isolates; 027, 3 isolates; 267 and 122, 1 each isolate and unidentified C1, 2 isolates. All 11 binary toxin-positive isolates were highly susceptible to clindamycin, moxifloxacin, metronidazole, vancomycin and piperacillin-tazobactam, however, 1 of 11 of the isolates was resistant to rifaximin. Binary toxin-producing C. difficile infection was not common in Korea and those isolates showed diverse PCR ribotypes with high susceptibility to antimicrobial agents. Glycopeptide use was a risk factor for CDI by those isolates.

Clinical and Microbiologic Characteristics of Clostridium difficile Infection Caused by Binary Toxin Producing Strain in Korea

PubMed Central

Kim, Jieun; Seo, Mi-ran; Kang, Jung Oak; Choi, Tae Yeal

2013-01-01

Background Binary toxin-producing Clostridium difficile infections (CDI) are known to be more severe and to cause higher case fatality rates than those by binary toxin-negative isolates. There has been few data of binary toxin-producing CDI in Korea. Objective of the study is to characterize clinical and microbiological trait of CDI cause by binary-toxin producing isolates in Korea. Materials and Methods From September 2008 through January 2010, clinical characteristics, medication history and treatment outcome of all the CDI patients were collected prospectively. Toxin characterization, PCR ribotyping and antibiotic susceptibility were performed with the stool isolates of C. difficile. Results During the period, CDI caused by 11binary toxin-producing isolates and 105 toxin A & toxin B-positive binary toxin-negative isolates were identified. Comparing the disease severity and clinical findings between two groups, leukocytosis and mucoid stool were more frequently observed in patients with binary toxin-positive isolates (OR: 5.2, 95% CI: 1.1 to 25.4, P = 0.043; OR: 7.6, 95% CI: 1.6 to 35.6, P = 0.010, respectively), but clinical outcome of 2 groups did not show any difference. For the risk factors for acquisition of binary toxin-positive isolates, previous use of glycopeptides was the significant risk factor (OR: 6.2, 95% CI: 1.4 to 28.6, P = 0.019), but use of probiotics worked as an inhibitory factor (OR: 0.1, 95% CI: 0.0 to 0.8; P = 0.026). PCR ribotypes of binary toxinproducing C. difficile showed variable patterns: ribotype 130, 4 isolates; 027, 3 isolates; 267 and 122, 1 each isolate and unidentified C1, 2 isolates. All 11 binary toxin-positive isolates were highly susceptible to clindamycin, moxifloxacin, metronidazole, vancomycin and piperacillin-tazobactam, however, 1 of 11 of the isolates was resistant to rifaximin. Conclusions Binary toxin-producing C. difficile infection was not common in Korea and those isolates showed diverse PCR ribotypes with high susceptibility to antimicrobial agents. Glycopeptide use was a risk factor for CDI by those isolates. PMID:24265965

Association of the Nurse Work Environment, Collective Efficacy, and Missed Care.

PubMed

Smith, Jessica G; Morin, Karen H; Wallace, Leigh E; Lake, Eileen T

2018-06-01

Missed nursing care is a significant threat to quality patient care. Promoting collective efficacy within nurse work environments could decrease missed care. The purpose was to understand how missed care is associated with nurse work environments and collective efficacy of hospital staff nurses. A cross-sectional, convenience sample was obtained through online surveys from registered nurses working at five southwestern U.S. hospitals. Descriptive, correlational, regression, and path analyses were conducted ( N = 233). The percentage of nurses who reported that at least one care activity was missed frequently or always was 94%. Mouth care (36.0% of nurses) and ambulation (35.3%) were missed frequently or always. Nurse work environments and collective efficacy were moderately, positively correlated. Nurse work environments and collective efficacy were associated with less missed care (χ 2 = 10.714, p = .0054). Fostering collective efficacy in the nurse work environment could reduce missed care and improve patient outcomes.

Missing incidents in community-dwelling people with dementia: understanding how these dangerous events differ from dementia-related ‘wandering’ is critical to assessment, intervention, and prevention.

PubMed

Rowe, Meredeth A; Greenblum, Catherine A; DʼAoust, Rita F

2012-12-01

At every stage of dementia, people with the condition are at risk for both missing incidents, in which they are unattended and unable to navigate a safe return to their caregiver, and "wandering," a term often used to describe repetitive locomotion with patterns such as lapping or pacing. By understanding the differences between these two phenomena, nurses can teach caregivers how to anticipate and prevent missing incidents, which are not necessarily related to wandering. The authors differentiate missing incidents from wandering, describe personal characteristics that may influence the outcomes in missing incidents, and suggest strategies for preventing and responding to missing incidents.

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

PubMed

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

Missing data and multiple imputation in clinical epidemiological research.

PubMed

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.

Missing data and multiple imputation in clinical epidemiological research

PubMed Central

Pedersen, Alma B; Mikkelsen, Ellen M; Cronin-Fenton, Deirdre; Kristensen, Nickolaj R; Pham, Tra My; Pedersen, Lars; Petersen, Irene

2017-01-01

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data. PMID:28352203

The Effect of the Dental Operating Microscope on the Outcome of Nonsurgical Root Canal Treatment: A Retrospective Case-control Study.

PubMed

Khalighinejad, Navid; Aminoshariae, Anita; Kulild, James C; Williams, Kristin A; Wang, Jeannie; Mickel, Andre

2017-05-01

The aim of the current investigation was to assess the effect of the use of a dental operating microscope on the outcome of nonsurgical root canal treatment (NS RCT) while treating the mesiobuccal (MB) root of the maxillary first molar. This retrospective investigation included endodontically treated maxillary first molars (ETMs) with apparent adequate previous NS RCT and restorations referred for endodontic retreatment at the endodontic graduate clinic. Inclusion criteria were ETMs that were diagnosed with irreversible pulpitis and normal periapical tissues before the initial NS RCT and ETMs that presented with a minimum of 1 identifiable periapical lesion (PAR) at 1 of the roots at the time of retreatment. One hundred ninety-five ETMs were included and divided into 2 groups: (1) the initial NS RCT had been performed using a microscope (n = 83) and (2) NS RCT had been performed without the use of a microscope (n = 112). Data extracted were whether the second MB (MB2) canal was located initially and the presence of an MB PAR at the time of retreatment. Data were statistically analyzed using binary logistic regression (α = 0.05). The MB root was 3 times more likely to present with a PAR at the time of retreatment if the initial NS RCT was performed without the use of a microscope (P < .05, odds ratio = 3.1). There was a significant association between a missed MB2 canal and an MB PAR in the group in which the initial NS RCT was performed without the use of a microscope (P < .05, odds ratio = 5.1). However, in cases in which the initial NS RCT was performed using a microscope, a missed MB2 canal was not associated with the presence of an MB PAR. With proper education, dentists can gain further insight into recognizing limitations in treating cases that require advanced training and advanced optics such as a microscope. Based on this strategy, it would appear that the outcome of NS RCT can be improved. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

The Impact of the Nursing Practice Environment on Missed Nursing Care.

PubMed

Hessels, Amanda J; Flynn, Linda; Cimiotti, Jeannie P; Cadmus, Edna; Gershon, Robyn R M

2015-12-01

Missed nursing care is an emerging problem negatively impacting patient outcomes. There are gaps in our knowledge of factors associated with missed nursing care. The aim of this study was to determine the relationship between the nursing practice environment and missed nursing care in acute care hospitals. This is a secondary analysis of cross sectional data from a survey of over 7.000 nurses from 70 hospitals on workplace and process of care. Ordinary least squares and multiple regression models were constructed to examine the relationship between the nursing practice environment and missed nursing care while controlling for characteristics of nurses and hospitals. Nurses missed delivering a significant amount of necessary patient care (10-27%). Inadequate staffing and inadequate resources were the practice environment factors most strongly associated with missed nursing care events. This multi-site study examined the risk and risk factors associated with missed nursing care. Improvements targeting modifiable risk factors may reduce the risk of missed nursing care.

Predictor Combination in Binary Decision-Making Situations

ERIC Educational Resources Information Center

McGrath, Robert E.

2008-01-01

Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid…

Design, implementation and reporting strategies to reduce the instance and impact of missing patient-reported outcome (PRO) data: a systematic review.

PubMed

Mercieca-Bebber, Rebecca; Palmer, Michael J; Brundage, Michael; Calvert, Melanie; Stockler, Martin R; King, Madeleine T

2016-06-15

Patient-reported outcomes (PROs) provide important information about the impact of treatment from the patients' perspective. However, missing PRO data may compromise the interpretability and value of the findings. We aimed to report: (1) a non-technical summary of problems caused by missing PRO data; and (2) a systematic review by collating strategies to: (A) minimise rates of missing PRO data, and (B) facilitate transparent interpretation and reporting of missing PRO data in clinical research. Our systematic review does not address statistical handling of missing PRO data. MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases (inception to 31 March 2015), and citing articles and reference lists from relevant sources. English articles providing recommendations for reducing missing PRO data rates, or strategies to facilitate transparent interpretation and reporting of missing PRO data were included. 2 reviewers independently screened articles against eligibility criteria. Discrepancies were resolved with the research team. Recommendations were extracted and coded according to framework synthesis. 117 sources (55% discussion papers, 26% original research) met the eligibility criteria. Design and methodological strategies for reducing rates of missing PRO data included: incorporating PRO-specific information into the protocol; carefully designing PRO assessment schedules and defining termination rules; minimising patient burden; appointing a PRO coordinator; PRO-specific training for staff; ensuring PRO studies are adequately resourced; and continuous quality assurance. Strategies for transparent interpretation and reporting of missing PRO data include utilising auxiliary data to inform analysis; transparently reporting baseline PRO scores, rates and reasons for missing data; and methods for handling missing PRO data. The instance of missing PRO data and its potential to bias clinical research can be minimised by implementing thoughtful design, rigorous methodology and transparent reporting strategies. All members of the research team have a responsibility in implementing such strategies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Inference in randomized trials with death and missingness.

PubMed

Wang, Chenguang; Scharfstein, Daniel O; Colantuoni, Elizabeth; Girard, Timothy D; Yan, Ying

2017-06-01

In randomized studies involving severely ill patients, functional outcomes are often unobserved due to missed clinic visits, premature withdrawal, or death. It is well known that if these unobserved functional outcomes are not handled properly, biased treatment comparisons can be produced. In this article, we propose a procedure for comparing treatments that is based on a composite endpoint that combines information on both the functional outcome and survival. We further propose a missing data imputation scheme and sensitivity analysis strategy to handle the unobserved functional outcomes not due to death. Illustrations of the proposed method are given by analyzing data from a recent non-small cell lung cancer clinical trial and a recent trial of sedation interruption among mechanically ventilated patients. © 2016, The International Biometric Society.

Causal inference with missing exposure information: Methods and applications to an obstetric study.

PubMed

Zhang, Zhiwei; Liu, Wei; Zhang, Bo; Tang, Li; Zhang, Jun

2016-10-01

Causal inference in observational studies is frequently challenged by the occurrence of missing data, in addition to confounding. Motivated by the Consortium on Safe Labor, a large observational study of obstetric labor practice and birth outcomes, this article focuses on the problem of missing exposure information in a causal analysis of observational data. This problem can be approached from different angles (i.e. missing covariates and causal inference), and useful methods can be obtained by drawing upon the available techniques and insights in both areas. In this article, we describe and compare a collection of methods based on different modeling assumptions, under standard assumptions for missing data (i.e. missing-at-random and positivity) and for causal inference with complete data (i.e. no unmeasured confounding and another positivity assumption). These methods involve three models: one for treatment assignment, one for the dependence of outcome on treatment and covariates, and one for the missing data mechanism. In general, consistent estimation of causal quantities requires correct specification of at least two of the three models, although there may be some flexibility as to which two models need to be correct. Such flexibility is afforded by doubly robust estimators adapted from the missing covariates literature and the literature on causal inference with complete data, and by a newly developed triply robust estimator that is consistent if any two of the three models are correct. The methods are applied to the Consortium on Safe Labor data and compared in a simulation study mimicking the Consortium on Safe Labor. © The Author(s) 2013.

Three challenges described for identifying participants with missing data in trials reports, and potential solutions suggested to systematic reviewers.

PubMed

Akl, Elie A; Kahale, Lara A; Ebrahim, Shanil; Alonso-Coello, Pablo; Schünemann, Holger J; Guyatt, Gordon H

2016-08-01

To categorize the challenges in determining the extent of missing participant data in randomized trials and suggest potential solutions for systematic review authors. During the process of updating a series of Cochrane systematic reviews on the topic of anticoagulation in patients with cancer, we identified challenges and used an iterative approach to improve, and a consensus process to agree on the challenges identified, and to suggest potential ways of dealing with them. The five systematic reviews included 58 trials and 75 meta-analyses for patient-important dichotomous outcomes with 27,037 randomized participants. We identified three categories of challenges: (1) Although systematic reviewers require information about missing data to be reported by outcome, trialists typically report the information by participant; (2) It is not always clear whether the trialists followed up participants in certain categories (e.g., noncompliers), that is, whether some categories of participants did or did not have missing data; (3) It is not always clear how the trialists dealt with missing data in their analysis (e.g., exclusion from the denominator vs. assumptions made for the numerator). We discuss potential solutions for each one of these challenges and suggest further research work. Current reporting of missing data is often not explicit and transparent, and although our potential solutions to problems of suboptimal reporting may be helpful, reliable and valid characterization of the extent and nature of missing data remains elusive. Reporting of missing data in trials needs further improvement. Copyright © 2016 Elsevier Inc. All rights reserved.

Striatal connectivity changes following gambling wins and near-misses: Associations with gambling severity.

PubMed

van Holst, Ruth J; Chase, Henry W; Clark, Luke

2014-01-01

Frontostriatal circuitry is implicated in the cognitive distortions associated with gambling behaviour. 'Near-miss' events, where unsuccessful outcomes are proximal to a jackpot win, recruit overlapping neural circuitry with actual monetary wins. Personal control over a gamble (e.g., via choice) is also known to increase confidence in one's chances of winning (the 'illusion of control'). Using psychophysiological interaction (PPI) analyses, we examined changes in functional connectivity as regular gamblers and non-gambling participants played a slot-machine game that delivered wins, near-misses and full-misses, and manipulated personal control. We focussed on connectivity with striatal seed regions, and associations with gambling severity, using voxel-wise regression. For the interaction term of near-misses (versus full-misses) by personal choice (participant-chosen versus computer-chosen), ventral striatal connectivity with the insula, bilaterally, was positively correlated with gambling severity. In addition, some effects for the contrast of wins compared to all non-wins were observed at an uncorrected (p < .001) threshold: there was an overall increase in connectivity between the striatal seeds and left orbitofrontal cortex and posterior insula, and a negative correlation for gambling severity with the connectivity between the right ventral striatal seed and left anterior cingulate cortex. These findings corroborate the 'non-categorical' nature of reward processing in gambling: near-misses and full-misses are objectively identical outcomes that are processed differentially. Ventral striatal connectivity with the insula correlated positively with gambling severity in the illusion of control contrast, which could be a risk factor for the cognitive distortions and loss-chasing that are characteristic of problem gambling.

Factors Associated With Missed and Cancelled Colonoscopy Appointments at Veterans Health Administration Facilities.

PubMed

Partin, Melissa R; Gravely, Amy; Gellad, Ziad F; Nugent, Sean; Burgess, James F; Shaukat, Aasma; Nelson, David B

2016-02-01

Cancelled and missed colonoscopy appointments waste resources, increase colonoscopy delays, and can adversely affect patient outcomes. We examined individual and organizational factors associated with missed and cancelled colonoscopy appointments in Veteran Health Administration facilities. From 69 facilities meeting inclusion criteria, we identified 27,994 patients with colonoscopy appointments scheduled for follow-up, on the basis of positive fecal occult blood test results, between August 16, 2009 and September 30, 2011. We identified factors associated with colonoscopy appointment status (completed, cancelled, or missed) by using hierarchical multinomial regression. Individual factors examined included age, race, sex, marital status, residence, drive time to nearest specialty care facility, limited life expectancy, comorbidities, colonoscopy in the past decade, referring facility type, referral month, and appointment lead time. Organizational factors included facility region, complexity, appointment reminders, scheduling, and prep education practices. Missed appointments were associated with limited life expectancy (odds ratio [OR], 2.74; P = .0004), no personal history of polyps (OR, 2.74; P < .0001), high facility complexity (OR, 2.69; P = .007), dual diagnosis of psychiatric disorders and substance abuse (OR, 1.82; P < .0001), and opt-out scheduling (OR, 1.57; P = .02). Cancelled appointments were associated with age (OR, 1.61; P = .0005 for 85 years or older and OR, 1.44; P < .0001 for 65-84 years old), no history of polyps (OR, 1.51; P < .0001), and opt-out scheduling (OR, 1.26; P = .04). Additional predictors of both outcomes included race, marital status, and lead time. Several factors within Veterans Health Administration clinic control can be targeted to reduce missed and cancelled colonoscopy appointments. Specifically, developing systems to minimize referrals for patients with limited life expectancy could reduce missed appointments, and use of opt-in scheduling and reductions in appointment lead time could improve both outcomes. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

A GDP-driven model for the binary and weighted structure of the International Trade Network

NASA Astrophysics Data System (ADS)

Almog, Assaf; Squartini, Tiziano; Garlaschelli, Diego

2015-01-01

Recent events such as the global financial crisis have renewed the interest in the topic of economic networks. One of the main channels of shock propagation among countries is the International Trade Network (ITN). Two important models for the ITN structure, the classical gravity model of trade (more popular among economists) and the fitness model (more popular among networks scientists), are both limited to the characterization of only one representation of the ITN. The gravity model satisfactorily predicts the volume of trade between connected countries, but cannot reproduce the missing links (i.e. the topology). On the other hand, the fitness model can successfully replicate the topology of the ITN, but cannot predict the volumes. This paper tries to make an important step forward in the unification of those two frameworks, by proposing a new gross domestic product (GDP) driven model which can simultaneously reproduce the binary and the weighted properties of the ITN. Specifically, we adopt a maximum-entropy approach where both the degree and the strength of each node are preserved. We then identify strong nonlinear relationships between the GDP and the parameters of the model. This ultimately results in a weighted generalization of the fitness model of trade, where the GDP plays the role of a ‘macroeconomic fitness’ shaping the binary and the weighted structure of the ITN simultaneously. Our model mathematically explains an important asymmetry in the role of binary and weighted network properties, namely the fact that binary properties can be inferred without the knowledge of weighted ones, while the opposite is not true.

The Upper and Lower Bounds of the Prediction Accuracies of Ensemble Methods for Binary Classification

PubMed Central

Wang, Xueyi; Davidson, Nicholas J.

2011-01-01

Ensemble methods have been widely used to improve prediction accuracy over individual classifiers. In this paper, we achieve a few results about the prediction accuracies of ensemble methods for binary classification that are missed or misinterpreted in previous literature. First we show the upper and lower bounds of the prediction accuracies (i.e. the best and worst possible prediction accuracies) of ensemble methods. Next we show that an ensemble method can achieve > 0.5 prediction accuracy, while individual classifiers have < 0.5 prediction accuracies. Furthermore, for individual classifiers with different prediction accuracies, the average of the individual accuracies determines the upper and lower bounds. We perform two experiments to verify the results and show that it is hard to achieve the upper and lower bounds accuracies by random individual classifiers and better algorithms need to be developed. PMID:21853162

Singular Isothermal Disks and the Formation of Multiple Stars

NASA Technical Reports Server (NTRS)

Galli, Daniele; Shu, Frank H.; Laughlin, Gregory; Lizano, Susana; DeVincenzi, Donald (Technical Monitor)

2000-01-01

A crucial missing ingredient in previous theoretical studies of fragmentation is the inclusion of dynamically important levels of magnetic fields. As a minimal model for a candidate presursor to the formation of binary and multiple stars, we therefore consider the equilibrium configuration of isopedically magnetized, scale-free, singular isothermal disks, without the assumption of axial symmetry. We find that lopsided (M = 1) configurations exist at any dimensionless rotation rate, including zero. Multiple-lobed (M = 2, 3, 4, ...) configurations bifurcate from an underlying axisymmetric sequence at progressively higher dimensionless rates of rotation, but such nonaxisymmetric sequences always terminate in shockwaves before they have a chance to fission into separate bodies. We advance the hypothesis that binary and multiple star-formation from smooth (i.e., not highly turbulent) starting states that are supercritical but in unstable mechanical balance requires the rapid (i.e., dynamical) loss of magnetic flux at some stage of the ensuing gravitational collapse.

The disruption of multiplanet systems through resonance with a binary orbit.

PubMed

Touma, Jihad R; Sridhar, S

2015-08-27

Most exoplanetary systems in binary stars are of S-type, and consist of one or more planets orbiting a primary star with a wide binary stellar companion. Planetary eccentricities and mutual inclinations can be large, perhaps forced gravitationally by the binary companion. Earlier work on single planet systems appealed to the Kozai-Lidov instability wherein a sufficiently inclined binary orbit excites large-amplitude oscillations in the planet's eccentricity and inclination. The instability, however, can be quenched by many agents that induce fast orbital precession, including mutual gravitational forces in a multiplanet system. Here we report that orbital precession, which inhibits Kozai-Lidov cycling in a multiplanet system, can become fast enough to resonate with the orbital motion of a distant binary companion. Resonant binary forcing results in dramatic outcomes ranging from the excitation of large planetary eccentricities and mutual inclinations to total disruption. Processes such as planetary migration can bring an initially non-resonant system into resonance. As it does not require special physical or initial conditions, binary resonant driving is generic and may have altered the architecture of many multiplanet systems. It can also weaken the multiplanet occurrence rate in wide binaries, and affect planet formation in close binaries.

A Comparison of Grid-based and SPH Binary Mass-transfer and Merger Simulations

DOE PAGES

Motl, Patrick M.; Frank, Juhan; Staff, Jan; ...

2017-03-29

There is currently a great amount of interest in the outcomes and astrophysical implications of mergers of double degenerate binaries. In a commonly adopted approximation, the components of such binaries are represented by polytropes with an index of n = 3/2. We present detailed comparisons of stellar mass-transfer and merger simulations of polytropic binaries that have been carried out using two very different numerical algorithms—a finite-volume "grid" code and a smoothed-particle hydrodynamics (SPH) code. We find that there is agreement in both the ultimate outcomes of the evolutions and the intermediate stages if the initial conditions for each code aremore » chosen to match as closely as possible. We find that even with closely matching initial setups, the time it takes to reach a concordant evolution differs between the two codes because the initial depth of contact cannot be matched exactly. There is a general tendency for SPH to yield higher mass transfer rates and faster evolution to the final outcome. Here, we also present comparisons of simulations calculated from two different energy equations: in one series, we assume a polytropic equation of state and in the other series an ideal gas equation of state. In the latter series of simulations, an atmosphere forms around the accretor, which can exchange angular momentum and cause a more rapid loss of orbital angular momentum. In the simulations presented here, the effect of the ideal equation of state is to de-stabilize the binary in both SPH and grid simulations, but the effect is more pronounced in the grid code.« less

The treatment of missing data in a large cardiovascular clinical outcomes study.

PubMed

Little, Roderick J; Wang, Julia; Sun, Xiang; Tian, Hong; Suh, Eun-Young; Lee, Michael; Sarich, Troy; Oppenheimer, Leonard; Plotnikov, Alexei; Wittes, Janet; Cook-Bruns, Nancy; Burton, Paul; Gibson, C Michael; Mohanty, Surya

2016-06-01

The potential impact of missing data on the results of clinical trials has received heightened attention recently. A National Research Council study provides recommendations for limiting missing data in clinical trial design and conduct, and principles for analysis, including the need for sensitivity analyses to assess robustness of findings to alternative assumptions about the missing data. A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome. This case study describes a variety of measures that were taken to address concerns about the missing data. A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The sensitivity analysis in the National Research Council study is modified in the context of survival analysis where some individuals are lost to follow-up. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between dropout and the end of the study. Tipping-point analyses are described, where the deviation from ignorable censoring that results in a reversal of significance of the treatment effect is determined. A study to determine the vital status of participants lost to follow-up was also conducted, and the results of including this additional information are assessed. Sensitivity analyses suggest that findings of the ATLAS ACS 2 TIMI 51 study are robust to missing data; this robustness is reinforced by the follow-up study, since inclusion of data from this study had little impact on the study conclusions. Missing data are a serious problem in clinical trials. The methods presented here, namely, the sensitivity analyses, the follow-up study to determine survival of missing cases, and the proposed measurement of missing data via the fraction of missing information, have potential application in other studies involving survival analysis where missing data are a concern. © The Author(s) 2016.

A Retrospective Study of Non-Ventilator-Associated Hospital Acquired Pneumonia Incidence and Missed Opportunities for Nursing Care.

PubMed

Tesoro, Mary; Peyser, Diane J; Villarente, Farley

2018-05-01

To determine non-ventilator-associated hospital-acquired pneumonia (NV-HAP) incidence, assess negative impacts on patient outcomes and cost, and identify missed preventive nursing care opportunities. NV-HAP is inadequately studied and underreported. Missed nursing care opportunities, particularly oral care, may aid NV-HAP prevention. This descriptive, observational, retrospective chart review identified adult NV-HAP cases and associated demographic and hospital care data. Two hundred five NV-HAP cases occurred in 1 year at Montefiore Medical Center, equating to an incidence of 0.47 per 1000 patient-days and an estimated excess cost of $8.2 million. ICU transfer following pneumonia occurred in 15.6% of cases. Care requirements from specialist nursing facilities increased at discharge (26.8%), as compared with care requirements on admission (17.6%). Complete nursing care documentation was missing for most patients, with oral care undocumented 60.5% of the time. Preventable NV-HAP cases and their negative impact on cost and patient outcomes may decrease through improved basic nursing care.

Proposed experiment to test fundamentally binary theories

NASA Astrophysics Data System (ADS)

Kleinmann, Matthias; Vértesi, Tamás; Cabello, Adán

2017-09-01

Fundamentally binary theories are nonsignaling theories in which measurements of many outcomes are constructed by selecting from binary measurements. They constitute a sensible alternative to quantum theory and have never been directly falsified by any experiment. Here we show that fundamentally binary theories are experimentally testable with current technology. For that, we identify a feasible Bell-type experiment on pairs of entangled qutrits. In addition, we prove that, for any n , quantum n -ary correlations are not fundamentally (n -1 ) -ary. For that, we introduce a family of inequalities that hold for fundamentally (n -1 ) -ary theories but are violated by quantum n -ary correlations.

Consequences of Delayed, Unfinished, or Missed Nursing Care During Labor and Birth.

PubMed

Simpson, Kathleen Rice; Lyndon, Audrey

: The purpose of this study was to examine the concept of delayed, unfinished, or missed nursing care when patient census and acuity exceed nurse staffing resources with nurses who care for women during labor and birth. Focus groups were held during which labor nurses were asked about aspects of nursing care that may be regularly delayed, unfinished, or completely missed during labor and birth, including possible reasons and potential consequences. Seventy-one labor nurses participated in 11 focus groups in 6 hospitals. Nurses focused on support and encouragement as aspects of care that they felt are essential but often not able to be performed when the unit is busy. Nurses seemed to assume technical features of care as a "given" in the background and not always noticed unless missed. They voiced concerns about risks to maternal and fetal well-being when they were short-staffed. Potential outcomes were discussed including cesarean birth, depressed infants at birth, hemorrhage, and negative effects on patient satisfaction, successful breast-feeding, and the overall patient experience. When essential aspects of nursing care are delayed, unfinished, or completely missed, there are potentially negative implications for numerous patient outcomes and patient safety is at risk.

Optimal simultaneous superpositioning of multiple structures with missing data

PubMed Central

Theobald, Douglas L.; Steindel, Phillip A.

2012-01-01

Motivation: Superpositioning is an essential technique in structural biology that facilitates the comparison and analysis of conformational differences among topologically similar structures. Performing a superposition requires a one-to-one correspondence, or alignment, of the point sets in the different structures. However, in practice, some points are usually ‘missing’ from several structures, for example, when the alignment contains gaps. Current superposition methods deal with missing data simply by superpositioning a subset of points that are shared among all the structures. This practice is inefficient, as it ignores important data, and it fails to satisfy the common least-squares criterion. In the extreme, disregarding missing positions prohibits the calculation of a superposition altogether. Results: Here, we present a general solution for determining an optimal superposition when some of the data are missing. We use the expectation–maximization algorithm, a classic statistical technique for dealing with incomplete data, to find both maximum-likelihood solutions and the optimal least-squares solution as a special case. Availability and implementation: The methods presented here are implemented in THESEUS 2.0, a program for superpositioning macromolecular structures. ANSI C source code and selected compiled binaries for various computing platforms are freely available under the GNU open source license from http://www.theseus3d.org. Contact: dtheobald@brandeis.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22543369

Adaptive detection of missed text areas in OCR outputs: application to the automatic assessment of OCR quality in mass digitization projects

NASA Astrophysics Data System (ADS)

Ben Salah, Ahmed; Ragot, Nicolas; Paquet, Thierry

2013-01-01

The French National Library (BnF*) has launched many mass digitization projects in order to give access to its collection. The indexation of digital documents on Gallica (digital library of the BnF) is done through their textual content obtained thanks to service providers that use Optical Character Recognition softwares (OCR). OCR softwares have become increasingly complex systems composed of several subsystems dedicated to the analysis and the recognition of the elements in a page. However, the reliability of these systems is always an issue at stake. Indeed, in some cases, we can find errors in OCR outputs that occur because of an accumulation of several errors at different levels in the OCR process. One of the frequent errors in OCR outputs is the missed text components. The presence of such errors may lead to severe defects in digital libraries. In this paper, we investigate the detection of missed text components to control the OCR results from the collections of the French National Library. Our verification approach uses local information inside the pages based on Radon transform descriptors and Local Binary Patterns descriptors (LBP) coupled with OCR results to control their consistency. The experimental results show that our method detects 84.15% of the missed textual components, by comparing the OCR ALTO files outputs (produced by the service providers) to the images of the document.

Neonatal screening for glutaric aciduria type I: strategies to proceed.

PubMed

Lindner, M; Ho, S; Fang-Hoffmann, J; Hoffmann, G F; Kölker, S

2006-01-01

Acute encephalopathic crisis in glutaric aciduria type I results in an unfavourable disease course and poor outcome, dominated by dystonia, feeding problems, seizures and reduced life expectancy. A conditio sine qua non for the prevention of irreversible brain damage is timely diagnosis and start of therapy, i.e. before the onset of neurological disease. As there are no specific clinical signs or symptoms that allow a reliable detection of these patients before the manifestation of encephalopathic crises, neonatal screening programmes for glutaric aciduria type I have been established in some countries using analysis of glutarylcarnitine in dried blood spots by tandem mass spectrometry. This article summarizes recent strategies, pitfalls and shortcomings of mass screening for glutaric aciduria type I, focusing on the relevant risk of missing patients with a mild biochemical phenotype (i.e. low excretors). Furthermore, it evaluates a binary strategy--using glutarylcarnitine as primary variable and glutarylcarnitine/acylcarnitine ratios as secondary variable--to improve the diagnostic sensitivity and specificity of neonatal screening for glutaric aciduria type I. An optimization of diagnostic as well as therapeutic procedures must be achieved before screening for glutaric aciduria type I can be regarded as reliable and beneficial for all patients.

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

Determinants of Maternal Near-Miss in Morocco: Too Late, Too Far, Too Sloppy?

PubMed Central

Assarag, Bouchra; Dujardin, Bruno; Delamou, Alexandre; Meski, Fatima-Zahra; De Brouwere, Vincent

2015-01-01

Background In Morocco, there is little information on the circumstances surrounding maternal near misses. This study aimed to determine the incidence, characteristics, and determinants of maternal near misses in Morocco. Method A prospective case-control study was conducted at 3 referral maternity hospitals in the Marrakech region of Morocco between February and July 2012. Near-miss cases included severe hemorrhage, hypertensive disorders, and prolonged obstructed labor. Three unmatched controls were selected for each near-miss case. Three categories of risk factors (sociodemographics, reproductive history, and delays), as well as perinatal outcomes, were assessed, and bivariate and multivariate analyses of the determinants were performed. A sample of 30 near misses and 30 non-near misses was interviewed. Results The incidence of near misses was 12‰ of births. Hypertensive disorders during pregnancy (45%) and severe hemorrhage (39%) were the most frequent direct causes of near miss. The main risk factors were illiteracy [OR = 2.35; 95% CI: (1.07–5.15)], lack of antenatal care [OR = 3.97; 95% CI: (1.42–11.09)], complications during pregnancy [OR = 2.81; 95% CI:(1.26–6.29)], and having experienced a first phase delay [OR = 8.71; 95% CI: (3.97–19.12)] and a first phase of third delay [OR = 4.03; 95% CI: (1.75–9.25)]. The main reasons for the first delay were lack of a family authority figure who could make a decision, lack of sufficient financial resources, lack of a vehicle, and fear of health facilities. The majority of near misses demonstrated a third delay with many referrals. The women’s perceptions of the quality of their care highlighted the importance of information, good communication, and attitude. Conclusion Women and newborns with serious obstetric complications have a greater chance of successful outcomes if they are immediately directed to a functioning referral hospital and if the providers are responsive. PMID:25612095

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

Multiphase, multicomponent phase behavior prediction

NASA Astrophysics Data System (ADS)

Dadmohammadi, Younas

Accurate prediction of phase behavior of fluid mixtures in the chemical industry is essential for designing and operating a multitude of processes. Reliable generalized predictions of phase equilibrium properties, such as pressure, temperature, and phase compositions offer an attractive alternative to costly and time consuming experimental measurements. The main purpose of this work was to assess the efficacy of recently generalized activity coefficient models based on binary experimental data to (a) predict binary and ternary vapor-liquid equilibrium systems, and (b) characterize liquid-liquid equilibrium systems. These studies were completed using a diverse binary VLE database consisting of 916 binary and 86 ternary systems involving 140 compounds belonging to 31 chemical classes. Specifically the following tasks were undertaken: First, a comprehensive assessment of the two common approaches (gamma-phi (gamma-ϕ) and phi-phi (ϕ-ϕ)) used for determining the phase behavior of vapor-liquid equilibrium systems is presented. Both the representation and predictive capabilities of these two approaches were examined, as delineated form internal and external consistency tests of 916 binary systems. For the purpose, the universal quasi-chemical (UNIQUAC) model and the Peng-Robinson (PR) equation of state (EOS) were used in this assessment. Second, the efficacy of recently developed generalized UNIQUAC and the nonrandom two-liquid (NRTL) for predicting multicomponent VLE systems were investigated. Third, the abilities of recently modified NRTL model (mNRTL2 and mNRTL1) to characterize liquid-liquid equilibria (LLE) phase conditions and attributes, including phase stability, miscibility, and consolute point coordinates, were assessed. The results of this work indicate that the ϕ-ϕ approach represents the binary VLE systems considered within three times the error of the gamma-ϕ approach. A similar trend was observed for the for the generalized model predictions using quantitative structure-property parameter generalizations (QSPR). For ternary systems, where all three constituent binary systems were available, the NRTL-QSPR, UNIQUAC-QSPR, and UNIFAC-6 models produce comparable accuracy. For systems where at least one constituent binary is missing, the UNIFAC-6 model produces larger errors than the QSPR generalized models. In general, the LLE characterization results indicate the accuracy of the modified models in reproducing the findings of the original NRTL model.

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.

PubMed

Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M; Stuart, Elizabeth A

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Examining the Error of Mis-Specifying Nonlinear Confounding Effect With Application on Accelerometer-Measured Physical Activity.

PubMed

Lee, Paul H

2017-06-01

Some confounders are nonlinearly associated with dependent variables, but they are often adjusted using a linear term. The purpose of this study was to examine the error of mis-specifying the nonlinear confounding effect. We carried out a simulation study to investigate the effect of adjusting for a nonlinear confounder in the estimation of a causal relationship between the exposure and outcome in 3 ways: using a linear term, binning into 5 equal-size categories, or using a restricted cubic spline of the confounder. Continuous, binary, and survival outcomes were simulated. We examined the confounder across varying measurement error. In addition, we performed a real data analysis examining the 3 strategies to handle the nonlinear effects of accelerometer-measured physical activity in the National Health and Nutrition Examination Survey 2003-2006 data. The mis-specification of a nonlinear confounder had little impact on causal effect estimation for continuous outcomes. For binary and survival outcomes, this mis-specification introduced bias, which could be eliminated using spline adjustment only when there is small measurement error of the confounder. Real data analysis showed that the associations between high blood pressure, high cholesterol, and diabetes and mortality adjusted for physical activity with restricted cubic spline were about 3% to 11% larger than their counterparts adjusted with a linear term. For continuous outcomes, confounders with nonlinear effects can be adjusting with a linear term. Spline adjustment should be used for binary and survival outcomes on confounders with small measurement error.

Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

2018-03-01

Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

Hot Jupiters Aren't As Lonely As We Thought

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-01-01

The Friends of Hot Jupiters (FOHJ) project is a systematic search for planetary- and stellar-mass companions in systems that have known hot Jupiters short-period, gas-giant planets. This survey has discovered that many more hot Jupiters may have companions than originally believed.Missing FriendsFOHJ was begun with the goal of better understanding the systems that host hot Jupiters, in order to settle several longstanding issues.The first problem was one of observational statistics. We know that roughly half of the Sun-like stars nearby are in binary systems, yet weve only discovered a handful of hot Jupiters around binaries. Are binary systems less likely to host hot Jupiters? Or have we just missed the binary companions in the hot-Jupiter-hosting systems weve seen so far?An additional issue relates to formation mechanisms. Hot Jupiters probably migrated inward from where they formed out beyond the ice lines in protoplanetary disks but how?This median-stacked image, obtained with adaptive optics, shows one of the newly-discovered stellar companions to a star hosting a hot Jupiter. The projected separation is ~180 AU. [Ngo et al. 2015]Observations reveal two populations of hot Jupiters: those with circular orbits aligned with their hosts spins, and those with eccentric, misaligned orbits. The former population support a migration model dominated by local planet-disk interactions, whereas the latter population suggest the hot Jupiters migrated through dynamical interactions with distant companions. A careful determination of the companion rate in hot-Jupiter-hosting systems could help establish the ability of these two models to explain the observed populations.Search for CompanionsThe FOHJ project began in 2012 and studied 51 systems hosting known, transiting hot Jupiters with roughly half on circular, aligned orbits and half on eccentric, misaligned orbits. The survey consisted of three different, complementary components:Study 1Lead author: Heather Knutson (Caltech)Technique: Long-term radial velocity monitoringSearching for: Planetary companions at 120 AU from the starStudy 2Lead author: Henry Ngo (Caltech)Technique: Adaptive-optics imagingSearching for: Stellar companions at 502000 AU from the starStudy 3Lead author: Danielle Piskorz (Caltech)Technique: SpectroscopySearching for: Any additional stellar companions at 125 AU from the starThe companion fraction found within Study 2, the adaptive-optics imagine search. The three curves show the total, the systems with hot Jupiters on aligned and circular orbits, and those with hot Jupiters on misaligned and eccentric orbits. [Ngo et al. 2015]Migration ImplicationsUsing these three different techniques, the team found a significant number of both planetary and stellar companions that had not been previously detected. After correcting their results for completeness, they found a multiple-star rate of ~50% for these systems, resolving the problem of the missing companions. So really, we just werent looking hard enough for the companions previously.Intriguingly, the binary companion rate found for these hot Jupiter systems is higher than the average rate for the field stars (which is below 25% for the semimajor-axis range the FOHJ studies are sensitive to). This suggests that companion stars may indeed play a role in hot Jupiter formation and migration.That said, none of the three studies found a significant difference in the binary fraction for aligned versus misaligned hot Jupiters which means that the answer is not as simple as thought, with companion stars causing the misaligned planets. Thus, while hot Jupiters friends may play a role in their formation and migration, we still have work to do in understanding what that role is.CitationDanielle Piskorz et al 2015 ApJ 814 148. doi:10.1088/0004-637X/814/2/148Henry Ngo et al 2015 ApJ 800 138. doi:10.1088/0004-637X/800/2/138Heather A. Knutson et al 2014 ApJ 785 126. doi:10.1088/0004-637X/785/2/126

Evaluation of techniques for handling missing cost-to-charge ratios in the USA Nationwide Inpatient Sample: a simulation study.

PubMed

Yu, Tzy-Chyi; Zhou, Huanxue

2015-09-01

Evaluate performance of techniques used to handle missing cost-to-charge ratio (CCR) data in the USA Healthcare Cost and Utilization Project's Nationwide Inpatient Sample. Four techniques to replace missing CCR data were evaluated: deleting discharges with missing CCRs (complete case analysis), reweighting as recommended by Healthcare Cost and Utilization Project, reweighting by adjustment cells and hot deck imputation by adjustment cells. Bias and root mean squared error of these techniques on hospital cost were evaluated in five disease cohorts. Similar mean cost estimates would be obtained with any of the four techniques when the percentage of missing data is low (<10%). When total cost is the outcome of interest, a reweighting technique to avoid underestimation from dropping observations with missing data should be adopted.

Missing School Matters

ERIC Educational Resources Information Center

Balfanz, Robert

2016-01-01

Results of a survey conducted by the Office for Civil Rights show that 6 million public school students (13%) are not attending school regularly. Chronic absenteeism--defined as missing more than 10% of school for any reason--has been negatively linked to many key academic outcomes. Evidence shows that students who exit chronic absentee status can…

Near-misses are an opportunity to improve patient safety: adapting strategies of high reliability organizations to healthcare.

PubMed

Van Spall, Harriette; Kassam, Alisha; Tollefson, Travis T

2015-08-01

Near-miss investigations in high reliability organizations (HROs) aim to mitigate risk and improve system safety. Healthcare settings have a higher rate of near-misses and subsequent adverse events than most high-risk industries, but near-misses are not systematically reported or analyzed. In this review, we will describe the strategies for near-miss analysis that have facilitated a culture of safety and continuous quality improvement in HROs. Near-miss analysis is routine and systematic in HROs such as aviation. Strategies implemented in aviation include the Commercial Aviation Safety Team, which undertakes systematic analyses of near-misses, so that findings can be incorporated into Standard Operating Procedures (SOPs). Other strategies resulting from incident analyses include Crew Resource Management (CRM) for enhanced communication, situational awareness training, adoption of checklists during operations, and built-in redundancy within systems. Health care organizations should consider near-misses as opportunities for quality improvement. The systematic reporting and analysis of near-misses, commonplace in HROs, can be adapted to health care settings to prevent adverse events and improve clinical outcomes.

A Comparison of Grid-based and SPH Binary Mass-transfer and Merger Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Motl, Patrick M.; Frank, Juhan; Clayton, Geoffrey C.

2017-04-01

There is currently a great amount of interest in the outcomes and astrophysical implications of mergers of double degenerate binaries. In a commonly adopted approximation, the components of such binaries are represented by polytropes with an index of n  = 3/2. We present detailed comparisons of stellar mass-transfer and merger simulations of polytropic binaries that have been carried out using two very different numerical algorithms—a finite-volume “grid” code and a smoothed-particle hydrodynamics (SPH) code. We find that there is agreement in both the ultimate outcomes of the evolutions and the intermediate stages if the initial conditions for each code are chosen to matchmore » as closely as possible. We find that even with closely matching initial setups, the time it takes to reach a concordant evolution differs between the two codes because the initial depth of contact cannot be matched exactly. There is a general tendency for SPH to yield higher mass transfer rates and faster evolution to the final outcome. We also present comparisons of simulations calculated from two different energy equations: in one series, we assume a polytropic equation of state and in the other series an ideal gas equation of state. In the latter series of simulations, an atmosphere forms around the accretor, which can exchange angular momentum and cause a more rapid loss of orbital angular momentum. In the simulations presented here, the effect of the ideal equation of state is to de-stabilize the binary in both SPH and grid simulations, but the effect is more pronounced in the grid code.« less

Likelihood-Based Random-Effect Meta-Analysis of Binary Events.

PubMed

Amatya, Anup; Bhaumik, Dulal K; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D

2015-01-01

Meta-analysis has been used extensively for evaluation of efficacy and safety of medical interventions. Its advantages and utilities are well known. However, recent studies have raised questions about the accuracy of the commonly used moment-based meta-analytic methods in general and for rare binary outcomes in particular. The issue is further complicated for studies with heterogeneous effect sizes. Likelihood-based mixed-effects modeling provides an alternative to moment-based methods such as inverse-variance weighted fixed- and random-effects estimators. In this article, we compare and contrast different mixed-effect modeling strategies in the context of meta-analysis. Their performance in estimation and testing of overall effect and heterogeneity are evaluated when combining results from studies with a binary outcome. Models that allow heterogeneity in both baseline rate and treatment effect across studies have low type I and type II error rates, and their estimates are the least biased among the models considered.

An instrumental variable random-coefficients model for binary outcomes

PubMed Central

Chesher, Andrew; Rosen, Adam M

2014-01-01

In this paper, we study a random-coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be required for a control function approach. The model fits within the spectrum of generalized instrumental variable models, and we thus apply identification results from our previous studies of such models to the present context, demonstrating their use. Specifically, we characterize the identified set for the distribution of random coefficients in the binary response model with endogeneity via a collection of conditional moment inequalities, and we investigate the structure of these sets by way of numerical illustration. PMID:25798048

Assessment of score- and Rasch-based methods for group comparison of longitudinal patient-reported outcomes with intermittent missing data (informative and non-informative).

PubMed

de Bock, Élodie; Hardouin, Jean-Benoit; Blanchin, Myriam; Le Neel, Tanguy; Kubis, Gildas; Sébille, Véronique

2015-01-01

The purpose of this study was to identify the most adequate strategy for group comparison of longitudinal patient-reported outcomes in the presence of possibly informative intermittent missing data. Models coming from classical test theory (CTT) and item response theory (IRT) were compared. Two groups of patients' responses to dichotomous items with three times of assessment were simulated. Different cases were considered: presence or absence of a group effect and/or a time effect, a total of 100 or 200 patients, 4 or 7 items and two different values for the correlation coefficient of the latent trait between two consecutive times (0.4 or 0.9). Cases including informative and non-informative intermittent missing data were compared at different rates (15, 30 %). These simulated data were analyzed with CTT using score and mixed model (SM) and with IRT using longitudinal Rasch mixed model (LRM). The type I error, the power and the bias of the group effect estimations were compared between the two methods. This study showed that LRM performs better than SM. When the rate of missing data rose to 30 %, estimations were biased with SM mainly for informative missing data. Otherwise, LRM and SM methods were comparable concerning biases. However, regardless of the rate of intermittent missing data, power of LRM was higher compared to power of SM. In conclusion, LRM should be favored when the rate of missing data is higher than 15 %. For other cases, SM and LRM provide similar results.

Predictors of Employment Outcomes for State-Federal Vocational Rehabilitation Consumers with HIV/AIDS

ERIC Educational Resources Information Center

Jung, Youngoh; Schaller, James; Bellini, James

2010-01-01

In this study, the authors investigated the effects of demographic, medical, and vocational rehabilitation service variables on employment outcomes of persons living with HIV/AIDS. Binary logistic regression analyses were conducted to determine predictors of employment outcomes using two groups drawn from Rehabilitation Services Administration…

Improved associative recall of binary data in volume holographic memories

NASA Astrophysics Data System (ADS)

Betzos, George A.; Laisné, Alexandre; Mitkas, Pericles A.

1999-11-01

A new technique is presented that improves the results of associative recall in a volume holographic memory system. A background is added to the normal search argument to increase the amount of optical power that is used to reconstruct the reference beams in the crystal. This is combined with post-processing of the captured image of the reference beams. The use of both the background and post-processing greatly improves the results by allowing associative recall using small arguments. In addition, the number of false hits is reduced and misses are virtually eliminated.

