Effect of random errors in planar PIV data on pressure estimation in vortex dominated flows

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2015-11-01

The sensitivity of pressure estimation techniques from Particle Image Velocimetry (PIV) measurements to random errors in measured velocity data is investigated using the flow over a circular cylinder as a test case. Direct numerical simulations are performed for ReD = 100, 300 and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A range of random errors typical for PIV measurements is applied to synthetic PIV data extracted from numerical results. A parametric study is then performed using a number of common pressure estimation techniques. Optimal temporal and spatial resolutions are derived based on the sensitivity of the estimated pressure fields to the simulated random error in velocity measurements, and the results are compared to an optimization model derived from error propagation theory. It is shown that the reductions in spatial and temporal scales at higher Reynolds numbers leads to notable changes in the optimal pressure evaluation parameters. The effect of smaller scale wake structures is also quantified. The errors in the estimated pressure fields are shown to depend significantly on the pressure estimation technique employed. The results are used to provide recommendations for the use of pressure and force estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Narrowband (LPC-10) Vocoder Performance under Combined Effects of Random Bit Errors and Jet Aircraft Cabin Noise.

DTIC Science & Technology

1983-12-01

rAD-141 333 NRRROWRAND (LPC-iB) VOCODER PERFORMANCE UNDER COMBINED i/ EFFECTS OF RRNDOM.(U) ROME AIR DEVELOPMENT CENTER GRIFFISS RFB NY C P SMITH DEC...LPC-10) VOCODER In House. PERFORMANCE UNDER COMBINED EFFECTS June 82 - Sept. 83 OF RANDOM BIT ERRORS AND JET AIRCRAFT Z PERFORMING ORG REPO- NUMSEF...PAGE(Wh.n Does Eneerd) 20. (contd) Compartment, and NCA Compartment were alike in their effects on overall vocoder performance . Composite performance

Effect of MLC leaf position, collimator rotation angle, and gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma

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

Bai, Sen; Li, Guangjun; Wang, Maojie

The purpose of this study was to investigate the effect of multileaf collimator (MLC) leaf position, collimator rotation angle, and accelerator gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma. To compare dosimetric differences between the simulating plans and the clinical plans with evaluation parameters, 6 patients with nasopharyngeal carcinoma were selected for simulation of systematic and random MLC leaf position errors, collimator rotation angle errors, and accelerator gantry rotation angle errors. There was a high sensitivity to dose distribution for systematic MLC leaf position errors in response to field size. When the systematic MLC position errors weremore » 0.5, 1, and 2 mm, respectively, the maximum values of the mean dose deviation, observed in parotid glands, were 4.63%, 8.69%, and 18.32%, respectively. The dosimetric effect was comparatively small for systematic MLC shift errors. For random MLC errors up to 2 mm and collimator and gantry rotation angle errors up to 0.5°, the dosimetric effect was negligible. We suggest that quality control be regularly conducted for MLC leaves, so as to ensure that systematic MLC leaf position errors are within 0.5 mm. Because the dosimetric effect of 0.5° collimator and gantry rotation angle errors is negligible, it can be concluded that setting a proper threshold for allowed errors of collimator and gantry rotation angle may increase treatment efficacy and reduce treatment time.« less

Simulation of wave propagation in three-dimensional random media

NASA Technical Reports Server (NTRS)

Coles, William A.; Filice, J. P.; Frehlich, R. G.; Yadlowsky, M.

1993-01-01

Quantitative error analysis for simulation of wave propagation in three dimensional random media assuming narrow angular scattering are presented for the plane wave and spherical wave geometry. This includes the errors resulting from finite grid size, finite simulation dimensions, and the separation of the two-dimensional screens along the propagation direction. Simple error scalings are determined for power-law spectra of the random refractive index of the media. The effects of a finite inner scale are also considered. The spatial spectra of the intensity errors are calculated and compared to the spatial spectra of intensity. The numerical requirements for a simulation of given accuracy are determined for realizations of the field. The numerical requirements for accurate estimation of higher moments of the field are less stringent.

A spatial error model with continuous random effects and an application to growth convergence

NASA Astrophysics Data System (ADS)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

PubMed Central

Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

2014-01-01

Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880

Effects of Heterogeneity and Uncertainties in Sources and Initial and Boundary Conditions on Spatiotemporal Variations of Groundwater Levels

NASA Astrophysics Data System (ADS)

Zhang, Y. K.; Liang, X.