Chandra Discovery of a Binary Active Galactic Nucleus in Mrk 739

NASA Astrophysics Data System (ADS)

Koss, Michael; Mushotzky, Richard; Treister, Ezequiel; Veilleux, Sylvain; Vasudevan, Ranjan; Miller, Neal; Sanders, D. B.; Schawinski, Kevin; Trippe, Margaret

2011-07-01

We have discovered a binary active galactic nucleus (AGN) in the galaxy Mrk 739 using Chandra and Swift BAT. We find two luminous (L 2-10 keV = 1.1 × 1043 and 1.0 × 1042 erg s-1), unresolved nuclei with a projected separation of 3.4 kpc (5farcs8 ± 0farcs1) coincident with two bulge components in the optical image. The western X-ray source (Mrk 739W) is highly variable (× 2.5) during the 4 hr Chandra observation and has a very hard spectrum consistent with an AGN. While the eastern component was already known to be an AGN based on the presence of broad optical recombination lines, Mrk 739W shows no evidence of being an AGN in optical, UV, and radio observations, suggesting the critical importance of high spatial resolution hard X-ray observations (>2 keV) in finding these binary AGNs. A high level of star formation combined with a very low L [O III]/L 2-10 keV ratio cause the AGN to be missed in optical observations. 12CO observations of the (3-2) and (2-1) lines indicate large amounts of molecular gas in the system that could be driven toward the black holes during the violent galaxy collision and be key to fueling the binary AGN. Mrk 739E has a high Eddington ratio of 0.71 and a small black hole (log M BH = 7.05 ± 0.3) consistent with an efficiently accreting AGN. Other than NGC 6240, this stands as the nearest case of a binary AGN discovered to date.

Evidence from Quasi-Periodic Oscillations for a Millisecond Pulsar in the Low Mass X-Ray Binary 4U 0614+091

NASA Technical Reports Server (NTRS)

Ford, E.; Kaaret, P.; Tavani, M.; Barret, D.; Bloser, P.; Grindlay, J.; Harmon, B. A.; Paciesas, W. S.; Zhang, S. N.

1997-01-01

We have detected quasi-periodic oscillations (QPOs) near 1 kHz from the low mass X-ray binary 4U 0614+091 in observations with RXTE. The observations span several months and sample the source over a large range of X-ray luminosity. In every interval QPOs are present above 400 Hz with fractional RMS amplitudes from 3 to 12% over the full PCA band. At high count rates, two high frequency QPOs are detected simultaneously. The difference of their frequency centroids is consistent with a constant value of 323 Hz in all observations. During one interval a third signal is detected at 328 +/- 2 Hz. This suggests the system has a stable 'clock' which is most likely the neutron star with spin period 3.1 msec. Thus, our observations of 4U 0614+091 and those of 4U 1728-34 provide the first evidence for millisecond pulsars within low-mass X-ray binary systems and reveal the 'missing-link' between millisecond radiopulsars and the late stages of binary evolution in low mass X-ray binaries. The constant difference of the high frequency QPOs sug,,ests a beat-frequency interpretation. In this model, the high frequency QPO is associated with the Keplerian frequency of the inner accretion disk and the lower frequency QPO is a 'beat' between the differential rotation frequency of the inner disk and the spinning neutron star. Assuming the high frequency QPO is a Keplerian orbital frequency for the accretion disk, we find a maximum mass of 1.9 solar mass and a maximum radius of 17 km for the neutron star.

The use of missing birth record data as a marker for adverse reproductive outcomes: a geocoded analysis of birth record data.

PubMed Central

Headley, Adrienne J.; Fulcomer, Mark C.; Bastardi, Matthew M.; Im, Wansoo; Sass, Marcia M.; Chung, Katherine

2006-01-01

Adverse reproductive outcomes (AROs) disproportionately affect black American infants and significantly contribute to the U.S. infant mortality rate. Without accurate understanding of AROs, there remains little hope of ameliorating infant mortality rates or eliminating infant health disparities. However, despite the importance of monitoring infant mortality rates and health disparities, birth record data quality is not assured. Racial disparities in the reporting of birth record data have been documented, and missing birth record data for AROs appears to be disproportionate. Due to the extent of missing birth record data, innovative strategies have been developed to evaluate relationships between maternal socioeconomic status (SES) and community-based ARO rates. Because addresses convey aggregate information about income level, education and occupation, ZIP codes, census tracts and census block-groups have been applied to geocoding efforts. The goals of this study are to: 1) analyze the extent of missing birth record data for New Jersey areas with high rates of an ARO (preterm birth), 2) evaluate associations between the extent of missing birth record data and other AROs, and 3) consider how geocoding strategies could be applied to provide a basis for understanding maternal SES risk factors and ARO resource allocation for at-risk communities. PMID:16895276

Quantifying the Consequences of Missing School: Linking School Nurses to Student Absences to Standardized Achievement

ERIC Educational Resources Information Center

Gottfried, Michael A.

2013-01-01

Background/Context: Parents, policymakers, and researchers uphold that missing school has negative implications on schooling success, particularly for students in urban schools. However, it has thus far been an empirical challenge within educational research to estimate the true effect that absences have on achievement outcomes. This study…

A Missing Link: People, Practice and Some Precarious Research!

ERIC Educational Resources Information Center

Higdon, Carolyn Wiles; Higdon, Lawrence W.

2004-01-01

The field of augmentative and alternative communication's (AAC) missing link is the discrepancy between what the research community identifies as needs and what the clinical community, including the AAC user, believes to be the AAC user's needs. An unrealistic picture of the AAC user occurs, developing a top-down effect of limited outcomes,…

Tailored nutrition education and food assistance improve adherence to HIV antiretroviral therapy: evidence from Honduras.

PubMed

Martinez, Homero; Palar, Kartika; Linnemayr, Sebastian; Smith, Alexandria; Derose, Kathryn Pitkin; Ramírez, Blanca; Farías, Hugo; Wagner, Glenn

2014-10-01

Food insecurity and malnutrition negatively affect adherence to antiretroviral therapy (ART) and are associated with poor HIV clinical outcomes. We examined the effect of providing household food assistance and nutrition education on ART adherence. A 12-month prospective clinical trial compared the effect of a monthly household food basket (FB) plus nutrition education (NE) versus NE alone on ART adherence on 400 HIV patients at four clinics in Honduras. Participants had been receiving ART for an average of 3.7 years and were selected because they had suboptimal adherence. Primary outcome measures were missed clinic appointments, delayed prescription refills, and self-reported missed doses of ART. These three adherence measures improved for both groups over 12 months (p < 0.01), mostly within 6 months. On-time prescription refills improved for the FB plus NE group by 19.6 % more than the group receiving NE alone after 6 months (p < 0.01), with no further change at 12 months. Change in missed appointments and self-reported missed ART doses did not significantly differ by intervention group.

Near miss and minor occupational injury: Does it share a common causal pathway with major injury?

PubMed

Alamgir, Hasanat; Yu, Shicheng; Gorman, Erin; Ngan, Karen; Guzman, Jaime

2009-01-01

An essential assumption of injury prevention programs is the common cause hypothesis that the causal pathways of near misses and minor injuries are similar to those of major injuries. The rates of near miss, minor injury and major injury of all reported incidents and musculoskeletal incidents (MSIs) were calculated for three health regions using information from a surveillance database and productive hours from payroll data. The relative distribution of individual causes and activities involved in near miss, minor injury and major injury were then compared. For all reported incidents, there were significant differences in the relative distribution of causes for near miss, minor, and major injury. However, the relative distribution of causes and activities involved in minor and major MSIs were similar. The top causes and activities involved were the same across near miss, minor, and major injury. Finding from this study support the use of near miss and minor injury data as potential outcome measures for injury prevention programs. (c) 2008 Wiley-Liss, Inc.

Medical surgical nurses describe missed nursing care tasks-Evaluating our work environment.

PubMed

Winsett, Rebecca P; Rottet, Kendra; Schmitt, Abby; Wathen, Ellen; Wilson, Debra

2016-11-01

The purpose of the study was to explore the nurse work environment by evaluating the self-report of missed nursing care and the reasons for the missed care. A convenience sample of medical surgical nurses from four hospitals was invited to complete the survey for this descriptive study. The sample included 168 nurses. The MISSCARE survey assessed the frequency and reason of 24 routine nursing care elements. The most frequently reported missed care was ambulation as ordered, medications given within a 30 minute window, and mouth care. Moderate or significant reasons reported for the missed care were: unexpected rise in volume/acuity, heavy admissions/discharges, inadequate assistants, inadequate staff, meds not available when needed, and urgent situations. Identifying missed nursing care and reasons for missed care provides an opportunity for exploring strategies to reduce interruptions, develop unit cohesiveness, improve the nurse work environment, and ultimately leading to improved patient outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Missing Link: Bayesian detection and measurement of intermediate-mass black-hole binaries

NASA Astrophysics Data System (ADS)

Graff, Philip B.; Buonanno, Alessandra; Sathyaprakash, B. S.

2015-07-01

We perform Bayesian analysis of gravitational-wave signals from nonspinning, intermediate-mass black-hole binaries (IMBHBs) with observed total mass, Mobs, from 50 M⊙ to 500 M⊙ and mass ratio 1-4 using advanced LIGO and Virgo detectors. We employ inspiral-merger-ringdown waveform models based on the effective-one-body formalism and include subleading modes of radiation beyond the leading (2,2) mode. The presence of subleading modes increases signal power for inclined binaries and allows for improved accuracy and precision in measurements of the masses as well as breaking of degeneracies in distance, orientation and polarization. For low total masses, Mobs≲50 M⊙ , for which the inspiral signal dominates, the observed chirp mass Mobs=Mobsη3 /5 (η being the symmetric mass ratio) is better measured. In contrast, as increasing power comes from merger and ringdown, we find that the total mass Mobs has better relative precision than Mobs. Indeed, at high Mobs (≥300 M⊙ ), the signal resembles a burst and the measurement thus extracts the dominant frequency of the signal that depends on Mobs. Depending on the binary's inclination, at signal-to-noise ratio (SNR) of 12, uncertainties in Mobs can be as large as ˜20 - 25 % while uncertainties in Mobs are ˜50 - 60 % in binaries with unequal masses (those numbers become ˜17 % vs. ˜22 % in more symmetric mass-ratio binaries). Although large, those uncertainties in Mobs will establish the existence of IMBHs. We find that effective-one-body waveforms with subleading modes are essential to confirm a signal's presence in the data, with calculated Bayesian evidences yielding a false alarm probability below 10-5 for SNR ≳9 in Gaussian noise. Our results show that gravitational-wave observations can offer a unique tool to observe and understand the formation, evolution and demographics of IMBHs, which are difficult to observe in the electromagnetic window.

Alternation blindness in the representation of binary sequences.

PubMed

Yu, Ru Qi; Osherson, Daniel; Zhao, Jiaying

2018-03-01

Binary information is prevalent in the environment and contains 2 distinct outcomes. Binary sequences consist of a mixture of alternation and repetition. Understanding how people perceive such sequences would contribute to a general theory of information processing. In this study, we examined how people process alternation and repetition in binary sequences. Across 4 paradigms involving estimation, working memory, change detection, and visual search, we found that the number of alternations is underestimated compared with repetitions (Experiment 1). Moreover, recall for binary sequences deteriorates as the sequence alternates more (Experiment 2). Changes in bits are also harder to detect as the sequence alternates more (Experiment 3). Finally, visual targets superimposed on bits of a binary sequence take longer to process as alternation increases (Experiment 4). Overall, our results indicate that compared with repetition, alternation in a binary sequence is less salient in the sense of requiring more attention for successful encoding. The current study thus reveals the cognitive constraints in the representation of alternation and provides a new explanation for the overalternation bias in randomness perception. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Assurance of Myeloid Growth Factor Administration in an Infusion Center: Pilot Quality Improvement Initiative.

PubMed

Ramirez, Pamela Maree; Peterson, Barry; Holtshopple, Christine; Borja, Kristina; Torres, Vincent; Valdivia-Peppers, Lucille; Harriague, Julio; Joe, Melanie D

2017-12-01

Four incident reports involving missed doses of myeloid growth factors (MGFs) triggered the need for an outcome-driven initiative. From March 1, 2015, to February 29, 2016, at University of California Irvine Health Chao Infusion Center, 116 of 3,300 MGF doses were missed (3.52%), including pegfilgrastim, filgrastim, and sargramostim. We hypothesized that with the application of Lean Six Sigma methodology, we would achieve our primary objective of reducing the number of missed MGF doses to < 0.5%. This quality improvement initiative was conducted at Chao Infusion Center as part of a Lean Six Sigma Green Belt Certification Program. Therefore, Lean Six Sigma principles and tools were used throughout each phase of the project. Retrospective and prospective medical record reviews and data analyses were performed to evaluate the extent of the identified problem and impact of the process changes. Improvements included systems applications, practice changes, process modifications, and safety-net procedures. Preintervention, 24 missed doses (20.7%) required patient supportive care measures, resulting in increased hospital costs and decreased quality of care. Postintervention, from June 8, 2016, to August 7, 2016, zero of 489 MGF doses were missed after 2 months of intervention ( P < .001). Chao Infusion Center reduced missed doses from 3.52% to 0%, reaching the goal of < 0.5%. The establishment of simplified and standardized processes with safety checks for error prevention increased quality of care. Lean Six Sigma methodology can be applied by other institutions to produce positive outcomes and implement similar practice changes.

The Role of Balanced Training and Testing Data Sets for Binary Classifiers in Bioinformatics

PubMed Central

Wei, Qiong; Dunbrack, Roland L.

2013-01-01

Training and testing of conventional machine learning models on binary classification problems depend on the proportions of the two outcomes in the relevant data sets. This may be especially important in practical terms when real-world applications of the classifier are either highly imbalanced or occur in unknown proportions. Intuitively, it may seem sensible to train machine learning models on data similar to the target data in terms of proportions of the two binary outcomes. However, we show that this is not the case using the example of prediction of deleterious and neutral phenotypes of human missense mutations in human genome data, for which the proportion of the binary outcome is unknown. Our results indicate that using balanced training data (50% neutral and 50% deleterious) results in the highest balanced accuracy (the average of True Positive Rate and True Negative Rate), Matthews correlation coefficient, and area under ROC curves, no matter what the proportions of the two phenotypes are in the testing data. Besides balancing the data by undersampling the majority class, other techniques in machine learning include oversampling the minority class, interpolating minority-class data points and various penalties for misclassifying the minority class. However, these techniques are not commonly used in either the missense phenotype prediction problem or in the prediction of disordered residues in proteins, where the imbalance problem is substantial. The appropriate approach depends on the amount of available data and the specific problem at hand. PMID:23874456

Rational and Boundedly Rational Behavior in a Binary Choice Sender-Receiver Game

ERIC Educational Resources Information Center

Landi, Massimiliano; Colucci, Domenico

2008-01-01

The authors investigate the strategic rationale behind the message sent by Osama bin Laden on the eve of the 2004 U.S. Presidential elections. They model this situation as a signaling game in which a population of receivers takes a binary choice, the outcome is decided by majority rule, sender and receivers have conflicting interests, and there is…

Autism spectrum disorders and fetal hypoxia in a population-based cohort: Accounting for missing exposures via Estimation-Maximization algorithm

PubMed Central

2011-01-01

Background Autism spectrum disorders (ASD) are associated with complications of pregnancy that implicate fetal hypoxia (FH); the excess of ASD in male gender is poorly understood. We tested the hypothesis that risk of ASD is related to fetal hypoxia and investigated whether this effect is greater among males. Methods Provincial delivery records (PDR) identified the cohort of all 218,890 singleton live births in the province of Alberta, Canada, between 01-01-98 and 12-31-04. These were followed-up for ASD via ICD-9 diagnostic codes assigned by physician billing until 03-31-08. Maternal and obstetric risk factors, including FH determined from blood tests of acidity (pH), were extracted from PDR. The binary FH status was missing in approximately half of subjects. Assuming that characteristics of mothers and pregnancies would be correlated with FH, we used an Estimation-Maximization algorithm to estimate HF-ASD association, allowing for both missing-at-random (MAR) and specific not-missing-at-random (NMAR) mechanisms. Results Data indicated that there was excess risk of ASD among males who were hypoxic at birth, not materially affected by adjustment for potential confounding due to birth year and socio-economic status: OR 1.13, 95%CI: 0.96, 1.33 (MAR assumption). Limiting analysis to full-term males, the adjusted OR under specific NMAR assumptions spanned 95%CI of 1.0 to 1.6. Conclusion Our results are consistent with a weak effect of fetal hypoxia on risk of ASD among males. E-M algorithm is an efficient and flexible tool for modeling missing data in the studied setting. PMID:21208442

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

PubMed Central

Zhong, Sheng; McPeek, Mary Sara

2016-01-01

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan. PMID:27695091

Five-minute Apgar score and educational outcomes: retrospective cohort study of 751,369 children.

PubMed

Tweed, Emily J; Mackay, Daniel F; Nelson, Scott M; Cooper, Sally-Ann; Pell, Jill P

2016-03-01

The Apgar score is used worldwide for assessing the clinical condition and short-term prognosis of newborn infants. Evidence for a relationship with long-term educational outcomes is conflicting. We investigated whether Apgar score at 5 min after birth was associated with additional support needs (ASN) and educational attainment. Data on pregnancy, delivery and later educational outcomes for children attending Scottish schools between 2006 and 2011 were collated by linking individual-level data from national educational and maternity databases. The relationship between Apgar score and overall ASN, type-specific ASN and educational attainment was assessed using binary, multinomial and generalised ordinal logistic regression models, respectively. Missing covariate data were imputed. Of the 751,369 children eligible, 9741 (1.3%) had a low or intermediate Apgar score and 49,962 (6.6%) had ASN. Low Apgar score was independently associated with overall ASN status (adjusted OR for Apgar ≤3, OR 1.52 95% CI 1.35 to 1.70), as well as ASN due to cognitive (OR 1.26, 95% CI 1.09 to 1.47), sensory (OR 2.49 95% CI 1.66 to 3.73) and motor (OR 3.57, 95% CI 2.86 to 4.47) impairments. There was a dose-response relationship between Apgar score and overall ASN status: of those scoring 0-3, 10.1% had ASN, compared with 9.1% of those scoring 4-7 and 6.6% of those scoring 7-10. A low Apgar score was associated with lower educational attainment, but this was not robust to adjustment for confounders. Apgar scores are associated with long-term as well as short-term prognoses, and with educational as well as clinical outcomes at the population level. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention

PubMed Central

Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M.; Stuart, Elizabeth A.

2016-01-01

We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration. PMID:27158217

Sequential parallel comparison design with binary and time-to-event outcomes.

PubMed

Silverman, Rachel Kloss; Ivanova, Anastasia; Fine, Jason

2018-04-30

Sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials especially trials with possibly high placebo effect. Sequential parallel comparison design is conducted with 2 stages. Participants are randomized between active therapy and placebo in stage 1. Then, stage 1 placebo nonresponders are rerandomized between active therapy and placebo. Data from the 2 stages are pooled to yield a single P value. We consider SPCD with binary and with time-to-event outcomes. For time-to-event outcomes, response is defined as a favorable event prior to the end of follow-up for a given stage of SPCD. We show that for these cases, the usual test statistics from stages 1 and 2 are asymptotically normal and uncorrelated under the null hypothesis, leading to a straightforward combined testing procedure. In addition, we show that the estimators of the treatment effects from the 2 stages are asymptotically normal and uncorrelated under the null and alternative hypothesis, yielding confidence interval procedures with correct coverage. Simulations and real data analysis demonstrate the utility of the binary and time-to-event SPCD. Copyright © 2018 John Wiley & Sons, Ltd.

Coping with missing data in phase III pivotal registration trials: Tolvaptan in subjects with kidney disease, a case study.

PubMed

Ouyang, John; Carroll, Kevin J; Koch, Gary; Li, Junfang

2017-07-01

Missing data cause challenging issues, particularly in phase III registration trials, as highlighted by the European Medicines Agency (EMA) and the US National Research Council. We explore, as a case study, how the issues from missing data were tackled in a double-blind phase III trial in subjects with autosomal dominant polycystic kidney disease. A total of 1445 subjects were randomized in a 2:1 ratio to receive active treatment (tolvaptan), or placebo. The primary outcome, the rate of change in total kidney volume, favored tolvaptan (P < .0001). The key secondary efficacy endpoints of clinical progression of disease and rate of decline in kidney function also favored tolvaptan. However, as highlighted by Food and Drug Administration and EMA, the interpretation of results was hampered by a high number of unevenly distributed dropouts, particularly early dropouts. In this paper, we outline the analyses undertaken to address the issue of missing data thoroughly. "Tipping point analyses" were performed to explore how extreme and detrimental outcomes among subjects with missing data must be to overturn the positive treatment effect attained in those subjects who had complete data. Nonparametric rank-based analyses were also performed accounting for missing data. In conclusion, straightforward and transparent analyses directly taking into account missing data convincingly support the robustness of the preplanned analyses on the primary and secondary endpoints. Tolvaptan was confirmed to be effective in slowing total kidney volume growth, which is considered an efficacy endpoint by EMA, and in lessening the decline in renal function in patients with autosomal dominant polycystic kidney disease. Copyright © 2017 John Wiley & Sons, Ltd.

Striatal connectivity changes following gambling wins and near-misses: Associations with gambling severity

PubMed Central

van Holst, Ruth J.; Chase, Henry W.; Clark, Luke

2014-01-01

Frontostriatal circuitry is implicated in the cognitive distortions associated with gambling behaviour. ‘Near-miss’ events, where unsuccessful outcomes are proximal to a jackpot win, recruit overlapping neural circuitry with actual monetary wins. Personal control over a gamble (e.g., via choice) is also known to increase confidence in one's chances of winning (the ‘illusion of control’). Using psychophysiological interaction (PPI) analyses, we examined changes in functional connectivity as regular gamblers and non-gambling participants played a slot-machine game that delivered wins, near-misses and full-misses, and manipulated personal control. We focussed on connectivity with striatal seed regions, and associations with gambling severity, using voxel-wise regression. For the interaction term of near-misses (versus full-misses) by personal choice (participant-chosen versus computer-chosen), ventral striatal connectivity with the insula, bilaterally, was positively correlated with gambling severity. In addition, some effects for the contrast of wins compared to all non-wins were observed at an uncorrected (p < .001) threshold: there was an overall increase in connectivity between the striatal seeds and left orbitofrontal cortex and posterior insula, and a negative correlation for gambling severity with the connectivity between the right ventral striatal seed and left anterior cingulate cortex. These findings corroborate the ‘non-categorical’ nature of reward processing in gambling: near-misses and full-misses are objectively identical outcomes that are processed differentially. Ventral striatal connectivity with the insula correlated positively with gambling severity in the illusion of control contrast, which could be a risk factor for the cognitive distortions and loss-chasing that are characteristic of problem gambling. PMID:25068112

A SEARCH FOR VERY HIGH ENERGY GAMMA RAYS FROM THE MISSING LINK BINARY PULSAR J1023+0038 WITH VERITAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aliu, E.; Archambault, S.; Archer, A.

2016-11-10

The binary millisecond radio pulsar PSR J1023+0038 exhibits many characteristics similar to the gamma-ray binary system PSR B1259–63/LS 2883, making it an ideal candidate for the study of high-energy nonthermal emission. It has been the subject of multiwavelength campaigns following the disappearance of the pulsed radio emission in 2013 June, which revealed the appearance of an accretion disk around the neutron star. We present the results of very high energy (VHE) gamma-ray observations carried out by the Very Energetic Radiation Imaging Telescope Array System before and after this change of state. Searches for steady and pulsed emission of both datamore » sets yield no significant gamma-ray signal above 100 GeV, and upper limits are given for both a steady and pulsed gamma-ray flux. These upper limits are used to constrain the magnetic field strength in the shock region of the PSR J1023+0038 system. Assuming that VHE gamma rays are produced via an inverse Compton mechanism in the shock region, we constrain the shock magnetic field to be greater than ∼2 G before the disappearance of the radio pulsar and greater than ∼10 G afterward.« less

Longitudinal data analysis with non-ignorable missing data.

PubMed

Tseng, Chi-hong; Elashoff, Robert; Li, Ning; Li, Gang

2016-02-01

A common problem in the longitudinal data analysis is the missing data problem. Two types of missing patterns are generally considered in statistical literature: monotone and non-monotone missing data. Nonmonotone missing data occur when study participants intermittently miss scheduled visits, while monotone missing data can be from discontinued participation, loss to follow-up, and mortality. Although many novel statistical approaches have been developed to handle missing data in recent years, few methods are available to provide inferences to handle both types of missing data simultaneously. In this article, a latent random effects model is proposed to analyze longitudinal outcomes with both monotone and non-monotone missingness in the context of missing not at random. Another significant contribution of this article is to propose a new computational algorithm for latent random effects models. To reduce the computational burden of high-dimensional integration problem in latent random effects models, we develop a new computational algorithm that uses a new adaptive quadrature approach in conjunction with the Taylor series approximation for the likelihood function to simplify the E-step computation in the expectation-maximization algorithm. Simulation study is performed and the data from the scleroderma lung study are used to demonstrate the effectiveness of this method. © The Author(s) 2012.

Growth Modeling with Nonignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial

ERIC Educational Resources Information Center

Muthen, Bengt; Asparouhov, Tihomir; Hunter, Aimee M.; Leuchter, Andrew F.

2011-01-01

This article uses a general latent variable framework to study a series of models for nonignorable missingness due to dropout. Nonignorable missing data modeling acknowledges that missingness may depend not only on covariates and observed outcomes at previous time points as with the standard missing at random assumption, but also on latent…

Corrupting Learning: Evidence from Missing Federal Education Funds in Brazil. NBER Working Paper No. 18150

ERIC Educational Resources Information Center

Ferraz, Claudio; Finan, Frederico; Moreira, Diana B.

2012-01-01

This paper examines if money matters in education by looking at whether missing resources due to corruption affect student outcomes. We use data from the auditing of Brazil's local governments to construct objective measures of corruption involving educational block grants transferred from the central government to municipalities. Using variation…

Ejecta evolutions and fates from the AIDA impact on the secondary of the binary asteroid Didymos: a NEOShield-2 project contribution

NASA Astrophysics Data System (ADS)

Michel, P.; Yu, Y.

2017-09-01

We simulated the evolutions and fates of ejecta produced by the impact of a projectile of the secondary of the binary asteroid Didymos, in the framework of the AIDA space mission project. Our results show how these evolutions and fates depend on the impact location on the secondary and ejection speeds of the ejecta. This information can be used to defined safe positions for an observing spacecraft and to better understand the outcome of an impact in the environment of a binary asteroid.

Molecular dynamics simulation of a needle-sphere binary mixture

NASA Astrophysics Data System (ADS)

Raghavan, Karthik

This paper investigates the dynamic behaviour of a hard needle-sphere binary system using a novel numerical technique called the Newton homotopy continuation (NHC) method. This mixture is representative of a polymer melt where both long chain molecules and monomers coexist. Since the intermolecular forces are generated from hard body interactions, the consequence of missed collisions or incorrect collision sequences have a significant bearing on the dynamic properties of the fluid. To overcome this problem, in earlier work NHC was chosen over traditional Newton-Raphson methods to solve the hard body dynamics of a needle fluid in random media composed of overlapping spheres. Furthermore, the simplicity of interactions and dynamics allows us to focus our research directly on the effects of particle shape and density on the transport behaviour of the mixture. These studies are also compared with earlier works that examined molecular chains in porous media primarily to understand the differences in molecular transport in the bulk versus porous systems.

Frequent statistics of link-layer bit stream data based on AC-IM algorithm

NASA Astrophysics Data System (ADS)

Cao, Chenghong; Lei, Yingke; Xu, Yiming

2017-08-01

At present, there are many relevant researches on data processing using classical pattern matching and its improved algorithm, but few researches on statistical data of link-layer bit stream. This paper adopts a frequent statistical method of link-layer bit stream data based on AC-IM algorithm for classical multi-pattern matching algorithms such as AC algorithm has high computational complexity, low efficiency and it cannot be applied to binary bit stream data. The method's maximum jump distance of the mode tree is length of the shortest mode string plus 3 in case of no missing? In this paper, theoretical analysis is made on the principle of algorithm construction firstly, and then the experimental results show that the algorithm can adapt to the binary bit stream data environment and extract the frequent sequence more accurately, the effect is obvious. Meanwhile, comparing with the classical AC algorithm and other improved algorithms, AC-IM algorithm has a greater maximum jump distance and less time-consuming.

Binary-space-partitioned images for resolving image-based visibility.

PubMed

Fu, Chi-Wing; Wong, Tien-Tsin; Tong, Wai-Shun; Tang, Chi-Keung; Hanson, Andrew J

2004-01-01

We propose a novel 2D representation for 3D visibility sorting, the Binary-Space-Partitioned Image (BSPI), to accelerate real-time image-based rendering. BSPI is an efficient 2D realization of a 3D BSP tree, which is commonly used in computer graphics for time-critical visibility sorting. Since the overall structure of a BSP tree is encoded in a BSPI, traversing a BSPI is comparable to traversing the corresponding BSP tree. BSPI performs visibility sorting efficiently and accurately in the 2D image space by warping the reference image triangle-by-triangle instead of pixel-by-pixel. Multiple BSPIs can be combined to solve "disocclusion," when an occluded portion of the scene becomes visible at a novel viewpoint. Our method is highly automatic, including a tensor voting preprocessing step that generates candidate image partition lines for BSPIs, filters the noisy input data by rejecting outliers, and interpolates missing information. Our system has been applied to a variety of real data, including stereo, motion, and range images.

Lineage-specific effects of Notch/Numb signaling in post-embryonic development of the Drosophila brain.

PubMed

Lin, Suewei; Lai, Sen-Lin; Yu, Huang-Hsiang; Chihara, Takahiro; Luo, Liqun; Lee, Tzumin

2010-01-01

Numb can antagonize Notch signaling to diversify the fates of sister cells. We report here that paired sister cells acquire different fates in all three Drosophila neuronal lineages that make diverse types of antennal lobe projection neurons (PNs). Only one in each pair of postmitotic neurons survives into the adult stage in both anterodorsal (ad) and ventral (v) PN lineages. Notably, Notch signaling specifies the PN fate in the vPN lineage but promotes programmed cell death in the missing siblings in the adPN lineage. In addition, Notch/Numb-mediated binary sibling fates underlie the production of PNs and local interneurons from common precursors in the lAL lineage. Furthermore, Numb is needed in the lateral but not adPN or vPN lineages to prevent the appearance of ectopic neuroblasts and to ensure proper self-renewal of neural progenitors. These lineage-specific outputs of Notch/Numb signaling show that a universal mechanism of binary fate decision can be utilized to govern diverse neural sibling differentiations.

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Medical, personal, and occupational outcomes for work-related amputations in Minnesota.

PubMed

Boyle, D; Larson, C; Parker, D; Pessoa-Brandão, L

2000-05-01

The Minnesota Sentinel Event Notification System for Occupational Risks (SENSOR) surveillance system has collected data on the medical, personal, and occupational outcomes associated with work-related amputations since 1992. SENSOR defined amputations as any finger amputation or the loss of any other body part; 832 workers were identified as having amputation injuries between 1994 and 1995 and 72% of these workers completed a telephone interview. Twenty percent of those injured required overnight hospitalization. Ninety-one percent of the cases reported having missed work, with 56% reporting missing ten or more days. Individuals working on their usual jobs at the time of injury were more likely to report less serious medical and occupational outcomes. Severe injuries were significantly associated with worse medical, personal, and occupational outcomes. Two groups of machines, material handling, and powered handtools were associated with a higher proportion of severe injuries. Copyright 2000 Wiley-Liss, Inc.

Is the placebo powerless? An analysis of clinical trials comparing placebo with no treatment.

PubMed

Hróbjartsson, A; Gøtzsche, P C

2001-05-24

Placebo treatments have been reported to help patients with many diseases, but the quality of the evidence supporting this finding has not been rigorously evaluated. We conducted a systematic review of clinical trials in which patients were randomly assigned to either placebo or no treatment. A placebo could be pharmacologic (e.g., a tablet), physical (e.g., a manipulation), or psychological (e.g., a conversation). We identified 130 trials that met our inclusion criteria. After the exclusion of 16 trials without relevant data on outcomes, there were 32 with binary outcomes (involving 3795 patients, with a median of 51 patients per trial) and 82 with continuous outcomes (involving 4730 patients, with a median of 27 patients per trial). As compared with no treatment, placebo had no significant effect on binary outcomes (pooled relative risk of an unwanted outcome with placebo, 0.95; 95 percent confidence interval, 0.88 to 1.02), regardless of whether these outcomes were subjective or objective. For the trials with continuous outcomes, placebo had a beneficial effect (pooled standardized mean difference in the value for an unwanted outcome between the placebo and untreated groups, -0.28; 95 percent confidence interval, -0.38 to -0.19), but the effect decreased with increasing sample size, indicating a possible bias related to the effects of small trials. The pooled standardized mean difference was significant for the trials with subjective outcomes (-0.36; 95 percent confidence interval, -0.47 to -0.25) but not for those with objective outcomes. In 27 trials involving the treatment of pain, placebo had a beneficial effect (-0.27; 95 percent confidence interval, -0.40 to -0.15). This corresponded to a reduction in the intensity of pain of 6.5 mm on a 100-mm visual-analogue scale. We found little evidence in general that placebos had powerful clinical effects. Although placebos had no significant effects on objective or binary outcomes, they had possible small benefits in studies with continuous subjective outcomes and for the treatment of pain. Outside the setting of clinical trials, there is no justification for the use of placebos.

The quality of hospital work environments and missed nursing care is linked to heart failure readmissions: a cross-sectional study of US hospitals

PubMed Central

Carthon, J Margo Brooks; Lasater, Karen B; Sloane, Douglas M; Kutney-Lee, Ann

2015-01-01

Introduction Threats to quality and patient safety may exist when necessary nursing care is omitted. Empirical research is needed to determine how missed nursing care is associated with patient outcomes. Aim The aim of this study was to examine the relationship between missed nursing care and hospital readmissions. Methods Cross-sectional examination, using three linked data sources—(1) nurse survey, (2) patient discharge data from three states (California, New Jersey and Pennsylvania) and (3) administrative hospital data— from 2005 to 2006. We explored the incidence of 30-day readmission for 160 930 patients with heart failure in 419 acute care hospitals in the USA. Logistic regression was used to assess the effect of missed care on the odds of readmission, adjusting for patient and hospital characteristics. Results The most frequently missed nursing care activities across all hospitals in our sample included talking to and comforting patients (42.0%), developing and updating care plans (35.8%) and educating patients and families (31.5%). For 4 of the 10 studied care activities, each 10 percentage-point increase in the number of nurses reporting having missed the activity was associated with an increase in the odds of readmission by 2–8% after adjusting for patient and hospital characteristics. However, missed nursing care was no longer a significant predictor of readmission once adjusting for the nurse work environment, except in the case of the delivery of treatments and procedures (OR 1.08, 95% CI 1.02 to 1.14). Conclusions Missed care is an independent predictor of heart failure readmissions. However, once adjusting for the quality of the nurse work environment, this relationship is attenuated. Improvements in nurses’ working conditions may be one strategy to reduce care omissions and improve patient outcomes. PMID:25672342

Nearest neighbor imputation using spatial–temporal correlations in wireless sensor networks

PubMed Central

Li, YuanYuan; Parker, Lynne E.

2016-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network’s performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a kd-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for kd-tree construction, and Euclidean distance for kd-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental results show that our proposed 𝒦-NN imputation method has a competitive accuracy with state-of-the-art Expectation–Maximization (EM) techniques, while using much simpler computational techniques, thus making it suitable for use in resource-constrained WSNs. PMID:28435414

Logic regression and its extensions.

PubMed

Schwender, Holger; Ruczinski, Ingo

2010-01-01

Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

Missing Data in Clinical Studies: Issues and Methods

PubMed Central

Ibrahim, Joseph G.; Chu, Haitao; Chen, Ming-Hui

2012-01-01

Missing data are a prevailing problem in any type of data analyses. A participant variable is considered missing if the value of the variable (outcome or covariate) for the participant is not observed. In this article, various issues in analyzing studies with missing data are discussed. Particularly, we focus on missing response and/or covariate data for studies with discrete, continuous, or time-to-event end points in which generalized linear models, models for longitudinal data such as generalized linear mixed effects models, or Cox regression models are used. We discuss various classifications of missing data that may arise in a study and demonstrate in several situations that the commonly used method of throwing out all participants with any missing data may lead to incorrect results and conclusions. The methods described are applied to data from an Eastern Cooperative Oncology Group phase II clinical trial of liver cancer and a phase III clinical trial of advanced non–small-cell lung cancer. Although the main area of application discussed here is cancer, the issues and methods we discuss apply to any type of study. PMID:22649133

Impact of high lipoprotein(a) levels on in-stent restenosis and long-term clinical outcomes of angina pectoris patients undergoing percutaneous coronary intervention with drug-eluting stents in Asian population.

PubMed

Park, Sang-Ho; Rha, Seung-Woon; Choi, Byoung-Geol; Park, Ji-Young; Jeon, Ung; Seo, Hong-Seog; Kim, Eung-Ju; Na, Jin-Oh; Choi, Cheol-Ung; Kim, Jin-Won; Lim, Hong-Euy; Park, Chang-Gyu; Oh, Dong-Joo

2015-06-01

Lipoprotein(a) (Lp(a)) is known to be associated with cardiovascular complications and atherothrombotic properties in general populations. However, it has not been examined whether Lp(a) levels are able to predict adverse cardiovascular outcomes in patients undergoing percutaneous coronary intervention (PCI) with drug-eluting stents (DES). A total of 595 consecutive patients with angina pectoris who underwent elective PCI with DES were enrolled from 2004 to 2010. The patients were divided into two groups according to the levels of Lp(a): Lp(a) < 50 mg/dL (n = 485 patients), and Lp(a) ≥ 50 mg/dL (n = 111 patients). The 6-9-month angiographic outcomes and 3-year cumulative major clinical outcomes were compared between the two groups. Binary restenosis occurred in 26 of 133 lesions (19.8%) in the high Lp(a) group and 43 of 550 lesions (7.9%) in the low Lp(a) group (P = 0.001). In multivariate analysis, the reference vessel diameter, low density lipoprotein cholesterol, total lesion length, and Lp(a) ≥ 50 mg/dL were predictors of binary restenosis. In the Cox proportional hazards regression analysis, Lp(a) > 50 mg/dL was significantly associated with the 3-year adverse clinical outcomes including any myocardial infarction, revascularization (target lesion revascularization (TLR) and target vessel revascularization (TVR)), TLR-major adverse cardiac events (MACEs), TVR-MACE, and All-MACEs. In our study, high Lp(a) level ≥ 50 mg/dL in angina pectoris patients undergoing elective PCI with DES was significantly associated with binary restenosis and 3-year adverse clinical outcomes in an Asian population. © 2015 Wiley Publishing Asia Pty Ltd.

Inferential Precision in Single-Case Time-Series Data Streams: How Well Does the EM Procedure Perform When Missing Observations Occur in Autocorrelated Data?

PubMed Central

Smith, Justin D.; Borckardt, Jeffrey J.; Nash, Michael R.

2013-01-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977).This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. PMID:22697454

Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model.

PubMed

Ahn, Jaeil; Morita, Satoshi; Wang, Wenyi; Yuan, Ying

2017-01-01

Analyzing longitudinal dyadic data is a challenging task due to the complicated correlations from repeated measurements and within-dyad interdependence, as well as potentially informative (or non-ignorable) missing data. We propose a dyadic shared-parameter model to analyze longitudinal dyadic data with ordinal outcomes and informative intermittent missing data and dropouts. We model the longitudinal measurement process using a proportional odds model, which accommodates the within-dyad interdependence using the concept of the actor-partner interdependence effects, as well as dyad-specific random effects. We model informative dropouts and intermittent missing data using a transition model, which shares the same set of random effects as the longitudinal measurement model. We evaluate the performance of the proposed method through extensive simulation studies. As our approach relies on some untestable assumptions on the missing data mechanism, we perform sensitivity analyses to evaluate how the analysis results change when the missing data mechanism is misspecified. We demonstrate our method using a longitudinal dyadic study of metastatic breast cancer.

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

PubMed

Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects

ERIC Educational Resources Information Center

Karl, Andrew T.; Yang, Yan; Lohr, Sharon L.

2013-01-01

Value-added models have been widely used to assess the contributions of individual teachers and schools to students' academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers' value-added scores.…

Genders and Individual Treatment Progress in (Non-)Binary Trans Individuals.

PubMed

Koehler, Andreas; Eyssel, Jana; Nieder, Timo O

2018-01-01

Health care for transgender and transsexual (ie, trans) individuals has long been based on a binary understanding of gender (ie, feminine vs masculine). However, the existence of non-binary or genderqueer (NBGQ) genders is increasingly recognized by academic and/or health care professionals. To gain insight into the individual health care experiences and needs of binary and NBGQ individuals to improve their health care outcomes and experience. Data were collected using an online survey study on experiences with trans health care. The non-clinical sample consisted of 415 trans individuals. An individual treatment progress score was calculated to report and compare participants' individual progress toward treatment completion and consider the individual treatment needs and definitions of completed treatment (ie, amount and types of different treatments needed to complete one's medical transition). Main outcome measures were (i) general and trans-related sociodemographic data and (ii) received and planned treatments. Participants reported binary (81.7%) and different NBGQ (18.3%) genders. The 2 groups differed significantly in basic demographic data (eg, mean age; P < .05). NBGQ participants reported significantly fewer received treatments compared with binary participants. For planned treatments, binary participants reported more treatments related to primary sex characteristics only. Binary participants required more treatments for a completed treatment than NBGQ participants (6.0 vs 4.0). There were no differences with regard to individual treatment progress score. Because traditional binary-focused treatment practice could have hindered NBGQ individuals from accessing trans health care or sufficiently articulating their needs, health care professionals are encouraged to provide a holistic and individual treatment approach and acknowledge genders outside the gender binary to address their needs appropriately. Because the study was made inclusive for non-patients and individuals who decided against trans health care, bias from a participant-patient double role was prevented, which is the reason the results are likely to have a higher level of validity than a clinical sample. However, because of the anonymity of an online survey, it remains unclear whether NBGQ individuals live according to their gender identity in their everyday life. The study highlights the broad spectrum of genders in trans-individuals and associated health care needs and provides a novel approach to measure individual treatment progress in trans individuals. Koehler A, Eyssel J, Nieder TO. Genders and Individual Treatment Progress in (Non-)Binary Trans Individuals. J Sex Med 2018;15:102-113. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

The Contribution of Missed Clinic Visits to Disparities in HIV Viral Load Outcomes

PubMed Central

Westfall, Andrew O.; Gardner, Lytt I.; Giordano, Thomas P.; Wilson, Tracey E.; Drainoni, Mari-Lynn; Keruly, Jeanne C.; Rodriguez, Allan E.; Malitz, Faye; Batey, D. Scott; Mugavero, Michael J.

2015-01-01

Objectives. We explored the contribution of missed primary HIV care visits (“no-show”) to observed disparities in virological failure (VF) among Black persons and persons with injection drug use (IDU) history. Methods. We used patient-level data from 6 academic clinics, before the Centers for Disease Control and Prevention and Health Resources and Services Administration Retention in Care intervention. We employed staged multivariable logistic regression and multivariable models stratified by no-show visit frequency to evaluate the association of sociodemographic factors with VF. We used multiple imputations to assign missing viral load values. Results. Among 10 053 patients (mean age = 46 years; 35% female; 64% Black; 15% with IDU history), 31% experienced VF. Although Black patients and patients with IDU history were significantly more likely to experience VF in initial analyses, race and IDU parameter estimates were attenuated after sequential addition of no-show frequency. In stratified models, race and IDU were not statistically significantly associated with VF at any no-show level. Conclusions. Because missed clinic visits contributed to observed differences in viral load outcomes among Black and IDU patients, achieving an improved understanding of differential visit attendance is imperative to reducing disparities in HIV. PMID:26270301

The effect of challenge and hindrance stressors on safety behavior and safety outcomes: a meta-analysis.

PubMed

Clarke, Sharon

2012-10-01

The significance of occupational stressors as a risk factor in accidents has long been recognized; however, the behavioral mechanisms underlying this relationship are currently not well-understood. Meta-analysis was utilized to test the relationships between occupational stressors (challenge and hindrance), safety behaviors (compliance and participation), and safety outcomes (occupational injuries and near-misses). It was hypothesized that hindrance stressors would have negative effects on both safety compliance and safety participation, and subsequently, safety outcomes, whereas challenge stressors would have positive effects. The hypotheses relating to hindrance stressors were supported, suggesting that hindrance stressors lead to a significant reduction in both compliance with safety rules and participation in safety-related activities. Hindrance stressors were also associated with higher levels of occupational injuries and near-misses. The relationship between hindrance stressors and occupational injuries was fully mediated by safety behaviors. However, the hypotheses related to challenge stressors were not supported. Challenge stressors had a nonsignificant, near-zero association with compliance and occupational injuries, a small negative association with participation, and a small positive association with near-misses. The theoretical and practical implications of the meta-analytic findings are discussed, as well as avenues for further research.

Sample size considerations for paired experimental design with incomplete observations of continuous outcomes.

PubMed

Zhu, Hong; Xu, Xiaohan; Ahn, Chul

2017-01-01

Paired experimental design is widely used in clinical and health behavioral studies, where each study unit contributes a pair of observations. Investigators often encounter incomplete observations of paired outcomes in the data collected. Some study units contribute complete pairs of observations, while the others contribute either pre- or post-intervention observations. Statistical inference for paired experimental design with incomplete observations of continuous outcomes has been extensively studied in literature. However, sample size method for such study design is sparsely available. We derive a closed-form sample size formula based on the generalized estimating equation approach by treating the incomplete observations as missing data in a linear model. The proposed method properly accounts for the impact of mixed structure of observed data: a combination of paired and unpaired outcomes. The sample size formula is flexible to accommodate different missing patterns, magnitude of missingness, and correlation parameter values. We demonstrate that under complete observations, the proposed generalized estimating equation sample size estimate is the same as that based on the paired t-test. In the presence of missing data, the proposed method would lead to a more accurate sample size estimate comparing with the crude adjustment. Simulation studies are conducted to evaluate the finite-sample performance of the generalized estimating equation sample size formula. A real application example is presented for illustration.

HSE management standards and stress-related work outcomes.

PubMed

Kerr, Robert; McHugh, Marie; McCrory, Mark

2009-12-01

The UK Health and Safety Executive's (HSE) Management Standards (MS) approach has been developed to help organizations manage potential sources of work-related stress. Although there is general support for the assessment model adopted by this approach, to date, there has been no empirical investigation of the relationship between the actual MS (as measured by the final revised version of the HSE Indicator Tool) and stress-related work outcomes. To investigate the relationship between the HSE MS and the following stress-related work outcomes: 'job satisfaction', job-related anxiety and depression and errors/near misses. An anonymous cross-sectional questionnaire was distributed by either e-mail or post to all employees within a community-based Health and Social Services Trust. Respondents completed the HSE Indicator Tool, a job-related anxiety and depression scale, a job satisfaction scale and an aggregated measure of the number of errors/near misses witnessed. Associations between the HSE Indicator Tool responses and stress-related work outcomes were analysed with regression statistics. A total of 707 employees completed the questionnaire, representing a low response rate of 29%. Controlling for age, gender and contract type, the HSE MS (as measured by the HSE Indicator Tool) were positively associated with job satisfaction and negatively associated with 'job-related anxiety', 'job-related depression' and 'witnessed errors/near misses'. This study provides empirical evidence to support the use of the MS approach in tackling workplace stress.

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

Outcome regimes of binary raindrop collisions

NASA Astrophysics Data System (ADS)

Testik, Firat Y.

2009-11-01

This study delineates the physical conditions that are responsible for the occurrence of main outcome regimes (i.e., bounce, coalescence, and breakup) for binary drop collisions with a precipitation microphysics perspective. Physical considerations based on the collision kinetic energy and the surface energies of the colliding drops lead to the development of a theoretical regime diagram for the drop/raindrop collision outcomes in the We- p plane ( We — Weber number, p — raindrop diameter ratio). This theoretical regime diagram is supported by laboratory experimental observations of drop collisions using high-speed imaging. Results of this fundamental study bring in new insights into the quantitative understanding of drop dynamics, applications of which extend beyond precipitation microphysics. In particular, results of this drop collision study are expected to give impetus to the physics-based dynamic modeling of the drop size distributions that is essential for various typical modern engineering applications, including numerical modeling of evolution of raindrop size distribution in rain shaft.

Mediation Analysis: A Practitioner's Guide.

PubMed

VanderWeele, Tyler J

2016-01-01

This article provides an overview of recent developments in mediation analysis, that is, analyses used to assess the relative magnitude of different pathways and mechanisms by which an exposure may affect an outcome. Traditional approaches to mediation in the biomedical and social sciences are described. Attention is given to the confounding assumptions required for a causal interpretation of direct and indirect effect estimates. Methods from the causal inference literature to conduct mediation in the presence of exposure-mediator interactions, binary outcomes, binary mediators, and case-control study designs are presented. Sensitivity analysis techniques for unmeasured confounding and measurement error are introduced. Discussion is given to extensions to time-to-event outcomes and multiple mediators. Further flexible modeling strategies arising from the precise counterfactual definitions of direct and indirect effects are also described. The focus throughout is on methodology that is easily implementable in practice across a broad range of potential applications.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Is there a relationship between the presence of the binary toxin genes in Clostridium difficile strains and the severity of C. difficile infection (CDI)?

PubMed

Berry, C E; Davies, K A; Owens, D W; Wilcox, M H

2017-12-01

Some strains of Clostridium difficile produce a binary toxin, in addition to the main C. difficile virulence factors (toxins A and B). There have been conflicting reports regarding the role of binary toxin and its relationship to the severity of C. difficile infection (CDI). Samples, isolates and clinical data were collected as part of a prospective multicentre diagnostic study. Clostridium difficile isolates (n = 1259) were tested by polymerase chain reaction (PCR) assay to detect binary toxin genes cdtA and cdtB. The PCR binary toxin gene results were compared with clinical severity and outcome data, including 30-day all-cause mortality. The 1259 isolates corresponded to 1083 different patients (October 2010 to September 2011). The prevalence of binary toxin positive strains was significantly higher in faecal samples with detectable toxin A/B than in those without toxin but that were positive by cytotoxigenic culture (26.3% vs. 10.3%, p < 0.001). The presence of binary toxin correlated moderately with markers of CDI severity (white cell count, serum albumin concentration and serum creatinine concentration). However, the risk ratio for all-cause mortality was 1.68 for binary toxin positive patients and patients were significantly less likely to survive if they had CDI caused by a binary toxin gene positive strain, even after adjusting for age (p < 0.001). The presence of binary toxin genes does not predict the clinical severity of CDI, but it is significantly associated with the risk of all-cause mortality.

What are the living conditions and health status of those who don’t report their migration status? a population-based study in Chile

PubMed Central

2012-01-01

Background Undocumented immigrants are likely to be missing from population databases, making it impossible to identify an accurate sampling frame in migration research. No population-based data has been collected in Chile regarding the living conditions and health status of undocumented immigrants. However, the CASEN survey (Caracterizacion Socio- Economica Nacional) asked about migration status in Chile for the first time in 2006 and provides an opportunity to set the base for future analysis of available migration data. We explored the living conditions and health of self-reported immigrants and respondents who preferred not to report their migration status in this survey. Methods Cross-sectional secondary analysis of CASEN survey in Chile in 2006. Outcomes: any disability, illness/accident, hospitalization/surgery, cancer/chronic condition (all binary variables); and the number of medical/emergency attentions received (count variables). Covariates: Demographics (age, sex, marital status, urban/rural, ethnicity), socioeconomic status (education level, employment status and household income), and material standard of living (overcrowding, sanitation, housing quality). Weighted regression models were estimated for each health outcome, crude and adjusted by sets of covariates, in STATA 10.0. Results About 1% of the total sample reported being immigrants and 0.7% preferred not to report their migration status (Migration Status - Missing Values; MS-MV). The MS-MV lived in more deprived conditions and reported a higher rate of health problems than immigrants. Some gender differences were observed by health status among immigrants and the MS-MV but they were not statistically significant. Regressions indicated that age, sex, SES and material factors consistently affected MS-MVs’ chance of presenting poor health and these patterns were different to those found among immigrants. Great heterogeneity in both the MS-MV and the immigrants, as indicated by wide confidence intervals, prevented the identification of other significantly associated covariates. Conclusion This is the first study to look at the living conditions and health of those that preferred not to respond their migration status in Chile. Respondents that do not report their migration status are vulnerable to poor health and may represent undocumented immigrants. Surveys that fail to identify these people are likely to misrepresent the experiences of immigrants and further quantitative and qualitative research is urgently required. PMID:23170824

Dopamine Modulates Reward Expectancy During Performance of a Slot Machine Task in Rats: Evidence for a ‘Near-miss' Effect

PubMed Central

Winstanley, Catharine A; Cocker, Paul J; Rogers, Robert D

2011-01-01

Cognitive accounts of gambling suggest that the experience of almost winning—so-called ‘near-misses'—encourage continued play and accelerate the development of pathological gambling (PG) in vulnerable individuals. One explanation for this effect is that near-misses signal imminent winning outcomes and heighten reward expectancy, galvanizing further play. Determining the neurochemical processes underlying the drive to gamble could facilitate the development of more effective treatments for PG. With this aim in mind, we evaluated rats' performance on a novel model of slot machine play, a form of gambling in which near-miss events are particularly salient. Subjects responded to a series of three flashing lights, loosely analogous to the wheels of a slot machine, causing the lights to set to ‘on' or ‘off'. A winning outcome was signaled if all three lights were illuminated. At the end of each trial, rats chose between responding on the ‘collect' lever, resulting in reward on win trials, but a time penalty on loss trials, or starting a new trial. Rats showed a marked preference for the collect lever when both two and three lights were illuminated, indicating heightened reward expectancy following near-misses similar to wins. Erroneous collect responses were increased by amphetamine and the D2 receptor agonist quinpirole, but not by the D1 receptor agonist SKF 81297 or receptor subtype selective antagonists. These data suggest that dopamine modulates reward expectancy following the experience of almost winning during slot machine play, via activity at D2 receptors, and this may result in an enhancement of the near-miss effect and facilitate further gambling. PMID:21209612

Dopamine modulates reward expectancy during performance of a slot machine task in rats: evidence for a 'near-miss' effect.

PubMed

Winstanley, Catharine A; Cocker, Paul J; Rogers, Robert D

2011-04-01

Cognitive accounts of gambling suggest that the experience of almost winning-so-called 'near-misses'-encourage continued play and accelerate the development of pathological gambling (PG) in vulnerable individuals. One explanation for this effect is that near-misses signal imminent winning outcomes and heighten reward expectancy, galvanizing further play. Determining the neurochemical processes underlying the drive to gamble could facilitate the development of more effective treatments for PG. With this aim in mind, we evaluated rats' performance on a novel model of slot machine play, a form of gambling in which near-miss events are particularly salient. Subjects responded to a series of three flashing lights, loosely analogous to the wheels of a slot machine, causing the lights to set to 'on' or 'off'. A winning outcome was signaled if all three lights were illuminated. At the end of each trial, rats chose between responding on the 'collect' lever, resulting in reward on win trials, but a time penalty on loss trials, or starting a new trial. Rats showed a marked preference for the collect lever when both two and three lights were illuminated, indicating heightened reward expectancy following near-misses similar to wins. Erroneous collect responses were increased by amphetamine and the D(2) receptor agonist quinpirole, but not by the D(1) receptor agonist SKF 81297 or receptor subtype selective antagonists. These data suggest that dopamine modulates reward expectancy following the experience of almost winning during slot machine play, via activity at D(2) receptors, and this may result in an enhancement of the near-miss effect and facilitate further gambling.

Graduation Odds and Probabilities among Baccalaureate Colleges and Universities

ERIC Educational Resources Information Center

Morrison, Michael C.

2013-01-01

Graduation outcomes are analyzed at public and private baccalaureate colleges and universities in the United States. The purpose is to determine the effect of institutional characteristics on a binary indicator of college graduation. The effect of the percentage of Pell grant recipients on graduation outcomes is of primary interest, controlling…

Distortion of Probability and Outcome Information in Risky Decisions

ERIC Educational Resources Information Center

DeKay, Michael L.; Patino-Echeverri, Dalia; Fischbeck, Paul S.

2009-01-01

Substantial evidence indicates that information is distorted during decision making, but very few studies have assessed the distortion of probability and outcome information in risky decisions. In two studies involving six binary decisions (e.g., banning blood donations from people who have visited England, because of "mad cow disease"),…

Binary toxin and its clinical importance in Clostridium difficile infection, Belgium.

PubMed

Pilate, T; Verhaegen, J; Van Ranst, M; Saegeman, V

2016-11-01

Binary toxin-producing Clostridium difficile strains such as ribotypes 027 and 078 have been associated with increased Clostridium difficile infection (CDI) severity. Our objective was to investigate the association between presence of the binary toxin gene and CDI severity and recurrence. We performed a laboratory-based retrospective study including patients between January 2013 and March 2015 whose fecal samples were analyzed by polymerase chain reaction (PCR) for the presence of the genes for toxin B and binary toxin and a deletion in the tcdC gene, specific for ribotype 027. Clinical and epidemiological characteristics were compared between 33 binary toxin-positive CDI patients and 33 binary toxin-negative CDI patients. Subsequently, the characteristics of 66 CDI patients were compared to those of 66 diarrhea patients who were carriers of non-toxigenic C. difficile strains. Fifty-nine of 1034 (5.7 %) fecal samples analyzed by PCR were binary toxin-positive, belonging to 33 different patients. No samples were positive for ribotype 027. Binary toxin-positive CDI patients did not differ from binary toxin-negative CDI patients in terms of disease recurrence, morbidity, or mortality, except for a higher peripheral leukocytosis in the binary toxin-positive group (16.30 × 10 9 /L vs. 11.65 × 10 9 /L; p = 0.02). The second part of our study showed that CDI patients had more severe disease, but not a higher 30-day mortality rate than diarrhea patients with a non-toxicogenic C. difficile strain. In our setting with a low prevalence of ribotype 027, the presence of the binary toxin gene is not associated with poor outcome.

Exploring the Influence of Nursing Work Environment and Patient Safety Culture on Missed Nursing Care in Korea.

PubMed

Kim, Kyoung-Ja; Yoo, Moon Sook; Seo, Eun Ji

2018-04-20

This study aimed to explore the influence of nurse work environment and patient safety culture in hospital on instances of missed nursing care in South Korea. A cross-sectional design was used, in which a structured questionnaire was administered to 186 nurses working at a tertiary university hospital. Data were analyzed using descriptive statistics, t-test or ANOVA, Pearson correlation and multiple regression analysis. Missed nursing care was found to be correlated with clinical career, nursing work environment and patient safety culture. The regression model explained approximately 30.3 % of missed nursing care. Meanwhile, staffing and resource adequacy (β = -.31, p = .001), nurse manager ability, leadership and support of nurses (β = -.26, p = .004), clinical career (β = -.21, p = .004), and perception on patient safety culture within unit (β = -.19, p = .041) were determined to be influencing factors on missed nursing care. This study has significance as it suggested that missed nursing care is affected by work environment factors within unit. This means that missed nursing care is a unit outcome affected by nurse work environment factors and patient safety culture. Therefore, missed nursing care can be managed through the implementation of interventions that promote a positive nursing work environment and patient safety culture. Copyright © 2018. Published by Elsevier B.V.

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks

PubMed Central

Cunningham, Corbin A.; Drew, Trafton; Wolfe, Jeremy M.

2017-01-01

In socially important visual search tasks such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer Aided Detection (CAD) programs have been developed specifically to help improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be “Binary”, giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system present an Analog signal that reflected strength of the signal at a location. In the experiments reported here, we compare analog and binary CAD presentations using non-expert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher. PMID:27928658

Binary Paths to Type Ia Supernovae Explosions: the Highlights

NASA Astrophysics Data System (ADS)

Ferrario, Lilia

2013-01-01

This symposium was focused on the hunt for the progenitors of Type Ia supernovae (SNe Ia). Is there a main channel for the production of SNe Ia? If so, are these elusive progenitors single degenerate or double degenerate systems? Although most participants seemed to favor the single degenerate channel, there was no general agreement on the type of binary system at play. An observational puzzle that was highlighted was the apparent paucity of supersoft sources in our Galaxy and also in external galaxies. The single degenerate channel (and as it was pointed out, quite possibly also the double degenerate channel) requires the binary system to pass through a phase of steady nuclear burning. However, the observed number of supersoft sources falls short by a factor of up to 100 in explaining the estimated birth rates of SNe Ia. Thus, are these supersoft sources somehow hidden away and radiating at different wavelengths, or are we missing some important pieces of this puzzle that may lead to the elimination of a certain class of progenitor? Another unanswered question concerns the dependence of SNe Ia luminosities on the age of their host galaxy. Several hypotheses were put forward, but none was singled out as the most likely explanation. It is fair to say that at the end of the symposium the definitive answer to the vexed progenitor question remained well and truly wide open.

Singular Isothermal Disks. Paper 2; Nonaxiymmetric Bifurcations and Equilibria

NASA Technical Reports Server (NTRS)

Galli, Danielle; Shu, Frank H.; Laughlin, Gregory; Lizano, Susana

2000-01-01

We review the difficulties of the classical fission and fragmentation hypotheses for the formation of binary and multiple stars. A crucial missing ingredient in previous theoretical studies is the inclusion of dynamically important levels of magnetic fields. As a minimal model for a candidate presursor to the formation of binary and multiple stars, we therefore formulate and solve the problem of the equilibria of isopedically magnetized, singular isothermal disks, without the assumption of axial symmetry. Considerable analytical progress can be made if we restrict our attention to models that are scale-free, i.e., that have surface densities that vary inversely with distance omega from the rotation axis of the system. In agreement with earlier analysis by Syer and Tremaine, we find that lopsided (M = 1) configurations exist at any dimensionless rotation rate, including zero. Multiple-lobed (M = 2, 3, 4, ...) configurations bifurcate from an underlying axisymmetric sequence at progressively higher dimensionless rates of rotation, but such nonaxisymmetric sequences always terminate in shockwaves before they have a chance to fission into M = 2, 3, 4, ... separate bodies. On the basis of our experience in this paper, we advance the hypothesis that binary and multiple star-formation from smooth (i.e., not highly turbulent) starting states that are supercritical but in unstable mechanical balance requires the rapid (i.e., dynamical) loss of magnetic flux at some stage of the ensuing gravitational collapse.

Factors associated with rushed and missed resident care in western Canadian nursing homes: a cross-sectional survey of health care aides.

PubMed

Knopp-Sihota, Jennifer A; Niehaus, Linda; Squires, Janet E; Norton, Peter G; Estabrooks, Carole A

2015-10-01

To describe the nature, frequency and factors associated with care that was rushed or missed by health care aides in western Canadian nursing homes. The growing number of nursing home residents with dementia has created job strain for frontline health care providers, the majority of whom are health care aides. Due to the associated complexity of care, health care aides are challenged to complete more care tasks in less time. Rushed or missed resident care are associated with adverse resident outcomes (e.g. falls) and poorer quality of staff work life (e.g. burnout) making this an important quality of care concern. Cross-sectional survey of health care aides (n = 583) working in a representative sample of nursing homes (30 urban, six rural) in western Canada. Data were collected in 2010 as part of the Translating Research in Elder Care study. We collected data on individual health care aides (demographic characteristics, job and vocational satisfaction, physical and mental health, burnout), unit level characteristics associated with organisational context, facility characteristics (location, size, owner/operator model), and the outcome variables of rushed and missed resident care. Most health care aides (86%) reported being rushed. Due to lack of time, 75% left at least one care task missed during their previous shift. Tasks most frequently missed were talking with residents (52% of health care aides) and assisting with mobility (51%). Health care aides working on units with higher organisational context scores were less likely to report rushed and missed care. Health care aides frequently report care that is rushed and tasks omitted due to lack of time. Considering the resident population in nursing homes today--many with advanced dementia and all with complex care needs--health care aides having enough time to provide physical and psychosocial care of high quality is a critical concern. © 2015 John Wiley & Sons Ltd.

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.

PubMed

Wendling, T; Jung, K; Callahan, A; Schuler, A; Shah, N H; Gallego, B

2018-06-03

There is growing interest in using routinely collected data from health care databases to study the safety and effectiveness of therapies in "real-world" conditions, as it can provide complementary evidence to that of randomized controlled trials. Causal inference from health care databases is challenging because the data are typically noisy, high dimensional, and most importantly, observational. It requires methods that can estimate heterogeneous treatment effects while controlling for confounding in high dimensions. Bayesian additive regression trees, causal forests, causal boosting, and causal multivariate adaptive regression splines are off-the-shelf methods that have shown good performance for estimation of heterogeneous treatment effects in observational studies of continuous outcomes. However, it is not clear how these methods would perform in health care database studies where outcomes are often binary and rare and data structures are complex. In this study, we evaluate these methods in simulation studies that recapitulate key characteristics of comparative effectiveness studies. We focus on the conditional average effect of a binary treatment on a binary outcome using the conditional risk difference as an estimand. To emulate health care database studies, we propose a simulation design where real covariate and treatment assignment data are used and only outcomes are simulated based on nonparametric models of the real outcomes. We apply this design to 4 published observational studies that used records from 2 major health care databases in the United States. Our results suggest that Bayesian additive regression trees and causal boosting consistently provide low bias in conditional risk difference estimates in the context of health care database studies. Copyright © 2018 John Wiley & Sons, Ltd.

Patterns of missing data in the use of the endometriosis symptom diary.

PubMed

Seitz, Christian; Lanius, Vivian; Lippert, Susanne; Gerlinger, Christoph; Haberland, Claudia; Oehmke, Frank; Tinneberg, Hans-Rudolf

2018-06-08

Endometriosis is a common, chronic condition in women of reproductive age that is characterized by the presence of functional endometriotic lesions outside the uterus. The Endometriosis Symptom Diary (ESD) is an electronic patient-reported outcome (ePRO) instrument that assesses women's experience of endometriosis symptoms, with pain scored using a 0-10 numeric rating scale. This study investigated patterns of data missing from the ESD in the VALEPRO study. Post hoc analyses of missing data were conducted. Of 272 participants using the ESD, 26.5% had no missing diary entries, 46.7% had > 0-5% of entries missing, 13.2% had > 5-10% of entries missing and 13.6% had > 10% of entries missing over the entire study period. The duration of missing episodes (defined as ≥1 consecutive days with missing diary entries) was generally short; most (81.4%) were 1 day. The difference in mean worst pain scores between missing and complete episodes per participant was - 0.1, suggesting that missing episodes were not related to severity of pain. Entries were significantly more likely to be missing on Fridays (18.5%) and Saturdays (22.9%) compared with other days of the week (p < 0.0001). Participants in the USA had significantly more long missing episodes than those in Germany (proportions of missing episodes longer than 1 day, 22.6 and 10.5%, respectively; p < 0.0001). The proportions of women with ≥1 missing entry were 50.0, 70.2 and 79.8% for women with elementary education, secondary education, and a college or university education, respectively. The proportions of women with ≥1 missing entry were similar for those with and without children (72.2 and 74.3%, respectively). Most participants were highly compliant with entering data in the ESD and the amount of missing data was low. Entries were significantly more likely to be missing on Fridays and Saturdays compared with other days of the week, and participants in the USA had significantly more long missing episodes than participants in Germany. Clinicaltrials.gov, NCT01643122 , registered 4 July 2012.

Inferential precision in single-case time-series data streams: how well does the em procedure perform when missing observations occur in autocorrelated data?

PubMed

Smith, Justin D; Borckardt, Jeffrey J; Nash, Michael R

2012-09-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977). This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. Copyright © 2011. Published by Elsevier Ltd.

Accounting for Resource Use at the School-Level and Below: The Missing Link in Education Administration and Policy Making. Working Paper #09-06

ERIC Educational Resources Information Center

Denison, Dwight V.; Stiefel, Leanna; Hartman, William; Deegan, Michele Moser

2009-01-01

A long standing debate among policymakers as well as researchers is whether and how funding affects the quality of education. Often missing from the discussion is information about the costs of providing education at the school level and below, yet such information could impart a better indication of the linkages between outcomes and resources…

Near Misses in Slot Machine Gambling Developed Through Generalization of Total Wins.

PubMed

Belisle, Jordan; Dixon, Mark R

2016-06-01

The purpose of the present study was to evaluate the development of the near miss effect in slot machine gambling as a product of stimulus generalization from total wins. The study was conducted across two experiments. Twelve college students participated in the first experiment, which demonstrated that greater post-reinforcement pauses followed losing outcomes that were formally similar to total wins, relative to losing outcomes that were formally dissimilar [F (5, 7) = 5.24, p = .025] along a generalization gradient (R (2) = .96). Additionally, 11 out of 12 participants showed greater response latencies following near-misses than following total wins. Thirteen college students participated in the second experiment, which demonstrated that symbols that more saliently indicated a loss resulted in lower response latencies than functionally equivalent but visually dissimilar losing symbols [F (3, 10) = 15.50, p = .01]. A generalization gradient was observed across winning symbols (R (2) = .98), and an inverse of the gradient observed across winning symbols was observed across symbols that were the least formally similar (R (2) = .69). The present study replicates and extends previous research on near misses in slot machine gambling, and provides discussion around the clinical utility of such findings on the prevention of problem gambling.

Assessing Equity beyond Knowledge- and Skills-Based Outcomes: A Comparative Ethnography of Two Fourth-Grade Reform-Based Science Classrooms

ERIC Educational Resources Information Center

Carlone, Heidi B.; Haun-Frank, Julie; Webb, Angela

2011-01-01

When evaluating equity, researchers often look at the "achievement gap." Privileging knowledge and skills as primary outcomes of science education misses other, more subtle, but critical, outcomes indexing inequitable science education. In this comparative ethnography, we examined what it meant to "be scientific" in two fourth-grade classes taught…

NONPARAMETRIC MANOVA APPROACHES FOR NON-NORMAL MULTIVARIATE OUTCOMES WITH MISSING VALUES

PubMed Central

He, Fanyin; Mazumdar, Sati; Tang, Gong; Bhatia, Triptish; Anderson, Stewart J.; Dew, Mary Amanda; Krafty, Robert; Nimgaonkar, Vishwajit; Deshpande, Smita; Hall, Martica; Reynolds, Charles F.

2017-01-01

Between-group comparisons often entail many correlated response variables. The multivariate linear model, with its assumption of multivariate normality, is the accepted standard tool for these tests. When this assumption is violated, the nonparametric multivariate Kruskal-Wallis (MKW) test is frequently used. However, this test requires complete cases with no missing values in response variables. Deletion of cases with missing values likely leads to inefficient statistical inference. Here we extend the MKW test to retain information from partially-observed cases. Results of simulated studies and analysis of real data show that the proposed method provides adequate coverage and superior power to complete-case analyses. PMID:29416225

Topology of black hole binary-single interactions

NASA Astrophysics Data System (ADS)

Samsing, Johan; Ilan, Teva

2018-05-01

We present a study on how the outcomes of binary-single interactions involving three black holes (BHs) distribute as a function of the initial conditions; a distribution we refer to as the topology. Using a N-body code that includes BH finite sizes and gravitational wave (GW) emission in the equation of motion (EOM), we perform more than a million binary-single interactions to explore the topology of both the Newtonian limit and the limit at which general relativistic (GR) effects start to become important. From these interactions, we are able to describe exactly under which conditions BH collisions and eccentric GW capture mergers form, as well as how GR in general modifies the Newtonian topology. This study is performed on both large- and microtopological scales. We further describe how the inclusion of GW emission in the EOM naturally leads to scenarios where the binary-single system undergoes two successive GW mergers.

A novel asynchronous access method with binary interfaces

PubMed Central

2008-01-01

Background Traditionally synchronous access strategies require users to comply with one or more time constraints in order to communicate intent with a binary human-machine interface (e.g., mechanical, gestural or neural switches). Asynchronous access methods are preferable, but have not been used with binary interfaces in the control of devices that require more than two commands to be successfully operated. Methods We present the mathematical development and evaluation of a novel asynchronous access method that may be used to translate sporadic activations of binary interfaces into distinct outcomes for the control of devices requiring an arbitrary number of commands to be controlled. With this method, users are required to activate their interfaces only when the device under control behaves erroneously. Then, a recursive algorithm, incorporating contextual assumptions relevant to all possible outcomes, is used to obtain an informed estimate of user intention. We evaluate this method by simulating a control task requiring a series of target commands to be tracked by a model user. Results When compared to a random selection, the proposed asynchronous access method offers a significant reduction in the number of interface activations required from the user. Conclusion This novel access method offers a variety of advantages over traditionally synchronous access strategies and may be adapted to a wide variety of contexts, with primary relevance to applications involving direct object manipulation. PMID:18959797

Parental coping, depressive symptoms, and children's asthma control and school attendance in low-income, racially, and ethnically diverse urban families.

PubMed

Rodríguez, Erin M; Kumar, Harsha; Alba-Suarez, Juliana; Sánchez-Johnsen, Lisa

2017-10-01

Low-income urban children of color are at elevated risk for poor asthma control. This cross-sectional study examined associations among parents' coping (primary control, secondary control, and disengagement), parental depressive symptoms, and children's asthma outcomes (asthma control and school attendance) in a predominantly low-income, racially/ethnically diverse sample of families. Parents (N = 78; 90% female) of children (33% female; 46% Black; 38% Latino) aged 5-17 years (M = 9.5 years) reported on their own coping and depressive symptoms, their child's asthma control, and full and partial days of school missed due to asthma. Parents' secondary control coping (i.e., coping efforts to accommodate/adapt to asthma-related stressors) was negatively correlated, and disengagement coping (i.e. coping efforts to avoid/detach from stressors) was positively correlated, with their depressive symptoms. Secondary control coping was also correlated with fewer partial days of school missed. Primary control coping (i.e., coping efforts to change stressors) was not associated with depressive symptoms or asthma outcomes. Parents' depressive symptoms were also positively correlated with poorer asthma control and partial days of school missed. Regression models showed direct and indirect effects of secondary control and disengagement coping on asthma outcomes via depressive symptoms, after controlling for demographic factors. Parents' secondary control and disengagement coping are related to children's asthma outcomes. Secondary control coping may support parents' mental health and children's asthma control in low-income urban families.

Evaluating the Use of Existing Data Sources, Probabilistic Linkage, and Multiple Imputation to Build Population-based Injury Databases Across Phases of Trauma Care

PubMed Central

Newgard, Craig; Malveau, Susan; Staudenmayer, Kristan; Wang, N. Ewen; Hsia, Renee Y.; Mann, N. Clay; Holmes, James F.; Kuppermann, Nathan; Haukoos, Jason S.; Bulger, Eileen M.; Dai, Mengtao; Cook, Lawrence J.

2012-01-01

Objectives The objective was to evaluate the process of using existing data sources, probabilistic linkage, and multiple imputation to create large population-based injury databases matched to outcomes. Methods This was a retrospective cohort study of injured children and adults transported by 94 emergency medical systems (EMS) agencies to 122 hospitals in seven regions of the western United States over a 36-month period (2006 to 2008). All injured patients evaluated by EMS personnel within specific geographic catchment areas were included, regardless of field disposition or outcome. The authors performed probabilistic linkage of EMS records to four hospital and postdischarge data sources (emergency department [ED] data, patient discharge data, trauma registries, and vital statistics files) and then handled missing values using multiple imputation. The authors compare and evaluate matched records, match rates (proportion of matches among eligible patients), and injury outcomes within and across sites. Results There were 381,719 injured patients evaluated by EMS personnel in the seven regions. Among transported patients, match rates ranged from 14.9% to 87.5% and were directly affected by the availability of hospital data sources and proportion of missing values for key linkage variables. For vital statistics records (1-year mortality), estimated match rates ranged from 88.0% to 98.7%. Use of multiple imputation (compared to complete case analysis) reduced bias for injury outcomes, although sample size, percentage missing, type of variable, and combined-site versus single-site imputation models all affected the resulting estimates and variance. Conclusions This project demonstrates the feasibility and describes the process of constructing population-based injury databases across multiple phases of care using existing data sources and commonly available analytic methods. Attention to key linkage variables and decisions for handling missing values can be used to increase match rates between data sources, minimize bias, and preserve sampling design. PMID:22506952

Inference and sample size calculation for clinical trials with incomplete observations of paired binary outcomes.

PubMed

Zhang, Song; Cao, Jing; Ahn, Chul

2017-02-20

We investigate the estimation of intervention effect and sample size determination for experiments where subjects are supposed to contribute paired binary outcomes with some incomplete observations. We propose a hybrid estimator to appropriately account for the mixed nature of observed data: paired outcomes from those who contribute complete pairs of observations and unpaired outcomes from those who contribute either pre-intervention or post-intervention outcomes. We theoretically prove that if incomplete data are evenly distributed between the pre-intervention and post-intervention periods, the proposed estimator will always be more efficient than the traditional estimator. A numerical research shows that when the distribution of incomplete data is unbalanced, the proposed estimator will be superior when there is moderate-to-strong positive within-subject correlation. We further derive a closed-form sample size formula to help researchers determine how many subjects need to be enrolled in such studies. Simulation results suggest that the calculated sample size maintains the empirical power and type I error under various design configurations. We demonstrate the proposed method using a real application example. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Modelling Chemical Reasoning to Predict and Invent Reactions.

PubMed

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lineage-specific effects of Notch/Numb signaling in post-embryonic development of the Drosophila brain

PubMed Central

Lin, Suewei; Lai, Sen-Lin; Yu, Huang-Hsiang; Chihara, Takahiro; Luo, Liqun; Lee, Tzumin

2010-01-01

Numb can antagonize Notch signaling to diversify the fates of sister cells. We report here that paired sister cells acquire different fates in all three Drosophila neuronal lineages that make diverse types of antennal lobe projection neurons (PNs). Only one in each pair of postmitotic neurons survives into the adult stage in both anterodorsal (ad) and ventral (v) PN lineages. Notably, Notch signaling specifies the PN fate in the vPN lineage but promotes programmed cell death in the missing siblings in the adPN lineage. In addition, Notch/Numb-mediated binary sibling fates underlie the production of PNs and local interneurons from common precursors in the lAL lineage. Furthermore, Numb is needed in the lateral but not adPN or vPN lineages to prevent the appearance of ectopic neuroblasts and to ensure proper self-renewal of neural progenitors. These lineage-specific outputs of Notch/Numb signaling show that a universal mechanism of binary fate decision can be utilized to govern diverse neural sibling differentiations. PMID:20023159

The experiences of women with maternal near miss and their perception of quality of care in Kelantan, Malaysia: a qualitative study.

PubMed

Norhayati, Mohd Noor; Nik Hazlina, Nik Hussain; Asrenee, Ab Razak; Sulaiman, Zaharah

2017-06-15

Maternal mortality has been the main way of ascertaining the outcome of maternal and obstetric care. However, maternal morbidities occur more frequently than maternal deaths; therefore, maternal near miss was suggested as a more useful indicator for the evaluation and improvement of maternal health services. Our study aimed to explore the experiences of women with maternal near miss and their perception of the quality of care in Kelantan, Malaysia. A qualitative phenomenological approach with in-depth interview method was conducted in two tertiary hospitals in Kelantan, Malaysia. All women admitted to labour room, obstetrics and gynaecology wards and intensive care units in 2014 were screened for the presence of any vital organ dysfunction or failure based on the World Health Organization criteria for maternal near miss. Pregnancy irrespective of the gestational age was included. Women younger than 18 years old, with psychiatric disorder and beyond 42 days of childbirth were excluded. Thirty women who had experienced maternal near miss events were included in the analysis. All were Malays between the ages of 22 and 45. Almost all women (93.3%) had secondary and tertiary education and 63.3% were employed. The women's perceptions of the quality of their care were influenced by the competency and promptness in the provision of care, interpersonal communication, information-sharing and the quality of physical resources. The predisposition to seek healthcare was influenced by costs, self-attitude and beliefs. Self-appraisal of maternal near miss, their perception of the quality of care, their predisposition to seek healthcare and the social support received were the four major themes that emerged from the experiences and perceptions of women with maternal near miss. The women with maternal near miss viewed their experiences as frightening and that they experienced other negative emotions and a sense of imminent death. The factors influencing women's perceptions of quality of care should be of concern to those seeking to improve services at healthcare facilities. The addition of a maternal near miss case review programme, allows for understanding on the factors related to providing care or to the predisposition to seek care; if addressed, may improve future healthcare and patient outcomes.

Minimally invasive scoliosis surgery assisted by O-arm navigation for Lenke Type 5C adolescent idiopathic scoliosis: a comparison with standard open approach spinal instrumentation.

PubMed

Zhu, Weiguo; Sun, Weixiang; Xu, Leilei; Sun, Xu; Liu, Zhen; Qiu, Yong; Zhu, Zezhang

2017-04-01

OBJECTIVE Recently, minimally invasive scoliosis surgery (MISS) was introduced for the correction of adult scoliosis. Multiple benefits including a good deformity correction rate and fewer complications have been demonstrated. However, few studies have reported on the use of MISS for the management of adolescent idiopathic scoliosis (AIS). The purpose of this study was to investigate the outcome of posterior MISS assisted by O-arm navigation for the correction of Lenke Type 5C AIS. METHODS The authors searched a database for all patients with AIS who had been treated with either MISS or PSF between November 2012 and January 2014. Levels of fusion, density of implants, operation time, and estimated blood loss (EBL) were recorded. Coronal and sagittal parameters were evaluated before surgery, immediately after surgery, and at the last follow-up. The accuracy of pedicle screw placement was assessed according to postoperative axial CT images in both groups. The 22-item Scoliosis Research Society questionnaire (SRS-22) results and complications were collected during follow-up. RESULTS The authors retrospectively reviewed the records of 45 patients with Lenke Type 5C AIS, 15 who underwent posterior MISS under O-arm navigation and 30 who underwent posterior spinal fusion (PSF). The 2 treatment groups were matched in terms of baseline characteristics. Comparison of radiographic parameters revealed no obvious difference between the 2 groups immediately after surgery or at the final follow-up; however, the MISS patients had significantly less EBL (p < 0.001) and longer operation times (p = 0.002). The evaluation of pain and self-image using the SRS-22 showed significantly higher scores in the MISS group (p = 0.013 and 0.046, respectively) than in the PSF group. Postoperative CT showed high accuracy in pedicle placement in both groups. No deep wound infection, pseudarthrosis, additional surgery, implant failure, or neurological complications were recorded in either group. CONCLUSIONS Minimally invasive scoliosis surgery is an effective and safe alternative to open surgery for patients with Lenke Type 5C AIS. Compared with results of the open approach, the outcomes of MISS are promising, with reduced morbidity. Before the routine use of MISS, however, long-term data are needed.

Field Evaluations of Tracking/Locating Technologies for Prevention of Missing Incidents.

PubMed

Bulat, Tatjana; Kerrigan, Michael V; Rowe, Meredeth; Kearns, William; Craighead, Jeffrey D; Ramaiah, Padmaja

2016-09-01

Persons with dementia are at risk of a missing incident, which is defined as an instance in which a demented person's whereabouts are unknown to the caregiver and the individual is not in an expected location. Since it is critical to determine the missing person's location as quickly as possible, we evaluated whether commercially available tracking technologies can assist in a rapid recovery. This study examined 7 commercially available tracking devices: 3 radio frequency (RF) based and 4 global positioning system (GPS) based, employing realistic tracking scenarios. Outcome measures were time to discovery and degree of deviation from a straight intercept course. Across all scenarios tested, GPS devices were found to be approximately twice as efficient as the RF devices in locating a "missing person." While the RF devices showed reasonable performance at close proximity, the GPS devices were found to be more appropriate overall for tracking/locating missing persons over unknown and larger distances. © The Author(s) 2016.

Predicting the Alpha Comae Berenices Time of Eclipse: How 3 Ambiguous Measurements Out of 609 Caused a 26 Year Binary’s Eclipse to be Missed

DTIC Science & Technology

2015-11-01

56862.52 0.0906 12.2 0.00127 1.41 Horch et al. (2015) 56862.52 0.0908 12.2 0.00127 1.41 Horch et al. (2015) 57038.4870368 0.04553 192.85 0.00081 1.02...from Speckle Interferometry (originally published in Horch et al. 2015, with uncertainties as assigned in that work, with the time in Modified Julian...G. 1989, AJ, 98, 1014 Hoffleit, D. 1996, JAVSO, 24, 105 Horch , E. P., van Altena, W. F., Demarque, P., et al. 2015, AJ, 149, 151 Mason, B. D., Wycoff

Untangling Binaries: Where Canada Sits in the "21st Century Debate"

ERIC Educational Resources Information Center

Gallagher, Tiffany L.; Rowsell, Jennifer

2017-01-01

This article examines the extent to which the competencies of the 21st century learner are reflected in the learning outcomes within the English language arts curriculum standards documents for the Canadian provinces. Manifest summative content analysis was used to code learning outcomes in accordance with themes derived from the competencies of…

Sufficient Dimension Reduction for Longitudinally Measured Predictors

PubMed Central

Pfeiffer, Ruth M.; Forzani, Liliana; Bura, Efstathia

2013-01-01

We propose a method to combine several predictors (markers) that are measured repeatedly over time into a composite marker score without assuming a model and only requiring a mild condition on the predictor distribution. Assuming that the first and second moments of the predictors can be decomposed into a time and a marker component via a Kronecker product structure, that accommodates the longitudinal nature of the predictors, we develop first moment sufficient dimension reduction techniques to replace the original markers with linear transformations that contain sufficient information for the regression of the predictors on the outcome. These linear combinations can then be combined into a score that has better predictive performance than the score built under a general model that ignores the longitudinal structure of the data. Our methods can be applied to either continuous or categorical outcome measures. In simulations we focus on binary outcomes and show that our method outperforms existing alternatives using the AUC, the area under the receiver-operator characteristics (ROC) curve, as a summary measure of the discriminatory ability of a single continuous diagnostic marker for binary disease outcomes. PMID:22161635

Occupation-specific absenteeism costs associated with obesity and morbid obesity.

PubMed

Cawley, John; Rizzo, John A; Haas, Kara

2007-12-01

To document the absenteeism costs associated with obesity and morbid obesity by occupation. Data from the Medical Expenditure Panel Survey for 2000-2004 are examined. The outcomes are probability of missing any work in the previous year and number of days of work missed in the previous year. Predictors include clinical weight classification, age, education, and race. Models are estimated separately by gender and occupation category. The probability of missing work in the past year, number of days missed, and costs of absenteeism rise with clinical weight classification for both women and men, and vary across occupation. Absenteeism costs associated with obesity total $4.3 billion annually in the United States. Substantial absenteeism costs are associated with obesity and morbid obesity. Employers should explore workplace interventions and health insurance expansions to reduce these costs.

A Bayesian Missing Data Framework for Generalized Multiple Outcome Mixed Treatment Comparisons

ERIC Educational Resources Information Center

Hong, Hwanhee; Chu, Haitao; Zhang, Jing; Carlin, Bradley P.

2016-01-01

Bayesian statistical approaches to mixed treatment comparisons (MTCs) are becoming more popular because of their flexibility and interpretability. Many randomized clinical trials report multiple outcomes with possible inherent correlations. Moreover, MTC data are typically sparse (although richer than standard meta-analysis, comparing only two…

Review of Exploration Systems Development (ESD) Integrated Hazard Development Process. Volume 1; Appendices

NASA Technical Reports Server (NTRS)

Smiles, Michael D.; Blythe, Michael P.; Bejmuk, Bohdan; Currie, Nancy J.; Doremus, Robert C.; Franzo, Jennifer C.; Gordon, Mark W.; Johnson, Tracy D.; Kowaleski, Mark M.; Laube, Jeffrey R.

2015-01-01

The Chief Engineer of the Exploration Systems Development (ESD) Office requested that the NASA Engineering and Safety Center (NESC) perform an independent assessment of the ESD's integrated hazard development process. The focus of the assessment was to review the integrated hazard analysis (IHA) process and identify any gaps/improvements in the process (e.g., missed causes, cause tree completeness, missed hazards). This document contains the outcome of the NESC assessment.

Review of Exploration Systems Development (ESD) Integrated Hazard Development Process. Appendices; Volume 2

NASA Technical Reports Server (NTRS)

Smiles, Michael D.; Blythe, Michael P.; Bejmuk, Bohdan; Currie, Nancy J.; Doremus, Robert C.; Franzo, Jennifer C.; Gordon, Mark W.; Johnson, Tracy D.; Kowaleski, Mark M.; Laube, Jeffrey R.

2015-01-01

The Chief Engineer of the Exploration Systems Development (ESD) Office requested that the NASA Engineering and Safety Center (NESC) perform an independent assessment of the ESD's integrated hazard development process. The focus of the assessment was to review the integrated hazard analysis (IHA) process and identify any gaps/improvements in the process (e.g. missed causes, cause tree completeness, missed hazards). This document contains the outcome of the NESC assessment.

Predictors of effective therapeutic relationships between pharmacists and patients with type 2 diabetes: Comparison between Arabic-speaking and Caucasian English-speaking patients.

PubMed

Alzubaidi, H; Mc Namara, K; Versace, V L

2017-11-23

The benefits of pharmacist-led interventions in achieving desired patient outcomes have been well established. Effective patient-pharmacist relationships are required to provide high-quality pharmacy care. Limited information is available about how Arabic-speaking migrants with diabetes, in Australia, perceive patient-pharmacist relationship and how these perspectives differ from the mainstream society (represented by Caucasian English-speaking people). To examine and compare the patient-pharmacist relationship, medication underuse and adherence levels among Arabic-speaking and Caucasian English-speaking patients with type 2 diabetes. A 98-item survey incorporating several previously-validated measurements was completed by Arabic-speaking migrants (ASMs) and Caucasian English-speaking patients (ESPs) with type 2 diabetes. Participants were recruited from various healthcare settings in the Melbourne metropolitan area and rural Victoria, Australia. This survey-based, cross-sectional study was designed to explore patients' perceptions of the patient-pharmacist relationship. A descriptive analysis of responses was undertaken, and binary logistic regression was used to explore patient-pharmacist relationships. A total of 701 participants were recruited; 392 ASMs and 309 ESPs. Of ASMs, 88.3% were non-adherent to their prescribed medication, compared with 45.1% of ESPs. The degree of relationship with community pharmacists differed significantly between ASMs and ESPs. Compared with ASMs, significantly more ESPs reported that they have thought about consulting a pharmacist when they had health problems (P = 0.002). Compared with ESPs, significantly fewer ASMs reported always following pharmacist recommendations (32% versus 61.9% respectively). Arabic-speaking migrants had less-effective relationships with community pharmacists when having their prescriptions filled. Community pharmacists' expertise appeared to be underused. These minimal relationships represent missed opportunities to improve health outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

Tackling Missing Data in Community Health Studies Using Additive LS-SVM Classifier.

PubMed

Wang, Guanjin; Deng, Zhaohong; Choi, Kup-Sze

2018-03-01

Missing data is a common issue in community health and epidemiological studies. Direct removal of samples with missing data can lead to reduced sample size and information bias, which deteriorates the significance of the results. While data imputation methods are available to deal with missing data, they are limited in performance and could introduce noises into the dataset. Instead of data imputation, a novel method based on additive least square support vector machine (LS-SVM) is proposed in this paper for predictive modeling when the input features of the model contain missing data. The method also determines simultaneously the influence of the features with missing values on the classification accuracy using the fast leave-one-out cross-validation strategy. The performance of the method is evaluated by applying it to predict the quality of life (QOL) of elderly people using health data collected in the community. The dataset involves demographics, socioeconomic status, health history, and the outcomes of health assessments of 444 community-dwelling elderly people, with 5% to 60% of data missing in some of the input features. The QOL is measured using a standard questionnaire of the World Health Organization. Results show that the proposed method outperforms four conventional methods for handling missing data-case deletion, feature deletion, mean imputation, and K-nearest neighbor imputation, with the average QOL prediction accuracy reaching 0.7418. It is potentially a promising technique for tackling missing data in community health research and other applications.

The association between nurse staffing and omissions in nursing care: A systematic review.

PubMed

Griffiths, Peter; Recio-Saucedo, Alejandra; Dall'Ora, Chiara; Briggs, Jim; Maruotti, Antonello; Meredith, Paul; Smith, Gary B; Ball, Jane

2018-03-08

To identify nursing care most frequently missed in acute adult inpatient wards and to determine evidence for the association of missed care with nurse staffing. Research has established associations between nurse staffing levels and adverse patient outcomes including in-hospital mortality. However, the causal nature of this relationship is uncertain and omissions of nursing care (referred as missed care, care left undone or rationed care) have been proposed as a factor which may provide a more direct indicator of nurse staffing adequacy. Systematic review. We searched the Cochrane Library, CINAHL, Embase and Medline for quantitative studies of associations between staffing and missed care. We searched key journals, personal libraries and reference lists of articles. Two reviewers independently selected studies. Quality appraisal was based on the National Institute for Health and Care Excellence quality appraisal checklist for studies reporting correlations and associations. Data were abstracted on study design, missed care prevalence and measures of association. Synthesis was narrative. Eighteen studies gave subjective reports of missed care. Seventy-five per cent or more nurses reported omitting some care. Fourteen studies found low nurse staffing levels were significantly associated with higher reports of missed care. There was little evidence that adding support workers to the team reduced missed care. Low Registered Nurse staffing is associated with reports of missed nursing care in hospitals. Missed care is a promising indicator of nurse staffing adequacy. The extent to which the relationships observed represent actual failures, is yet to be investigated. © 2018 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Application of pattern mixture models to address missing data in longitudinal data analysis using SPSS.

PubMed

Son, Heesook; Friedmann, Erika; Thomas, Sue A

2012-01-01

Longitudinal studies are used in nursing research to examine changes over time in health indicators. Traditional approaches to longitudinal analysis of means, such as analysis of variance with repeated measures, are limited to analyzing complete cases. This limitation can lead to biased results due to withdrawal or data omission bias or to imputation of missing data, which can lead to bias toward the null if data are not missing completely at random. Pattern mixture models are useful to evaluate the informativeness of missing data and to adjust linear mixed model (LMM) analyses if missing data are informative. The aim of this study was to provide an example of statistical procedures for applying a pattern mixture model to evaluate the informativeness of missing data and conduct analyses of data with informative missingness in longitudinal studies using SPSS. The data set from the Patients' and Families' Psychological Response to Home Automated External Defibrillator Trial was used as an example to examine informativeness of missing data with pattern mixture models and to use a missing data pattern in analysis of longitudinal data. Prevention of withdrawal bias, omitted data bias, and bias toward the null in longitudinal LMMs requires the assessment of the informativeness of the occurrence of missing data. Missing data patterns can be incorporated as fixed effects into LMMs to evaluate the contribution of the presence of informative missingness to and control for the effects of missingness on outcomes. Pattern mixture models are a useful method to address the presence and effect of informative missingness in longitudinal studies.

Orbital evolution of small binary asteroids

NASA Astrophysics Data System (ADS)

Ćuk, Matija; Nesvorný, David

2010-06-01

About 15% of both near-Earth and main-belt asteroids with diameters below 10 km are now known to be binary. These small asteroid binaries are relatively uniform and typically contain a fast-spinning, flattened primary and a synchronously rotating, elongated secondary that is 20-40% as large (in diameter) as the primary. The principal formation mechanism for these binaries is now thought to be YORP (Yarkovsky-O'Keefe-Radzievskii-Paddack) effect induced spin-up of the primary followed by mass loss and accretion of the secondary from the released material. It has previously been suggested (Ćuk, M. [2007]. Astrophys. J. 659, L57-L60) that the present population of small binary asteroids is in a steady state between production through YORP and destruction through binary YORP (BYORP), which should increase or decrease secondary's orbit, depending on the satellite's shape. However, BYORP-driven evolution has not been directly modeled until now. Here we construct a simple numerical model of the binary's orbital as well the secondary's rotational dynamics which includes BYORP and selected terms representing main solar perturbations. We find that many secondaries should be vulnerable to chaotic rotation even for relatively low-eccentricity mutual orbits. We also find that the precession of the mutual orbit for typical small binary asteroids might be dominated by the perturbations from the prolate and librating secondary, rather than the oblate primary. When we evolve the mutual orbit by BYORP we find that the indirect effects on the binary's eccentricity (through the coupling between the orbit and the secondary's spin) dominate over direct ones caused by the BYORP acceleration. In particular, outward evolution causes eccentricity to increase and eventually triggers chaotic rotation of the secondary. We conclude that the most likely outcome will be reestablishing of the synchronous lock with a "flipped" secondary which would then evolve back in. For inward evolution we find an initial decrease of eccentricity and secondary's librations, to be followed by later increase. We think that it is likely that various forms of dissipation we did not model may damp the secondary's librations close to the primary, allowing for further inward evolution and a possible merger. We conclude that a merger or a tidal disruption of the secondary are the most likely outcomes of the BYORP evolution. Dissociation into heliocentric pairs by BYORP alone should be very difficult, and satellite loss might be restricted to the minority of systems containing more than one satellite at the time.

Catquest questionnaire for use in cataract surgery care: assessment of surgical outcomes.

PubMed

Lundström, M; Stenevi, U; Thorburn, W; Roos, P

1998-07-01

To demonstrate the outcome for patients after cataract extraction using the Catquest cataract questionnaire and discuss the models validity in assessing outcome. Thirty-five Swedish departments of ophthalmology. Patients having cataract extraction performed by surgeons from 35 Swedish departments of opthalmology participated in the study. The questionnaire was given to 2970 consecutive patients having surgery during March 1995 at the participating surgical units. The questionnaire was sent by mail to patients and completed on a voluntary basis. It focuses on visual disabilities in daily life, activity level, cataract symptoms, and degree of independence. The results form the questionnaire are interpreted using a benefit matrix that credits not only a decrease in visual disabilities and cataract symptoms but also an improvement in or maintenance of a preoperative activity level. Complete surgical outcome data and completed preoperative and postoperative questionnaires were available in 1933 cases (65.1%). Benefit from surgery according to the model was achieved by 90.9% of the patients. Patients having their second cataract extraction had the highest frequency of the greatest benefit form surgery. There was good agreement between the different levels of benefit from surgery according to the model and the patient's global rating of his or her vision or achieved visual acuity after surgery, respectively. Patients with missing data (did not return postoperative questionnaire or had missing surgical result variables) were older and had a higher frequency of other diseases and handicaps. The Catquest cataract questionnaire allowed the outcome of cataract surgery to be graded by different levels of benefit. There seemed to be good agreement between this model of assessment and the patient's global rating of his or her vision. Missing data may be a problem when a postal questionnaire is used.

The role of infection and sepsis in the Brazilian Network for Surveillance of Severe Maternal Morbidity.

PubMed

Pfitscher, L C; Cecatti, J G; Haddad, S M; Parpinelli, M A; Souza, J P; Quintana, S M; Surita, F G; Costa, M L

2016-02-01

To identify the burden of severe infection within the Brazilian Network for Surveillance of Severe Maternal Morbidity and factors associated with worse maternal outcomes. This was a multicentre cross-sectional study involving 27 referral maternity hospitals in Brazil. WHO's standardised criteria for potentially life-threatening conditions and maternal near miss were used to identify cases through prospective surveillance and the main cause of morbidity was identified as infection or other causes (hypertension, haemorrhage or clinical/surgical). Complications due to infection were compared to complications due to the remaining causes of morbidity. Factors associated with a severe maternal outcome were assessed for the cases of infection. A total of 502 (5.3%) cases of maternal morbidity were associated with severe infection vs. 9053 cases (94.7%) with other causes. Considering increased severity of cases, infection was responsible for one-fourth of all maternal near miss (23.6%) and nearly half (46.4%) of maternal deaths, with a maternal near miss to maternal death ratio three times (2.8:1) that of cases without infection (7.8:1) and a high mortality index (26.3%). Within cases of infection, substandard care was present in over one half of the severe maternal outcome cases. Factors independently associated with worse maternal outcomes were HIV/AIDS, hysterectomy, prolonged hospitalisation, intensive care admission and delays in medical care. Infection is an alarming cause of maternal morbidity and mortality and timely diagnosis and adequate management are key to improving outcomes during pregnancy. Delays should be addressed, risk factors identified, and specific protocols of surveillance and care developed for use during pregnancy. © 2015 John Wiley & Sons Ltd.

Can Fan-Beam Interactive Computed Tomography Accurately Predict Indirect Decompression in Minimally Invasive Spine Surgery Fusion Procedures?

PubMed

Janssen, Insa; Lang, Gernot; Navarro-Ramirez, Rodrigo; Jada, Ajit; Berlin, Connor; Hilis, Aaron; Zubkov, Micaella; Gandevia, Lena; Härtl, Roger

2017-11-01

Recently, novel mobile intraoperative fan-beam computed tomography (CT) was introduced, allowing for real-time navigation and immediate intraoperative evaluation of neural decompression in spine surgery. This study sought to investigate whether intraoperatively assessed neural decompression during minimally invasive spine surgery (MISS) has a predictive value for clinical and radiographic outcome. A retrospective study of patients undergoing intraoperative CT (iCT)-guided extreme lateral interbody fusion or transforaminal lumbar interbody fusion was conducted. 1) Preoperative, 2) intraoperative (after cage implantation, 3) postoperative, and 4) follow-up radiographic and clinical parameters obtained from radiography or CT were quantified. Thirty-four patients (41 spinal segments) were analyzed. iCT-based navigation was successfully accomplished in all patients. Radiographic parameters showed significant improvement from preoperatively to intraoperatively after cage implantation in both MISS procedures (extreme lateral interbody fusion/transforaminal lumbar interbody fusion) (P ≤ 0.05). Radiologic parameters for both MISS fusion procedures did not show significant differences to the assessed radiographic measures at follow-up (P > 0.05). Radiologic outcome values did not decrease when compared intraoperatively (after cage implantation) to latest follow-up. Intraoperative fan-beam CT is capable of assessing neural decompression intraoperatively with high accuracy, allowing for precise prediction of radiologic outcome and earliest possible feedback during MISS fusion procedures. These findings are highly valuable for routine practice and future investigations toward finding a threshold for neural decompression that translates into clinical improvement. If sufficient neural decompression has been confirmed with iCT imaging studies, additional postoperative and/or follow-up imaging studies might no longer be required if patients remain asymptomatic. Copyright © 2017 Elsevier Inc. All rights reserved.

Roles of context in acquisition of human instrumental learning: Implications for the understanding of the mechanisms underlying context-switch effects.

PubMed

Gámez, A Matías; León, Samuel P; Rosas, Juan M

2017-09-01

Four experiments in human instrumental learning explored the associations involving the context that develop after three trials of training on simple discriminations. Experiments 1 and 4 found a deleterious effect of switching the learning context that cannot be explained by the context-outcome binary associations commonly used to explain context-switch effects after short training in human predictive learning and in animal Pavlovian conditioning. Evidence for context-outcome (Experiment 2), context-discriminative stimulus (Experiment 3), and context-instrumental response (Experiment 4) binary associations was found within the same training paradigm, suggesting that contexts became associated with all the elements of the situation, regardless of whether those associations played a role in a specific context-switch effect detected on performance.

Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best?

PubMed

MacNeil Vroomen, Janet; Eekhout, Iris; Dijkgraaf, Marcel G; van Hout, Hein; de Rooij, Sophia E; Heymans, Martijn W; Bosmans, Judith E

2016-11-01

Cost and effect data often have missing data because economic evaluations are frequently added onto clinical studies where cost data are rarely the primary outcome. The objective of this article was to investigate which multiple imputation strategy is most appropriate to use for missing cost-effectiveness data in a randomized controlled trial. Three incomplete data sets were generated from a complete reference data set with 17, 35 and 50 % missing data in effects and costs. The strategies evaluated included complete case analysis (CCA), multiple imputation with predictive mean matching (MI-PMM), MI-PMM on log-transformed costs (log MI-PMM), and a two-step MI. Mean cost and effect estimates, standard errors and incremental net benefits were compared with the results of the analyses on the complete reference data set. The CCA, MI-PMM, and the two-step MI strategy diverged from the results for the reference data set when the amount of missing data increased. In contrast, the estimates of the Log MI-PMM strategy remained stable irrespective of the amount of missing data. MI provided better estimates than CCA in all scenarios. With low amounts of missing data the MI strategies appeared equivalent but we recommend using the log MI-PMM with missing data greater than 35 %.

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

PubMed

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

Missing persons-missing data: the need to collect antemortem dental records of missing persons.

PubMed

Blau, Soren; Hill, Anthony; Briggs, Christopher A; Cordner, Stephen M

2006-03-01

The subject of missing persons is of great concern to the community with numerous associated emotional, financial, and health costs. This paper examines the forensic medical issues raised by the delayed identification of individuals classified as "missing" and highlights the importance of including dental data in the investigation of missing persons. Focusing on Australia, the current approaches employed in missing persons investigations are outlined. Of particular significance is the fact that each of the eight Australian states and territories has its own Missing Persons Unit that operates within distinct state and territory legislation. Consequently, there is a lack of uniformity within Australia about the legal and procedural framework within which investigations of missing persons are conducted, and the interaction of that framework with coronial law procedures. One of the main investigative problems in missing persons investigations is the lack of forensic medical, particularly, odontological input. Forensic odontology has been employed in numerous cases in Australia where identity is unknown or uncertain because of remains being skeletonized, incinerated, or partly burnt. The routine employment of the forensic odontologist to assist in missing person inquiries, has however, been ignored. The failure to routinely employ forensic odontology in missing persons inquiries has resulted in numerous delays in identification. Three Australian cases are presented where the investigation of individuals whose identity was uncertain or unknown was prolonged due to the failure to utilize the appropriate (and available) dental resources. In light of the outcomes of these cases, we suggest that a national missing persons dental records database be established for future missing persons investigations. Such a database could be easily managed between a coronial system and a forensic medical institute. In Australia, a national missing persons dental records database could be incorporated into the National Coroners Information System (NCIS) managed, on behalf of Australia's Coroners, by the Victorian Institute of Forensic Medicine. The existence of the NCIS would ensure operational collaboration in the implementation of the system and cost savings to Australian policing agencies involved in missing person inquiries. The implementation of such a database would facilitate timely and efficient reconciliation of clinical and postmortem dental records and have subsequent social and financial benefits.

Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial.

PubMed

Mason, Alexina J; Gomes, Manuel; Grieve, Richard; Ulug, Pinar; Powell, Janet T; Carpenter, James

2017-08-01

The analyses of randomised controlled trials with missing data typically assume that, after conditioning on the observed data, the probability of missing data does not depend on the patient's outcome, and so the data are 'missing at random' . This assumption is usually implausible, for example, because patients in relatively poor health may be more likely to drop out. Methodological guidelines recommend that trials require sensitivity analysis, which is best informed by elicited expert opinion, to assess whether conclusions are robust to alternative assumptions about the missing data. A major barrier to implementing these methods in practice is the lack of relevant practical tools for eliciting expert opinion. We develop a new practical tool for eliciting expert opinion and demonstrate its use for randomised controlled trials with missing data. We develop and illustrate our approach for eliciting expert opinion with the IMPROVE trial (ISRCTN 48334791), an ongoing multi-centre randomised controlled trial which compares an emergency endovascular strategy versus open repair for patients with ruptured abdominal aortic aneurysm. In the IMPROVE trial at 3 months post-randomisation, 21% of surviving patients did not complete health-related quality of life questionnaires (assessed by EQ-5D-3L). We address this problem by developing a web-based tool that provides a practical approach for eliciting expert opinion about quality of life differences between patients with missing versus complete data. We show how this expert opinion can define informative priors within a fully Bayesian framework to perform sensitivity analyses that allow the missing data to depend upon unobserved patient characteristics. A total of 26 experts, of 46 asked to participate, completed the elicitation exercise. The elicited quality of life scores were lower on average for the patients with missing versus complete data, but there was considerable uncertainty in these elicited values. The missing at random analysis found that patients randomised to the emergency endovascular strategy versus open repair had higher average (95% credible interval) quality of life scores of 0.062 (-0.005 to 0.130). Our sensitivity analysis that used the elicited expert information as pooled priors found that the gain in average quality of life for the emergency endovascular strategy versus open repair was 0.076 (-0.054 to 0.198). We provide and exemplify a practical tool for eliciting the expert opinion required by recommended approaches to the sensitivity analyses of randomised controlled trials. We show how this approach allows the trial analysis to fully recognise the uncertainty that arises from making alternative, plausible assumptions about the reasons for missing data. This tool can be widely used in the design, analysis and interpretation of future trials, and to facilitate this, materials are available for download.

Improving the recognition of near-miss events on NASA missions

NASA Astrophysics Data System (ADS)

Dillon, R. L.; Rogers, E. W.; Madsen, P.; Tinsley, C. H.

Organizations that ignore near-miss data may be inappropriately rewarding risky behavior. If managers engage in risky behavior and succeed, research shows that these managers are likely to be promoted without close scrutiny of their risky decisions, even if the success is because of good fortune. Over time such risk taking compounds as similar near-misses are repeatedly observed and the ability to recognize anomalies and document the events decreases (i.e., normalization of deviance). History from the shuttle program shows that only the occasional large failure increases attention to anomalies again. This research demonstrates the presence of normalization of deviance in NASA missions and also examines a factor (the significance of the project) that may increase people's awareness of near-misses to counter this trend. Increasing awareness of chance success should increase the likelihood that significant learning can occur from the mission regardless of outcome. We conclude with prescriptions for project managers based on several on-going activities at NASA Goddard Space Flight Center (GSFC) to improve organizational learning. We discuss how these efforts can contribute to reducing near-miss bias and the normalization of deviance. This research should help organizations design learning processes that draw lessons from near-misses.

Comparing multiple imputation methods for systematically missing subject-level data.

PubMed

Kline, David; Andridge, Rebecca; Kaizar, Eloise

2017-06-01

When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data. When the studies to combine are longitudinal, missing data can occur on the observation-level (time-varying) or the subject-level (non-time-varying). Traditionally, the focus of missing data methods for longitudinal data has been on missing observation-level variables. In this paper, we focus on missing subject-level variables and compare two multiple imputation approaches: a joint modeling approach and a sequential conditional modeling approach. We find the joint modeling approach to be preferable to the sequential conditional approach, except when the covariance structure of the repeated outcome for each individual has homogenous variance and exchangeable correlation. Specifically, the regression coefficient estimates from an analysis incorporating imputed values based on the sequential conditional method are attenuated and less efficient than those from the joint method. Remarkably, the estimates from the sequential conditional method are often less efficient than a complete case analysis, which, in the context of research synthesis, implies that we lose efficiency by combining studies. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

What are the appropriate methods for analyzing patient-reported outcomes in randomized trials when data are missing?

PubMed

Hamel, J F; Sebille, V; Le Neel, T; Kubis, G; Boyer, F C; Hardouin, J B

2017-12-01

Subjective health measurements using Patient Reported Outcomes (PRO) are increasingly used in randomized trials, particularly for patient groups comparisons. Two main types of analytical strategies can be used for such data: Classical Test Theory (CTT) and Item Response Theory models (IRT). These two strategies display very similar characteristics when data are complete, but in the common case when data are missing, whether IRT or CTT would be the most appropriate remains unknown and was investigated using simulations. We simulated PRO data such as quality of life data. Missing responses to items were simulated as being completely random, depending on an observable covariate or on an unobserved latent trait. The considered CTT-based methods allowed comparing scores using complete-case analysis, personal mean imputations or multiple-imputations based on a two-way procedure. The IRT-based method was the Wald test on a Rasch model including a group covariate. The IRT-based method and the multiple-imputations-based method for CTT displayed the highest observed power and were the only unbiased method whatever the kind of missing data. Online software and Stata® modules compatibles with the innate mi impute suite are provided for performing such analyses. Traditional procedures (listwise deletion and personal mean imputations) should be avoided, due to inevitable problems of biases and lack of power.

Examining the Relationships between Student Learning Habits and Post-Secondary Educational Outcomes: The Missing Component

ERIC Educational Resources Information Center

Goodlowe-Scott, Quinhon N.

2017-01-01

In high schools across the country, college readiness standards have emerged as an important post-secondary educational outcome. Previous reform efforts have largely focused on "failing schools" versus "failing students" (Weissberg, 2010). This study takes the view that student learning habits might be better determinants of…

R package to estimate intracluster correlation coefficient with confidence interval for binary data.

PubMed

Chakraborty, Hrishikesh; Hossain, Akhtar

2018-03-01

The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of Healthcare Information Technology on Nursing Practice.

PubMed

Piscotty, Ronald J; Kalisch, Beatrice; Gracey-Thomas, Angel

2015-07-01

To report additional mediation findings from a descriptive cross sectional study to examine if nurses' perceptions of the impact of healthcare information technology on their practice mediates the relationship between electronic nursing care reminder use and missed nursing care. The study used a descriptive design. The sample (N = 165) was composed of registered nurses working on acute care hospital units. The sample was obtained from a large teaching hospital in Southeast Michigan in the fall of 2012. All eligible nursing units (n = 19) were included. The MISSCARE Survey, Nursing Care Reminders Usage Survey, and the Impact of Healthcare Information Technology Scale were used to collect data to test for mediation. Mediation was tested using the method described by Baron and Kenny. Multiple regression equations were used to analyze the data to determine if mediation occurred between the variables. Missed nursing care, the outcome variable, was regressed on the predictor variable, reminder usage, and the mediator variable impact of technology on nursing practice. The impact of healthcare information technology (IHIT) on nursing practice negatively affected missed nursing care (t = -4.12, p < .001), explaining 9.8% of variance in missed nursing care. With IHIT present, the predictor (reminder usage) was no longer significant (t = -.70, p = .48). Thus, the reduced direct association between reminder usage and missed nursing care when IHIT was in the model supported the hypothesis that IHIT was at least one of the mediators in the relationship between reminder usage and missed nursing care. The perceptions of the impact of healthcare information technology mediates the relationship between nursing care reminder use and missed nursing care. The findings are beneficial to the advancement of healthcare technology in that designers of healthcare information technology systems need to keep in mind that perceptions regarding impacts of the technology will influence usage. Many times, information technology systems are not designed to match the workflow of nurses. Systems built with redundant or impertinent reminders may be ignored. System designers must study which reminders nurses find most useful and which reminders result in the best quality outcomes. © 2015 Sigma Theta Tau International.

Treatment Effect Estimation Using Nonlinear Two-Stage Instrumental Variable Estimators: Another Cautionary Note.

PubMed

Chapman, Cole G; Brooks, John M

2016-12-01

To examine the settings of simulation evidence supporting use of nonlinear two-stage residual inclusion (2SRI) instrumental variable (IV) methods for estimating average treatment effects (ATE) using observational data and investigate potential bias of 2SRI across alternative scenarios of essential heterogeneity and uniqueness of marginal patients. Potential bias of linear and nonlinear IV methods for ATE and local average treatment effects (LATE) is assessed using simulation models with a binary outcome and binary endogenous treatment across settings varying by the relationship between treatment effectiveness and treatment choice. Results show that nonlinear 2SRI models produce estimates of ATE and LATE that are substantially biased when the relationships between treatment and outcome for marginal patients are unique from relationships for the full population. Bias of linear IV estimates for LATE was low across all scenarios. Researchers are increasingly opting for nonlinear 2SRI to estimate treatment effects in models with binary and otherwise inherently nonlinear dependent variables, believing that it produces generally unbiased and consistent estimates. This research shows that positive properties of nonlinear 2SRI rely on assumptions about the relationships between treatment effect heterogeneity and choice. © Health Research and Educational Trust.

Cost-effectiveness analysis in minimally invasive spine surgery.

PubMed

Al-Khouja, Lutfi T; Baron, Eli M; Johnson, J Patrick; Kim, Terrence T; Drazin, Doniel

2014-06-01

Medical care has been evolving with the increased influence of a value-based health care system. As a result, more emphasis is being placed on ensuring cost-effectiveness and utility in the services provided to patients. This study looks at this development in respect to minimally invasive spine surgery (MISS) costs. A literature review using PubMed, the Cost-Effectiveness Analysis (CEA) Registry, and the National Health Service Economic Evaluation Database (NHS EED) was performed. Papers were included in the study if they reported costs associated with minimally invasive spine surgery (MISS). If there was no mention of cost, CEA, cost-utility analysis (CUA), quality-adjusted life year (QALY), quality, or outcomes mentioned, then the article was excluded. Fourteen studies reporting costs associated with MISS in 12,425 patients (3675 undergoing minimally invasive procedures and 8750 undergoing open procedures) were identified through PubMed, the CEA Registry, and NHS EED. The percent cost difference between minimally invasive and open approaches ranged from 2.54% to 33.68%-all indicating cost saving with a minimally invasive surgical approach. Average length of stay (LOS) for minimally invasive surgery ranged from 0.93 days to 5.1 days compared with 1.53 days to 12 days for an open approach. All studies reporting EBL reported lower volume loss in an MISS approach (range 10-392.5 ml) than in an open approach (range 55-535.5 ml). There are currently an insufficient number of studies published reporting the costs of MISS. Of the studies published, none have followed a standardized method of reporting and analyzing cost data. Preliminary findings analyzing the 14 studies showed both cost saving and better outcomes in MISS compared with an open approach. However, more Level I CEA/CUA studies including cost/QALY evaluations with specifics of the techniques utilized need to be reported in a standardized manner to make more accurate conclusions on the cost effectiveness of minimally invasive spine surgery.

Tale of the Tails, the Missing Postpartum IUCD Strings.

PubMed

Mishra, Sujnanendra

2017-06-01

Using an intrauterine device (IUD) is many times safer than pregnancy and more effective in preventing pregnancy than oral contraceptives, condoms, spermicidal, any barrier method, or natural family planning. Benefits of healthy timing and spacing of pregnancy are many. Postpartum contraception is becoming popular after introduction of PPIUCD services. To study the incidence, management, clinical outcome of missing strings cases in post-placental and intra-cesarean IUCD. This study was a retrospective observational study, carried out in the district of Balangir, Odisha, India. Status of women who had post-placental and intra-cesarean IUCD insertion in various institutions between January 2010 and December 2012 having follow-up as per the protocol was taken for the study. All the complications were recorded and studied. Incidence, clinical outcome, and management of missing strings were analyzed. Records of 1343 clients were studied. Six hundred and seventeen cases had failed to report for follow-up as per the study design. Seven hundred and twenty-six cases had follow-up as per the protocol. Of them, 36 had expulsion, and rest 690 cases were taken for the study. There were 209 missing strings at 3 months. At the end of the study, there was spontaneous descend in 138 cases. More than 50 % cases were asymptomatic. Ultrasonography was the method of diagnosis, and simple sounding of the uterus alone could also establish IUD in uterine cavity. Removal rate was higher in missing strings group, Continuation rate is higher in String visible group. Post-placental intra-cesarean Copper T 380A insertion is a safe and effective method of reversible contraception; missing string is emerging as a potential distracter of its use. It is important that every user must be followed up and the providers must be competent in managing complication. Better after care in form of effective follow-up and complication management is needed to maintain popularity. Introduction of compensation scheme will also help improving the acceptance.

Getting patients in the door: medical appointment reminder preferences.

PubMed

Crutchfield, Trisha M; Kistler, Christine E

2017-01-01

Between 23% and 34% of outpatient appointments are missed annually. Patients who frequently miss medical appointments have poorer health outcomes and are less likely to use preventive health care services. Missed appointments result in unnecessary costs and organizational inefficiencies. Appointment reminders may help reduce missed appointments; particular types may be more effective than other types. We used a survey with a discrete choice experiment (DCE) to learn why individuals miss appointments and to assess appointment reminder preferences. We enrolled a national sample of adults from an online survey panel to complete demographic and appointment habit questions as well as a 16-task DCE designed in Sawtooth Software's Discover tool. We assessed preferences for four reminder attributes - initial reminder type, arrival of initial reminder, reminder content, and number of reminders. We derived utilities and importance scores. We surveyed 251 adults nationally, with a mean age of 43 (range 18-83) years: 51% female, 84% White, and 8% African American. Twenty-three percent of individuals missed one or more appointments in the past 12 months. Two primary reasons given for missing an appointment include transportation problems (28%) and forgetfulness (26%). Participants indicated the initial reminder type (21%) was the most important attribute, followed by the number of reminders (10%). Overall, individuals indicated a preference for a single reminder, arriving via email, phone call, or text message, delivered less than 2 weeks prior to an appointment. Preferences for reminder content were less clear. The number of missed appointments and reasons for missing appointments are consistent with prior research. Patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients' needs. Future research is necessary to determine if preferred reminders used in practice will result in improved appointment attendance in clinical settings.

Informatively missing quality of life and unmet needs sex data for immigrant and Anglo-Australian cancer patients and survivors.

PubMed

Bell, Melanie L; Butow, Phyllis N; Goldstein, David

2013-12-01

Although cancer can seriously affect peoples' sexual well-being, survivors and patients may be reluctant to answer questions about sex. This reluctance may be stronger for immigrants. This study aimed to investigate missing sex data rates and predictors of missingness in two large studies on immigrants and Anglo-Australian controls with cancer and to investigate whether those with missing sex data may have worse sexual outcomes than those with complete data. We carried out two studies aimed at describing the quality of life (QoL) and unmet needs amongst Arabic, Chinese and Greek immigrants versus Anglo-Australians cancer survivors (n = 596, recruited from cancer registries) and patients (n = 845). Logistic regression was used to model the probability of having missing sex data in either of the questionnaires. We compared the mean of the unmet sex needs responses of those who had missing QoL sex data (but not needs) to those who had completed both, and vice versa. Missing sex data rates were as high as 65 %, with immigrants more likely to skip sex items than Anglo-Australians (p = 0.02 for registry study, p < 0.0001 for hospital study). Women, older participants and participants with more advanced disease had increased odds of missingness. There was evidence that data were informatively missing. Additionally, the questionnaire which stated that the sex questions are optional had higher missing data rates. High missing data rates and informatively missing data can lead to biased results. Using the questionnaires that state that they may skip sex items may lead to an underestimation of sexual problems or an overestimation of quality of life.

Missing data in FFQs: making assumptions about item non-response.

PubMed

Lamb, Karen E; Olstad, Dana Lee; Nguyen, Cattram; Milte, Catherine; McNaughton, Sarah A

2017-04-01

FFQs are a popular method of capturing dietary information in epidemiological studies and may be used to derive dietary exposures such as nutrient intake or overall dietary patterns and diet quality. As FFQs can involve large numbers of questions, participants may fail to respond to all questions, leaving researchers to decide how to deal with missing data when deriving intake measures. The aim of the present commentary is to discuss the current practice for dealing with item non-response in FFQs and to propose a research agenda for reporting and handling missing data in FFQs. Single imputation techniques, such as zero imputation (assuming no consumption of the item) or mean imputation, are commonly used to deal with item non-response in FFQs. However, single imputation methods make strong assumptions about the missing data mechanism and do not reflect the uncertainty created by the missing data. This can lead to incorrect inference about associations between diet and health outcomes. Although the use of multiple imputation methods in epidemiology has increased, these have seldom been used in the field of nutritional epidemiology to address missing data in FFQs. We discuss methods for dealing with item non-response in FFQs, highlighting the assumptions made under each approach. Researchers analysing FFQs should ensure that missing data are handled appropriately and clearly report how missing data were treated in analyses. Simulation studies are required to enable systematic evaluation of the utility of various methods for handling item non-response in FFQs under different assumptions about the missing data mechanism.

High-intensity interval training versus moderate-intensity steady-state training in UK cardiac rehabilitation programmes (HIIT or MISS UK): study protocol for a multicentre randomised controlled trial and economic evaluation.

PubMed

McGregor, Gordon; Nichols, Simon; Hamborg, Thomas; Bryning, Lucy; Tudor-Edwards, Rhiannon; Markland, David; Mercer, Jenny; Birkett, Stefan; Ennis, Stuart; Powell, Richard; Begg, Brian; Haykowsky, Mark J; Banerjee, Prithwish; Ingle, Lee; Shave, Rob; Backx, Karianne

2016-11-16

Current international guidelines for cardiac rehabilitation (CR) advocate moderate-intensity exercise training (MISS, moderate-intensity steady state). This recommendation predates significant advances in medical therapy for coronary heart disease (CHD) and may not be the most appropriate strategy for the 'modern' patient with CHD. High-intensity interval training (HIIT) appears to be a safe and effective alternative, resulting in greater improvements in peak oxygen uptake (VO 2 peak ). To date, HIIT trials have predominantly been proof-of-concept studies in the laboratory setting and conducted outside the UK. The purpose of this multicentre randomised controlled trial is to compare the effects of HIIT and MISS training in patients with CHD attending UK CR programmes. This pragmatic study will randomly allocate 510 patients with CHD to 8 weeks of twice weekly HIIT or MISS training at 3 centres in the UK. HIIT will consist of 10 high-intensity (85-90% peak power output (PPO)) and 10 low-intensity (20-25% PPO) intervals, each lasting 1 min. MISS training will follow usual care recommendations, adhering to currently accepted UK guidelines (ie, >20 min continuous exercise at 40-70% heart rate reserve). Outcome measures will be assessed at baseline, 8 weeks and 12 months. The primary outcome for the trial will be change in VO 2 peak as determined by maximal cardiopulmonary exercise testing. Secondary measures will assess physiological, psychosocial and economic outcomes. The study protocol V.1.0, dated 1 February 2016, was approved by the NHS Health Research Authority, East Midlands-Leicester South Research Ethics Committee (16/EM/0079). Recruitment will start in August 2016 and will be completed in June 2018. Results will be published in peer-reviewed journals, presented at national and international scientific meetings and are expected to inform future national guidelines for exercise training in UK CR. NCT02784873; pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

High-intensity interval training versus moderate-intensity steady-state training in UK cardiac rehabilitation programmes (HIIT or MISS UK): study protocol for a multicentre randomised controlled trial and economic evaluation

PubMed Central

McGregor, Gordon; Nichols, Simon; Hamborg, Thomas; Bryning, Lucy; Tudor-Edwards, Rhiannon; Markland, David; Mercer, Jenny; Birkett, Stefan; Ennis, Stuart; Powell, Richard; Begg, Brian; Haykowsky, Mark J; Banerjee, Prithwish; Ingle, Lee; Shave, Rob; Backx, Karianne

2016-01-01

Introduction Current international guidelines for cardiac rehabilitation (CR) advocate moderate-intensity exercise training (MISS, moderate-intensity steady state). This recommendation predates significant advances in medical therapy for coronary heart disease (CHD) and may not be the most appropriate strategy for the ‘modern’ patient with CHD. High-intensity interval training (HIIT) appears to be a safe and effective alternative, resulting in greater improvements in peak oxygen uptake (VO2 peak). To date, HIIT trials have predominantly been proof-of-concept studies in the laboratory setting and conducted outside the UK. The purpose of this multicentre randomised controlled trial is to compare the effects of HIIT and MISS training in patients with CHD attending UK CR programmes. Methods and analysis This pragmatic study will randomly allocate 510 patients with CHD to 8 weeks of twice weekly HIIT or MISS training at 3 centres in the UK. HIIT will consist of 10 high-intensity (85–90% peak power output (PPO)) and 10 low-intensity (20–25% PPO) intervals, each lasting 1 min. MISS training will follow usual care recommendations, adhering to currently accepted UK guidelines (ie, >20 min continuous exercise at 40–70% heart rate reserve). Outcome measures will be assessed at baseline, 8 weeks and 12 months. The primary outcome for the trial will be change in VO2 peak as determined by maximal cardiopulmonary exercise testing. Secondary measures will assess physiological, psychosocial and economic outcomes. Ethics and dissemination The study protocol V.1.0, dated 1 February 2016, was approved by the NHS Health Research Authority, East Midlands—Leicester South Research Ethics Committee (16/EM/0079). Recruitment will start in August 2016 and will be completed in June 2018. Results will be published in peer-reviewed journals, presented at national and international scientific meetings and are expected to inform future national guidelines for exercise training in UK CR. Trial registration number NCT02784873; pre-results. PMID:27852718

Association of sleep habits with accidents and near misses in United States transportation operators.

PubMed

Johnson, Kevin D; Patel, Sanjay R; Baur, Dorothee M; Edens, Edward; Sherry, Patrick; Malhotra, Atul; Kales, Stefanos N

2014-05-01

To explore sleep risk factors and their association with adverse events in transportation operators. Self-reported sleep-related behaviors were analyzed in transportation operators (drivers, pilots, and rail operators) aged 26 to 78 years who completed the National Sleep Foundation's 2012 "Planes, Trains, Automobiles, and Sleep" survey. Regression analyses were used to assess the associations of various sleep-related variables with the combined outcome of self-reported accidents and near misses. Age- and body mass-adjusted predictors of accidents/near misses included an accident while commuting (odds ratio [OR] = 4.6; confidence interval [CI], 2.1 to 9.8), driving drowsy (OR = 4.1; CI, 2.5 to 6.7), and Sheehan Disability Scale score greater than 15 (OR = 3.5; CI, 2.2 to 5.5). Sleeping more than 7 hours nightly was protective for accident/near misses (OR = 0.6; CI, 0.4 to 0.9). Recognized risk factors for poor sleep or excessive daytime sleepiness were significantly associated with self-reported near misses and/or accidents in transportation operators.

Association of Sleep Habits With Accidents and Near Misses in United States Transportation Operators

PubMed Central

Johnson, Kevin D.; Patel, Sanjay R.; Baur, Dorothee M.; Edens, Edward; Sherry, Patrick; Malhotra, Atul; Kales, Stefanos N.

2015-01-01

Objective To explore sleep risk factors and their association with adverse events in transportation operators. Methods Self-reported sleep-related behaviors were analyzed in transportation operators (drivers, pilots, and rail operators) aged 26 to 78 years who completed the National Sleep Foundation’s 2012 “Planes, Trains, Automobiles, and Sleep” survey. Regression analyses were used to assess the associations of various sleep-related variables with the combined outcome of self-reported accidents and near misses. Results Age- and body mass–adjusted predictors of accidents/near misses included an accident while commuting (odds ratio [OR] = 4.6; confidence interval [CI], 2.1 to 9.8), driving drowsy (OR = 4.1; CI, 2.5 to 6.7), and Sheehan Disability Scale score greater than 15 (OR = 3.5; CI, 2.2 to 5.5). Sleeping more than 7 hours nightly was protective for accident/near misses (OR = 0.6; CI, 0.4 to 0.9). Conclusion Recognized risk factors for poor sleep or excessive daytime sleepiness were significantly associated with self-reported near misses and/or accidents in transportation operators. PMID:24806564

Job demands, job resources and safety outcomes: The roles of emotional exhaustion and safety compliance.

PubMed

Li, Feng; Jiang, Li; Yao, Xiang; Li, YongJuan

2013-03-01

The aim of this study was to assess the effectiveness of the job demands-resources (JD-R) model in explaining the relationship of job demands and resources with safety outcomes (i.e., workplace injuries and near-misses). We collected self-reported data from 670 crude oil production workers from three sub-companies of a major oilfield company in China. The results of a structural equation analysis indicated that job demands (psychological and physical demands) and job resources (decision latitude, supervisor support and coworker support) could affect emotional exhaustion and safety compliance, and thus influence the occurrence of injuries and near-misses. The implications of the present findings regarding both the JD-R model and occupational safety research were discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clinical trials in pediatric neuro-oncology: what is missing and how we can improve.

PubMed

Byer, Lennox; Kline, Cassie; Mueller, Sabine

2016-10-01

Brain tumors are the most common solid tumor in childhood, yet outcomes vary dramatically. High-grade gliomas have dismal outcomes with poor survival. By contrast, low-grade gliomas, have high survival rates, but children suffer from morbidity of tumor burden and therapy-associated side effects. In this article, we discuss how current trial designs often miss the opportunity to include end points beyond tumor response and thus fail to offer complete assessments of therapeutic approaches. Quality of life, neurocognitive function and neurofunctional deficits need to be considered when assessing overall success of a therapy. Herein, we identify specific end points that should be included in the interpretation of clinical trial results and accordingly, offer a more comprehensive approach to treatment decision-making.

Power analysis on the time effect for the longitudinal Rasch model.

PubMed

Feddag, M L; Blanchin, M; Hardouin, J B; Sebille, V

2014-01-01

Statistics literature in the social, behavioral, and biomedical sciences typically stress the importance of power analysis. Patient Reported Outcomes (PRO) such as quality of life and other perceived health measures (pain, fatigue, stress,...) are increasingly used as important health outcomes in clinical trials or in epidemiological studies. They cannot be directly observed nor measured as other clinical or biological data and they are often collected through questionnaires with binary or polytomous items. The Rasch model is the well known model in the item response theory (IRT) for binary data. The article proposes an approach to evaluate the statistical power of the time effect for the longitudinal Rasch model with two time points. The performance of this method is compared to the one obtained by simulation study. Finally, the proposed approach is illustrated on one subscale of the SF-36 questionnaire.

Infalling clouds on to supermassive black hole binaries - II. Binary evolution and the final parsec problem

NASA Astrophysics Data System (ADS)

Goicovic, Felipe G.; Sesana, Alberto; Cuadra, Jorge; Stasyszyn, Federico

2017-11-01

The formation of massive black hole binaries (MBHBs) is an unavoidable outcome of galaxy evolution via successive mergers. However, the mechanism that drives their orbital evolution from parsec separations down to the gravitational wave dominated regime is poorly understood, and their final fate is still unclear. If such binaries are embedded in gas-rich and turbulent environments, as observed in remnants of galaxy mergers, the interaction with gas clumps (such as molecular clouds) may efficiently drive their orbital evolution. Using numerical simulations, we test this hypothesis by studying the dynamical evolution of an equal mass, circular MBHB accreting infalling molecular clouds. We investigate different orbital configurations, modelling a total of 13 systems to explore different possible impact parameters and relative inclinations of the cloud-binary encounter. We focus our study on the prompt, transient phase during the first few orbits when the dynamical evolution of the binary is fastest, finding that this evolution is dominated by the exchange of angular momentum through gas capture by the individual black holes and accretion. Building on these results, we construct a simple model for evolving an MBHB interacting with a sequence of clouds, which are randomly drawn from reasonable populations with different levels of anisotropy in their angular momenta distributions. We show that the binary efficiently evolves down to the gravitational wave emission regime within a few hundred million years, overcoming the 'final parsec' problem regardless of the stellar distribution.

Altering the near-miss effect in slot machine gamblers.

PubMed

Dixon, Mark R; Nastally, Becky L; Jackson, James E; Habib, Reza

2009-01-01

This study investigated the potential for recreational gamblers to respond as if certain types of losing slot machine outcomes were actually closer to a win than others (termed the near-miss effect). Exposure to conditional discrimination training and testing disrupted this effect for 10 of the 16 participants. These 10 participants demonstrated high percentages of conditional discrimination testing performance, and the remaining 6 participants failed the discrimination tests. The implications for a verbally based behavioral explanation of gambling are presented.

The stars with H-alpha missing

NASA Technical Reports Server (NTRS)

Downes, Ronald A.

1987-01-01

During the course of a survey for ultraviolet-excess objects, a group of objects were found that spectroscopically resemble the subdwarf B stars, except for variable strength H-alpha absorption. The H-alpha line can have the nominal strength predicted from the other Balmer lines, or it can be completely absent. Observations reveal significant changes in the H-alpha profile on both a night-to-night and month-to-month basis. IUE observations of three stars reveal few features in the ultraviolet region and, when combined with optical data, allow a rough determination of photospheric temperatures. A binary model is proposed for these systems, and the ramifications of the objects found here and in the Palomar-Green survey are discussed.

Obstetrical referrals by traditional birth attendants.

PubMed

Mustafa, Rozina; Hashmi, Haleema; Mustafa, Rubina

2012-01-01

In Pakistan 90% of births are conducted by TBA's. In most cases, TBA's are unable to diagnose the complications and are often unable to take decisions on timely referral. The objective of this study was to determine the prevalence, nature and outcome of life threatening obstetrical conditions in referrals by Traditional Birth Attendants (TBAs). This Observational, Descriptive study was conducted from January to December 2007, in the obstetrical unit of Fatima Hospital, Baqai Medical University, a tertiary care community based hospital. The study included patients referred by TBA's who developed life threatening obstetric conditions (LTOCs). Total 64 patients were referred by TBA's. The prevalence was 7.8%. Out of them, 53 (82.8%) patients admitted with life threatening obstetric conditions. The near-miss morbidities and mortalities were 45 (84.9%) and 8 (15%) respectively. Maternal mortality to Near-miss morbidity ratio was 1:6. Obstructed labour caused near-miss morbidity in 32 (60.3%) patients with no mortality. Postpartum haemorrhage as life threatening condition developed in 16 (30.1%) patients with 10 (18.8%) near-miss morbidities and 6 (11.3%) mortalities. Puerperal sepsis accounted for 1 (1.88%) near-miss morbidity and 2 (3.76%) mortalities. The mortality index for puerperal sepsis is (66.6%) almost double of postpartum haemorrhage (37.5%). Mortality to near miss morbidity ratio is high. Misidentification and late referrals of complicated cases by TBA's were responsible for near-miss morbidities and mortalities.

Modeling Nonignorable Missing Data with Item Response Theory (IRT). Research Report. ETS RR-10-11

ERIC Educational Resources Information Center

Rose, Norman; von Davier, Matthias; Xu, Xueli

2010-01-01

Large-scale educational surveys are low-stakes assessments of educational outcomes conducted using nationally representative samples. In these surveys, students do not receive individual scores, and the outcome of the assessment is inconsequential for respondents. The low-stakes nature of these surveys, as well as variations in average performance…

"Miss, I Am Not Being Fully Prepared": Student-Teachers' Concerns about Their Preparation at a Teacher Training Institution in Jamaica

ERIC Educational Resources Information Center

Roofe, Carmel G.; Miller, Paul

2013-01-01

The issue of teacher preparation continues to occupy academic discourse relating to student outcomes and student achievement (Stronge, Ward & Grant, 2011). Research has supported the view that there is an inextricable connection between student outcomes, quality of teaching and teachers, and teacher preparation (Darling-Hammond 2005; Grover…

The Missing Manual: Using National Student Clearinghouse Data to Track Postsecondary Outcomes

ERIC Educational Resources Information Center

Dynarski, Susan M.; Hemelt, Steven W.; Hyman, Joshua M.

2015-01-01

This article explores the promises and pitfalls of using National Student Clearinghouse (NSC) data to measure a variety of postsecondary outcomes. We first describe the history of the NSC, the basic structure of its data, and recent research interest in using NSC data. Second, using information from the Integrated Postsecondary Education Data…

Planet Formation in Stellar Binaries: How Disk Gravity Can Lower theFragmentation Barrier

NASA Astrophysics Data System (ADS)

Silsbee, Kedron; Rafikov, Roman R.

2014-11-01

Binary star systems present a challenge to current theories of planet formation. Perturbations from the companion star dynamically excite the protoplanetary disk, which can lead to destructive collisions between planetesimals, and prevent growth from 1 km to 100 km sized planetesimals. Despite this apparent barrier to coagulation, planets have been discovered within several small-separation (<20 AU), eccentric (eb 0.4) binaries, such as alpha Cen and gamma Cep. We address this problem by analytically exploring planetesimal dynamics under the simultaneous action of (1) binary perturbation, (2) gas drag (which tends to align planetesimal orbits), and (3), the gravity of an eccentric protoplanetary disk. We then use our dynamical solutions to assess the outcomes of planetesimal collisions (growth, destruction, erosion) for a variety of disk models. We find that planets in small-separation binaries can form at their present locations if the primordial protoplanetary disks were massive (>0.01M⊙) and not very eccentric (eccentricity of order several per cent at the location of planet). This constraint on the disk mass is compatible with the high masses of the giant planets in known gamma Cep-like binaries, which require a large mass reservoir for their formation. We show that for these massive disks, disk gravity is dominant over the gravity of the binary companion at the location of the observed planets. Therefore, planetesimal growth is highly sensitive to disk properties. The requirement of low disk eccentricity is in line with the recent hydrodynamic simulations that tend to show gaseous disks in eccentric binaries developing very low eccentricity, at the level of a few percent. A massive purely axisymmetric disk makes for a friendlier environment for planetesimal growth by driving rapid apsidal precession of planetesimals, and averaging out the eccentricity excitation from the binary companion. When the protoplanetary disk is eccentric we find that the most favorable conditions for planetesimal growth emerge when the disk is non-precessing and is apsidally aligned with the orbit of the binary.

Effects of Oral Nutritional Supplements on Mortality, Missed Dialysis Treatments, and Nutritional Markers in Hemodialysis Patients.

PubMed

Benner, Debbie; Brunelli, Steven M; Brosch, Becky; Wheeler, Jane; Nissenson, Allen R

2018-05-01

Protein-energy wasting is common in end-stage renal disease patients undergoing dialysis and is strongly associated with mortality and adverse outcomes. Intradialytic oral nutritional supplements (ONS) reduce risk of mortality in these patients. Large studies characterizing the impact of ONS on other outcomes are lacking. We assessed the associations between administration of ONS and clinical and nutritional outcomes. Retrospective evaluation of a pilot program providing ONS to patients at a large dialysis organization in the United States. The pilot program provided ONS to in-center hemodialysis patients with serum albumin ≤3.5 g/dL at 408 facilities. ONS patients were compared to matched controls with serum albumin ≤3.5 g/dL, identified from facilities not participating in the ONS program (n = 3,374 per group). Receipt of ONS. Death, missed dialysis treatments, hospitalizations, serum albumin, normalized protein catabolic rate, and postdialysis body weight were abstracted from large dialysis organization electronic medical records. There was a 69% reduction in deaths (hazard ratio = 0.31; 95% confidence interval = 0.25-0.39), and 33% fewer missed dialysis treatments (incidence rate ratio = 0.77; 95% confidence interval = 0.73-0.82) among ONS patients compared to controls (P < .001 for both). The effects of ONS on nutritional indices were mixed: serum albumin was lower, whereas normalized protein catabolic rate values, a surrogate for dietary protein intake, and postdialysis body weights were higher for ONS patients compared to controls during follow-up. Our evaluation confirmed the beneficial effects of ONS in reducing mortality and improving some indices of nutritional status for hypoalbuminemic hemodialysis patients. We also report the novel finding that ONS can reduce the number of missed dialysis treatments. These results support the use of intradialytic ONS as an effective intervention to improve the outcomes in hemodialysis patients with low serum albumin. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Meta-analysis with missing study-level sample variance data.

PubMed

Chowdhry, Amit K; Dworkin, Robert H; McDermott, Michael P

2016-07-30

We consider a study-level meta-analysis with a normally distributed outcome variable and possibly unequal study-level variances, where the object of inference is the difference in means between a treatment and control group. A common complication in such an analysis is missing sample variances for some studies. A frequently used approach is to impute the weighted (by sample size) mean of the observed variances (mean imputation). Another approach is to include only those studies with variances reported (complete case analysis). Both mean imputation and complete case analysis are only valid under the missing-completely-at-random assumption, and even then the inverse variance weights produced are not necessarily optimal. We propose a multiple imputation method employing gamma meta-regression to impute the missing sample variances. Our method takes advantage of study-level covariates that may be used to provide information about the missing data. Through simulation studies, we show that multiple imputation, when the imputation model is correctly specified, is superior to competing methods in terms of confidence interval coverage probability and type I error probability when testing a specified group difference. Finally, we describe a similar approach to handling missing variances in cross-over studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial

PubMed Central

Mason, Alexina J; Gomes, Manuel; Grieve, Richard; Ulug, Pinar; Powell, Janet T; Carpenter, James

2017-01-01

Background/aims: The analyses of randomised controlled trials with missing data typically assume that, after conditioning on the observed data, the probability of missing data does not depend on the patient’s outcome, and so the data are ‘missing at random’ . This assumption is usually implausible, for example, because patients in relatively poor health may be more likely to drop out. Methodological guidelines recommend that trials require sensitivity analysis, which is best informed by elicited expert opinion, to assess whether conclusions are robust to alternative assumptions about the missing data. A major barrier to implementing these methods in practice is the lack of relevant practical tools for eliciting expert opinion. We develop a new practical tool for eliciting expert opinion and demonstrate its use for randomised controlled trials with missing data. Methods: We develop and illustrate our approach for eliciting expert opinion with the IMPROVE trial (ISRCTN 48334791), an ongoing multi-centre randomised controlled trial which compares an emergency endovascular strategy versus open repair for patients with ruptured abdominal aortic aneurysm. In the IMPROVE trial at 3 months post-randomisation, 21% of surviving patients did not complete health-related quality of life questionnaires (assessed by EQ-5D-3L). We address this problem by developing a web-based tool that provides a practical approach for eliciting expert opinion about quality of life differences between patients with missing versus complete data. We show how this expert opinion can define informative priors within a fully Bayesian framework to perform sensitivity analyses that allow the missing data to depend upon unobserved patient characteristics. Results: A total of 26 experts, of 46 asked to participate, completed the elicitation exercise. The elicited quality of life scores were lower on average for the patients with missing versus complete data, but there was considerable uncertainty in these elicited values. The missing at random analysis found that patients randomised to the emergency endovascular strategy versus open repair had higher average (95% credible interval) quality of life scores of 0.062 (−0.005 to 0.130). Our sensitivity analysis that used the elicited expert information as pooled priors found that the gain in average quality of life for the emergency endovascular strategy versus open repair was 0.076 (−0.054 to 0.198). Conclusion: We provide and exemplify a practical tool for eliciting the expert opinion required by recommended approaches to the sensitivity analyses of randomised controlled trials. We show how this approach allows the trial analysis to fully recognise the uncertainty that arises from making alternative, plausible assumptions about the reasons for missing data. This tool can be widely used in the design, analysis and interpretation of future trials, and to facilitate this, materials are available for download. PMID:28675302

Evidence regarding lingual fixed orthodontic appliances' therapeutic and adverse effects is insufficient.

PubMed

Afrashtehfar, Kelvin I

2016-06-01

Data sourcesMedline, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Cochrane Central Register of Controlled Trials, Virtual Health Library and Web of Science were systematically searched up to July 2015 without limitations. Scopus, Google Scholar, ClinicalTrials.gov, the ISRCTN registry as well as reference lists of the trials included and relevant reviews were manually searched.Study selectionRandomised (RCTs) and prospective non-randomised clinical trials (non-RCTs) on human patients that compared therapeutic and adverse effects of lingual and labial appliances were considered. One reviewer initially screened titles and subsequently two reviewers independently screened the selected abstracts and full texts.Data extraction and synthesisThe data were extracted independently by the reviewers. Missing or unclear information, ongoing trials and raw data from split-mouth trials were requested from the authors of the trials. The quality of the included trials and potential bias across studies were assessed using Cochrane's risk of bias tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. For parallel trials, mean difference (MD) and the relative risk (RR) were used for continuous (objective speech performance, subjective speech performance, intercanine width, intermolar width and sagittal anchorage loss) and binary outcomes (eating difficulty), respectively. The standardised mean difference (SMD) was chosen to pool, after conversion, the outcome (oral discomfort) that assessed both binary and continuous. Random-effects meta-analyses were conducted, followed by subgroup and sensitivity analyses.ResultsThirteen papers pertaining to 11 clinical trials (three parallel RCTs, one split-mouth RCT and seven parallel prospective non-RCTs) were included with a total of 407 (34% male/66% female) patients. All trials had at least one bias domain at high risk of bias. Compared with labial appliances, lingual appliances were associated with increased overall oral discomfort, increased speech impediment (measured using auditory analysis), worse speech performance assessed by laypersons, increased eating difficulty and decreased intermolar width. On the other hand, lingual appliances were associated with increased intercanine width and significantly decreased anchorage loss of the maxillary first molar during space closure. However, the quality of all analyses included was judged as very low because of the high risk of bias of the included trials, inconsistency and imprecision.ConclusionsBased on existing trials there is insufficient evidence to make robust recommendations for lingual fixed orthodontic appliances regarding their therapeutic or adverse effects, as the quality of evidence was low.

Impact of Missing Physiologic Data on Performance of the Simplified Acute Physiology Score 3 Risk-Prediction Model.

PubMed

Engerström, Lars; Nolin, Thomas; Mårdh, Caroline; Sjöberg, Folke; Karlström, Göran; Fredrikson, Mats; Walther, Sten M

2017-12-01

The Simplified Acute Physiology 3 outcome prediction model has a narrow time window for recording physiologic measurements. Our objective was to examine the prevalence and impact of missing physiologic data on the Simplified Acute Physiology 3 model's performance. Retrospective analysis of prospectively collected data. Sixty-three ICUs in the Swedish Intensive Care Registry. Patients admitted during 2011-2014 (n = 107,310). None. Model performance was analyzed using the area under the receiver operating curve, scaled Brier's score, and standardized mortality rate. We used a recalibrated Simplified Acute Physiology 3 model and examined model performance in the original dataset and in a dataset of complete records where missing data were generated (simulated dataset). One or more data were missing in 40.9% of the admissions, more common in survivors and low-risk admissions than in nonsurvivors and high-risk admissions. Discrimination did not decrease with one to two missing variables, but accuracy was highest with no missing data. Calibration was best in the original dataset with a mix of full records and records with some missing values (area under the receiver operating curve was 0.85, scaled Brier 27%, and standardized mortality rate 0.99). With zero, one, and two data missing, the scaled Brier was 31%, 26%, and 21%; area under the receiver operating curve was 0.84, 0.87, and 0.89; and standardized mortality rate was 0.92, 1.05 and 1.10, respectively. Datasets where the missing data were simulated for oxygenation or oxygenation and hydrogen ion concentration together performed worse than datasets with these data originally missing. There is a coupling between missing physiologic data, admission type, low risk, and survival. Increased loss of physiologic data reduced model performance and will deflate mortality risk, resulting in falsely high standardized mortality rates.

On Estimation of the Survivor Average Causal Effect in Observational Studies when Important Confounders are Missing Due to Death

PubMed Central

Egleston, Brian L.; Scharfstein, Daniel O.; MacKenzie, Ellen

2008-01-01

We focus on estimation of the causal effect of treatment on the functional status of individuals at a fixed point in time t* after they have experienced a catastrophic event, from observational data with the following features: (1) treatment is imposed shortly after the event and is non-randomized, (2) individuals who survive to t* are scheduled to be interviewed, (3) there is interview non-response, (4) individuals who die prior to t* are missing information on pre-event confounders, (5) medical records are abstracted on all individuals to obtain information on post-event, pre-treatment confounding factors. To address the issue of survivor bias, we seek to estimate the survivor average causal effect (SACE), the effect of treatment on functional status among the cohort of individuals who would survive to t* regardless of whether or not assigned to treatment. To estimate this effect from observational data, we need to impose untestable assumptions, which depend on the collection of all confounding factors. Since pre-event information is missing on those who die prior to t*, it is unlikely that these data are missing at random (MAR). We introduce a sensitivity analysis methodology to evaluate the robustness of SACE inferences to deviations from the MAR assumption. We apply our methodology to the evaluation of the effect of trauma center care on vitality outcomes using data from the National Study on Costs and Outcomes of Trauma Care. PMID:18759833

Evaluation of missing value methods for predicting ambient BTEX concentrations in two neighbouring cities in Southwestern Ontario Canada

NASA Astrophysics Data System (ADS)

Miller, Lindsay; Xu, Xiaohong; Wheeler, Amanda; Zhang, Tianchu; Hamadani, Mariam; Ejaz, Unam

2018-05-01

High density air monitoring campaigns provide spatial patterns of pollutant concentrations which are integral in exposure assessment. Such analysis can assist with the determination of links between air quality and health outcomes, however, problems due to missing data can threaten to compromise these studies. This research evaluates four methods; mean value imputation, inverse distance weighting (IDW), inter-species ratios, and regression, to address missing spatial concentration data ranging from one missing data point up to 50% missing data. BTEX (benzene, toluene, ethylbenzene, and xylenes) concentrations were measured in Windsor and Sarnia, Ontario in the fall of 2005. Concentrations and inter-species ratios were generally similar between the two cities. Benzene (B) was observed to be higher in Sarnia, whereas toluene (T) and the T/B ratios were higher in Windsor. Using these urban, industrialized cities as case studies, this research demonstrates that using inter-species ratios or regression of the data for which there is complete information, along with one measured concentration (i.e. benzene) to predict for missing concentrations (i.e. TEX) results in good agreement between predicted and measured values. In both cities, the general trend remains that best agreement is observed for the leave-one-out scenario, followed by 10% and 25% missing, and the least agreement for the 50% missing cases. In the absence of any known concentrations IDW can provide reasonable agreement between observed and estimated concentrations for the BTEX species, and was superior over mean value imputation which was not able to preserve the spatial trend. The proposed methods can be used to fill in missing data, while preserving the general characteristics and rank order of the data which are sufficient for epidemiologic studies.

The effect of maternal near miss on adverse infant nutritional outcomes.

PubMed

Zanardi, Dulce M; Moura, Erly C; Santos, Leonor P; Leal, Maria C; Cecatti, Jose G

2016-10-01

To evaluate the association between self-reported maternal near miss and adverse nutritional status in children under one year of age. This study is a secondary analysis of a study in which women who took their children under one year of age to the national vaccine campaign were interviewed. The self-reported condition of maternal near miss used the criteria of Intensive Care Unit admission; eclampsia; blood transfusion and hysterectomy; and their potential associations with any type of nutritional disorder in children, including deficits in weight-for-age, deficits in height-for-age, obesity and breastfeeding. The rates of near miss for the country, regions and states were initially estimated. The relative risks of infant adverse nutritional status according to near miss and maternal/childbirth characteristics were estimated with their 95% CIs using bivariate and multiple analyses. The overall prevalence of near miss was 2.9% and was slightly higher for the Legal Amazon than for other regions. No significant associations were found with nutritional disorders in children. Only a 12% decrease in overall maternal breastfeeding was associated with near miss. Living in the countryside and child over 6 months of age increased the risk of altered nutritional status by approximately 15%, while female child gender decreased this risk by 30%. Maternal near miss was not associated with an increased risk of any alteration in infant nutritional status. There was no association between maternal near miss and altered nutritional status in children up to one year of age. The risk of infant adverse nutritional status was greater in women living in the countryside, for children over 6 months of age and for male gender.

Revised Household-Based Microplanning in Polio Supplemental Immunization Activities in Kano State, Nigeria. 2013-2014.

PubMed

Gali, Emmanuel; Mkanda, Pascal; Banda, Richard; Korir, Charles; Bawa, Samuel; Warigon, Charity; Abdullahi, Suleiman; Abba, Bashir; Isiaka, Ayodeji; Yahualashet, Yared G; Touray, Kebba; Chevez, Ana; Tegegne, Sisay G; Nsubuga, Peter; Etsano, Andrew; Shuaib, Faisal; Vaz, Rui G

2016-05-01

Remarkable progress had been made since the launch of the Global Polio Eradication Initiative in 1988. However endemic wild poliovirus transmission in Nigeria, Pakistan, and Afghanistan remains an issue of international concern. Poor microplanning has been identified as a major contributor to the high numbers of chronically missed children. We assessed the contribution of the revised household-based microplanning process implemented in Kano State from September 2013 to April 2014 to the outcomes of subsequent polio supplemental immunization activities using used preselected planning and outcome indicators. There was a 38% increase in the number of settlements enumerated, a 30% reduction in the number of target households, and a 54% reduction in target children. The reported number of children vaccinated and the doses of oral polio vaccine used during subsequent polio supplemental immunization activities showed a decline. Postvaccination lot quality assurance sampling and chronically missed settlement reports also showed a progressive reduction in the number of children and settlements missed. We observed improvement in Kano State's performance based on the selected postcampaign performance evaluation indicators and reliability of baseline demographic estimates after the revised household-based microplanning exercise. © 2016 World Health Organization; licensee Oxford Journals.

Revised Household-Based Microplanning in Polio Supplemental Immunization Activities in Kano State, Nigeria. 2013–2014

PubMed Central

Gali, Emmanuel; Mkanda, Pascal; Banda, Richard; Korir, Charles; Bawa, Samuel; Warigon, Charity; Abdullahi, Suleiman; Abba, Bashir; Isiaka, Ayodeji; Yahualashet, Yared G.; Touray, Kebba; Chevez, Ana; Tegegne, Sisay G.; Nsubuga, Peter; Etsano, Andrew; Shuaib, Faisal; Vaz, Rui G.

2016-01-01

Background. Remarkable progress had been made since the launch of the Global Polio Eradication Initiative in 1988. However endemic wild poliovirus transmission in Nigeria, Pakistan, and Afghanistan remains an issue of international concern. Poor microplanning has been identified as a major contributor to the high numbers of chronically missed children. Methods. We assessed the contribution of the revised household-based microplanning process implemented in Kano State from September 2013 to April 2014 to the outcomes of subsequent polio supplemental immunization activities using used preselected planning and outcome indicators. Results. There was a 38% increase in the number of settlements enumerated, a 30% reduction in the number of target households, and a 54% reduction in target children. The reported number of children vaccinated and the doses of oral polio vaccine used during subsequent polio supplemental immunization activities showed a decline. Postvaccination lot quality assurance sampling and chronically missed settlement reports also showed a progressive reduction in the number of children and settlements missed. Conclusions. We observed improvement in Kano State's performance based on the selected postcampaign performance evaluation indicators and reliability of baseline demographic estimates after the revised household-based microplanning exercise. PMID:26908755

Formation and Evolution of X-ray Binaries

NASA Astrophysics Data System (ADS)

Shao, Y.

2017-07-01

X-ray binaries are a class of binary systems, in which the accretor is a compact star (i.e., black hole, neutron star, or white dwarf). They are one of the most important objects in the universe, which can be used to study not only binary evolution but also accretion disks and compact stars. Statistical investigations of these binaries help to understand the formation and evolution of galaxies, and sometimes provide useful constraints on the cosmological models. The goal of this thesis is to investigate the formation and evolution processes of X-ray binaries including Be/X-ray binaries, low-mass X-ray binaries (LMXBs), ultraluminous X-ray sources (ULXs), and cataclysmic variables. In Chapter 1 we give a brief review on the basic knowledge of the binary evolution. In Chapter 2 we discuss the formation of Be stars through binary interaction. In this chapter we investigate the formation of Be stars resulting from mass transfer in binaries in the Galaxy. Using binary evolution and population synthesis calculations, we find that in Be/neutron star binaries the Be stars have a lower limit of mass ˜ 8 M⊙ if they are formed by a stable (i.e., without the occurrence of common envelope evolution) and nonconservative mass transfer. We demonstrate that the isolated Be stars may originate from both mergers of two main-sequence stars and disrupted Be binaries during the supernova explosions of the primary stars, but mergers seem to play a much more important role. Finally the fraction of Be stars produced by binary interactions in all B type stars can be as high as ˜ 13%-30% , implying that most of Be stars may result from binary interaction. In Chapter 3 we show the evolution of intermediate- and low-mass X-ray binaries (I/LMXBs) and the formation of millisecond pulsars. Comparing the calculated results with the observations of binary radio pulsars, we report the following results: (1) The allowed parameter space for forming binary pulsars in the initial orbital period-donor mass plane increases with the increasing neutron star mass. This may help to explain why some millisecond pulsars with orbital periods longer than ˜ 60 d seem to have less massive white dwarfs than expected. Alternatively, some of these wide binary pulsars may be formed through mass transfer driven by planet/brown dwarf-involved common envelope evolution; (2) Some of the pulsars in compact binaries might have evolved from intermediate-mass X-ray binaries with an anomalous magnetic braking; (3) The equilibrium spin periods of neutron stars in low-mass X-ray binaries are in general shorter than the observed spin periods of binary pulsars by more than one order of magnitude, suggesting that either the simple equilibrium spin model does not apply, or there are other mechanisms/processes spinning down the neutron stars. In Chapter 4, angular momentum loss mechanisms in the cataclysmic variables below the period gap are presented. By considering several kinds of consequential angular momentum loss mechanisms, we find that neither isotropic wind from the white dwarf nor outflow from the L1 point can explain the extra angular momentum loss rate, while an ouflow from the L2 point or a circumbinary disk can effectively extract the angular momentum provided that ˜ 15%-45% of the transferred mass is lost from the binary. A more promising mechanism is a circumbinary disk exerting a gravitational torque on the binary. In this case the mass loss fraction can be as low as ≲ 10-3. In Chapter 5 we present a study on the population of ultraluminous X-ray sources with an accreting neutron star. Most ULXs are believed to be X-ray binary systems, but previous observational and theoretical studies tend to prefer a black hole rather than a neutron star accretor. The recent discovery of 1.37 s pulsations from the ULX M82 X-2 has established its nature as a magnetized neutron star. In this chapter we model the formation history of neutron star ULXs in an M82- or Milky Way-like galaxy, by use of both binary population synthesis and detailed binary evolution calculations. We find that the birthrate is around 10-4 yr-1 for the incipient X-ray binaries in both cases. We demonstrate the distribution of the ULX population in the donor mass - orbital period plane. Our results suggest that, compared with black hole X-ray binaries, neutron star X-ray binaries may significantly contribute to the ULX population, and high/intermediate-mass X-ray binaries dominate the neutron star ULX population in M82/Milky Way-like galaxies, respectively. In Chapter 6, the population of intermediate- and low-mass X-ray binaries in the Galaxy is explored. We investigate the formation and evolutionary sequences of Galactic intermediate- and low-mass X-ray binaries by combining binary population synthesis (BPS) and detailed stellar evolutionary calculations. Using an updated BPS code we compute the evolution of massive binaries that leads to the formation of incipient I/LMXBs, and present their distribution in the initial donor mass vs. initial orbital period diagram. We then follow the evolution of I/LMXBs until the formation of binary millisecond pulsars (BMSPs). We show that during the evolution of I/LMXBs they are likely to be observed as relatively compact binaries. The resultant BMSPs have orbital periods ranging from about 1 day to a few hundred days. These features are consistent with observations of LMXBs and BMSPs. We also confirm the discrepancies between theoretical predictions and observations mentioned in the literature, that is, the theoretical average mass transfer rates of LMXBs are considerably lower than observed, and the number of BMSPs with orbital periods ˜ 0.1-1 \\unit{d} is severely underestimated. Both imply that something is missing in the modeling of LMXBs, which is likely to be related to the mechanisms of the orbital angular momentum loss. Finally in Chapter 7 we summarize our results and give the prospects for the future work.

Pre-eclampsia, eclampsia and adverse maternal and perinatal outcomes: a secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health.

PubMed

Abalos, E; Cuesta, C; Carroli, G; Qureshi, Z; Widmer, M; Vogel, J P; Souza, J P

2014-03-01

To assess the incidence of hypertensive disorders of pregnancy and related severe complications, identify other associated factors and compare maternal and perinatal outcomes in women with and without these conditions. Secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health (WHOMCS) database. Cross-sectional study implemented at 357 health facilities conducting 1000 or more deliveries annually in 29 countries from Africa, Asia, Latin America and the Middle East. All women suffering from any hypertensive disorder during pregnancy, the intrapartum or early postpartum period in the participating hospitals during the study period. We calculated the proportion of the pre-specified outcomes in the study population and their distribution according to hypertensive disorders' severity. We estimated the association between them and maternal deaths, near-miss cases, and severe maternal complications using a multilevel logit model. Hypertensive disorders of pregnancy. Potentially life-threatening conditions among maternal near-miss cases, maternal deaths and cases without severe maternal outcomes. Overall, 8542 (2.73%) women suffered from hypertensive disorders. Incidences of pre-eclampsia, eclampsia and chronic hypertension were 2.16%, 0.28% and 0.29%, respectively. Maternal near-miss cases were eight times more frequent in women with pre-eclampsia, and increased to up to 60 times more frequent in women with eclampsia, when compared with women without these conditions. The analysis of this large database provides estimates of the global distribution of the incidence of hypertensive disorders of pregnancy. The information on the most frequent complications related to pre-eclampsia and eclampsia could be of interest to inform policies for health systems organisation. © 2014 RCOG The World Health Organization retains copyright and all other rights in the manuscript of this article as submitted for publication.

A unified procedure for meta-analytic evaluation of surrogate end points in randomized clinical trials

PubMed Central

Dai, James Y.; Hughes, James P.

2012-01-01

The meta-analytic approach to evaluating surrogate end points assesses the predictiveness of treatment effect on the surrogate toward treatment effect on the clinical end point based on multiple clinical trials. Definition and estimation of the correlation of treatment effects were developed in linear mixed models and later extended to binary or failure time outcomes on a case-by-case basis. In a general regression setting that covers nonnormal outcomes, we discuss in this paper several metrics that are useful in the meta-analytic evaluation of surrogacy. We propose a unified 3-step procedure to assess these metrics in settings with binary end points, time-to-event outcomes, or repeated measures. First, the joint distribution of estimated treatment effects is ascertained by an estimating equation approach; second, the restricted maximum likelihood method is used to estimate the means and the variance components of the random treatment effects; finally, confidence intervals are constructed by a parametric bootstrap procedure. The proposed method is evaluated by simulations and applications to 2 clinical trials. PMID:22394448

Unbiased All-Optical Random-Number Generator

NASA Astrophysics Data System (ADS)

Steinle, Tobias; Greiner, Johannes N.; Wrachtrup, Jörg; Giessen, Harald; Gerhardt, Ilja

2017-10-01

The generation of random bits is of enormous importance in modern information science. Cryptographic security is based on random numbers which require a physical process for their generation. This is commonly performed by hardware random-number generators. These often exhibit a number of problems, namely experimental bias, memory in the system, and other technical subtleties, which reduce the reliability in the entropy estimation. Further, the generated outcome has to be postprocessed to "iron out" such spurious effects. Here, we present a purely optical randomness generator, based on the bistable output of an optical parametric oscillator. Detector noise plays no role and postprocessing is reduced to a minimum. Upon entering the bistable regime, initially the resulting output phase depends on vacuum fluctuations. Later, the phase is rigidly locked and can be well determined versus a pulse train, which is derived from the pump laser. This delivers an ambiguity-free output, which is reliably detected and associated with a binary outcome. The resulting random bit stream resembles a perfect coin toss and passes all relevant randomness measures. The random nature of the generated binary outcome is furthermore confirmed by an analysis of resulting conditional entropies.

The long term economic impact of severe obstetric complications for women and their children in Burkina Faso.

PubMed

Ilboudo, Patrick G C; Russell, Steve; D'Exelle, Ben

2013-01-01

This study investigates the long term economic impact of severe obstetric complications for women and their children in Burkina Faso, focusing on measures of food security, expenditures and related quality of life measures. It uses a hospital based cohort, first visited in 2004/2005 and followed up four years later. This cohort of 1014 women consisted of two main groups of comparison: 677 women who had an uncomplicated delivery and 337 women who experienced a severe obstetric complication which would have almost certainly caused death had they not received hospital care (labelled a "near miss" event). To analyze the impact of such near miss events as well as the possible interaction with the pregnancy outcome, we compared household and individual level indicators between women without a near miss event and women with a near miss event who either had a live birth, a perinatal death or an early pregnancy loss. We used propensity score matching to remove initial selection bias. Although we found limited effects for the whole group of near miss women, the results indicated negative impacts: a) for near miss women with a live birth, on child development and education, on relatively expensive food consumption and on women's quality of life; b) for near miss women with perinatal death, on relatively expensive foods consumption and children's education and c) for near miss women who had an early pregnancy loss, on overall food security. Our results showed that severe obstetric complications have long lasting consequences for different groups of women and their children and highlighted the need for carefully targeted interventions.

Missing data handling in non-inferiority and equivalence trials: A systematic review.

PubMed

Rabe, Brooke A; Day, Simon; Fiero, Mallorie H; Bell, Melanie L

2018-05-25

Non-inferiority (NI) and equivalence clinical trials test whether a new treatment is therapeutically no worse than, or equivalent to, an existing standard of care. Missing data in clinical trials have been shown to reduce statistical power and potentially bias estimates of effect size; however, in NI and equivalence trials, they present additional issues. For instance, they may decrease sensitivity to differences between treatment groups and bias toward the alternative hypothesis of NI (or equivalence). Our primary aim was to review the extent of and methods for handling missing data (model-based methods, single imputation, multiple imputation, complete case), the analysis sets used (Intention-To-Treat, Per-Protocol, or both), and whether sensitivity analyses were used to explore departures from assumptions about the missing data. We conducted a systematic review of NI and equivalence trials published between May 2015 and April 2016 by searching the PubMed database. Articles were reviewed primarily by 2 reviewers, with 6 articles reviewed by both reviewers to establish consensus. Of 109 selected articles, 93% reported some missing data in the primary outcome. Among those, 50% reported complete case analysis, and 28% reported single imputation approaches for handling missing data. Only 32% reported conducting analyses of both intention-to-treat and per-protocol populations. Only 11% conducted any sensitivity analyses to test assumptions with respect to missing data. Missing data are common in NI and equivalence trials, and they are often handled by methods which may bias estimates and lead to incorrect conclusions. Copyright © 2018 John Wiley & Sons, Ltd.

Airline Safety Improvement Through Experience with Near-Misses: A Cautionary Tale.

PubMed

Madsen, Peter; Dillon, Robin L; Tinsley, Catherine H

2016-05-01

In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near-misses. The processes that create these near-misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near-misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near-misses-those where the possible dangers are salient. Unfortunately, airlines do not improve following near-miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near-misses, we conclude with recommendations for improving airline learning from all near-misses. © 2015 Society for Risk Analysis.

STELLAR: fast and exact local alignments

PubMed Central

2011-01-01

Background Large-scale comparison of genomic sequences requires reliable tools for the search of local alignments. Practical local aligners are in general fast, but heuristic, and hence sometimes miss significant matches. Results We present here the local pairwise aligner STELLAR that has full sensitivity for ε-alignments, i.e. guarantees to report all local alignments of a given minimal length and maximal error rate. The aligner is composed of two steps, filtering and verification. We apply the SWIFT algorithm for lossless filtering, and have developed a new verification strategy that we prove to be exact. Our results on simulated and real genomic data confirm and quantify the conjecture that heuristic tools like BLAST or BLAT miss a large percentage of significant local alignments. Conclusions STELLAR is very practical and fast on very long sequences which makes it a suitable new tool for finding local alignments between genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows, and Mac OS X at http://www.seqan.de/projects/stellar. The source code is freely distributed with the SeqAn C++ library version 1.3 and later at http://www.seqan.de. PMID:22151882

MCR Container Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haas, Nicholas Q; Gillen, Robert E; Karnowski, Thomas P

MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting frommore » them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.« less

Methodological Challenges in the Analysis of MOOC Data for Exploring the Relationship between Discussion Forum Views and Learning Outcomes

ERIC Educational Resources Information Center

Bergner, Yoav; Kerr, Deirdre; Pritchard, David E.

2015-01-01

Determining how learners use MOOCs effectively is critical to providing feedback to instructors, schools, and policy-makers on this highly scalable technology. However, drawing inferences about student learning outcomes in MOOCs has proven to be quite difficult due to large amounts of missing data (of various kinds) and to the diverse population…

Impact of ibrutinib dose adherence on therapeutic efficacy in patients with previously treated CLL/SLL.

PubMed

Barr, Paul M; Brown, Jennifer R; Hillmen, Peter; O'Brien, Susan; Barrientos, Jacqueline C; Reddy, Nishitha M; Coutre, Steven; Mulligan, Stephen P; Jaeger, Ulrich; Furman, Richard R; Cymbalista, Florence; Montillo, Marco; Dearden, Claire; Robak, Tadeusz; Moreno, Carol; Pagel, John M; Burger, Jan A; Suzuki, Samuel; Sukbuntherng, Juthamas; Cole, George; James, Danelle F; Byrd, John C

2017-05-11

Ibrutinib, an oral inhibitor of Bruton's tyrosine kinase (BTK), at a once-daily dose of 420 mg achieved BTK active-site occupancy in patients with chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) that was maintained at 24 hours. It is unknown if intermittent interruption of ibrutinib therapy contributes to altered clinical outcomes. We therefore evaluated the effect of ibrutinib dose adherence on patient outcomes in the phase 3 RESONATE trial. The overall mean dose intensity (DI) was 95% with median treatment duration of ∼9 months. Pharmacokinetic assessment of ibrutinib exposure at 420-mg dose suggested similar exposure regardless of patient weight or age. As assessed by independent review committee, patients with higher DI experienced longer median progression-free survival (PFS) compared with those with lower DI regardless of del17p and/or TP53 status. Of 79 patients requiring a drug hold, treatment was restarted at the original dose in 73 (92%) patients. Mean duration of a missed-dose event was 18.7 days (range, 8-56). Patients missing ≥8 consecutive days of ibrutinib had a shorter median PFS vs those missing <8 days (10.9 months vs not reached). These results support sustained adherence to once-daily ibrutinib dosing at 420 mg as clinically feasible to achieve optimal outcomes in patients with previously treated CLL. The trial was registered at www.clinicaltrials.gov as #NCT01578707. © 2017 by The American Society of Hematology.

No-signaling quantum key distribution: solution by linear programming

NASA Astrophysics Data System (ADS)

Hwang, Won-Young; Bae, Joonwoo; Killoran, Nathan

2015-02-01

We outline a straightforward approach for obtaining a secret key rate using only no-signaling constraints and linear programming. Assuming an individual attack, we consider all possible joint probabilities. Initially, we study only the case where Eve has binary outcomes, and we impose constraints due to the no-signaling principle and given measurement outcomes. Within the remaining space of joint probabilities, by using linear programming, we get bound on the probability of Eve correctly guessing Bob's bit. We then make use of an inequality that relates this guessing probability to the mutual information between Bob and a more general Eve, who is not binary-restricted. Putting our computed bound together with the Csiszár-Körner formula, we obtain a positive key generation rate. The optimal value of this rate agrees with known results, but was calculated in a more straightforward way, offering the potential of generalization to different scenarios.

Two-Part and Related Regression Models for Longitudinal Data

PubMed Central

Farewell, V.T.; Long, D.L.; Tom, B.D.M.; Yiu, S.; Su, L.

2017-01-01

Statistical models that involve a two-part mixture distribution are applicable in a variety of situations. Frequently, the two parts are a model for the binary response variable and a model for the outcome variable that is conditioned on the binary response. Two common examples are zero-inflated or hurdle models for count data and two-part models for semicontinuous data. Recently, there has been particular interest in the use of these models for the analysis of repeated measures of an outcome variable over time. The aim of this review is to consider motivations for the use of such models in this context and to highlight the central issues that arise with their use. We examine two-part models for semicontinuous and zero-heavy count data, and we also consider models for count data with a two-part random effects distribution. PMID:28890906

Brief report: Associations between in-person and electronic bullying victimization and missing school because of safety concerns among U.S. high school students.

PubMed

Steiner, Riley J; Rasberry, Catherine N

2015-08-01

Although associations between bullying and health risk behaviors are well-documented, research on bullying and education-related outcomes, including school attendance, is limited. This study examines associations between bullying victimization (in-person and electronic) and missing school because of safety concerns among a nationally representative sample of U.S. high school students. We used logistic regression analyses to analyze data from the 2013 national Youth Risk Behavior Survey of students in grades 9-12. In-person and electronic victimization were each associated with increased odds of missing school due to safety concerns compared to no bullying victimization. Having been bullied both in-person and electronically was associated with greater odds of missing school compared to electronic bullying only for female students and in-person bullying only for male students. Collaborations between health professionals and educators to prevent bullying may improve school attendance. Published by Elsevier Ltd.

Multivariate longitudinal data analysis with censored and intermittent missing responses.

PubMed

Lin, Tsung-I; Lachos, Victor H; Wang, Wan-Lun

2018-05-08

The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach. Copyright © 2018 John Wiley & Sons, Ltd.

Adverse Outcomes After Hospitalization and Delirium in Persons With Alzheimer Disease

PubMed Central

Fong, Tamara G.; Jones, Richard N.; Marcantonio, Edward R.; Tommet, Douglas; Gross, Alden L.; Habtemariam, Daniel; Schmitt, Eva; Yap, Liang; Inouye, Sharon K.

2012-01-01

Background Hospitalization, frequently complicated by delirium, can be a life-changing event for patients with Alzheimer disease (AD). Objective To determine risks for institutionalization, cognitive decline, or death associated with hospitalization and delirium in patients with AD. Design Prospective cohort enrolled between 1991 and 2006 into the Massachusetts Alzheimer’s Disease Research Center (MADRC) patient registry. Setting Community-based. Participants 771 persons aged 65 years or older with a clinical diagnosis of AD. Measurements Hospitalization, delirium, death, and institutionalization were identified through administrative databases. Cognitive decline was defined as a decrease of 4 or more points on the Blessed Information-Memory-Concentration test score. Multivariate analysis was used to calculate adjusted relative risks (RRs). Results Of 771 participants with AD, 367 (48%) were hospitalized and 194 (25%) developed delirium. Hospitalized patients who did not have delirium had an increased risk for death (adjusted RR, 4.7 [95% CI, 1.9 to 11.6]) and institutionalization (adjusted RR, 6.9 [CI, 4.0 to 11.7]). With delirium, risk for death (adjusted RR, 5.4 [CI, 2.3 to 12.5]) and institutionalization (adjusted RR, 9.3 [CI, 5.5 to 15.7]) increased further. With hospitalization and delirium, the adjusted RR for cognitive decline for patients with AD was 1.6 (CI, 1.2 to 2.3). Among hospitalized patients with AD, 21% of the incidences of cognitive decline, 15% of institutionalization, and 6% of deaths were associated with delirium. Limitations Cognitive outcome was missing in 291 patients. Sensitivity analysis was performed to test the effect of missing data, and a composite outcome was used to decrease the effect of missing data. Conclusion Approximately 1 in 8 hospitalized patients with AD who develop delirium will have at least 1 adverse outcome, including death, institutionalization, or cognitive decline, associated with delirium. Delirium prevention may represent an important strategy for reducing adverse outcomes in this population. Primary Funding Source National Institute on Aging and the MADRC. PMID:22711077

The Relationship between Case-Volume, Care Quality, and Outcomes of Complex Cancer Surgery

PubMed Central

Auerbach, Andrew D; Maselli, Judith; Carter, Jonathan; Pekow, Penelope S; Lindenauer, Peter K

2010-01-01

Background How case volume and quality of care relate to each other and to results of complex cancer surgery is not well understood. Study Design Observational cohort of 14,170 patients 18 or older who underwent pneumonectomy, esophagectomy, pancreatectomy, or pelvic surgery for cancer between 10/1/2003 and 9/1/2005 at a United States hospital participating in a large benchmarking database. Case volumes were estimated within our dataset. Quality was measured by determining whether ideal patients did not receive appropriate perioperative medications (such as antibiotics to prevent surgical site infections) both as individual ‘missed’ measures, as well as the overall number missed. We used hierarchical models to estimate effects of volume and quality on 30-day readmission, in-hospital mortality, length of stay, and costs. Results After adjustment, we noted no consistent associations between higher hospital or surgeon volume and mortality, readmission, length of stay, or costs. Adherence to individual measures was not consistently associated with improvement in readmission, mortality, or other outcomes. For example, continuing antimicrobials past 24 hours was associated with longer length of stay (21.5% higher, 95% CI 19.5% to 23.6%) and higher costs (17% higher, 95% CI 16% to 19%). In contrast, overall adherence, while not not associated with differences in mortality or readmission, was consistently associated with longer length of stay (7.4% longer with one missed measure and 16.4% longer with 2 or more) and higher costs (5% higher with one missed measure, and 11% higher with 2 or more). Conclusions While hospital and surgeon volume were not associated with outcomes, lower overall adherence to quality measures is associated with higher costs, but not improved outcomes. This finding may provide a rationale for improving care systems by maximizing care consistency, even if outcomes are not affected. PMID:20829079

True ternary fission, the collinear cluster tripartition (CCT) of {sup 252}Cf

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oertzen, W. von; Pyatkov, Y. V.; Kamanin, D.

2012-10-20

In systematic work over the last decade (see Pyatkov et al. [12] and refs therein), the ternary fission decay of heavy nuclei, in {sup 235}U(n,fff) and {sup 252}Cf(sf) has been studied in a collinear geometry. The name used for this process is (CCT), with three fragments of similar size in a collinear decay, it is the true ternary fission. This decay has been observed in spontaneous fission as well as in a neutron induced reaction. The measurements are based on different experimental set-ups, with binary coincidences containing TOF and energy determinations. With two detector telescopes placed at 180 Degree-Sign ,more » the measurements of masses and energies of each of the registered two fragments, give complete kinematic solutions. Thus the missing mass events in binary coincidences can be determined, these events are obtained by blocking one of the lighter fragments on a structure in front of the detectors. The relatively high yield of CCT (more than 10{sup -3} per binary fission) is explained. It is due to the favourable Q-values (more positive than for binary) and the large phase space of the ternary CCT-decay, dominated by three (magic) clusters: e.g. isotopes of Sn, Ca and Ni, {sup 132}Sn+{sup 50}Ca+{sup 70}Ni. It is shown that the collinear (prolate) geometry has the favoured potential energy relative to the oblate shapes. The ternary fission is considered to be a sequential process. With this assumption the kinetic energies of the fragments have been calculated by Vijay et al.. The third fragments have very low kinetic energies (below 20 MeV) and have thus escaped their detection in previous work on 'ternary fission', where in addition an oblate shape and a triangle for the momentum vectors have been assumed.« less

Incomplete Data in Smart Grid: Treatment of Values in Electric Vehicle Charging Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Majipour, Mostafa; Chu, Peter; Gadh, Rajit

2014-11-03

In this paper, five imputation methods namely Constant (zero), Mean, Median, Maximum Likelihood, and Multiple Imputation methods have been applied to compensate for missing values in Electric Vehicle (EV) charging data. The outcome of each of these methods have been used as the input to a prediction algorithm to forecast the EV load in the next 24 hours at each individual outlet. The data is real world data at the outlet level from the UCLA campus parking lots. Given the sparsity of the data, both Median and Constant (=zero) imputations improved the prediction results. Since in most missing value casesmore » in our database, all values of that instance are missing, the multivariate imputation methods did not improve the results significantly compared to univariate approaches.« less

Instrumental Variable Methods for Continuous Outcomes That Accommodate Nonignorable Missing Baseline Values.

PubMed

Ertefaie, Ashkan; Flory, James H; Hennessy, Sean; Small, Dylan S

2017-06-15

Instrumental variable (IV) methods provide unbiased treatment effect estimation in the presence of unmeasured confounders under certain assumptions. To provide valid estimates of treatment effect, treatment effect confounders that are associated with the IV (IV-confounders) must be included in the analysis, and not including observations with missing values may lead to bias. Missing covariate data are particularly problematic when the probability that a value is missing is related to the value itself, which is known as nonignorable missingness. In such cases, imputation-based methods are biased. Using health-care provider preference as an IV method, we propose a 2-step procedure with which to estimate a valid treatment effect in the presence of baseline variables with nonignorable missing values. First, the provider preference IV value is estimated by performing a complete-case analysis using a random-effects model that includes IV-confounders. Second, the treatment effect is estimated using a 2-stage least squares IV approach that excludes IV-confounders with missing values. Simulation results are presented, and the method is applied to an analysis comparing the effects of sulfonylureas versus metformin on body mass index, where the variables baseline body mass index and glycosylated hemoglobin have missing values. Our result supports the association of sulfonylureas with weight gain. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Compressibility of binary powder formulations: investigation and evaluation with compaction equations.

PubMed

Gentis, Nicolaos D; Betz, Gabriele

2012-02-01

The purpose of this work was to investigate and evaluate the powder compressibility of binary mixtures containing a well-compressible compound (microcrystalline cellulose) and a brittle active drug (paracetamol and mefenamic acid) and its progression after a drug load increase. Drug concentration range was 0%-100% (m/m) with 10% intervals. The powder formulations were compacted to several relative densities with the Zwick material tester. The compaction force and tensile strength were fitted to several mathematical models that give representative factors for the powder compressibility. The factors k and C (Heckel and modified Heckel equation) showed mostly a nonlinear correlation with increasing drug load. The biggest drop in both factors occurred at far regions and drug load ranges. This outcome is crucial because in binary mixtures the drug load regions with higher changeover of plotted factors could be a hint for an existing percolation threshold. The susceptibility value (Leuenberger equation) showed varying values for each formulation without the expected trend of decrease for higher drug loads. The outcomes of this study showed the main challenges for good formulation design. Thus, we conclude that such mathematical plots are mandatory for a scientific evaluation and prediction of the powder compaction process. Copyright © 2011 Wiley Periodicals, Inc.

Polynomial algorithms for the Maximal Pairing Problem: efficient phylogenetic targeting on arbitrary trees

PubMed Central

2010-01-01

Background The Maximal Pairing Problem (MPP) is the prototype of a class of combinatorial optimization problems that are of considerable interest in bioinformatics: Given an arbitrary phylogenetic tree T and weights ωxy for the paths between any two pairs of leaves (x, y), what is the collection of edge-disjoint paths between pairs of leaves that maximizes the total weight? Special cases of the MPP for binary trees and equal weights have been described previously; algorithms to solve the general MPP are still missing, however. Results We describe a relatively simple dynamic programming algorithm for the special case of binary trees. We then show that the general case of multifurcating trees can be treated by interleaving solutions to certain auxiliary Maximum Weighted Matching problems with an extension of this dynamic programming approach, resulting in an overall polynomial-time solution of complexity (n4 log n) w.r.t. the number n of leaves. The source code of a C implementation can be obtained under the GNU Public License from http://www.bioinf.uni-leipzig.de/Software/Targeting. For binary trees, we furthermore discuss several constrained variants of the MPP as well as a partition function approach to the probabilistic version of the MPP. Conclusions The algorithms introduced here make it possible to solve the MPP also for large trees with high-degree vertices. This has practical relevance in the field of comparative phylogenetics and, for example, in the context of phylogenetic targeting, i.e., data collection with resource limitations. PMID:20525185

Lighthouse in the dust: infrared echoes of periodic emission from massive black hole binaries★

NASA Astrophysics Data System (ADS)

D'Orazio, Daniel J.; Haiman, Zoltán

2017-09-01

The optical and UV emission from sub-parsec massive black hole binaries (MBHBs) in active galactic nuclei (AGNs) is believed to vary periodically, on time-scales comparable to the binary's orbital time. If driven by accretion rate fluctuations, the variability could be isotropic. If dominated by relativistic Doppler modulation, the variability should instead be anisotropic, resembling a rotating forward-beamed lighthouse. We consider the infrared (IR) reverberation of either type of periodic emission by pc-scale circumbinary dust tori. We predict the phase and amplitude of IR variability as a function of the ratio of dust light crossing time to the source variability period, and of the torus inclination and opening angle. We enumerate several differences between the isotropic and anisotropic cases. Interestingly, for a nearly face-on binary with an inclined dust torus, the Doppler boost can produce IR variability without any observable optical/UV variability. Such orphan-IR variability would have been missed in optical searches for periodic AGNs. We apply our models to time-domain WISE IR data from the MBHB candidate PG 1302-102 and find consistency with dust reverberation by both isotropically emitting and Doppler-boosted sources in the shorter wavelength W1-W2 (2.8 → 5.3 μm) bands. We constrain the dust torus to be thin (aspect ratio ˜ 0.1), with an inner radius at 1-5 pc. More generally, our dust-echo models will aid in identifying new MBHB candidates, determining their nature and constraining the physical properties of MBHBs and their dust tori.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

Stratified exact tests for the weak causal null hypothesis in randomized trials with a binary outcome.

PubMed

Chiba, Yasutaka

2017-09-01

Fisher's exact test is commonly used to compare two groups when the outcome is binary in randomized trials. In the context of causal inference, this test explores the sharp causal null hypothesis (i.e. the causal effect of treatment is the same for all subjects), but not the weak causal null hypothesis (i.e. the causal risks are the same in the two groups). Therefore, in general, rejection of the null hypothesis by Fisher's exact test does not mean that the causal risk difference is not zero. Recently, Chiba (Journal of Biometrics and Biostatistics 2015; 6: 244) developed a new exact test for the weak causal null hypothesis when the outcome is binary in randomized trials; the new test is not based on any large sample theory and does not require any assumption. In this paper, we extend the new test; we create a version of the test applicable to a stratified analysis. The stratified exact test that we propose is general in nature and can be used in several approaches toward the estimation of treatment effects after adjusting for stratification factors. The stratified Fisher's exact test of Jung (Biometrical Journal 2014; 56: 129-140) tests the sharp causal null hypothesis. This test applies a crude estimator of the treatment effect and can be regarded as a special case of our proposed exact test. Our proposed stratified exact test can be straightforwardly extended to analysis of noninferiority trials and to construct the associated confidence interval. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Workplace discrimination and missing limbs: the national EEOC ADA research project.

PubMed

West, Steven L; McMahon, Brian T; Monasterio, Eugenio; Belongia, Lisa; Kramer, Kelley

2005-01-01

Using the Integrated Mission System of the Equal Employment Opportunity Commission, the employment discrimination experience of Americans with missing limbs is documented. Researchers compare and contrast the key dimensions of workplace discrimination involving Americans with missing limbs and persons with back and other non-paralytic orthopedic impairments. Specifically, the researchers examine demographic characteristics of the charging parties; the industry designation, location, and size of employers against whom complaints are filed; the nature of discrimination (i.e., type of adverse action) alleged to occur; and the legal outcome or resolution of these complaints. Findings indicate that persons with missing limbs were more likely to encounter discrimination if they were male, under 20 or over 65 years of age, and White or Native American. They were also more likely to encounter more frequent discrimination when they worked for employers in the Southern United States, those with 200 or fewer employers, or whose industry designation involved manufacturing, construction, or transportation. Finally, the nature of job discrimination experienced by Americans with missing limbs is more likely to involve hiring, promotion, or job training than other issues. Implications for policy and advocacy are addressed.

New model helps find missing link between financial and clinical health care management.

PubMed

Dasso, E; Wilson, T

2001-01-01

U.S. health care is missing a link between the financial managers and clinical health managers of defined patient populations. Utilization and cost management try to bridge the gap by focusing on restricted access to care or tightly managed provider reimbursement to control costs. But frequently, they do not take clinical outcomes or health status into consideration. Take a look at another method based on the science of epidemiology that brings a more balanced knowledge of the clinical world to financial managers and more financial insight to clinicians.

Characteristics of patients with missing information on stage: a population-based study of patients diagnosed with colon, lung or breast cancer in England in 2013.

PubMed

Di Girolamo, Chiara; Walters, Sarah; Benitez Majano, Sara; Rachet, Bernard; Coleman, Michel P; Njagi, Edmund Njeru; Morris, Melanie

2018-05-02

Stage is a key predictor of cancer survival. Complete cancer staging is vital for understanding outcomes at population level and monitoring the efficacy of early diagnosis initiatives. Cancer registries usually collect details of the disease extent but staging information may be missing because a stage was never assigned to a patient or because it was not included in cancer registration records. Missing stage information introduce methodological difficulties for analysis and interpretation of results. We describe the associations between missing stage and socio-demographic and clinical characteristics of patients diagnosed with colon, lung or breast cancer in England in 2013. We assess how these associations change when completeness is high, and administrative issues are assumed to be minimal. We estimate the amount of avoidable missing stage data if high levels of completeness reached by some Clinical Commissioning Groups (CCGs), were achieved nationally. Individual cancer records were retrieved from the National Cancer Registration and linked to the Routes to Diagnosis and Hospital Episode Statistics datasets to obtain additional clinical information. We used multivariable beta binomial regression models to estimate the strength of the association between socio-demographic and clinical characteristics of patients and missing stage and to derive the amount of avoidable missing stage. Multivariable modelling showed that old age was associated with missing stage irrespective of the cancer site and independent of comorbidity score, short-term mortality and patient characteristics. This remained true for patients in the CCGs with high completeness. Applying the results from these CCGs to the whole cohort showed that approximately 70% of missing stage information was potentially avoidable. Missing stage was more frequent in older patients, including those residing in CCGs with high completeness. This disadvantage for older patients was not explained fully by the presence of comorbidity. A substantial gain in completeness could have been achieved if administrative practices were improved to the level of the highest performing areas. Reasons for missing stage information should be carefully assessed before any study, and potential distortions introduced by how missing stage is handled should be considered in order to draw the most correct inference from available statistics.

Obstetric near-miss and maternal mortality in maternity university hospital, Damascus, Syria: a retrospective study

PubMed Central

2010-01-01

Background Investigating severe maternal morbidity (near-miss) is a newly recognised tool that identifies women at highest risk of maternal death and helps allocate resources especially in low income countries. This study aims to i. document the frequency and nature of maternal near-miss at hospital level in Damascus, Capital of Syria, ii. evaluate the level of care at maternal life-saving emergency services by comparatively analysing near-misses and maternal mortalities. Methods Retrospective facility-based review of cases of near-miss and maternal mortality that took place in the years 2006-2007 at Damascus Maternity University Hospital, Syria. Near-miss cases were defined based on disease-specific criteria (Filippi 2005) including: haemorrhage, hypertensive disorders in pregnancy, dystocia, infection and anaemia. Main outcomes included maternal mortality ratio (MMR), maternal near miss ratio (MNMR), mortality indices and proportion of near-miss cases and mortality cases to hospital admissions. Results There were 28 025 deliveries, 15 maternal deaths and 901 near-miss cases. The study showed a MNMR of 32.9/1000 live births, a MMR of 54.8/100 000 live births and a relatively low mortality index of 1.7%. Hypertensive disorders (52%) and haemorrhage (34%) were the top causes of near-misses. Late pregnancy haemorrhage was the leading cause of maternal mortality (60%) while sepsis had the highest mortality index (7.4%). Most cases (93%) were referred in critical conditions from other facilities; namely traditional birth attendants homes (67%), primary (5%) and secondary (10%) healthcare unites and private practices (11%). 26% of near-miss cases were admitted to Intensive Care Unit (ICU). Conclusion Near-miss analyses provide valuable information on obstetric care. The study highlights the need to improve antenatal care which would help early identification of high risk pregnancies. It also emphasises the importance of both: developing protocols to prevent/manage post-partum haemorrhage and training health care professionals to manage infrequent but fatal conditions like sepsis. An urgent review of the referral system and the emergency obstetric care in Syria is highly recommended. PMID:20959012

A randomised tandem colonoscopy trial of narrow band imaging versus white light examination to compare neoplasia miss rates.

PubMed

Kaltenbach, T; Friedland, S; Soetikno, R

2008-10-01

Colonoscopy, the "gold standard" screening test for colorectal cancer (CRC), has known diagnostic limitations. Advances in endoscope technology have focused on improving mucosal visualisation. In addition to increased angle of view and resolution features, recent colonoscopes have non-white-light optics, such as narrow band imaging (NBI), to enhance image contrast. We aimed to study the neoplasia diagnostic characteristics of NBI, by comparing the neoplasm miss rate when the colonoscopy was performed under NBI versus white light (WL). Randomised controlled trial. US Veterans hospital. Elective colonoscopy adults. We randomly assigned patients to undergo a colonoscopic examination using NBI or WL. All patients underwent a second examination using WL, as the reference standard. The primary end point was the difference in the neoplasm miss rate, and secondary outcome was the neoplasm detection rate. In 276 tandem colonoscopy patients, there was no significant difference of miss or detection rates between NBI or WL colonoscopy techniques. Of the 135 patients in the NBI group, 17 patients (12.6%; 95% confidence interval (CI) 7.5 to 19.4%) had a missed neoplasm, as compared with 17 of the 141 patients (12.1%; 95% CI 7.2 to 18.6%) in the WL group, with a miss rate risk difference of 0.5% (95% CI -7.2 to 8.3). 130 patients (47%) had at least one neoplasm. Missed lesions with NBI showed similar characteristics to those missed with WL. All missed neoplasms were tubular adenomas, the majority (78%) was < or = 5 mm and none were larger than 1 cm (one-sided 95% CI up to 1%). Nonpolypoid lesions represented 35% (13/37) of missed neoplasms. NBI did not improve the colorectal neoplasm miss rate compared to WL; the miss rate for advanced adenomas was less than 1% and for all adenomas was 12%. The neoplasm detection rates were similar high using NBI or WL; almost a half the study patients had at least one adenoma. Clinicaltrials.gov identifier: NCT00628147.

How to deal with missing longitudinal data in cost of illness analysis in Alzheimer's disease-suggestions from the GERAS observational study.

PubMed

Belger, Mark; Haro, Josep Maria; Reed, Catherine; Happich, Michael; Kahle-Wrobleski, Kristin; Argimon, Josep Maria; Bruno, Giuseppe; Dodel, Richard; Jones, Roy W; Vellas, Bruno; Wimo, Anders

2016-07-18

Missing data are a common problem in prospective studies with a long follow-up, and the volume, pattern and reasons for missing data may be relevant when estimating the cost of illness. We aimed to evaluate the effects of different methods for dealing with missing longitudinal cost data and for costing caregiver time on total societal costs in Alzheimer's disease (AD). GERAS is an 18-month observational study of costs associated with AD. Total societal costs included patient health and social care costs, and caregiver health and informal care costs. Missing data were classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Simulation datasets were generated from baseline data with 10-40 % missing total cost data for each missing data mechanism. Datasets were also simulated to reflect the missing cost data pattern at 18 months using MAR and MNAR assumptions. Naïve and multiple imputation (MI) methods were applied to each dataset and results compared with complete GERAS 18-month cost data. Opportunity and replacement cost approaches were used for caregiver time, which was costed with and without supervision included and with time for working caregivers only being costed. Total costs were available for 99.4 % of 1497 patients at baseline. For MCAR datasets, naïve methods performed as well as MI methods. For MAR, MI methods performed better than naïve methods. All imputation approaches were poor for MNAR data. For all approaches, percentage bias increased with missing data volume. For datasets reflecting 18-month patterns, a combination of imputation methods provided more accurate cost estimates (e.g. bias: -1 % vs -6 % for single MI method), although different approaches to costing caregiver time had a greater impact on estimated costs (29-43 % increase over base case estimate). Methods used to impute missing cost data in AD will impact on accuracy of cost estimates although varying approaches to costing informal caregiver time has the greatest impact on total costs. Tailoring imputation methods to the reason for missing data will further our understanding of the best analytical approach for studies involving cost outcomes.

Getting patients in the door: medical appointment reminder preferences

PubMed Central

Crutchfield, Trisha M; Kistler, Christine E

2017-01-01

Purpose Between 23% and 34% of outpatient appointments are missed annually. Patients who frequently miss medical appointments have poorer health outcomes and are less likely to use preventive health care services. Missed appointments result in unnecessary costs and organizational inefficiencies. Appointment reminders may help reduce missed appointments; particular types may be more effective than other types. We used a survey with a discrete choice experiment (DCE) to learn why individuals miss appointments and to assess appointment reminder preferences. Methods We enrolled a national sample of adults from an online survey panel to complete demographic and appointment habit questions as well as a 16-task DCE designed in Sawtooth Software’s Discover tool. We assessed preferences for four reminder attributes – initial reminder type, arrival of initial reminder, reminder content, and number of reminders. We derived utilities and importance scores. Results We surveyed 251 adults nationally, with a mean age of 43 (range 18–83) years: 51% female, 84% White, and 8% African American. Twenty-three percent of individuals missed one or more appointments in the past 12 months. Two primary reasons given for missing an appointment include transportation problems (28%) and forgetfulness (26%). Participants indicated the initial reminder type (21%) was the most important attribute, followed by the number of reminders (10%). Overall, individuals indicated a preference for a single reminder, arriving via email, phone call, or text message, delivered less than 2 weeks prior to an appointment. Preferences for reminder content were less clear. Conclusion The number of missed appointments and reasons for missing appointments are consistent with prior research. Patient-centered appointment reminders may improve appointment attendance by addressing some of the reasons individuals report missing appointments and by meeting patients’ needs. Future research is necessary to determine if preferred reminders used in practice will result in improved appointment attendance in clinical settings. PMID:28182131

Multiple imputation to deal with missing EQ-5D-3L data: Should we impute individual domains or the actual index?

PubMed

Simons, Claire L; Rivero-Arias, Oliver; Yu, Ly-Mee; Simon, Judit

2015-04-01

Missing data are a well-known and widely documented problem in cost-effectiveness analyses alongside clinical trials using individual patient-level data. Current methodological research recommends multiple imputation (MI) to deal with missing health outcome data, but there is little guidance on whether MI for multi-attribute questionnaires, such as the EQ-5D-3L, should be carried out at domain or at summary score level. In this paper, we evaluated the impact of imputing individual domains versus imputing index values to deal with missing EQ-5D-3L data using a simulation study and developed recommendations for future practice. We simulated missing data in a patient-level dataset with complete EQ-5D-3L data at one point in time from a large multinational clinical trial (n = 1,814). Different proportions of missing data were generated using a missing at random (MAR) mechanism and three different scenarios were studied. The performance of using each method was evaluated using root mean squared error and mean absolute error of the actual versus predicted EQ-5D-3L indices. In large sample sizes (n > 500) and a missing data pattern that follows mainly unit non-response, imputing domains or the index produced similar results. However, domain imputation became more accurate than index imputation with pattern of missingness following an item non-response. For smaller sample sizes (n < 100), index imputation was more accurate. When MI models were misspecified, both domain and index imputations were inaccurate for any proportion of missing data. The decision between imputing the domains or the EQ-5D-3L index scores depends on the observed missing data pattern and the sample size available for analysis. Analysts conducting this type of exercises should also evaluate the sensitivity of the analysis to the MAR assumption and whether the imputation model is correctly specified.

Social and Emotional Wellbeing Screening for Aboriginal and Torres Strait Islanders within Primary Health Care: A Series of Missed Opportunities?

PubMed

Langham, Erika; McCalman, Janya; Matthews, Veronica; Bainbridge, Roxanne Gwendalyn; Nattabi, Barbara; Kinchin, Irina; Bailie, Ross

2017-01-01

Social and emotional wellbeing (SEWB) is a critical determinant of health outcomes for Indigenous Australians. This study examined the extent to which primary healthcare services (PHSs) undertake SEWB screening and management of Aboriginal and Torres Strait Islander clients, and the variation in SEWB screening and management across Indigenous PHS. Cross-sectional analysis between 2012 and 2014 of 3,407 Indigenous client records from a non-representative sample of 100 PHSs in 4 Australian states/territory was undertaken to examine variation in the documentation of: (1) SEWB screening using identified measurement instruments, (2) concern regarding SEWB, (3) actions in response to concern, and (4) follow up actions. Binary logistic regression was used to determine the factors associated with screening. The largest variation in SEWB screening occurred at the state/territory level. The mean rate of screening across the sample was 26.6%, ranging from 13.7 to 37.1%. Variation was also related to PHS characteristics. A mean prevalence of identified SEWB concern was 13% across the sample, ranging from 9 to 45.1%. For the clients where SEWB concern was noted, 25.4% had no referral or PHS action recorded. Subsequent internal PHS follow up after 1 month occurred in 54.7% of cases; and six-monthly follow up of referrals to external services occurred in 50.9% of cases. Our findings suggest that the lack of a clear model or set of guidelines on best practice for screening for SEWB in Indigenous health may contribute to the wide variation in SEWB service provision. The results tell a story of missed opportunities: 73.4% of clients were not screened and no further action was taken for 25.4% for whom an SEWB concern was identified. There was no follow up for just under half of those for whom action was taken. There is a need for the development of national best practice guidelines for SEWB screening and management, accompanied by dedicated SEWB funding, and training for health service providers as well as ongoing monitoring of adherence with the guidelines. Further research on barriers to screening and follow up actions is also warranted.

Logits and Tigers and Bears, Oh My! A Brief Look at the Simple Math of Logistic Regression and How It Can Improve Dissemination of Results

ERIC Educational Resources Information Center

Osborne, Jason W.

2012-01-01

Logistic regression is slowly gaining acceptance in the social sciences, and fills an important niche in the researcher's toolkit: being able to predict important outcomes that are not continuous in nature. While OLS regression is a valuable tool, it cannot routinely be used to predict outcomes that are binary or categorical in nature. These…

Modification of the Sandwich Estimator in Generalized Estimating Equations with Correlated Binary Outcomes in Rare Event and Small Sample Settings

PubMed Central

Rogers, Paul; Stoner, Julie

2016-01-01

Regression models for correlated binary outcomes are commonly fit using a Generalized Estimating Equations (GEE) methodology. GEE uses the Liang and Zeger sandwich estimator to produce unbiased standard error estimators for regression coefficients in large sample settings even when the covariance structure is misspecified. The sandwich estimator performs optimally in balanced designs when the number of participants is large, and there are few repeated measurements. The sandwich estimator is not without drawbacks; its asymptotic properties do not hold in small sample settings. In these situations, the sandwich estimator is biased downwards, underestimating the variances. In this project, a modified form for the sandwich estimator is proposed to correct this deficiency. The performance of this new sandwich estimator is compared to the traditional Liang and Zeger estimator as well as alternative forms proposed by Morel, Pan and Mancl and DeRouen. The performance of each estimator was assessed with 95% coverage probabilities for the regression coefficient estimators using simulated data under various combinations of sample sizes and outcome prevalence values with an Independence (IND), Autoregressive (AR) and Compound Symmetry (CS) correlation structure. This research is motivated by investigations involving rare-event outcomes in aviation data. PMID:26998504

Chandra Studies of Unidentified X-ray Sources in the Galactic Bulge

NASA Astrophysics Data System (ADS)

Mori, Hideyuki

2013-09-01

We propose to study a complete X-ray sample in the luminosity range of > 10^34 erg s^-1 in the Galactic bulge, including 5 unidentified sources detected in the ROSAT All Sky Survey. Our goal is to obtain a clear picture about X-ray populations in the bulge, by utilizing the excellent Chandra position accuracy leading to unique optical identification together with the X-ray spectral properties. This is a new step toward understanding the formation history of the bulge. Furthermore, because the luminosity range we observe corresponds to a ``missing link'' region ever studied for a neutron star or blackhole X-ray binary, our results are also unique to test accretion disk theories at intermediate mass accretion rates.

Structural and spectral studies of sunspots. [umbral core modelling

NASA Technical Reports Server (NTRS)

Wyller, A. A.

1974-01-01

Observations of umbral cores, both by multicolor photometry and by narrow band photometry in the vicinity of the sodium D lines, are described, and evidence is given which supports the validity of many umbral models, each of which describes different aspects of the observed umbral cores. Theoretical studies carried on at the observatory include the following: (1) Zeeman profiles of the sodium D sub 2 line and other lines; (2) turbulent heat conduction, sound waves, and the missing flux in sunspots; (3) chromospheric heating above spots by Alfven waves; (4) magnetic convection in the sun and solar neutrinos; (5) models of starspots on flare stars; (5) starspots on the primaries of contact binary systems; and (6) implications of starspots on red dwarfs.

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review.

PubMed

Weir, Christopher J; Butcher, Isabella; Assi, Valentina; Lewis, Stephanie C; Murray, Gordon D; Langhorne, Peter; Brady, Marian C

2018-03-07

Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.

Close Binaries in the Orion Nebula Cluster: On the Universality of Stellar Multiplicity and the Origin of Field Stars

NASA Astrophysics Data System (ADS)

Duchene, Gaspard; Lacour, Sylvestre; Moraux, Estelle; Bouvier, Jerome; Goodwin, Simon

2018-01-01

While stellar multiplicity is an ubiquitous outcome of star formation, there is a clear dichotomy between the multiplicity properties of young (~1 Myr-old) stellar clusters, like the ONC, which host a mostly field-like population of visual binaries, and those of equally young sparse populations, like the Taurus-Auriga region, which host twice as many stellar companions. Two distinct scenarios can account for this observation: one in which different star-forming regions form different number of stars, and one in which multiplicity properties are universal at birth but where internal cluster dynamics destroy many wide binaries. To solve this ambiguity, one must probe binaries that are sufficiently close so as not to be destroyed through interactions with other cluster members. To this end, we have conducted a survey for 10-100 au binaries in the ONC using the aperture masking technique with the VLT adaptive optics system. Among our sample of the 42 ONC members, we discovered 13 companions in this range of projected separations. This is consistent with the companion frequency observed in the Taurus population and twice as high as that observed among field stars. This survey thus strongly supports the idea that stellar multiplicity is characterized by near-universal initial properties that can later be dynamically altered. On the other hand, this exacerbates the question of the origin of field stars, since only clusters much denser than the ONC can effectively destroyed binaries closer than 100 au.

Estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers.

PubMed

Li, Shanshan; Ning, Yang

2015-09-01

Covariate-specific time-dependent ROC curves are often used to evaluate the diagnostic accuracy of a biomarker with time-to-event outcomes, when certain covariates have an impact on the test accuracy. In many medical studies, measurements of biomarkers are subject to missingness due to high cost or limitation of technology. This article considers estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers. To incorporate the covariate effect, we assume a proportional hazards model for the failure time given the biomarker and the covariates, and a semiparametric location model for the biomarker given the covariates. In the presence of missing biomarkers, we propose a simple weighted estimator for the ROC curves where the weights are inversely proportional to the selection probability. We also propose an augmented weighted estimator which utilizes information from the subjects with missing biomarkers. The augmented weighted estimator enjoys the double-robustness property in the sense that the estimator remains consistent if either the missing data process or the conditional distribution of the missing data given the observed data is correctly specified. We derive the large sample properties of the proposed estimators and evaluate their finite sample performance using numerical studies. The proposed approaches are illustrated using the US Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. © 2015, The International Biometric Society.

Multiple Chronic Conditions and Labor Force Outcomes: A Population Study of U.S. Adults

PubMed Central

Ward, Brian W.

2015-01-01

Background Although 1-in-5 adults have multiple (≥2) chronic conditions, limited attention has been given to the association between multiple chronic conditions and employment. Methods Cross-sectional data (2011 National Health Interview Survey) and multivariate regression analyses were used to examine the association among multiple chronic conditions, employment, and labor force outcomes for U.S. adults aged 18–64 years, controlling for covariates. Results Among U.S. adults aged 18–64 years (unweighted n=25,458), having multiple chronic conditions reduced employment probability by 11%–29%. Some individual chronic conditions decreased employment probability. Among employed adults (unweighted n=16,096), having multiple chronic conditions increased the average number of work days missed due to injury/illness in the past year by 3–9 days. Conclusions Multiple chronic conditions are be a barrier to employment and increase the number of work days missed, placing affected individuals at a financial disadvantage. Researchers interested in examining consequences of multiple chronic conditions should give consideration to labor force outcomes. PMID:26103096

Mixed models approaches for joint modeling of different types of responses.

PubMed

Ivanova, Anna; Molenberghs, Geert; Verbeke, Geert

2016-01-01

In many biomedical studies, one jointly collects longitudinal continuous, binary, and survival outcomes, possibly with some observations missing. Random-effects models, sometimes called shared-parameter models or frailty models, received a lot of attention. In such models, the corresponding variance components can be employed to capture the association between the various sequences. In some cases, random effects are considered common to various sequences, perhaps up to a scaling factor; in others, there are different but correlated random effects. Even though a variety of data types has been considered in the literature, less attention has been devoted to ordinal data. For univariate longitudinal or hierarchical data, the proportional odds mixed model (POMM) is an instance of the generalized linear mixed model (GLMM; Breslow and Clayton, 1993). Ordinal data are conveniently replaced by a parsimonious set of dummies, which in the longitudinal setting leads to a repeated set of dummies. When ordinal longitudinal data are part of a joint model, the complexity increases further. This is the setting considered in this paper. We formulate a random-effects based model that, in addition, allows for overdispersion. Using two case studies, it is shown that the combination of random effects to capture association with further correction for overdispersion can improve the model's fit considerably and that the resulting models allow to answer research questions that could not be addressed otherwise. Parameters can be estimated in a fairly straightforward way, using the SAS procedure NLMIXED.

The Role of Feature Selection and Statistical Weighting in ...

EPA Pesticide Factsheets

Our study assesses the value of both in vitro assay and quantitative structure activity relationship (QSAR) data in predicting in vivo toxicity using numerous statistical models and approaches to process the data. Our models are built on datasets of (i) 586 chemicals for which both in vitro and in vivo data are currently available in EPA’s Toxcast and ToxRefDB databases, respectively, and (ii) 769 chemicals for which both QSAR data and in vivo data exist. Similar to a previous study (based on just 309 chemicals, Thomas et al. 2012), after converting the continuous values from each dataset to binary values, the majority of more than 1,000 in vivo endpoints are poorly predicted. Even for the endpoints that are well predicted (about 40 with an F1 score of >0.75), imbalances in in vivo endpoint data or cytotoxicity across in vitro assays may be skewing results. In order to better account for these types of considerations, we examine best practices in data preprocessing and model fitting in real-world contexts where data are rife with imperfections. We discuss options for dealing with missing data, including omitting observations, aggregating variables, and imputing values. We also examine the impacts of feature selection (from both a statistical and biological perspective) on performance and efficiency, and we weight outcome data to reduce endpoint imbalances to account for potential chemical selection bias and assess revised performance. For example, initial weig

Improving the analysis of composite endpoints in rare disease trials.

PubMed

McMenamin, Martina; Berglind, Anna; Wason, James M S

2018-05-22

Composite endpoints are recommended in rare diseases to increase power and/or to sufficiently capture complexity. Often, they are in the form of responder indices which contain a mixture of continuous and binary components. Analyses of these outcomes typically treat them as binary, thus only using the dichotomisations of continuous components. The augmented binary method offers a more efficient alternative and is therefore especially useful for rare diseases. Previous work has indicated the method may have poorer statistical properties when the sample size is small. Here we investigate small sample properties and implement small sample corrections. We re-sample from a previous trial with sample sizes varying from 30 to 80. We apply the standard binary and augmented binary methods and determine the power, type I error rate, coverage and average confidence interval width for each of the estimators. We implement Firth's adjustment for the binary component models and a small sample variance correction for the generalized estimating equations, applying the small sample adjusted methods to each sub-sample as before for comparison. For the log-odds treatment effect the power of the augmented binary method is 20-55% compared to 12-20% for the standard binary method. Both methods have approximately nominal type I error rates. The difference in response probabilities exhibit similar power but both unadjusted methods demonstrate type I error rates of 6-8%. The small sample corrected methods have approximately nominal type I error rates. On both scales, the reduction in average confidence interval width when using the adjusted augmented binary method is 17-18%. This is equivalent to requiring a 32% smaller sample size to achieve the same statistical power. The augmented binary method with small sample corrections provides a substantial improvement for rare disease trials using composite endpoints. We recommend the use of the method for the primary analysis in relevant rare disease trials. We emphasise that the method should be used alongside other efforts in improving the quality of evidence generated from rare disease trials rather than replace them.

Mortality and missed opportunities along the pathway of care for ST-elevation myocardial infarction: a national cohort study.

PubMed

Simms, A D; Weston, C F; West, R M; Hall, A S; Batin, P D; Timmis, A; Hemingway, H; Fox, Kaa; Gale, C P

2015-06-01

To examine the association between cumulative missed opportunities for care (CMOC) and mortality in patients with ST-elevation myocardial infarction (STEMI). A cohort study of 112,286 STEMI patients discharged from hospital alive between January 2007 and December 2010, using data from the Myocardial Ischaemia National Audit Project (MINAP). A CMOC score was calculated for each patient and included: pre-hospital ECG, acute use of aspirin, timely reperfusion, prescription at hospital discharge of aspirin, thienopyridine inhibitor, ACE-inhibitor (or equivalent), HMG-CoA reductase inhibitor and β-blocker, and referral for cardiac rehabilitation. Mixed-effects logistic regression models evaluated the effect of CMOC on risk-adjusted 30-day and 1-year mortality (RAMR). 44.5% of patients were ineligible for ≥1 care component. Of patients eligible for all nine components, 50.6% missed ≥1 opportunity. Pre-hospital ECG and timely reperfusion were most frequently missed, predicting further missed care at discharge (pre-hospital ECG incident rate ratio [95% CI]: 1.64 [1.58-1.70]; timely reperfusion 9.94 [9.51-10.40]). Patients ineligible for care had higher RAMR than those eligible for care (30-days: 1.7% vs. 1.1%; 1-year: 8.6% vs. 5.2%), whilst those with no missed care had lower mortality than patients with ≥4 CMOC (30-days: 0.5% vs. 5.4%, adjusted OR (aOR) per CMOC group 1.22, 95% CI: 1.05-1.42; 1-year: 3.2% vs. 22.8%, aOR 1.23, 1.13-1.34). Opportunities for care in STEMI are commonly missed and significantly associated with early and later mortality. Thus, outcomes after STEMI may be improved by greater attention to missed opportunities to eligible care. © The European Society of Cardiology 2014.

Using the missed opportunity tool as an application of the Lives Saved Tool (LiST) for intervention prioritization.

PubMed

Tam, Yvonne; Pearson, Luwei

2017-11-07

The Missed Opportunity tool was developed as an application in the Lives Saved Tool (LiST) to allow users to quickly compare the relative impact of interventions. Global Financing Facility (GFF) investment cases have been identified as a potential application of the Missed Opportunity analyses in Democratic Republic of the Congo (DRC), Ethiopia, Kenya, and Tanzania, to use 'lives saved' as a normative factor to set priorities. The Missed Opportunity analysis draws on data and methods in LiST to project maternal, stillbirth, and child deaths averted based on changes in interventions' coverage. Coverage of each individual intervention in LiST was automated to be scaled up from current coverage to 90% in the next year, to simulate a scenario where almost every mother and child receive proven interventions that they need. The main outcome of the Missed Opportunity analysis is deaths averted due to each intervention. When reducing unmet need for contraception is included in the analysis, it ranks as the top missed opportunity across the four countries. When it is not included in the analysis, top interventions with the most total deaths averted are hospital-based interventions such as labor and delivery management in the CEmOC and BEmOC level, and full treatment and supportive care for premature babies, and for sepsis/pneumonia. The Missed Opportunity tool can be used to provide a quick, first look at missed opportunities in a country or geographic region, and help identify interventions for prioritization. While it is a useful advocate for evidence-based priority setting, decision makers need to consider other factors that influence decision making, and also discuss how to implement, deliver, and sustain programs to achieve high coverage.

Application of strict criteria in adrenal venous sampling increases the proportion of missed patients with unilateral disease who benefit from surgery for primary aldosteronism.

PubMed

Kline, Gregory; Leung, Alexander; So, Benny; Chin, Alex; Harvey, Adrian; Pasieka, Janice L

2018-06-01

Adrenal vein sampling (AVS) is intended to confirm unilateral forms of primary aldosteronism, which are amenable to surgical cure. Excessively strict AVS criteria to define lateralization may result in many patients incorrectly categorized as bilateral primary aldosteronism and opportunity for surgical cure missed. Retrospective review of an AVS-primary aldosteronism database in which surgical cases are verified by standardized outcomes. Having used 'less strict' AVS criteria for lateralization, we examined the distribution of AVS lateralization indices in our confirmed unilateral primary aldosteronism cases both with and without cosyntropin stimulation. The proportion of proven unilateral cases that would have been missed with stricter AVS interpretation criteria was calculated. Particular focus was given to the proportion of missed cases according to use of international guidelines. False-positive lateralization with 'less strict' interpretation was also calculated. Of 80 surgical primary aldosteronism cases, 10-23% would have been missed with AVS lateralization indices of 3 : 1 to 5 : 1, with or without cosyntropin. If strict selectivity indices (for confirmation of catheterization) were combined with strict lateralization indices, up to 70% of unilateral primary aldosteronism cases could have been missed. Use of Endocrine Society AVS guidelines would have missed 21-43% of proven unilateral cases. 'Less strict' AVS interpretation yielded one case (1.2%) of false lateralization. Excessively strict AVS interpretation criteria will result in a high rate of missed unilateral primary aldosteronism with subsequent loss of opportunity for intervention. Use of more lenient lateralization criteria will improve the detection rate of unilateral primary aldosteronism with very low false-positive rate.

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

A Peer-to-Peer Mentoring Program for In-Center Hemodialysis: A Patient-Centered Quality Improvement Program.

PubMed

St Clair Russell, Jennifer; Southerland, Shiree; Huff, Edwin D; Thomson, Maria; Meyer, Klemens B; Lynch, Janet R

2017-01-01

A patient-centered quality improvement program implemented in one Virginia hemodialysis facility sought to determine if peer-to-peer (P2P) programs can assist patients on in-center hemodialysis with self-management and improve outcomes. Using a single-arm, repeatedmeasurement, quasi-experimental design, 46 patients participated in a four-month P2P intervention. Outcomes include knowledge, self-management behaviors, and psychosocial health indicators: self-efficacy, perceived social support, hemodialysis social support, and healthrelated quality of life (HRQoL). Physiological health indicators included missed and shortened treatments, arteriovenous fistula placement, interdialytic weight gain, serum phosphorus, and hospitalizations. Mentees demonstrated increased knowledge, self-efficacy, perceived social support, hemodialysis social support, and HRQoL. Missed treatments decreased. Mentors experienced increases in knowledge, self-management, and social support. A P2P mentoring program for in-center hemodialysis can benefit both mentees and mentors. Copyright© by the American Nephrology Nurses Association.

Factors associated with study attrition among HIV-infected risky drinkers in St. Petersburg, Russia.

PubMed

Kiriazova, T; Cheng, D M; Coleman, S M; Blokhina, E; Krupitsky, E; Lira, M C; Bridden, C; Raj, A; Samet, J H

2014-01-01

Participant attrition in HIV longitudinal studies may introduce bias and diminish research quality. The identification of participant characteristics that are predictive of attrition might inform retention strategies. The study aimed to identify factors associated with attrition among HIV-infected Russian risky drinkers from the secondary HIV prevention HERMITAGE trial. We examined whether current injection drug use (IDU), binge drinking, depressive symptoms, HIV status nondisclosure, stigma, and lifetime history of incarceration were predictors of study attrition. We also explored effect modification due to gender. Complete loss to follow-up (LTFU), defined as no follow-up visits after baseline, was the primary outcome, and time to first missed visit was the secondary outcome. We used multiple logistic regression models for the primary analysis, and Cox proportional hazards models for the secondary analysis. Of 660 participants, 101 (15.3%) did not return after baseline. No significant associations between independent variables and complete LTFU were observed. Current IDU and HIV status nondisclosure were significantly associated with time to first missed visit (adjusted hazard ratio [AHR], 1.39; 95% CI, 1.03-1.87; AHR, 1.38; 95% CI, 1.03-1.86, respectively). Gender stratified analyses suggested a larger impact of binge drinking among men and history of incarceration among women with time to first missed visit. Although no factors were significantly associated with complete LTFU, current IDU and HIV status nondisclosure were significantly associated with time to first missed visit in HIV-infected Russian risky drinkers. An understanding of these predictors may inform retention efforts in longitudinal studies.

Thermodynamics of Liquid Alkali Metals and Their Binary Alloys

NASA Astrophysics Data System (ADS)

Thakor, P. B.; Patel, Minal H.; Gajjar, P. N.; Jani, A. R.

2009-07-01

The theoretical investigation of thermodynamic properties like internal energy, entropy, Helmholtz free energy, heat of mixing (ΔE) and entropy of mixing (ΔS) of liquid alkali metals and their binary alloys are reported in the present paper. The effect of concentration on the thermodynamic properties of Ac1Bc2 alloy of the alkali-alkali elements is investigated and reported for the first time using our well established local pseudopotential. To investigate influence of exchange and correlation effects, we have used five different local field correction functions viz; Hartree(H), Taylor(T), Ichimaru and Utsumi(IU), Farid et al. (F) and Sarkar et al. (S). The increase of concentration C2, increases the internal energy and Helmholtz free energy of liquid alloy Ac1Bc2. The behavior of present computation is not showing any abnormality in the outcome and hence confirms the applicability of our model potential in explaining the thermodynamics of liquid binary alloys.

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

PubMed

Jarvis, Stuart; Kovacs, Caroline; Briggs, Jim; Meredith, Paul; Schmidt, Paul E; Featherstone, Peter I; Prytherch, David R; Smith, Gary B

2015-08-01

Although the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. We truncated 36 published 'standard' EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve--AUROC) of each standard EWS and its truncated 'binary' equivalent. The binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. The performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Two-Center Validation of "Patient Does Not Follow Commands" and Three Other Simplified Measures to Replace the Glasgow Coma Scale for Field Trauma Triage.

PubMed

Hopkins, Emily; Green, Steven M; Kiemeney, Michael; Haukoos, Jason S

2018-05-02

Out-of-hospital personnel worldwide calculate the 13-point Glasgow Coma Scale (GCS) score as a routine part of field trauma triage. We wish to independently validate a simpler binary assessment to replace the GCS for this task. We analyzed trauma center registries from Loma Linda University Health (2003 to 2015) and Denver Health Medical Center (2009 to 2015) to compare the binary assessment "patient does not follow commands" (ie, GCS motor score <6) with GCS score less than or equal to 13 for the prediction of 5 trauma outcomes: emergency intubation, clinically significant brain injury, need for neurosurgical intervention, Injury Severity Score greater than 15, and mortality. As a secondary analysis, we similarly evaluated 3 other measures simpler than the GCS: GCS motor score less than 5, Simplified Motor Score, and the "alert, voice, pain, unresponsive" scale. In this analysis of 47,973 trauma patients, we found that the binary assessment "patient does not follow commands" was essentially identical to GCS score less than or equal to 13 for the prediction of all 5 trauma outcomes, with slightly superior positive likelihood ratios (eg, those for mortality 2.37 versus 2.13) offsetting slightly inferior negative ones (eg, those for mortality 0.25 versus 0.24) and its graphic depiction of sensitivity versus specificity superimposing the GCS prediction curve. We found similar results for the 3 other simplified measures. In this 2-center external validation, we confirmed that a simple binary assessment-"patient does not follow commands"-could effectively replace the more complicated GCS for field trauma triage. Copyright © 2018 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Selective reporting bias of harm outcomes within studies: findings from a cohort of systematic reviews.

PubMed

Saini, Pooja; Loke, Yoon K; Gamble, Carrol; Altman, Douglas G; Williamson, Paula R; Kirkham, Jamie J

2014-11-21

To determine the extent and nature of selective non-reporting of harm outcomes in clinical studies that were eligible for inclusion in a cohort of systematic reviews. Cohort study of systematic reviews from two databases. Outcome reporting bias in trials for harm outcomes (ORBIT II) in systematic reviews from the Cochrane Library and a separate cohort of systematic reviews of adverse events. 92 systematic reviews of randomised controlled trials and non-randomised studies published in the Cochrane Library between issue 9, 2012 and issue 2, 2013 (Cochrane cohort) and 230 systematic reviews published between 1 January 2007 and 31 December 2011 in other publications, synthesising data on harm outcomes (adverse event cohort). A 13 point classification system for missing outcome data on harm was developed and applied to the studies. 86% (79/92) of reviews in the Cochrane cohort did not include full data from the main harm outcome of interest of each review for all of the eligible studies included within that review; 76% (173/230) for the adverse event cohort. Overall, the single primary harm outcome was inadequately reported in 76% (705/931) of the studies included in the 92 reviews from the Cochrane cohort and not reported in 47% (4159/8837) of the 230 reviews in the adverse event cohort. In a sample of primary studies not reporting on the single primary harm outcome in the review, scrutiny of the study publication revealed that outcome reporting bias was suspected in nearly two thirds (63%, 248/393). The number of reviews suspected of outcome reporting bias as a result of missing or partially reported harm related outcomes from at least one eligible study is high. The declaration of important harms and the quality of the reporting of harm outcomes must be improved in both primary studies and systematic reviews. © Saini et al 2014.

Not All Are Lost: Interrupted Laboratory Monitoring, Early Death, and Loss to Follow-Up (LTFU) in a Large South African Treatment Program

PubMed Central

Ahonkhai, Aima A.; Noubary, Farzad; Munro, Alison; Stark, Ruth; Wilke, Marisa; Freedberg, Kenneth A.; Wood, Robin; Losina, Elena

2012-01-01

Background Many HIV treatment programs in resource-limited settings are plagued by high rates of loss to follow-up (LTFU). Most studies have not distinguished between those who briefly interrupt, but return to care, and those more chronically lost to follow-up. Methods We conducted a retrospective cohort study of 11,397 adults initiating antiretroviral therapy (ART) in 71 Southern African Catholic Bishops Conference/Catholic Relief Services HIV treatment clinics between January 2004 and December 2008. We distinguished among patients with early death, within the first 7 months on ART; patients with interruptions in laboratory monitoring (ILM), defined as missing visits in the first 7 months on ART, but returning to care by 12 months; and those LTFU, defined as missing all follow-up visits in the first 12 months on ART. We used multilevel logistic regression models to determine patient and clinic-level characteristics associated with these outcomes. Results In the first year on ART, 60% of patients remained in care, 30% missed laboratory visits, and 10% suffered early death. Of the 3,194 patients who missed laboratory visits, 40% had ILM, resuming care by 12 months. After 12 months on ART, patients with ILM had a 30% increase in detectable viremia compared to those who remained in care. Risk of LTFU decreased with increasing enrollment year, and was lowest for patients who enrolled in 2008 compared to 2004 [OR 0.49, 95%CI 0.39–0.62]. Conclusions In a large community-based cohort in South Africa, nearly 30% of patients miss follow-up visits for CD4 monitoring in the first year after starting ART. Of those, 40% have ILM but return to clinic with worse virologic outcomes than those who remain in care. The risk of chronic LTFU decreased with enrollment year. As ART availability increases, interruptions in care may become more common, and should be accounted for in addressing program LTFU. PMID:22427925

Inverted U-Shaped Curvilinear Relationship between Challenge and One's Intrinsic Motivation: Evidence from Event-Related Potentials.

PubMed

Ma, Qingguo; Pei, Guanxiong; Meng, Liang

2017-01-01

The balance between task demand and one's competence is critical for the maintenance of intrinsic motivation. According to Flow theory and Self-determination theory, optimal challenge gives rise to the maximum intrinsic motivation, and an inverted U-shaped curvilinear relationship between perceived challenge and one's intrinsic motivation is suggested. In order to provide direct experimental evidences for predictions of these theories, in this study, we employed the two-player StopWatch game that we previously designed, which made references to the game format of a badminton tournament. According to our manipulation, a male participant was defeated by the same-sex player paired with him (played by a well-trained confederate of the experimenter) in two matches, one with a wide margin (the complete defeat condition) and another with a narrow one (the near miss condition). Participants performed better and reported to enjoy the near miss match to a greater extent. Besides, an enlarged Stimulus-preceding negativity was elicited when participants were actively anticipating outcomes in the near miss condition, suggesting greater anticipatory attention toward the outcome and an enhanced intrinsic motivation to win. Thus, converging electrophysiological evidences from this study and our former study confirmed the inverted U-shaped curvilinear relationship between perceived challenge and one's intrinsic motivation.

Effects on employees of controlling working hours and working schedules.

PubMed

Kubo, T; Takahashi, M; Togo, F; Liu, X; Shimazu, A; Tanaka, K; Takaya, M

2013-03-01

High levels of control over working time and low variability in working hours have been associated with improved health-related outcomes. The potential mechanisms for this association remain unclear. To examine how work-time control and variability of working times are associated with fatigue recovery, sleep quality, work-life balance, and 'near misses' at work. Manufacturing sector employees completed a questionnaire that assessed work-time control, work-time variability, fatigue recovery, sleep quality, work-life balance and the frequency of near misses in the past 6 months. Mixed model analysis of covariance and multiple logistic regression analysis tested the main effects of work-time control and variability and their interaction, while adjusting for age, sex, work schedules, and overtime work in the past month. Subscales of work-time control were also investigated (control over daily working hours and over days off). One thousand three hundred and seventy-two completed questionnaires were returned, a response rate of 69%. A significantly higher quality of sleep and better work-life balance were found in the 'high control with low variability' reference group than in the other groups. Significantly better recovery of fatigue was also observed in the group having control over days off with low variability. While near misses were more frequent in the group with high control over daily working hours coupled with high variability compared with the reference group this was not significant. High work-time control and low variability were associated with favourable outcomes of health and work-life balance. This combined effect was not observed for the safety outcome addressed here.

Evaluation of methods to estimate missing days' supply within pharmacy data of the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN).

PubMed

Lum, Kirsten J; Newcomb, Craig W; Roy, Jason A; Carbonari, Dena M; Saine, M Elle; Cardillo, Serena; Bhullar, Harshvinder; Gallagher, Arlene M; Lo Re, Vincent

2017-01-01

The extent to which days' supply data are missing in pharmacoepidemiologic databases and effective methods for estimation is unknown. We determined the percentage of missing days' supply on prescription and patient levels for oral anti-diabetic drugs (OADs) and evaluated three methods for estimating days' supply within the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN). We estimated the percentage of OAD prescriptions and patients with missing days' supply in each database from 2009 to 2013. Within a random sample of prescriptions with known days' supply, we measured the accuracy of three methods to estimate missing days' supply by imputing the following: (1) 28 days' supply, (2) mode number of tablets/day by drug strength and number of tablets/prescription, and (3) number of tablets/day via a machine learning algorithm. We determined incidence rates (IRs) of acute myocardial infarction (AMI) using each method to evaluate the impact on ascertainment of exposure time and outcomes. Days' supply was missing for 24 % of OAD prescriptions in CPRD and 33 % in THIN (affecting 48 and 57 % of patients, respectively). Methods 2 and 3 were very accurate in estimating days' supply for OADs prescribed at a consistent number of tablets/day. Method 3 was more accurate for OADs prescribed at varying number of tablets/day. IRs of AMI were similar across methods for most OADs. Missing days' supply is a substantial problem in both databases. Method 2 is easy and very accurate for most OADs and results in IRs comparable to those from method 3.

Past and future implications of near-misses and their emotional consequences.

PubMed

Zhang, Qiyuan; Covey, Judith

2014-01-01

The Reflection and Evaluation Model (REM) of comparative thinking predicts that temporal perspective could moderate people's emotional reactions to close counterfactuals following near-misses (Markman & McMullen, 2003). The experiments reported in this paper tested predictions derived from this theory by examining how people's emotional reactions to a near-miss at goal during a football match (Experiment 1) or a close score in a TV game show (Experiment 2) depended on the level of perceived future possibility. In support of the theory it was found that the presence of future possibility enhanced affective assimilation (e.g., if the near-miss occurred at the beginning of the game the players who had nearly scored were hopeful of future success) whereas the absence of future possibility enhanced affective contrast (e.g., if the near-miss occurred at the end of the game the players who had nearly scored were disappointed about missing an opportunity). Furthermore the experiments built upon our theoretical understanding by exploring the mechanisms which produce assimilation and contrast effects. In Experiment 1 we examined the incidence of present-oriented or future-oriented thinking, and in Experiment 2 we examined the mediating role of counterfactual thinking in the observed effect of proximity on emotions by testing whether stronger counterfactuals (measured using counterfactual probability estimates) produce bigger contrast and assimilation effects. While the results of these investigations generally support the REM, they also highlight the necessity to consider other psychological mechanisms (e.g., social comparison), in addition to counterfactual thinking, that might contribute to the emotional consequences of near-miss outcomes.

Methods for using clinical laboratory test results as baseline confounders in multi-site observational database studies when missing data are expected.

PubMed

Raebel, Marsha A; Shetterly, Susan; Lu, Christine Y; Flory, James; Gagne, Joshua J; Harrell, Frank E; Haynes, Kevin; Herrinton, Lisa J; Patorno, Elisabetta; Popovic, Jennifer; Selvan, Mano; Shoaibi, Azadeh; Wang, Xingmei; Roy, Jason

2016-07-01

Our purpose was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods. Using the Mini-Sentinel Distributed Database from three sites, we selected three exposure-outcome scenarios with laboratory results as baseline confounders. We compared hazard ratios (HRs) or risk differences (RDs) and 95% confidence intervals (CIs) from models that omitted laboratory results, included only available results (complete cases), and included results after applying missing data methods (multiple imputation [MI] regression, MI predictive mean matching [PMM] indicator). Scenario 1 considered glucose among second-generation antipsychotic users and diabetes. Across sites, glucose was available for 27.7-58.9%. Results differed between complete case and missing data models (e.g., olanzapine: HR 0.92 [CI 0.73, 1.12] vs 1.02 [0.90, 1.16]). Across-site models employing different MI approaches provided similar HR and CI; site-specific models provided differing estimates. Scenario 2 evaluated creatinine among individuals starting high versus low dose lisinopril and hyperkalemia. Creatinine availability: 44.5-79.0%. Results differed between complete case and missing data models (e.g., HR 0.84 [CI 0.77, 0.92] vs. 0.88 [0.83, 0.94]). HR and CI were identical across MI methods. Scenario 3 examined international normalized ratio (INR) among warfarin users starting interacting versus noninteracting antimicrobials and bleeding. INR availability: 20.0-92.9%. Results differed between ignoring INR versus including INR using missing data methods (e.g., RD 0.05 [CI -0.03, 0.13] vs 0.09 [0.00, 0.18]). Indicator and PMM methods gave similar estimates. Multi-site studies must consider site variability in missing data. Different missing data methods performed similarly. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Prevalence of Apical Periodontitis in Endodontically Treated Premolars and Molars with Untreated Canal: A Cone-beam Computed Tomography Study.

PubMed

Karabucak, Bekir; Bunes, Alf; Chehoud, Christel; Kohli, Meetu R; Setzer, Frank

2016-04-01

The purpose of this retrospective cohort study was to evaluate the incidence of missed canals in endodontically treated teeth in the Greater Philadelphia area patient population and to evaluate the effect of untreated canals on endodontic outcome. A total of 1397 cone-beam computed tomography (CBCT) volumes taken from January 2013 to July 2015 were investigated. Limited view CBCT images were taken with Kodak 9000 3D System field of view at voxel size, 76 μm or Morita Veraviewpocs 3D F40 field of view at voxel size, 125 μm. All root canal-treated premolars and molars were included in the study. Unfilled canals appearing from cementoenamel junction to apex including splitting from a main canal at coronal, mid, or apical third were defined as missed-untreated canal. A periapical lesion was diagnosed when disruption of the lamina dura was detected and the low density area associated with the radiographic apex was at least twice the width of the periodontal ligament space. The overall incidence of missed canals was 23.04%. The incidence of missed canals per tooth was highest in tooth #14 at 46.5% and tooth #3 at 41.3%. The incidence of missed canals was highest in the upper molars at 40.1% and lowest in the upper premolars at 9.5%. There was a significant difference in lesion prevalence when a canal was missed-untreated (P < .05). Teeth with a missed canal were 4.38 times more likely to be associated with a lesion. Limited field-of-view CBCT should be examined before any endodontic retreatment to identify missed canals. This knowledge would not only help clinicians to locate missed canals clinically but would also help in deciding the surgical approach. Copyright © 2016 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.

PubMed

Schmid, Matthias; Küchenhoff, Helmut; Hoerauf, Achim; Tutz, Gerhard

2016-02-28

Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior. Copyright © 2015 John Wiley & Sons, Ltd.

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

PubMed

Tan, Chuen Seng; Støer, Nathalie C; Chen, Ying; Andersson, Marielle; Ning, Yilin; Wee, Hwee-Lin; Khoo, Eric Yin Hao; Tai, E-Shyong; Kao, Shih Ling; Reilly, Marie

2017-01-01

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

Making an unknown unknown a known unknown: Missing data in longitudinal neuroimaging studies.

PubMed

Matta, Tyler H; Flournoy, John C; Byrne, Michelle L

2017-10-28

The analysis of longitudinal neuroimaging data within the massively univariate framework provides the opportunity to study empirical questions about neurodevelopment. Missing outcome data are an all-to-common feature of any longitudinal study, a feature that, if handled improperly, can reduce statistical power and lead to biased parameter estimates. The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data. This paper begins with a review of the hierarchy of missing data mechanisms and their relationship to likelihood-based methods, a review that is necessary not just for likelihood-based methods, but also for multiple-imputation methods. Next, the paper provides a series of simulation studies with designs common in longitudinal neuroimaging studies to help illustrate missing data concepts regardless of interpretation. Finally, two applied examples are used to demonstrate the sensitivity of inferences under different missing data assumptions and how this may change the substantive interpretation. The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bramante, Joseph; Linden, Tim

Recent observations of Reticulum II have uncovered an overabundance of r -process elements compared to similar ultra-faint dwarf spheroidal galaxies (UFDs). Because the metallicity and star formation history of Reticulum II appear consistent with all known UFDs, the high r -process abundance of Reticulum II suggests enrichment through a single, rare event, such as a double neutron star (NS) merger. However, we note that this scenario is extremely unlikely, as binary stellar evolution models require significant supernova natal kicks to produce NS–NS or NS–black hole (BH) mergers, and these kicks would efficiently remove compact binary systems from the weak gravitationalmore » potentials of UFDs. We examine alternative mechanisms for the production of r -process elements in UFDs, including a novel mechanism wherein NSs in regions of high dark matter (DM) density implode after accumulating a BH-forming mass of DM. We find that r -process proto-material ejection by tidal forces, when a single NS implodes into a BH, can occur at a rate matching the r -process abundance of both Reticulum II and the Milky Way. Remarkably, DM models which collapse a single NS in observed UFDs also solve the missing pulsar problem in the Milky Way Galactic Center. We propose tests specific to DM r -process production which may uncover or rule out this model.« less

Analysis of binary responses with outcome-specific misclassification probability in genome-wide association studies.

PubMed

Rekaya, Romdhane; Smith, Shannon; Hay, El Hamidi; Farhat, Nourhene; Aggrey, Samuel E

2016-01-01

Errors in the binary status of some response traits are frequent in human, animal, and plant applications. These error rates tend to differ between cases and controls because diagnostic and screening tests have different sensitivity and specificity. This increases the inaccuracies of classifying individuals into correct groups, giving rise to both false-positive and false-negative cases. The analysis of these noisy binary responses due to misclassification will undoubtedly reduce the statistical power of genome-wide association studies (GWAS). A threshold model that accommodates varying diagnostic errors between cases and controls was investigated. A simulation study was carried out where several binary data sets (case-control) were generated with varying effects for the most influential single nucleotide polymorphisms (SNPs) and different diagnostic error rate for cases and controls. Each simulated data set consisted of 2000 individuals. Ignoring misclassification resulted in biased estimates of true influential SNP effects and inflated estimates for true noninfluential markers. A substantial reduction in bias and increase in accuracy ranging from 12% to 32% was observed when the misclassification procedure was invoked. In fact, the majority of influential SNPs that were not identified using the noisy data were captured using the proposed method. Additionally, truly misclassified binary records were identified with high probability using the proposed method. The superiority of the proposed method was maintained across different simulation parameters (misclassification rates and odds ratios) attesting to its robustness.

Reduced risk of pre-eclampsia with organic vegetable consumption: results from the prospective Norwegian Mother and Child Cohort Study

PubMed Central

Torjusen, Hanne; Brantsæter, Anne Lise; Haugen, Margaretha; Alexander, Jan; Bakketeig, Leiv S; Lieblein, Geir; Stigum, Hein; Næs, Tormod; Swartz, Jackie; Holmboe-Ottesen, Gerd; Roos, Gun; Meltzer, Helle Margrete

2014-01-01

Objective Little is known about the potential health effects of eating organic food either in the general population or during pregnancy. The aim of this study was to examine associations between organic food consumption during pregnancy and the risk of pre-eclampsia among nulliparous Norwegian women. Design Prospective cohort study. Setting Norway, years 2002–2008. Participants 28 192 pregnant women (nulliparous, answered food frequency questionnaire and general health questionnaire in mid-pregnancy and no missing information on height, body weight or gestational weight gain). Main outcome measure Relative risk was estimated as ORs by performing binary logistic regression with pre-eclampsia as the outcome and organic food consumption as the exposure. Results The prevalence of pre-eclampsia in the study sample was 5.3% (n=1491). Women who reported to have eaten organic vegetables ‘often’ or ‘mostly’ (n=2493, 8.8%) had lower risk of pre-eclampsia than those who reported ‘never/rarely’ or ‘sometimes’ (crude OR=0.76, 95% CI 0.61 to 0.96; adjusted OR=0.79, 95% CI 0.62 to 0.99). The lower risk associated with high organic vegetable consumption was evident also when adjusting for overall dietary quality, assessed as scores on a healthy food pattern derived by principal component analysis. No associations with pre-eclampsia were found for high intake of organic fruit, cereals, eggs or milk, or a combined index reflecting organic consumption. Conclusions These results show that choosing organically grown vegetables during pregnancy was associated with reduced risk of pre-eclampsia. Possible explanations for an association between pre-eclampsia and use of organic vegetables could be that organic vegetables may change the exposure to pesticides, secondary plant metabolites and/or influence the composition of the gut microbiota. PMID:25208850

LIKELIHOOD MODELS FOR CLUSTERED BINARY AND CONTINUOUS OUTCOMES: APPLICATION TO DEVELOPMENTAL TOXICOLOGY. (R824757)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

The formation mechanism of 4179 Toutatis' elongated bilobed structure in a close Earth encounter scenario

NASA Astrophysics Data System (ADS)

Hu, Shoucun; Ji, Jianghui; Richardson, Derek C.; Zhao, Yuhui; Zhang, Yun

2018-07-01

The optical images of near-Earth asteroid 4179 Toutatis acquired by Chang'e-2 spacecraft show that Toutatis has an elongated contact binary configuration, with the contact point located along the long axis. We speculate that such configuration may have resulted from a low-speed impact between two components. In this work, we performed a series of numerical simulations and compared the results with the optical images, to examine the mechanism and better understand the formation of Toutatis. Herein, we propose a scenario that an assumed separated binary precursor could undergo a close encounter with Earth, leading to an impact between the primary and secondary, and the elongation is caused by Earth's tide. The precursor is assumed to be a doubly synchronous binary with a semimajor axis of 4Rp (radius of primary) and the two components are represented as spherical cohesionless self-gravitating granular aggregates. The mutual orbits are simulated in a Monte Carlo routine to provide appropriate parameters for our N-body simulations of impact and tidal distortion. We employ the PKDGRAV package with a soft-sphere discrete element method to explore the entire scenarios. The results show that contact binary configurations are natural outcomes under this scenario, whereas the shape of the primary is almost not affected by the impact of the secondary. However, our simulations further provide an elongated contact binary configuration best matching to the shape of Toutatis at an approaching distance rp = 1.4-1.5 Re (Earth radius), indicative of a likely formation scenario for configurations of Toutatis-like elongated contact binaries.

The formation mechanism of 4179 Toutatis' elongated bi-lobed structure in a close Earth encounter scenario

NASA Astrophysics Data System (ADS)

Hu, Shoucun; Ji, Jianghui; Richardson, Derek C.; Zhao, Yuhui; Zhang, Yun

2018-04-01

The optical images of near-Earth asteroid 4179 Toutatis acquired by Chang'e-2 spacecraft show that Toutatis has an elongated contact binary configuration, with the contact point located along the long axis. We speculate that such configuration may have resulted from a low-speed impact between two components. In this work, we performed a series of numerical simulations and compared the results with the optical images, to examine the mechanism and better understand the formation of Toutatis. Herein we propose an scenario that an assumed separated binary precursor could undergo a close encounter with Earth, leading to an impact between the primary and secondary, and the elongation is caused by Earth's tide. The precursor is assumed to be a doubly synchronous binary with a semi-major axis of 4 Rp (radius of primary) and the two components are represented as spherical cohesionless self-gravitating granular aggregates. The mutual orbits are simulated in a Monte Carlo routine to provide appropriate parameters for our N-body simulations of impact and tidal distortion. We employ the pkdgrav package with a soft-sphere discrete element method (SSDEM) to explore the entire scenarios. The results show that contact binary configurations are natural outcomes under this scenario, whereas the shape of the primary is almost not affected by the impact of the secondary. However, our simulations further provide an elongated contact binary configuration best-matching to the shape of Toutatis at an approaching distance rp = 1.4 ˜ 1.5 Re (Earth radius), indicative of a likely formation scenario for configurations of Toutatis-like elongated contact binaries.

A Bayesian network meta-analysis for binary outcome: how to do it.

PubMed

Greco, Teresa; Landoni, Giovanni; Biondi-Zoccai, Giuseppe; D'Ascenzo, Fabrizio; Zangrillo, Alberto

2016-10-01

This study presents an overview of conceptual and practical issues of a network meta-analysis (NMA), particularly focusing on its application to randomised controlled trials with a binary outcome of interest. We start from general considerations on NMA to specifically appraise how to collect study data, structure the analytical network and specify the requirements for different models and parameter interpretations, with the ultimate goal of providing physicians and clinician-investigators a practical tool to understand pros and cons of NMA. Specifically, we outline the key steps, from the literature search to sensitivity analysis, necessary to perform a valid NMA of binomial data, exploiting Markov Chain Monte Carlo approaches. We also apply this analytical approach to a case study on the beneficial effects of volatile agents compared to total intravenous anaesthetics for surgery to further clarify the statistical details of the models, diagnostics and computations. Finally, datasets and models for the freeware WinBUGS package are presented for the anaesthetic agent example. © The Author(s) 2013.

Predicting treatment effect from surrogate endpoints and historical trials: an extrapolation involving probabilities of a binary outcome or survival to a specific time

PubMed Central

Sargent, Daniel J.; Buyse, Marc; Burzykowski, Tomasz

2011-01-01

SUMMARY Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty from using a predicted instead of true result for the estimated treatment effect, we compute its multiplier of standard error. Software is available for download. PMID:21838732

GAC: Gene Associations with Clinical, a web based application.

PubMed

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2017-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC.

Missed injuries in the era of the trauma scan.

PubMed

Lawson, Christy M; Daley, Brian J; Ormsby, Christine B; Enderson, Blaine

2011-02-01

A rapid computed tomography technique or "trauma scan" (TS) provides high-resolution studies of the head, cervical spine, chest, abdomen, and pelvis. We sought to determine whether TS has decreased missed injuries. A previous study of TS found a 3% missed rate. After institutional review board approval, trauma patients from January 2001 through December 2008 were reviewed for delayed diagnosis (DD) of injury to the head, cervical spine, chest, abdomen, or pelvis. Missed extremity injuries were excluded. Injury Severity Score, length of stay, type of injury, outcomes, and days to detection were captured. Of 26,264 patients reviewed, 90 patients had DD, with an incidence of 0.34%. DD most commonly presented on day 2. Injuries included 16 bowel/mesentery, 12 spine, 11 pelvic, 8 spleen, 6 diaphragm, 5 clavicle, 4 scapula, 4 cervical spine, 4 intracranial, 4 sternum, 3 maxillofacial, 3 liver, 2 heart/aorta, 2 vascular, 2 urethra/bladder, 2 pneumothorax, and 2 pancreas/common bile duct. DD resulted in 1 death, 6 prolonged intensive care unit stays, 19 operative interventions, and 38 additional interventions. TS is an effective way of evaluating trauma patients for intracranial, cervical spine, chest, abdomen, and pelvic injuries that have the potential to impact morbidity and mortality. The incidence of injuries missed in these crucial areas has been reduced at our institution by the use of this radiographic modality. The most common missed injury remains bowel, and so a high index of suspicion and the tertiary survey must remain a mainstay of therapy.

Moderation analysis with missing data in the predictors.

PubMed

Zhang, Qian; Wang, Lijuan

2017-12-01

The most widely used statistical model for conducting moderation analysis is the moderated multiple regression (MMR) model. In MMR modeling, missing data could pose a challenge, mainly because the interaction term is a product of two or more variables and thus is a nonlinear function of the involved variables. In this study, we consider a simple MMR model, where the effect of the focal predictor X on the outcome Y is moderated by a moderator U. The primary interest is to find ways of estimating and testing the moderation effect with the existence of missing data in X. We mainly focus on cases when X is missing completely at random (MCAR) and missing at random (MAR). Three methods are compared: (a) Normal-distribution-based maximum likelihood estimation (NML); (b) Normal-distribution-based multiple imputation (NMI); and (c) Bayesian estimation (BE). Via simulations, we found that NML and NMI could lead to biased estimates of moderation effects under MAR missingness mechanism. The BE method outperformed NMI and NML for MMR modeling with missing data in the focal predictor, missingness depending on the moderator and/or auxiliary variables, and correctly specified distributions for the focal predictor. In addition, more robust BE methods are needed in terms of the distribution mis-specification problem of the focal predictor. An empirical example was used to illustrate the applications of the methods with a simple sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Adherence Barriers to Chronic Dialysis in the United States

PubMed Central

Thadhani, Ravi I.; Maddux, Franklin W.

2014-01-01

Hemodialysis patients often do not attend their scheduled treatment session. We investigated factors associated with missed appointments and whether such nonadherence poses significant harm to patients and increases overall health care utilization in an observational analysis of 44 million hemodialysis treatments for 182,536 patients with ESRD in the United States. We assessed the risk of hospitalization, emergency room visit, or intensive-coronary care unit (ICU-CCU) admission in the 2 days after a missed treatment relative to the risk for patients who received hemodialysis. Over the 5-year study period, the average missed treatment rate was 7.1 days per patient-year. In covariate adjusted logistic regression, the risk of hospitalization (odds ratio [OR], 3.98; 95% confidence interval [95% CI], 3.93 to 4.04), emergency room visit (OR, 2.00; 95% CI, 1.87 to 2.14), or ICU-CCU admission (OR, 3.89; 95% CI, 3.81 to 3.96) increased significantly after a missed treatment. Overall, 0.9 missed treatment days per year associated with suboptimal transportation to dialysis, inclement weather, holidays, psychiatric illness, pain, and gastrointestinal upset. These barriers also associated with excess hospitalization (5.6 more events per patient-year), emergency room visits (1.1 more visits), and ICU-CCU admissions (0.8 more admissions). In conclusion, poor adherence to hemodialysis treatments may be a substantial roadblock to achieving better patient outcomes. Addressing systemic and patient barriers that impede access to hemodialysis care may decrease missed appointments and reduce patient morbidity. PMID:24762400

Kinetic Monte Carlo Simulations of Rod Eutectics and the Surface Roughening Transition in Binary Alloys

NASA Technical Reports Server (NTRS)

Bentz, Daniel N.; Betush, William; Jackson, Kenneth A.

2003-01-01

In this paper we report on two related topics: Kinetic Monte Carlo simulations of the steady state growth of rod eutectics from the melt, and a study of the surface roughness of binary alloys. We have implemented a three dimensional kinetic Monte Carlo (kMC) simulation with diffusion by pair exchange only in the liquid phase. Entropies of fusion are first chosen to fit the surface roughness of the pure materials, and the bond energies are derived from the equilibrium phase diagram, by treating the solid and liquid as regular and ideal solutions respectively. A simple cubic lattice oriented in the {100} direction is used. Growth of the rods is initiated from columns of pure B material embedded in an A matrix, arranged in a close packed array with semi-periodic boundary conditions. The simulation cells typically have dimensions of 50 by 87 by 200 unit cells. Steady state growth is compliant with the Jackson-Hunt model. In the kMC simulations, using the spin-one Ising model, growth of each phase is faceted or nonfaceted phases depending on the entropy of fusion. There have been many studies of the surface roughening transition in single component systems, but none for binary alloy systems. The location of the surface roughening transition for the phases of a eutectic alloy determines whether the eutectic morphology will be regular or irregular. We have conducted a study of surface roughness on the spin-one Ising Model with diffusion using kMC. The surface roughness was found to scale with the melting temperature of the alloy as given by the liquidus line on the equilibrium phase diagram. The density of missing lateral bonds at the surface was used as a measure of surface roughness.

General relativistic magnetohydrodynamic simulations of binary neutron star mergers forming a long-lived neutron star

NASA Astrophysics Data System (ADS)

Ciolfi, Riccardo; Kastaun, Wolfgang; Giacomazzo, Bruno; Endrizzi, Andrea; Siegel, Daniel M.; Perna, Rosalba

2017-03-01

Merging binary neutron stars (BNSs) represent the ultimate targets for multimessenger astronomy, being among the most promising sources of gravitational waves (GWs), and, at the same time, likely accompanied by a variety of electromagnetic counterparts across the entire spectrum, possibly including short gamma-ray bursts (SGRBs) and kilonova/macronova transients. Numerical relativity simulations play a central role in the study of these events. In particular, given the importance of magnetic fields, various aspects of this investigation require general relativistic magnetohydrodynamics (GRMHD). So far, most GRMHD simulations focused the attention on BNS mergers leading to the formation of a hypermassive neutron star (NS), which, in turn, collapses within few tens of ms into a black hole surrounded by an accretion disk. However, recent observations suggest that a significant fraction of these systems could form a long-lived NS remnant, which will either collapse on much longer time scales or remain indefinitely stable. Despite the profound implications for the evolution and the emission properties of the system, a detailed investigation of this alternative evolution channel is still missing. Here, we follow this direction and present a first detailed GRMHD study of BNS mergers forming a long-lived NS. We consider magnetized binaries with different mass ratios and equations of state and analyze the structure of the NS remnants, the rotation profiles, the accretion disks, the evolution and amplification of magnetic fields, and the ejection of matter. Moreover, we discuss the connection with the central engine of SGRBs and provide order-of-magnitude estimates for the kilonova/macronova signal. Finally, we study the GW emission, with particular attention to the post-merger phase.

Chemical abundances of fast-rotating massive stars . II. Interpretation and comparison with evolutionary models

NASA Astrophysics Data System (ADS)

Cazorla, Constantin; Nazé, Yaël; Morel, Thierry; Georgy, Cyril; Godart, Mélanie; Langer, Norbert

2017-08-01

Aims: Past observations of fast-rotating massive stars exhibiting normal nitrogen abundances at their surface have raised questions about the rotational mixing paradigm. We revisit this question thanks to a spectroscopic analysis of a sample of bright fast-rotating OB stars, with the goal of quantifying the efficiency of rotational mixing at high rotation rates. Methods: Our sample consists of 40 fast rotators on the main sequence, with spectral types comprised between B0.5 and O4. We compare the abundances of some key element indicators of mixing (He, CNO) with the predictions of evolutionary models for single objects and for stars in interacting binary systems. Results: The properties of half of the sample stars can be reproduced by single evolutionary models, even in the case of probable or confirmed binaries that can therefore be true single stars in a pre-interaction configuration. The main problem for the rest of the sample is a mismatch for the [N/O] abundance ratio (we confirm the existence of fast rotators with a lack of nitrogen enrichment) and/or a high helium abundance that cannot be accounted for by models. Modifying the diffusion coefficient implemented in single-star models does not solve the problem as it cannot simultaneously reproduce the helium abundances and [N/O] abundance ratios of our targets. Since part of them actually are binaries, we also compared their chemical properties with predictions for post-mass transfer systems. We found that these models can explain the abundances measured for a majority of our targets, including some of the most helium-enriched, but fail to reproduce them in other cases. Our study thus reveals that some physical ingredients are still missing in current models.

Efficacy outcome selection in the therapeutic hypothermia after pediatric cardiac arrest trials.

PubMed

Holubkov, Richard; Clark, Amy E; Moler, Frank W; Slomine, Beth S; Christensen, James R; Silverstein, Faye S; Meert, Kathleen L; Pollack, Murray M; Dean, J Michael

2015-01-01

The Therapeutic Hypothermia After Pediatric Cardiac Arrest trials will determine whether therapeutic hypothermia improves survival with good neurobehavioral outcome, as assessed by the Vineland Adaptive Behavior Scales Second Edition, in children resuscitated after cardiac arrest in the in-hospital and out-of-hospital settings. We describe the innovative efficacy outcome selection process during Therapeutic Hypothermia After Pediatric Cardiac Arrest protocol development. Consensus assessment of potential outcomes and evaluation timepoints. None. We evaluated practical and technical advantages of several follow-up timepoints and continuous/categorical outcome variants. Simulations estimated power assuming varying hypothermia benefit on mortality and on neurobehavioral function among survivors. Twelve months after arrest was selected as the optimal assessment timepoint for pragmatic and clinical reasons. Change in Vineland Adaptive Behavior Scales Second Edition from prearrest level, measured as quasicontinuous with death and vegetative status being worst-possible levels, yielded optimal statistical power. However, clinicians preferred simpler multicategorical or binary outcomes because of easier interpretability and favored outcomes based solely on postarrest status because of concerns about accurate parental assessment of prearrest status and differing clinical impact of a given Vineland Adaptive Behavior Scales Second Edition change depending on prearrest status. Simulations found only modest power loss from categorizing or dichotomizing quasicontinuous outcomes because of high expected mortality. The primary outcome selected was survival with 12-month Vineland Adaptive Behavior Scales Second Edition no less than two SD below a reference population mean (70 points), necessarily evaluated only among children with prearrest Vineland Adaptive Behavior Scales Second Edition greater than or equal to 70. Two secondary efficacy outcomes, 12-month survival and quasicontinuous Vineland Adaptive Behavior Scales Second Edition change from prearrest level, will be evaluated among all randomized children, including those with compromised function prearrest. Extensive discussion of optimal efficacy assessment timing, and of the advantages versus drawbacks of incorporating prearrest status and using quasicontinuous versus simpler outcomes, was highly beneficial to the final Therapeutic Hypothermia After Pediatric Cardiac Arrest design. A relatively simple, binary primary outcome evaluated at 12 months was selected, with two secondary outcomes that address the potential disadvantages of primary outcome.

NASA Double Asteroid Redirection Test (DART) Trajectory Validation and Robutness

NASA Technical Reports Server (NTRS)

Sarli, Bruno V.; Ozimek, Martin T.; Atchison, Justin A.; Englander, Jacob A.; Barbee, Brent W.

2017-01-01

The Double Asteroid Redirection Test (DART) mission will be the first to test the concept of a kinetic impactor. Several studies have been made on asteroid redirection and impact mitigation, however, to this date no mission tested the proposed concepts. An impact study on a representative body allows the measurement of the effects on the target's orbit and physical structure. With this goal, DART's objective is to verify the effectiveness of the kinetic impact concept for planetary defense. The spacecraft uses solar electric propulsion to escape Earth, fly by (138971) 2001 CB21 for impact rehearsal, and impact Didymos-B, the secondary body of the binary (65803) Didymos system. This work focuses on the heliocentric transfer design part of the mission with the validation of the baseline trajectory, performance comparison to other mission objectives, and assessment of the baseline robustness to missed thrust events. Results show a good performance of the selected trajectory for different mission objectives: latest possible escape date, maximum kinetic energy on impact, shortest possible time of flight, and use of an Earth swing-by. The baseline trajectory was shown to be robust to a missed thrust with 1% of fuel margin being enough to recover the mission for failures of more than 14 days.

Effect of feedback mode and task difficulty on quality of timing decisions in a zero-sum game.

PubMed

Tikuisis, Peter; Vartanian, Oshin; Mandel, David R

2014-09-01

The objective was to investigate the interaction between the mode of performance outcome feedback and task difficulty on timing decisions (i.e., when to act). Feedback is widely acknowledged to affect task performance. However, the extent to which feedback display mode and its impact on timing decisions is moderated by task difficulty remains largely unknown. Participants repeatedly engaged a zero-sum game involving silent duels with a computerized opponent and were given visual performance feedback after each engagement. They were sequentially tested on three different levels of task difficulty (low, intermediate, and high) in counterbalanced order. Half received relatively simple "inside view" binary outcome feedback, and the other half received complex "outside view" hit rate probability feedback. The key dependent variables were response time (i.e., time taken to make a decision) and survival outcome. When task difficulty was low to moderate, participants were more likely to learn and perform better from hit rate probability feedback than binary outcome feedback. However, better performance with hit rate feedback exacted a higher cognitive cost manifested by higher decision response time. The beneficial effect of hit rate probability feedback on timing decisions is partially moderated by task difficulty. Performance feedback mode should be judiciously chosen in relation to task difficulty for optimal performance in tasks involving timing decisions.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

Evaluation of the Outcome of Lung Nodules Missed on 18F-FDG PET/MRI Compared with 18F-FDG PET/CT in Patients with Known Malignancies.

PubMed

Sawicki, Lino M; Grueneisen, Johannes; Buchbender, Christian; Schaarschmidt, Benedikt M; Gomez, Benedikt; Ruhlmann, Verena; Umutlu, Lale; Antoch, Gerald; Heusch, Philipp

2016-01-01

The lower detection rate of (18)F-FDG PET/MRI than (18)F-FDG PET/CT regarding small lung nodules should be considered in the staging of malignant tumors. The purpose of this study was to evaluate the outcome of these small lung nodules missed by (18)F-FDG PET/MRI. Fifty-one oncologic patients (mean age ± SD, 56.6 ± 14.0 y; 29 women, 22 men; tumor stages, I [n = 7], II [n = 7], III [n = 9], IV [n = 28]) who underwent (18)F-FDG PET/CT and subsequent (18)F-FDG PET/MRI on the same day were retrospectively enrolled. Images were analyzed by 2 interpreters in random order and separate sessions with a minimum of 4 wk apart. A maximum of 10 lung nodules was identified for each patient on baseline imaging. The presence, size, and presence of focal tracer uptake was noted for each lung nodule detected on (18)F-FDG PET/CT and (18)F-FDG PET/MRI using a postcontrast T1-weighted 3-dimensional gradient echo volume-interpolated breath-hold examination sequence with fat suppression as morphologic dataset. Follow-up CT or (18)F-FDG PET/CT (mean time to follow-up, 11 mo; range, 3-35 mo) was used as a reference standard to define each missed nodule as benign or malignant based on changes in size and potential new tracer uptake. Nodule-to-nodule comparison between baseline and follow-up was performed using descriptive statistics. Out of 134 lung nodules found on (18)F-FDG PET/CT, (18)F-FDG PET/MRI detected 92 nodules. Accordingly, 42 lung nodules (average size ± SD, 3.9 ± 1.3 mm; range, 2-7 mm) were missed by (18)F-FDG PET/MRI. None of the missed lung nodules presented with focal tracer uptake on baseline imaging or follow-up (18)F-FDG PET/CT. Thirty-three out of 42 missed lung nodules (78.6%) in 26 patients were rated benign, whereas 9 nodules (21.4%) in 4 patients were rated malignant. As a result, 1 patient required upstaging from tumor stage I to IV. Although most small lung nodules missed on (18)F-FDG PET/MRI were found to be benign, there was a relevant number of undetected metastases. However, in patients with advanced tumor stages the clinical impact remains controversial as upstaging is usually more relevant in lower stages. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Associations of Military Divorce with Mental, Behavioral, and Physical Health Outcomes

DTIC Science & Technology

2015-06-19

recent divorce re - ported subsequent poor health and military outcomes compared to those who remained married during the same time frame. We...determined using DMDC re - cords and were backfilled with self-reported data to reduce missing values. Baseline functional health was eval- uated with the...4.8 %, 3.0 %, and 3.0 % developing each of these conditions, re - spectively, between baseline and follow-up. Smoking initi- ation and recidivism

Demographic Characteristics Associated with Pregnant and Postpartum Youth Referred for Mental Health Services in a Community Outreach Center

PubMed Central

Norris, Sandhaya; Norris, Mark L.; Sibbald, Emily; Aubry, Tim; Harrison, Megan E.; Lafontaine, Genevieve; Gandhi, Jasmine

2016-01-01

Objective Pregnancy in youth is considered high risk from a number of different standpoints. At present, limited data has explored demographic factors associated with Canadian cohorts of pregnant and postpartum youth seeking mental health services. We aimed to describe demographic characteristics associated with pregnant and postpartum youth and young adults referred for mental health services in the community and to compare this with data drawn from a hospital-based perinatal mental health clinic. Method Patients were recruited at a young parents’ outreach center (YPOC) in a large urban Canadian city. The patients completed questionnaires at the time of initial assessment. The number of attended and missed appointments was tracked and compared to a hospital-based control group in an effort to determine whether the community-based clinic would result in fewer missed appointments. Results A total of 28 patients were assessed at the YPOC. The mean age of all participants was 19.4 years (+/− 2.3 years) as compared to 18.57 years (± 1.81 years) for the hospital-based group. Rates of poverty were high, and high school completion and level of social support low for many patients. Patients attending the YPOC clinic missed fewer appointments overall. Conclusions Pregnant and postpartum adolescents and young adults possess multiple risk factors across various domains that threaten short and long term health outcomes. Establishment of outreach mental health clinics may help minimize barriers to care as demonstrated in the present study by fewer missed appointments and should be investigated further as a means of improving mental health access and outcomes. PMID:27924145

Incidence and Outcomes of Cardiopulmonary Resuscitation in Pediatric Intensive Care Units

PubMed Central

Berg, Robert A.; Nadkarni, Vinay M.; Clark, Amy E.; Moler, Frank; Meert, Kathleen; Harrison, Rick E.; Newth, Christopher J. L.; Sutton, Robert M.; Wessel, David L.; Berger, John T.; Carcillo, Joseph; Dalton, Heidi; Heidemann, Sabrina; Shanley, Thomas P.; Zuppa, Athena F.; Doctor, Allan; Tamburro, Robert F.; Jenkins, Tammara L.; Dean, J. Michael; Holubkov, Richard; Pollack, Murray M.

2015-01-01

Objective To determine the incidence of cardiopulmonary resuscitation (CPR) in pediatric intensive care units (PICU) and subsequent outcomes. Design, Setting, and Patients Multi-center prospective observational study of children 30 minutes, p30 minutes of CPR. Conclusions These data establish that contemporary PICU CPR, including long durations of CPR, results in high rates of survival to hospital discharge (45%) and favorable neurologic outcomes among survivors (89%). Rates of survival with favorable neurologic outcomes were similar among cardiac and non-cardiac patients. The rigorous prospective, observational study design avoided the limitations of missing data and potential selection biases inherent in registry and administrative data. PMID:26646466

Spatial cluster detection for repeatedly measured outcomes while accounting for residential history.

PubMed

Cook, Andrea J; Gold, Diane R; Li, Yi

2009-10-01

Spatial cluster detection has become an important methodology in quantifying the effect of hazardous exposures. Previous methods have focused on cross-sectional outcomes that are binary or continuous. There are virtually no spatial cluster detection methods proposed for longitudinal outcomes. This paper proposes a new spatial cluster detection method for repeated outcomes using cumulative geographic residuals. A major advantage of this method is its ability to readily incorporate information on study participants relocation, which most cluster detection statistics cannot. Application of these methods will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between environmental exposures and repeated measured outcome, occurrence of wheeze in the last 6 months, while taking into account mobile locations.

Yoga as part of a package of care versus standard care for schizophrenia.

PubMed

Broderick, Julie; Vancampfort, Davy

2017-09-29

Yoga is an ancient spiritual practice that originated in India and is currently accepted in the Western world as a form of relaxation and exercise. It has been of interest for people with schizophrenia to determine the efficacy of yoga delivered as a package of care versus standard care. To examine the effects of yoga as a package of care versus standard care. We searched the Cochrane Schizophrenia Group Trials Register (latest 30 March 2017) which is based on regular searches of MEDLINE, PubMed, Embase, CINAHL, BIOSS, AMED, PsychINFO, and registries of clinical trials. We searched the references of all included studies. There are no language, date, document type, or publication status limitations for inclusion of records in the register. All randomised controlled trials (RCTs) including people with schizophrenia comparing yoga as a package of care with standard-care control. The review authors independently selected studies, quality rated these, and extracted data. For binary outcomes, we calculated risk difference (RD) and its 95% confidence interval (CI), on an intention-to-treat (ITT) basis. For continuous data, we estimated the mean difference (MD) between groups and its CI. We employed mixed-effect and fixed-effect models for analysis. We examined heterogeneity (I 2 technique), assessed risk of bias for included studies, and created a 'Summary of findings' table using GRADE (Grading of Recommendations Assessment, Development and Evaluation). Three studies are included in this review. All outcomes were short term (less than eight weeks). Useable data were reported for two outcomes only; leaving the study early and quality of life. None of the participants left the studies early and there was some evidence in favour of the yoga package for quality of life endpoint scores (1 RCT, n=80, MD 22.93 CI 19.74 to 26.12, low-quality evidence). Leaving the study early data were equivocal between the treatment groups (3 RCTs, n=193, RD 0.06 CI -0.01 to 0.13, medium-quality evidence, high heterogeneity). Overall, this review has an inordinate number of missing key outcomes, which included mental and global state, social functioning, physical health, adverse effects and costs of care. A small number of small studies were included in this review and these lacked many key outcomes. The sparse data means we cannot state with any degree of certainty if yoga delivered as a package of care is beneficial in comparison to standard care.

Analyzing time-ordered event data with missed observations.

PubMed

Dokter, Adriaan M; van Loon, E Emiel; Fokkema, Wimke; Lameris, Thomas K; Nolet, Bart A; van der Jeugd, Henk P

2017-09-01

A common problem with observational datasets is that not all events of interest may be detected. For example, observing animals in the wild can difficult when animals move, hide, or cannot be closely approached. We consider time series of events recorded in conditions where events are occasionally missed by observers or observational devices. These time series are not restricted to behavioral protocols, but can be any cyclic or recurring process where discrete outcomes are observed. Undetected events cause biased inferences on the process of interest, and statistical analyses are needed that can identify and correct the compromised detection processes. Missed observations in time series lead to observed time intervals between events at multiples of the true inter-event time, which conveys information on their detection probability. We derive the theoretical probability density function for observed intervals between events that includes a probability of missed detection. Methodology and software tools are provided for analysis of event data with potential observation bias and its removal. The methodology was applied to simulation data and a case study of defecation rate estimation in geese, which is commonly used to estimate their digestive throughput and energetic uptake, or to calculate goose usage of a feeding site from dropping density. Simulations indicate that at a moderate chance to miss arrival events ( p  = 0.3), uncorrected arrival intervals were biased upward by up to a factor 3, while parameter values corrected for missed observations were within 1% of their true simulated value. A field case study shows that not accounting for missed observations leads to substantial underestimates of the true defecation rate in geese, and spurious rate differences between sites, which are introduced by differences in observational conditions. These results show that the derived methodology can be used to effectively remove observational biases in time-ordered event data.

Effectiveness of a home-based missing incident prevention program for community-dwelling elderly patients with dementia.

PubMed

Lau, Wing Man; Chan, Tak Yeung; Szeto, Sze Lok

2018-05-03

ABSTRACTBackground:Getting lost is a recognized complication in patients with dementia. Preventive measures are lacking. This study aims to investigate the effectiveness of a home-based missing incident prevention program (HMIPP) in reducing missing incidents, time of searching, and caregivers' stress. The design was a pre- and post-intervention study. Patients were recruited from a hospital-based Geriatric Memory Clinic. Inclusion criteria were as follows: aged 60 years or above, established dementia, and Modified Functional Ambulation Categories score VI or VII. An occupational therapist performed the interventions at the patients's home. These included dementia education, prescription of assistive devices, on-site skills training, environmental modifications, community service referrals, and redesigning of daily life routine tasks. The number of missing incidents and caregivers' stress at three months and one year were compared with baseline data from one year before and the secondary outcome was time for searching of the last incident. A total of 54 patients were recruited. The mean age was 78.8 years and 54% were females. Majority of patients had moderate dementia. The mean number of missing incidents per year was significantly reduced at three months and one year (0.70, 0.22, and 0.14 at 0, 3, and 12 months, respectively; p < 0.001). The time for searching of last missing episode was reduced significantly (6.25, 0.13, and 0.35 hours, respectively; p < 0.001). The caregivers' stress also decreased significantly at three months and one year. The HMIPP was effective in reducing the number of missing incidents, searching time, and caregivers' stress at three months and one year.

D-dimer threshold increase with pretest probability unlikely for pulmonary embolism to decrease unnecessary computerized tomographic pulmonary angiography

PubMed Central

Hogg, Melanie M.; Courtney, D. Mark; Miller, Chadwick D.; Jones, Alan E.; Smithline, Howard A

2012-01-01

Background Increasing the threshold to define a positive D-dimer could reduce unnecessary computed tomographic pulmonary angiography (CTPA) for suspected PE but might increase rates of missed PE and missed pneumonia, the most common nonthromboembolic diagnosis seen on CTPA. Objective Measure the effect of doubling the standard D-dimer threshold for “PE unlikely” Revised Geneva (RGS) or Wells’ scores on the exclusion rate, frequency and size of missed PE and missed pneumonia. Methods Patients evaluated for suspected PE with 64-channel CTPA were prospectively enrolled from EDs and inpatient units of four hospitals. Pretest probability data were collected in real time and the D-dimer was measured in a central laboratory. Criterion standard was CPTA interpretation by two independent radiologists combined with clinical outcome at 30 days. Results Of 678 patients enrolled, 126 (19%) were PE+ and 93 (14%) had pneumonia. Use of either Wells≤4 or RGS≤6 produced similar results. For example, with RGS≤6 and standard threshold (<500 ng/mL), D-dimer was negative in 110/678 (16%), and 4/110 were PE+ (posterior probability 3.8%), and 9/110 (8.2%) had pneumonia. With RGS≤6 and a threshold <1000 ng/mL, D-dimer was negative in 208/678 (31%) and 11/208 (5.3%) were PE+, but 10/11 missed PEs were subsegmental, and none had concomitant DVT. Pneumonia was found in 12/208 (5.4%) with RGS≤6 and D-dimer<1000 ng/mL. Conclusions Doubling the threshold for a positive D-dimer with a PE unlikely pretest probability could reduce CTPA scanning with a slightly increased risk of missed isolated subsegmental PE, and no increase in rate of missed pneumonia. PMID:22284935

Characteristics of HIV patients who missed their scheduled appointments

PubMed Central

Nagata, Delsa; Gutierrez, Eliana Battaggia

2016-01-01

ABSTRACT OBJECTIVE To analyze whether sociodemographic characteristics, consultations and care in special services are associated with scheduled infectious diseases appointments missed by people living with HIV. METHODS This cross-sectional and analytical study included 3,075 people living with HIV who had at least one scheduled appointment with an infectologist at a specialized health unit in 2007. A secondary data base from the Hospital Management & Information System was used. The outcome variable was missing a scheduled medical appointment. The independent variables were sex, age, appointments in specialized and available disciplines, hospitalizations at the Central Institute of the Clinical Hospital at the Faculdade de Medicina of the Universidade de São Paulo, antiretroviral treatment and change of infectologist. Crude and multiple association analysis were performed among the variables, with a statistical significance of p ≤ 0.05. RESULTS More than a third (38.9%) of the patients missed at least one of their scheduled infectious diseases appointments; 70.0% of the patients were male. The rate of missed appointments was 13.9%, albeit with no observed association between sex and absences. Age was inversely associated to missed appointment. Not undertaking anti-retroviral treatment, having unscheduled infectious diseases consultations or social services care and being hospitalized at the Central Institute were directly associated to missed appointments. CONCLUSIONS The Hospital Management & Information System proved to be a useful tool for developing indicators related to the quality of health care of people living with HIV. Other informational systems, which are often developed for administrative purposes, can also be useful for local and regional management and for evaluating the quality of care provided for patients living with HIV. PMID:26786472

A robust method using propensity score stratification for correcting verification bias for binary tests

PubMed Central

He, Hua; McDermott, Michael P.

2012-01-01

Sensitivity and specificity are common measures of the accuracy of a diagnostic test. The usual estimators of these quantities are unbiased if data on the diagnostic test result and the true disease status are obtained from all subjects in an appropriately selected sample. In some studies, verification of the true disease status is performed only for a subset of subjects, possibly depending on the result of the diagnostic test and other characteristics of the subjects. Estimators of sensitivity and specificity based on this subset of subjects are typically biased; this is known as verification bias. Methods have been proposed to correct verification bias under the assumption that the missing data on disease status are missing at random (MAR), that is, the probability of missingness depends on the true (missing) disease status only through the test result and observed covariate information. When some of the covariates are continuous, or the number of covariates is relatively large, the existing methods require parametric models for the probability of disease or the probability of verification (given the test result and covariates), and hence are subject to model misspecification. We propose a new method for correcting verification bias based on the propensity score, defined as the predicted probability of verification given the test result and observed covariates. This is estimated separately for those with positive and negative test results. The new method classifies the verified sample into several subsamples that have homogeneous propensity scores and allows correction for verification bias. Simulation studies demonstrate that the new estimators are more robust to model misspecification than existing methods, but still perform well when the models for the probability of disease and probability of verification are correctly specified. PMID:21856650

On the Run-Time Optimization of the Boolean Logic of a Program.

ERIC Educational Resources Information Center

Cadolino, C.; Guazzo, M.

1982-01-01

Considers problem of optimal scheduling of Boolean expression (each Boolean variable represents binary outcome of program module) on single-processor system. Optimization discussed consists of finding operand arrangement that minimizes average execution costs representing consumption of resources (elapsed time, main memory, number of…

PREventing Maternal And Neonatal Deaths (PREMAND): a study protocol for examining social and cultural factors contributing to infant and maternal deaths and near-misses in rural northern Ghana.

PubMed

Moyer, Cheryl A; Aborigo, Raymond A; Kaselitz, Elizabeth B; Gupta, Mira L; Oduro, Abraham; Williams, John

2016-03-09

While Ghana is a leader in some health indicators among West African nations, it still struggles with high maternal and neonatal morbidity and mortality rates, especially in the northern areas. The clinical causes of mortality and morbidity are relatively well understood in Ghana, but little is known about the impact of social and cultural factors on maternal and neonatal outcomes. Less still is understood about how such factors may vary by geographic location, and how such variability may inform locally-tailored solutions. Preventing Maternal And Neonatal Deaths (PREMAND) is a three-year, three-phase project that takes place in four districts in the Upper East, Upper West, and Northern Regions of Ghana. PREMAND will prospectively identify all maternal and neonatal deaths and 'near-misses', or those mothers and babies who survive a life threatening complication, in the project districts. Each event will be followed by either a social autopsy (in the case of deaths) or a sociocultural audit (in the case of near-misses). Geospatial technology will be used to visualize the variability in outcomes as well as the social, cultural, and clinical predictors of those outcomes. Data from PREMAND will be used to generate maps for local leaders, community members and Government of Ghana to identify priority areas for intervention. PREMAND is an effort of the Navrongo Health Research Centre and the University of Michigan Medical School. PREMAND uses an innovative, multifaceted approach to better understand and address neonatal and maternal morbidity and mortality in northern Ghana. It will provide unprecedented access to information on the social and cultural factors that contribute to deaths and near-misses in the project regions, and will allow such causal factors to be situated geographically. PREMAND will create the opportunity for local, regional, and national stakeholders to see how these events cluster, and place them relative to traditional healer compounds, health facilities, and other important geographic markers. Finally, PREMAND will enable local communities to generate their own solutions to maternal and neonatal morbidity and mortality, an effort that has great potential for long-term impact.

Time-to-event methodology improved statistical evaluation in register-based health services research.

PubMed

Bluhmki, Tobias; Bramlage, Peter; Volk, Michael; Kaltheuner, Matthias; Danne, Thomas; Rathmann, Wolfgang; Beyersmann, Jan

2017-02-01

Complex longitudinal sampling and the observational structure of patient registers in health services research are associated with methodological challenges regarding data management and statistical evaluation. We exemplify common pitfalls and want to stimulate discussions on the design, development, and deployment of future longitudinal patient registers and register-based studies. For illustrative purposes, we use data from the prospective, observational, German DIabetes Versorgungs-Evaluation register. One aim was to explore predictors for the initiation of a basal insulin supported therapy in patients with type 2 diabetes initially prescribed to glucose-lowering drugs alone. Major challenges are missing mortality information, time-dependent outcomes, delayed study entries, different follow-up times, and competing events. We show that time-to-event methodology is a valuable tool for improved statistical evaluation of register data and should be preferred to simple case-control approaches. Patient registers provide rich data sources for health services research. Analyses are accompanied with the trade-off between data availability, clinical plausibility, and statistical feasibility. Cox' proportional hazards model allows for the evaluation of the outcome-specific hazards, but prediction of outcome probabilities is compromised by missing mortality information. Copyright © 2016 Elsevier Inc. All rights reserved.

Outcomes of conception subsequent to methotrexate treatment for an unruptured ectopic pregnancy.

PubMed

Svirsky, Ran; Ben-Ami, Ido; Berkovitch, Matitiahu; Halperin, Reuvit; Rozovski, Uri

2017-11-01

To assess the risk of adverse pregnancy outcomes in subsequent pregnancies among women treated with methotrexate for ectopic pregnancy. In a retrospective single-center study, data were assessed for women treated with methotrexate for ectopic pregnancy at Asaf Harofe Medical Center, Zerifin, Israel, between May 2004 and May 2014. Overall, 226 women were treated with methotrexate for ectopic pregnancy and subsequently conceived. The median time from treatment to conception was 10 months (range 1-120 months), and 127 women conceived within 12 months of treatment. Except for early missed abortion-which affected 23 (10.2%) pregnancies-adverse pregnancy outcomes such as fetal malformations were rare. The frequency of early abortion was lowest for women who conceived within 6 months of treatment with methotrexate (3/93, 3.2%), increased between 6 and 23 months (15/83, 18.1%), and remained high thereafter (7/50, 14.0%; P=0.006). The frequency of fetal malformation in a subsequent pregnancy was low among women treated with methotrexate for ectopic pregnancy. The frequency of early missed abortion was lowest during the first 6 months after treatment with methotrexate. © 2017 International Federation of Gynecology and Obstetrics.

The sex and age of older adults influence the outcome of induced trips.

PubMed

Pavol, M J; Owings, T M; Foley, K T; Grabiner, M D

1999-02-01

Falls are a significant source of morbidity and mortality in older adults, with up to 53% of these falls due to tripping. To aid in fall prevention, there is a need to identify the factors that determine whether a trip is recoverable and those factors that increase an older adult's risk of falling. Trips were induced during gait in 79 healthy, community-dwelling, safety-harnessed older adults (50 women) using a concealed, mechanical obstacle. Trip outcomes were graded as recoveries, falls, rope-assists, or misses. Kinematics were recorded during normal gait, without and with the safety harness. Selected gait parameters were compared to determine whether the experimental conditions affected gait at the time of the trip. Thirty-nine trip outcomes were classified as recoveries, 10 as falls, 12 as rope-assists, and 18 as misses. Women fell more than four times as frequently as men. Women younger than 70 years fell more than three times as frequently as those older. Trip outcomes in the men were essentially unaffected by age. The foot obstructed to induce the trip did not affect the trip outcome. The presence of the safety harness had almost no effect on gait. The length of the stride preceding the trip did not differ from normal. The majority of trips in healthy older adults did not result in falls. Older women were more likely than men to fall following a trip. The likelihood of falling from a trip was greatest in the youngest older women.

Results of Database Studies in Spine Surgery Can Be Influenced by Missing Data.

PubMed

Basques, Bryce A; McLynn, Ryan P; Fice, Michael P; Samuel, Andre M; Lukasiewicz, Adam M; Bohl, Daniel D; Ahn, Junyoung; Singh, Kern; Grauer, Jonathan N

2017-12-01

National databases are increasingly being used for research in spine surgery; however, one limitation of such databases that has received sparse mention is the frequency of missing data. Studies using these databases often do not emphasize the percentage of missing data for each variable used and do not specify how patients with missing data are incorporated into analyses. This study uses the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database to examine whether different treatments of missing data can influence the results of spine studies. (1) What is the frequency of missing data fields for demographics, medical comorbidities, preoperative laboratory values, operating room times, and length of stay recorded in ACS-NSQIP? (2) Using three common approaches to handling missing data, how frequently do those approaches agree in terms of finding particular variables to be associated with adverse events? (3) Do different approaches to handling missing data influence the outcomes and effect sizes of an analysis testing for an association with these variables with occurrence of adverse events? Patients who underwent spine surgery between 2005 and 2013 were identified from the ACS-NSQIP database. A total of 88,471 patients undergoing spine surgery were identified. The most common procedures were anterior cervical discectomy and fusion, lumbar decompression, and lumbar fusion. Demographics, comorbidities, and perioperative laboratory values were tabulated for each patient, and the percent of missing data was noted for each variable. These variables were tested for an association with "any adverse event" using three separate multivariate regressions that used the most common treatments for missing data. In the first regression, patients with any missing data were excluded. In the second regression, missing data were treated as a negative or "reference" value; for continuous variables, the mean of each variable's reference range was computed and imputed. In the third regression, any variables with > 10% rate of missing data were removed from the regression; among variables with ≤ 10% missing data, individual cases with missing values were excluded. The results of these regressions were compared to determine how the different treatments of missing data could affect the results of spine studies using the ACS-NSQIP database. Of the 88,471 patients, as many as 4441 (5%) had missing elements among demographic data, 69,184 (72%) among comorbidities, 70,892 (80%) among preoperative laboratory values, and 56,551 (64%) among operating room times. Considering the three different treatments of missing data, we found different risk factors for adverse events. Of 44 risk factors found to be associated with adverse events in any analysis, only 15 (34%) of these risk factors were common among the three regressions. The second treatment of missing data (assuming "normal" value) found the most risk factors (40) to be associated with any adverse event, whereas the first treatment (deleting patients with missing data) found the fewest associations at 20. Among the risk factors associated with any adverse event, the 10 with the greatest effect size (odds ratio) by each regression were ranked. Of the 15 variables in the top 10 for any regression, six of these were common among all three lists. Differing treatments of missing data can influence the results of spine studies using the ACS-NSQIP. The current study highlights the importance of considering how such missing data are handled. Until there are better guidelines on the best approaches to handle missing data, investigators should report how missing data were handled to increase the quality and transparency of orthopaedic database research. Readers of large database studies should note whether handling of missing data was addressed and consider potential bias with high rates or unspecified or weak methods for handling missing data.

Patient-reported outcome measures in arthroplasty registries

PubMed Central

Bohm, Eric; Franklin, Patricia; Lyman, Stephen; Denissen, Geke; Dawson, Jill; Dunn, Jennifer; Eresian Chenok, Kate; Dunbar, Michael; Overgaard, Søren; Garellick, Göran; Lübbeke, Anne

2016-01-01

Abstract — The International Society of Arthroplasty Registries (ISAR) Patient-Reported Outcome Measures (PROMs) Working Group have evaluated and recommended best practices in the selection, administration, and interpretation of PROMs for hip and knee arthroplasty registries. The 2 generic PROMs in common use are the Short Form health surveys (SF-36 or SF-12) and EuroQol 5-dimension (EQ-5D). The Working Group recommends that registries should choose specific PROMs that have been appropriately developed with good measurement properties for arthroplasty patients. The Working Group recommend the use of a 1-item pain question (“During the past 4 weeks, how would you describe the pain you usually have in your [right/left] [hip/knee]?”; response: none, very mild, mild, moderate, or severe) and a single-item satisfaction outcome (“How satisfied are you with your [right/left] [hip/knee] replacement?”; response: very unsatisfied, dissatisfied, neutral, satisfied, or very satisfied). Survey logistics include patient instructions, paper- and electronic-based data collection, reminders for follow-up, centralized as opposed to hospital-based follow-up, sample size, patient- or joint-specific evaluation, collection intervals, frequency of response, missing values, and factors in establishing a PROMs registry program. The Working Group recommends including age, sex, diagnosis at joint, general health status preoperatively, and joint pain and function score in case-mix adjustment models. Interpretation and statistical analysis should consider the absolute level of pain, function, and general health status as well as improvement, missing data, approaches to analysis and case-mix adjustment, minimal clinically important difference, and minimal detectable change. The Working Group recommends data collection immediately before and 1 year after surgery, a threshold of 60% for acceptable frequency of response, documentation of non-responders, and documentation of incomplete or missing data. PMID:27228230

Solutions for filling gaps in accountable care measure sets.

PubMed

Valuck, Tom; Dugan, Donna; Dubois, Robert W; Westrich, Kimberly; Penso, Jerry; McClellan, Mark

2015-10-01

A primary objective of accountable care is to support providers in reforming care to improve outcomes and lower costs. Gaps in accountable care measure sets may cause missed opportunities for improvement and missed signals of problems in care. Measures to balance financial incentives may be particularly important for high-cost conditions or specialty treatments. This study explored gaps in measure sets for specific conditions and offers strategies for more comprehensive measurement that do not necessarily require more measures. A descriptive analysis of measure gaps in accountable care programs and proposed solutions for filling the gaps. We analyzed gaps in 2 accountable care organization measure sets for 20 high-priority clinical conditions by comparing the measures in those sets with clinical guidelines and assessing the use of outcome measures. Where we identified gaps, we looked for existing measures to address the gaps. Gaps not addressed by existing measures were considered areas for measure development or measurement strategy refinement. We found measure gaps across all 20 conditions, including those conditions that are commonly addressed in current measure sets. In addition, we found many gaps that could not be filled by existing measures. Results across all 20 conditions informed recommendations for measure set improvement. Addressing all gaps in accountable care measure sets with more of the same types of measures and approaches to measurement would require an impractical number of measures and would miss the opportunity to use better measures and innovative approaches. Strategies for effectively filling measure gaps include using preferred measure types such as cross-cutting, outcome, and patient-reported measures. Program implementers should also apply new approaches to measurement, including layered and modular models.

Evaluation of the ProPublica Surgeon Scorecard "Adjusted Complication Rate" Measure Specifications.

PubMed

Ban, Kristen A; Cohen, Mark E; Ko, Clifford Y; Friedberg, Mark W; Stulberg, Jonah J; Zhou, Lynn; Hall, Bruce L; Hoyt, David B; Bilimoria, Karl Y

2016-10-01

The ProPublica Surgeon Scorecard is the first nationwide, multispecialty public reporting of individual surgeon outcomes. However, ProPublica's use of a previously undescribed outcome measure (composite of in-hospital mortality or 30-day related readmission) and inclusion of only inpatients have been questioned. Our objectives were to (1) determine the proportion of cases excluded by ProPublica's specifications, (2) assess the proportion of inpatient complications excluded from ProPublica's measure, and (3) examine the validity of ProPublica's outcome measure by comparing performance on the measure to well-established postoperative outcome measures. Using ACS-NSQIP data (2012-2014) for 8 ProPublica procedures and for All Operations, the proportion of cases meeting all ProPublica inclusion criteria was determined. We assessed the proportion of complications occurring inpatient, and thus not considered by ProPublica's measure. Finally, we compared risk-adjusted performance based on ProPublica's measure specifications to established ACS-NSQIP outcome measure performance (eg, death/serious morbidity, mortality). ProPublica's inclusion criteria resulted in elimination of 82% of all operations from assessment (range: 42% for total knee arthroplasty to 96% for laparoscopic cholecystectomy). For all ProPublica operations combined, 84% of complications occur during inpatient hospitalization (range: 61% for TURP to 88% for total hip arthroplasty), and are thus missed by the ProPublica measure. Hospital-level performance on the ProPublica measure correlated weakly with established complication measures, but correlated strongly with readmission (R = 0.834, P < 0.001). ProPublica's outcome measure specifications exclude 82% of cases, miss 84% of postoperative complications, and correlate poorly with well-established postoperative outcomes. Thus, the validity of the ProPublica Surgeon Scorecard is questionable.

Reporting and Methodology of Multivariable Analyses in Prognostic Observational Studies Published in 4 Anesthesiology Journals: A Methodological Descriptive Review.

PubMed

Guglielminotti, Jean; Dechartres, Agnès; Mentré, France; Montravers, Philippe; Longrois, Dan; Laouénan, Cedric

2015-10-01

Prognostic research studies in anesthesiology aim to identify risk factors for an outcome (explanatory studies) or calculate the risk of this outcome on the basis of patients' risk factors (predictive studies). Multivariable models express the relationship between predictors and an outcome and are used in both explanatory and predictive studies. Model development demands a strict methodology and a clear reporting to assess its reliability. In this methodological descriptive review, we critically assessed the reporting and methodology of multivariable analysis used in observational prognostic studies published in anesthesiology journals. A systematic search was conducted on Medline through Web of Knowledge, PubMed, and journal websites to identify observational prognostic studies with multivariable analysis published in Anesthesiology, Anesthesia & Analgesia, British Journal of Anaesthesia, and Anaesthesia in 2010 and 2011. Data were extracted by 2 independent readers. First, studies were analyzed with respect to reporting of outcomes, design, size, methods of analysis, model performance (discrimination and calibration), model validation, clinical usefulness, and STROBE (i.e., Strengthening the Reporting of Observational Studies in Epidemiology) checklist. A reporting rate was calculated on the basis of 21 items of the aforementioned points. Second, they were analyzed with respect to some predefined methodological points. Eighty-six studies were included: 87.2% were explanatory and 80.2% investigated a postoperative event. The reporting was fairly good, with a median reporting rate of 79% (75% in explanatory studies and 100% in predictive studies). Six items had a reporting rate <36% (i.e., the 25th percentile), with some of them not identified in the STROBE checklist: blinded evaluation of the outcome (11.9%), reason for sample size (15.1%), handling of missing data (36.0%), assessment of colinearity (17.4%), assessment of interactions (13.9%), and calibration (34.9%). When reported, a few methodological shortcomings were observed, both in explanatory and predictive studies, such as an insufficient number of events of the outcome (44.6%), exclusion of cases with missing data (93.6%), or categorization of continuous variables (65.1%.). The reporting of multivariable analysis was fairly good and could be further improved by checking reporting guidelines and EQUATOR Network website. Limiting the number of candidate variables, including cases with missing data, and not arbitrarily categorizing continuous variables should be encouraged.

Telephone-based Assessments to Minimize Missing Data in Longitudinal Depression Trials: A Project IMPACTS Study Report

PubMed Central

Claassen, Cindy; Kurian, Ben; Trivedi, Madhukar H.; Grannemann, Bruce D.; Tuli, Ekta; Pipes, Ronny; Preston, Anne Marie; Flood, Ariell

2012-01-01

Purpose Missing data in clinical efficacy and effectiveness trials continue to be a major threat to the validity of study findings. The purpose of this report is to describe methods developed to ensure completion of outcome assessments with public mental health sector subjects participating in a longitudinal, repeated measures study for the treatment of major depressive disorder. We developed longitudinal assessment procedures that included telephone-based clinician interviews in order to minimize missing data commonly encountered with face-to-face assessment procedures. Methods A pre-planned, multi-step strategy was developed to ensure completeness of data collection. The procedure included obtaining multiple pieces of patient contact information at baseline, careful education of both staff and patients concerning the purpose of assessments, establishing good patient rapport, and finally being flexible and persistent with phone appointments to ensure the completion of telephone-based follow-up assessments. A well-developed administrative and organizational structure was also put in place prior to study implementation. Results The assessment completion rate for the primary outcome for 310 of 504 subjects who enrolled and completed 52 weeks (at the time of manuscript) of telephone-based follow-up assessments was 96.8%. Conclusion By utilizing telephone-based follow-up procedures and adapting our easy-to-use pre-defined multi-step approach, researchers can maximize patient data retention in longitudinal studies. PMID:18761427

Adaptive allocation for binary outcomes using decreasingly informative priors.

PubMed

Sabo, Roy T

2014-01-01

A method of outcome-adaptive allocation is presented using Bayes methods, where a natural lead-in is incorporated through the use of informative yet skeptical prior distributions for each treatment group. These prior distributions are modeled on unobserved data in such a way that their influence on the allocation scheme decreases as the trial progresses. Simulation studies show this method to behave comparably to the Bayesian adaptive allocation method described by Thall and Wathen (2007), who incorporate a natural lead-in through sample-size-based exponents.

Measuring Intervention Effectiveness: The Benefits of an Item Response Theory Approach

ERIC Educational Resources Information Center

McEldoon, Katherine; Cho, Sun-Joo; Rittle-Johnson, Bethany

2012-01-01

Assessing the effectiveness of educational interventions relies on quantifying differences between interventions groups over time in a between-within design. Binary outcome variables (e.g., correct responses versus incorrect responses) are often assessed. Widespread approaches use percent correct on assessments, and repeated measures analysis of…

Feasibility of Community Food Item Collection for the National Children's Study

EPA Science Inventory

The National Children’s Study proposes to investigate the role of contaminants on health outcomes in pregnant women and children. A specific area of concern is contaminant exposure through the ingestion of solid foods. National food contaminant databases may miss environmental ex...

Statistical Discourse Analysis: A Method for Modelling Online Discussion Processes

ERIC Educational Resources Information Center

Chiu, Ming Ming; Fujita, Nobuko

2014-01-01

Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non-sequential messages), outcome variables (discrete…

The (Missing) Link between Instruction and Assessment

ERIC Educational Resources Information Center

Gurvitch, Rachel; Lund, Jackie

2011-01-01

Many physical educators understand the important role formative assessment has on their teaching and student learning outcomes. However, when carefully examining different physical education settings they learn instruction is oftentimes disconnected from assessment. When talking about assessment, educators first need to distinguish between the two…

Editorial: Let's talk about sex - the gender binary revisited.

PubMed

Oldehinkel, Albertine J

2017-08-01

Sex refers to biological differences and gender to socioculturally delineated masculine and feminine roles. Sex or gender are included as a covariate or effect modifier in the majority of child psychology and psychiatry studies, and differences found between boys and girls have inspired many researchers to postulate underlying mechanisms. Empirical tests of whether including these proposed explanatory variables actually reduces the variance explained by gender are lagging behind somewhat. That is a pity, because a lot can be gained from a greater focus on the active agents of specific gender differences. As opposed to biological sex as such, some of the processes explaining why a specific outcome shows gender differences may be changeable and so possible prevention targets. Moreover, while the sex binary may be reasonable adequate as a classification variable, the gender binary is far from perfect. Gender is a multidimensional, partly context-dependent factor, and the dichotomy generally used in research does not do justice to the diversity existing within boys and girls. © 2017 Association for Child and Adolescent Mental Health.

How much of the income inequality effect can be explained by public policy? Evidence from oral health in Brazil.

PubMed

Celeste, Roger Keller; Nadanovsky, Paulo

2010-10-01

To evaluate the association between income inequality, a public policy scale and to oral health. Analysis, using the Brazilian oral health survey in 2002-2003, included 23,573 15-19-year-old subjects clustered in 330 municipalities. Missing and decayed teeth and malocclusion assessments were the outcomes. Gini coefficient and a novel Scale of Municipal Public Policies were the main exposure variables. Individual level covariates were used as controls in multilevel regressions. An increase from the lowest to the highest Gini value in Brazil was associated with an increase in the number of missing (rate ratio, RR=2.11 confidence interval 95% 1.18-3.77) and decayed teeth (RR=2.92 CI 95% 1.83-4.65). After adjustment for public policies and water fluoridation, the Gini effect was non-significant and public policies explained most of the variation in missing and decayed teeth. The public policy scale remained significant after adjustment with a rate ratio of 0.64 for missing and 0.72 for decayed teeth. Neither Gini nor public policies were significantly related to malocclusion. The public policy effect on missing and decayed teeth was stronger among those with higher education and income. Income inequality effect was explained mainly by public policies, which had an independent effect that was greater among the better-off. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

PubMed Central

Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

PubMed

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

2013-10-30

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

News From The Erebos Project

NASA Astrophysics Data System (ADS)

Schaffenroth, Veronika; Barlow, Brad; Geier, Stephan; Vučković, Maja; Kilkenny, Dave; Schaffenroth, Johannes

2017-12-01

Planets and brown dwarfs in close orbits will interact with their host stars, as soon as the stars evolve to become red giants. However, the outcome of those interactions is still unclear. Recently, several brown dwarfs have been discovered orbiting hot subdwarf stars at very short orbital periods of 0.065 - 0.096 d. More than 8% of the close hot subdwarf binaries might have sub-stellar companions. This shows that such companions can significantly affect late stellar evolution and that sdB binaries are ideal objects to study this influence. Thirty-eight new eclipsing sdB binary systems with cool low-mass companions and periods from 0.05 to 0.5 d were discovered based on their light curves by the OGLE project. In the recently published catalog of eclipsing binaries in the Galactic bulge, we discovered 75 more systems. We want to use this unique and homogeneously selected sample to derive the mass distribution of the companions, constrain the fraction of sub-stellar companions and determine the minimum mass needed to strip off the red-giant envelope. We are especially interested in testing models that predict hot Jupiter planets as possible companions. Therefore, we started the EREBOS (Eclipsing Reflection Effect Binaries from the OGLE Survey) project, which aims at analyzing those new HW Vir systems based on a spectroscopic and photometric follow up. For this we were granted an ESO Large Program for ESO-VLT/FORS2. Here we give an update on the the current status of the project and present some preliminary results.

Adherence barriers to chronic dialysis in the United States.

PubMed

Chan, Kevin E; Thadhani, Ravi I; Maddux, Franklin W

2014-11-01

Hemodialysis patients often do not attend their scheduled treatment session. We investigated factors associated with missed appointments and whether such nonadherence poses significant harm to patients and increases overall health care utilization in an observational analysis of 44 million hemodialysis treatments for 182,536 patients with ESRD in the United States. We assessed the risk of hospitalization, emergency room visit, or intensive-coronary care unit (ICU-CCU) admission in the 2 days after a missed treatment relative to the risk for patients who received hemodialysis. Over the 5-year study period, the average missed treatment rate was 7.1 days per patient-year. In covariate adjusted logistic regression, the risk of hospitalization (odds ratio [OR], 3.98; 95% confidence interval [95% CI], 3.93 to 4.04), emergency room visit (OR, 2.00; 95% CI, 1.87 to 2.14), or ICU-CCU admission (OR, 3.89; 95% CI, 3.81 to 3.96) increased significantly after a missed treatment. Overall, 0.9 missed treatment days per year associated with suboptimal transportation to dialysis, inclement weather, holidays, psychiatric illness, pain, and gastrointestinal upset. These barriers also associated with excess hospitalization (5.6 more events per patient-year), emergency room visits (1.1 more visits), and ICU-CCU admissions (0.8 more admissions). In conclusion, poor adherence to hemodialysis treatments may be a substantial roadblock to achieving better patient outcomes. Addressing systemic and patient barriers that impede access to hemodialysis care may decrease missed appointments and reduce patient morbidity. Copyright © 2014 by the American Society of Nephrology.

Household water insecurity, missed schooling, and the mediating role of caregiver depression in rural Uganda.

PubMed

Cooper-Vince, C E; Kakuhikire, B; Vorechovska, D; McDonough, A Q; Perkins, J; Venkataramani, A S; Mushavi, R C; Baguma, C; Ashaba, S; Bangsberg, D R; Tsai, A C

2017-01-01

School attendance rates in sub-Saharan Africa are among the lowest worldwide, placing children at heightened risk for poor educational and economic outcomes. One understudied risk factor for missed schooling is household water insecurity, which is linked to depression among women and may increase children's water-fetching burden at the expense of educational activities, particularly among children of depressed caregivers. In this study conducted in rural Uganda, we assessed the association between household water insecurity and child school participation and the mediating pathways behind these associations. We conducted a population-based, cross-sectional study of female household heads ( N = 257) and their children ages 5-17 ( N = 551) in the rural regions surrounding the town of Mbarara, in southwestern Uganda. We used multivariable linear regressions to estimate the association between water insecurity and missed schooling. We then assessed the extent to which the association was mediated by caregiver depression. Among children, water insecurity had a statistically significant association with the number of missed school days (a standard deviation increase in water insecurity resulted in 0.30 more missed school days in the last week). The estimated association was partially mediated by caregiver depression. When stratified by sex, this mediating pathway remained significant for boys, but not among girls. Water insecurity is a risk factor for missed schooling among children in rural Uganda. Caregiver depression partially mediated this relationship. Also addressing caregiver mental health in water insecure families may more fully address the needs of sub-Saharan African families and promote educational participation among youth.

A Randomized, Double-Blind, Placebo-Controlled Trial of Citicoline for Cocaine Dependence in Bipolar I Disorder.

PubMed

Brown, E Sherwood; Todd, Jackie Peterson; Hu, Lisa T; Schmitz, Joy M; Carmody, Thomas J; Nakamura, Alyson; Sunderajan, Prabha; Rush, A John; Adinoff, Bryon; Bret, Mary Ellen; Holmes, Traci; Lo, Alexander

2015-10-01

Although drug dependence is common in patients with bipolar disorder, minimal data are available on the treatment of drug dependence in this patient population. The authors previously reported a decreased risk of relapse to cocaine use in a pilot study of citicoline in patients with bipolar disorder and cocaine dependence. The primary aim of the present study was to determine whether citicoline reduces cocaine use in outpatients with bipolar I disorder and current cocaine dependence and active cocaine use. A total of 130 outpatients with bipolar I disorder (depressed or mixed mood state) and cocaine dependence received citicoline or placebo add-on therapy for 12 weeks. Results of thrice-weekly urine drug screens were analyzed using a generalized linear mixed model that was fitted to the binary outcome of cocaine-positive screens at each measurement occasion for 12 weeks. Mood was assessed with the Inventory of Depressive Symptomatology-Self Report, the Hamilton Depression Rating Scale, and the Young Mania Rating Scale. In the intent-to-treat sample (N=61 in both groups), significant treatment group and group-by-time effects were observed, whether or not missing urine screens were imputed as cocaine positive. The group effect was greatest early in the study and tended to decline with time. No between-group differences in mood symptoms or side effects were observed. Citicoline was well tolerated for treatment of cocaine dependence in patients with bipolar disorder. Cocaine use was significantly reduced with citicoline initially, although treatment effects diminished over time, suggesting the need for augmentation strategies to optimize long-term benefit.

Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie

2014-11-20

Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection

USGS Publications Warehouse

Jarnevich, Catherine S.; Talbert, Marian; Morisette, Jeffrey T.; Aldridge, Cameron L.; Brown, Cynthia; Kumar, Sunil; Manier, Daniel; Talbert, Colin; Holcombe, Tracy R.

2017-01-01

Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pseudo-absence locations, and method choice affects model outcomes. We evaluated combinations of both model algorithms (simple and complex generalized linear models, multivariate adaptive regression splines, Maxent, boosted regression trees, and random forest) and background methods (random, minimum convex polygon, and continuous and binary kernel density estimator (KDE)) to assess the sensitivity of model outcomes to choices made. We evaluated six questions related to model results, including five beyond the common comparison of model accuracy assessment metrics (biological interpretability of response curves, cross-validation robustness, independent data accuracy and robustness, and prediction consistency). For our case study with cheatgrass in the western US, random forest was least sensitive to background choice and the binary KDE method was least sensitive to model algorithm choice. While this outcome may not hold for other locations or species, the methods we used can be implemented to help determine appropriate methodologies for particular research questions.

Causal inference in survival analysis using pseudo-observations.

PubMed

Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

2017-07-30

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Drug-Coated Balloon vs. Conventional Balloon Angioplasty in Dialysis Patients With Symptomatic Femoropopliteal Disease　- A Matched Comparison.

PubMed

Chou, Hsin-Hua; Huang, Hsuan-Li; Hsieh, Chien-An; Jang, Shih-Jung; Tzeng, I-Shiang; Ko, Yu-Lin

2018-04-26

Recent randomized trials have shown the treatment benefits of use of a drug-coated balloon (DCB) over conventional percutaneous transluminal angioplasty (PTA) in patients with femoropopliteal disease. However, the effectiveness and safety of DCB for dialysis patients remain unclear.Methods and Results:Consecutive dialysis patients, who underwent PTA or DCB for femoropopliteal disease, were assessed retrospectively via 2:1 propensity score matching. Effectiveness and safety endpoints, including binary restenosis, clinically driven target lesion revascularization (CD-TLR), amputations, major adverse cardiac events (MACE), and deaths, were compared between groups. A total of 278 dialysis patients with 339 limbs were eligible for matching: 84 limbs from 77 patients treated with PTA and 46 limbs from 37 patients treated with DCB were compared after matching. Baseline patient and lesion characteristics were not different between groups. Patients treated with DCB had significantly higher rates of freedom from binary restenosis (52.4% vs. 18.6%, P<0.001) and CD-TLR (56.4% vs. 25.9%, P=0.001) at 2 years compared with patients treated with PTA. Both groups had similar outcomes for amputation, MACE, and death. Cox proportional analysis showed that treatment with DCB was independently associated with a reduction of binary restenosis (hazard ratio [HR] 0.368, P=0.001) and CD-TLR (HR 0.390, P=0.004). This study suggested superior 2-year outcomes using DCB compared with PTA and similar safety profiles in dialysis patients with femoropopliteal disease.

The Completeness of Intervention Descriptions in Randomised Trials of Supervised Exercise Training in Peripheral Arterial Disease

PubMed Central

Tew, Garry A.; Brabyn, Sally; Cook, Liz; Peckham, Emily

2016-01-01

Research supports the use of supervised exercise training as a primary therapy for improving the functional status of people with peripheral arterial disease (PAD). Several reviews have focused on reporting the outcomes of exercise interventions, but none have critically examined the quality of intervention reporting. Adequate reporting of the exercise protocols used in randomised controlled trials (RCTs) is central to interpreting study findings and translating effective interventions into practice. The purpose of this review was to evaluate the completeness of intervention descriptions in RCTs of supervised exercise training in people with PAD. A systematic search strategy was used to identify relevant trials published until June 2015. Intervention description completeness in the main trial publication was assessed using the Template for Intervention Description and Replication checklist. Missing intervention details were then sought from additional published material and by emailing authors. Fifty-eight trials were included, reporting on 76 interventions. Within publications, none of the interventions were sufficiently described for all of the items required for replication; this increased to 24 (32%) after contacting authors. Although programme duration, and session frequency and duration were well-reported in publications, complete descriptions of the equipment used, intervention provider, and number of participants per session were missing for three quarters or more of interventions (missing for 75%, 93% and 80% of interventions, respectively). Furthermore, 20%, 24% and 26% of interventions were not sufficiently described for the mode of exercise, intensity of exercise, and tailoring/progression, respectively. Information on intervention adherence/fidelity was also frequently missing: attendance rates were adequately described for 29 (38%) interventions, whereas sufficient detail about the intensity of exercise performed was presented for only 8 (11%) interventions. Important intervention details are commonly missing for supervised exercise programmes in the PAD trial literature. This has implications for the interpretation of outcome data, the investigation of dose-response effects, and the replication of protocols in future studies and clinical practice. Researchers should be mindful of intervention reporting guidelines when attempting to publish information about supervised exercise programmes, regardless of the population being studied. PMID:26938879

The Rapid Benefit Indicators (RBI) Approach: A Process for Assessing the Social Benefits of Ecological Restoration

EPA Science Inventory

Environmental managers face difficult decisions about allocating resources to the most beneficial projects. Focusing solely on ecological outcomes can lead to missed opportunities to provide social benefits, yet few methods exist to easily compare the social benefits of ecologica...

ICT and Pedagogy: Opportunities Missed?

ERIC Educational Resources Information Center

Adams, Paul

2011-01-01

The pace of Information and Communications Technology (ICT) development necessitates radical and rapid change for education. Given the English prevalence for an economically determinist orientation for educational outcomes, it seems pertinent to ask how learning in relation to ICT is to be conceptualised. Accepting the view that education needs to…

Spirituality, Religiousness, and Alcoholism Treatment Outcomes: A Comparison between Black and White Participants

PubMed Central

Krentzman, Amy R.; Farkas, Kathleen J.; Townsend, Aloen L.

2012-01-01

This study addresses an unexplained finding in the alcoholism treatment field: despite the health and socioeconomic disparities that exist between blacks and whites at intake, blacks and whites achieve equivalent treatment outcomes. Using Project MATCH data, this study explores religiousness and spirituality as strengths in the African American community that may account in part for equivalent outcomes. Using binary logistic regression, this study found that as purpose in life increased, blacks were more likely to achieve sobriety than whites. This study provides evidence that purpose in life is a cultural strength and an advantage among blacks in achieving sobriety. PMID:22707846

Black holes, disks, and jets following binary mergers and stellar collapse: The narrow range of electromagnetic luminosities and accretion rates.

PubMed

Shapiro, Stuart L

2017-05-15

We have performed magnetohydrodynamic simulations in general relativity of binary neutron star and binary black hole-neutron star mergers, as well as the magnetorotational collapse of supermassive stars. In many cases the outcome is a spinnng black hole (BH) immersed in a magnetized disk, with a jet emanating from the poles of the BH. While their formation scenarios differ and their BH masses, as well as their disk masses, densities, and magnetic field strengths, vary by orders of magnitude, these features conspire to generate jet Poynting luminosities that all lie in the same, narrow range of ~10 52±1 erg s -1 . A similar result applies to their BH accretion rates upon jet launch, which is ~0.1-10 M ⊙ s -1 . We provide a simple model that explains these unanticipated findings. Interestingly, these luminosities reside in the same narrow range characterizing the observed luminosity distributions of over 400 short and long GRBs with distances inferred from spectroscopic redshifts or host galaxies. This result, together with the GRB lifetimes predicted by the model, supports the belief that a compact binary merger is the progenitor of an SGRB, while a massive, stellar magnetorotational collapse is the progenitor of an LGRB.

Black holes, disks, and jets following binary mergers and stellar collapse: The narrow range of electromagnetic luminosities and accretion rates

PubMed Central

Shapiro, Stuart L.

2018-01-01

We have performed magnetohydrodynamic simulations in general relativity of binary neutron star and binary black hole-neutron star mergers, as well as the magnetorotational collapse of supermassive stars. In many cases the outcome is a spinnng black hole (BH) immersed in a magnetized disk, with a jet emanating from the poles of the BH. While their formation scenarios differ and their BH masses, as well as their disk masses, densities, and magnetic field strengths, vary by orders of magnitude, these features conspire to generate jet Poynting luminosities that all lie in the same, narrow range of ~1052±1 erg s−1. A similar result applies to their BH accretion rates upon jet launch, which is ~0.1–10 M⊙ s−1. We provide a simple model that explains these unanticipated findings. Interestingly, these luminosities reside in the same narrow range characterizing the observed luminosity distributions of over 400 short and long GRBs with distances inferred from spectroscopic redshifts or host galaxies. This result, together with the GRB lifetimes predicted by the model, supports the belief that a compact binary merger is the progenitor of an SGRB, while a massive, stellar magnetorotational collapse is the progenitor of an LGRB. PMID:29881790

Tenofovir stock shortages have limited impact on clinic- and patient-level HIV treatment outcomes in public sector clinics in South Africa.

PubMed

Brennan, Alana T; Bor, Jacob; Davies, Mary-Ann; Conradie, Francesca; Maskew, Mhairi; Long, Lawrence; Sanne, Ian; Fox, Matthew P

2017-02-01

Using data from four public sector clinics in South Africa, we sought to investigate provider- and patient-level outcomes, to understand how the 2012 tenofovir stock shortage affected the HIV care and monitoring of ART patients. Prospective cohort analysis of ART-naïve, non-pregnant, HIV-infected patients >18 years initiating first-line ART between 1 July 2011-31 March 2013. Linear regression was used for all outcomes (number of ART initiates, days between pharmacy visits, transfers, single-drug substitutions, treatment interruptions, missed pharmacy visits, loss to follow-up and elevated viral load). We fit splines to smooth curves with knots at the beginning (1 February 2012) and end (31 August 2012) of the stock shortage and displayed results graphically by clinic. Difference-in-difference models were used to evaluate the effect of the stock shortage on outcomes. Results suggest a potential shift in the management of patients during the shortage, mainly fewer average days between visits during the shortage vs. before or after at all four clinics, and a significant difference in the proportion of patients missing visits during vs. before (RD: 1.2%; 95% CI: 0.5%, 2.0%). No significant difference was seen in other outcomes. While South Africa has made great strides to extend access to ART and increase the quality of the health services provided, patient care can be affected when stock shortages/outs occur. While our results show little effect on treatment outcomes, this most likely reflects the clinics' ability to mitigate the crisis by continuing to keep patient care and treatment as consistent as possible. © 2016 John Wiley & Sons Ltd.

Shifts in reinforcement signalling while playing slot-machines as a function of prior experience and impulsivity

PubMed Central

Shao, R; Read, J; Behrens, T E J; Rogers, R D

2013-01-01

Electronic gaming machines (EGMs) offer significant revenue streams for mercantile gambling. However, limited clinical and experimental evidence suggests that EGMs are associated with heightened risks of clinically problematic patterns of play. Little is known about the neural structures that might mediate the transition from exploratory EGM play to the ‘addictive' play seen in problem gamblers; neither is it known how personality traits associated with gambling activity (and gambling problems) influence reinforcement processing while playing EGMs. Using functional magnetic resonance imaging in healthy participants, we show that a single episode of slot-machine play is subsequently associated with reduced amplitudes of blood-oxygenation-level-dependent signals within reinforcement-related structures, such as the ventral striatum and caudate nucleus, following winning game outcomes; but increased amplitudes of anticipatory signals within the ventral striatum and amygdala while watching the game reels spin. Trait impulsivity enhanced positive signals within the ventral striatum and amygdala following the delivery of winning outcomes but diminished positive signals following the experience of almost-winning ('near-misses'). These results indicate that a single episode of slot-machine play engages the well-characterised reinforcement-learning mechanisms mediated by ascending dopamine mesolimbic and mesostriatal pathways, to shift reward value of EGMs away from game outcomes towards anticipatory states. Impulsivity, itself linked to problem gambling and heightened vulnerability to other addictive disorders, is associated with divergent coding of winning outcomes and almost-winning experiences within the ventral striatum and amygdala, potentially enhancing the reward value of successful slot-machine game outcomes but, at the same time, modulating the aversive motivational consequences of near-miss outcomes. PMID:23321810

Processing and Probability Analysis of Pulsed Terahertz NDE of Corrosion under Shuttle Tile Data

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Madaras, Eric I.; Seebo, Jeffrey P.; Ely, Thomas M.

2009-01-01

This paper examines data processing and probability analysis of pulsed terahertz NDE scans of corrosion defects under a Shuttle tile. Pulsed terahertz data collected from an aluminum plate with fabricated corrosion defects and covered with a Shuttle tile is presented. The corrosion defects imaged were fabricated by electrochemically etching areas of various diameter and depth in the plate. In this work, the aluminum plate echo signal is located in the terahertz time-of-flight data and a threshold is applied to produce a binary image of sample features. Feature location and area are examined and identified as corrosion through comparison with the known defect layout. The results are tabulated with hit, miss, or false call information for a probability of detection analysis that is used to identify an optimal processing threshold.

Does the Anticipation of a Merit Grade Motivate Vocational Test-Takers?

ERIC Educational Resources Information Center

Johnson, Martin

2007-01-01

This study explores whether the anticipation of a graded (merit, pass, fail) test outcome rather than a binary (pass, fail) form of feedback influenced the motivation of learners taking a vocationally related test. Ninety-four students currently taking a vocationally related qualification were divided into control and experimental groups. Each…

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

PubMed

Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

GAC: Gene Associations with Clinical, a web based application

PubMed Central

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2018-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC. PMID:29263780

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

A Missing Link? Contemporary Insights into Principal Preparation and Training in Russia

ERIC Educational Resources Information Center

Bysik, Nadezhda; Evstigneeva, Nadezhda; Isaeva, Natalia; Kukso, Katsiaryna; Harris, Alma; Jones, Michelle

2015-01-01

Over the last decade, the Russian education system has undergone significant transformation that has radically changed the expectations placed upon the school principals. This current reform process has placed far greater responsibilities and accountabilities upon principals to secure school effectiveness and improved student learning outcomes.…

The Missed Promotion: An Exercise Demonstrating the Importance of Organizational Justice

ERIC Educational Resources Information Center

Caza, Arran; Caza, Brianna Barker; Lind, E. Allan

2011-01-01

Treating employees fairly produces many positive outcomes, but evidence suggests that managers' efforts to be fair are often unsuccessful because they emphasize the wrong aspects of justice. Managers tend to emphasize distributive justice, though employees may be most concerned with procedural and interactional justice. Organizational justice…

Can Neighbor Attributes Predict School Absences?

ERIC Educational Resources Information Center

Gottfried, Michael A.

2014-01-01

Recent evidence suggests that the neighborhood context, particularly for urban youth, can influence a range of outcomes. This study makes contributions to the field by examining how the neighborhood context directly relates to missing school. To do so, this study employs a large-scale, longitudinal data set of multilevel observations for entire…

Critical and Creative Thinking Nexus: Learning Experiences of Doctoral Students

ERIC Educational Resources Information Center

Brodin, Eva M.

2016-01-01

Critical and creative thinking constitute important learning outcomes at doctoral level across the world. While the literature on doctoral education illuminates this matter through the lens of experienced senior researchers, the doctoral students' own perspective is missing. Based upon interviews with 14 doctoral students from four disciplines at…

The Deconstructive Approach to Understanding Community College Students' Pathways and Outcomes

ERIC Educational Resources Information Center

Bahr, Peter Riley

2013-01-01

Two related themes currently dominate discourse on open-access colleges, particularly community colleges: increasing college-going and degree attainment and improving the performance of postsecondary institutions with respect to producing graduates. Largely missing from this discourse, however, is cogency concerning the innumerable ways in which…

The effect of working hours on outcome from major trauma.

PubMed

Guly, H R; Leighton, G; Woodford, M; Bouamra, O; Lecky, F

2006-04-01

To determine whether being admitted with major trauma to an emergency department outside rather than within working hours results in an adverse outcome. The data were collected from hospitals in England and Wales participating in the Trauma Audit and Research Network (TARN). Data from the TARN database were used. Admission time and discharge status were cross matched, and this was repeated while controlling for Injury Severity Score (ISS) values. Logistic regression was carried out, calculating the effects of Revised Trauma Score (RTS), ISS, age, and time of admission on outcome from major trauma. This allowed observed versus expected mortality rates (Ws) scores to be compared within and outside working hours. As much of the RTS data were missing, this was repeated using the Glasgow Coma Score instead of RTS. In total, 5.2% of people admitted "out of hours" died, compared with 5.3% of people within working hours, and 12.2% of people admitted outside working hours had an ISS score greater than 15, compared with 10.1% admitted within working hours. Outcome in cases with comparable ISS values were very similar (31.1% of cases with ISS >15 died out of hours, compared with 33.5% inside working hours.) The subgroup of data with missing RTS values had a significantly increased risk of death. Therefore, GCS was used to calculate severity adjusted odds of death instead of RTS. However, with either model, Ws scores were identical (both 0%) within and outside working hours. Out of hours admission does not in itself have an adverse effect on outcome from major trauma.

Impact of Diabetes Mellitus on Occupational Health Outcomes in Canada.

PubMed

Li, Anson Kc; Nowrouzi-Kia, Behdin

2017-04-01

Research suggests that diabetes mellitus (DM) has a negative impact on employment and workplace injury, but there is little data within the Canadian context. To determine if DM has an impact on various occupational health outcomes using the Canadian Community Health Survey (CCHS). CCHS data between 2001 and 2014 were used to assess the relationships between DM and various occupational health outcomes. The final sample size for the 14-year study period was 505 606, which represented 159 432 239 employed Canadians aged 15-75 years during this period. We found significant associations between people with diabetes and their type of occupation (business, finance, administration: 2009, p=0.002; 2010, p=0.002; trades, transportation, equipment: 2008, p=0.025; 2011, p=0.002; primary industry, processing, manufacturing, utility: 2013, p=0.018), reasons for missing work (looking for work: 2001, p=0.024; school or education: 2003, p=0.04; family responsibilities: 2014, p=0.015; other reasons: 2001, p<0.001; 2003, p<0.001; 2010, p=0.015), the number of work days missed (2010, 3 days, p=0.033; 4 days, p=0.038; 11 days, p<0.001; 24 days, p<0.001), and work-related injuries (traveling to and from work: 2014, p=0.003; working at a job or business: 2009, p=0.021; 2014, p=0.001). DM is associated with various occupational health outcomes, including work-related injury, work loss productivity, and occupation type. This allows stakeholders to assess the impact of DM on health outcomes in workplace.

Failure mode and effective analysis ameliorate awareness of medical errors: a 4-year prospective observational study in critically ill children.

PubMed

Daverio, Marco; Fino, Giuliana; Luca, Brugnaro; Zaggia, Cristina; Pettenazzo, Andrea; Parpaiola, Antonella; Lago, Paola; Amigoni, Angela

2015-12-01

Errors in are estimated to occur with an incidence of 3.7-16.6% in hospitalized patients. The application of systems for detection of adverse events is becoming a widespread reality in healthcare. Incident reporting (IR) and failure mode and effective analysis (FMEA) are strategies widely used to detect errors, but no studies have combined them in the setting of a pediatric intensive care unit (PICU). The aim of our study was to describe the trend of IR in a PICU and evaluate the effect of FMEA application on the number and severity of the errors detected. With this prospective observational study, we evaluated the frequency IR documented in standard IR forms completed from January 2009 to December 2012 in the PICU of Woman's and Child's Health Department of Padova. On the basis of their severity, errors were classified as: without outcome (55%), with minor outcome (16%), with moderate outcome (10%), and with major outcome (3%); 16% of reported incidents were 'near misses'. We compared the data before and after the introduction of FMEA. Sixty-nine errors were registered, 59 (86%) concerning drug therapy (83% during prescription). Compared to 2009-2010, in 2011-2012, we noted an increase of reported errors (43 vs 26) with a reduction of their severity (21% vs 8% 'near misses' and 65% vs 38% errors with no outcome). With the introduction of FMEA, we obtained an increased awareness in error reporting. Application of these systems will improve the quality of healthcare services. © 2015 John Wiley & Sons Ltd.

What are the living conditions and health status of those who don't report their migration status? A population-based study in Chile.

PubMed

Cabieses, Baltica; Pickett, Kate E; Tunstall, Helena

2012-11-21

Undocumented immigrants are likely to be missing from population databases, making it impossible to identify an accurate sampling frame in migration research. No population-based data has been collected in Chile regarding the living conditions and health status of undocumented immigrants. However, the CASEN survey (Caracterizacion Socio- Economica Nacional) asked about migration status in Chile for the first time in 2006 and provides an opportunity to set the base for future analysis of available migration data. We explored the living conditions and health of self-reported immigrants and respondents who preferred not to report their migration status in this survey. Cross-sectional secondary analysis of CASEN survey in Chile in 2006. any disability, illness/accident, hospitalization/surgery, cancer/chronic condition (all binary variables); and the number of medical/emergency attentions received (count variables). Covariates: Demographics (age, sex, marital status, urban/rural, ethnicity), socioeconomic status (education level, employment status and household income), and material standard of living (overcrowding, sanitation, housing quality). Weighted regression models were estimated for each health outcome, crude and adjusted by sets of covariates, in STATA 10.0. About 1% of the total sample reported being immigrants and 0.7% preferred not to report their migration status (Migration Status - Missing Values; MS-MV). The MS-MV lived in more deprived conditions and reported a higher rate of health problems than immigrants. Some gender differences were observed by health status among immigrants and the MS-MV but they were not statistically significant. Regressions indicated that age, sex, SES and material factors consistently affected MS-MVs' chance of presenting poor health and these patterns were different to those found among immigrants. Great heterogeneity in both the MS-MV and the immigrants, as indicated by wide confidence intervals, prevented the identification of other significantly associated covariates. This is the first study to look at the living conditions and health of those that preferred not to respond their migration status in Chile. Respondents that do not report their migration status are vulnerable to poor health and may represent undocumented immigrants. Surveys that fail to identify these people are likely to misrepresent the experiences of immigrants and further quantitative and qualitative research is urgently required.

Critical thinking, delegation, and missed care in nursing practice.

PubMed

Bittner, Nancy Phoenix; Gravlin, Gayle

2009-03-01

The aim of this study was to understand how nurses use critical thinking to delegate nursing care. Nurses must synthesize large amounts of information and think through complex and often emergent clinical situations when making critical decisions about patient care, including delegation. A qualitative, descriptive study was used in this article. Before delegating, nurses reported considering patient condition, competency, experience, and workload of unlicensed assistive personnel (UAP). Nurses expected UAP to report significant findings and have higher level knowledge, including assessment and prioritizing skills. Successful delegation was dependent on the relationship between the RN and the UAP, communication, system support, and nursing leadership. Nurses reported frequent instances of missed or omitted routine care. Findings from this project provide insight into factors that influence delegation effectiveness. These can guide CNOs and frontline nurse leaders to focus on implementing strategies to mitigate the consequence of missed care. Ineffective delegation of basic nursing care can result in poor patient outcomes, potentially impacting quality measures, satisfaction, and reimbursement for the institution.