2014-12-01

Effects of aquifer heterogeneity and uncertainties in source/sink, and initial and boundary conditions in a groundwater flow model on the spatiotemporal variations of groundwater level, h(x,t), were investigated. Analytical solutions for the variance and covariance of h(x, t) in an unconfined aquifer described by a linearized Boussinesq equation with a white noise source/sink and a random transmissivity field were derived. It was found that in a typical aquifer the error in h(x,t) in early time is mainly caused by the random initial condition and the error reduces as time goes to reach a constant error in later time. The duration during which the effect of the random initial condition is significant may last a few hundred days in most aquifers. The constant error in groundwater in later time is due to the combined effects of the uncertain source/sink and flux boundary: the closer to the flux boundary, the larger the error. The error caused by the uncertain head boundary is limited in a narrow zone near the boundary but it remains more or less constant over time. The effect of the heterogeneity is to increase the variation of groundwater level and the maximum effect occurs close to the constant head boundary because of the linear mean hydraulic gradient. The correlation of groundwater level decreases with temporal interval and spatial distance. In addition, the heterogeneity enhances the correlation of groundwater level, especially at larger time intervals and small spatial distances.

The statistical pitfalls of the partially randomized preference design in non-blinded trials of psychological interventions.

PubMed

Gemmell, Isla; Dunn, Graham

2011-03-01

In a partially randomized preference trial (PRPT) patients with no treatment preference are allocated to groups at random, but those who express a preference receive the treatment of their choice. It has been suggested that the design can improve the external and internal validity of trials. We used computer simulation to illustrate the impact that an unmeasured confounder could have on the results and conclusions drawn from a PRPT. We generated 4000 observations ("patients") that reflected the distribution of the Beck Depression Index (DBI) in trials of depression. Half were randomly assigned to a randomized controlled trial (RCT) design and half were assigned to a PRPT design. In the RCT, "patients" were evenly split between treatment and control groups; whereas in the preference arm, to reflect patient choice, 87.5% of patients were allocated to the experimental treatment and 12.5% to the control. Unadjusted analyses of the PRPT data consistently overestimated the treatment effect and its standard error. This lead to Type I errors when the true treatment effect was small and Type II errors when the confounder effect was large. The PRPT design is not recommended as a method of establishing an unbiased estimate of treatment effect due to the potential influence of unmeasured confounders. Copyright © 2011 John Wiley & Sons, Ltd.

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

PubMed Central

Thorlund, Kristian; Imberger, Georgina; Walsh, Michael; Chu, Rong; Gluud, Christian; Wetterslev, Jørn; Guyatt, Gordon; Devereaux, Philip J.; Thabane, Lehana

2011-01-01

Background Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. Methods We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. Results The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. Conclusions Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation. PMID:22028777

Random synaptic feedback weights support error backpropagation for deep learning

NASA Astrophysics Data System (ADS)

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-11-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning.

Random synaptic feedback weights support error backpropagation for deep learning

PubMed Central

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-01-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

Stochastic goal-oriented error estimation with memory

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

An Analysis of Computational Errors in the Use of Division Algorithms by Fourth-Grade Students.

ERIC Educational Resources Information Center

Stefanich, Greg P.; Rokusek, Teri

1992-01-01

Presents a study that analyzed errors made by randomly chosen fourth grade students (25 of 57) while using the division algorithm and investigated the effect of remediation on identified systematic errors. Results affirm that error pattern diagnosis and directed remediation lead to new learning and long-term retention. (MDH)

Effects of random tooth profile errors on the dynamic behaviors of planetary gears

NASA Astrophysics Data System (ADS)

Xun, Chao; Long, Xinhua; Hua, Hongxing

2018-02-01

In this paper, a nonlinear random model is built to describe the dynamics of planetary gear trains (PGTs), in which the time-varying mesh stiffness, tooth profile modification (TPM), tooth contact loss, and random tooth profile error are considered. A stochastic method based on the method of multiple scales (MMS) is extended to analyze the statistical property of the dynamic performance of PGTs. By the proposed multiple-scales based stochastic method, the distributions of the dynamic transmission errors (DTEs) are investigated, and the lower and upper bounds are determined based on the 3σ principle. Monte Carlo method is employed to verify the proposed method. Results indicate that the proposed method can be used to determine the distribution of the DTE of PGTs high efficiently and allow a link between the manufacturing precision and the dynamical response. In addition, the effects of tooth profile modification on the distributions of vibration amplitudes and the probability of tooth contact loss with different manufacturing tooth profile errors are studied. The results show that the manufacturing precision affects the distribution of dynamic transmission errors dramatically and appropriate TPMs are helpful to decrease the nominal value and the deviation of the vibration amplitudes.

Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors

PubMed Central

Shah, Priya; Wyatt, Jeremy C; Makubate, Boikanyo; Cross, Frank W

2011-01-01

Objective Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems. Design A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task. Measurements The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants' preferences for the prescribing alerts and their views on clinical decision support systems. Results Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04). Conclusions Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than non-modal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes. PMID:21836158

Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Zhang, Li-jie

2017-10-01

Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

The Gulliver Effect: The Impact of Error in an Elephantine Subpopulation on Estimates for Lilliputian Subpopulations

ERIC Educational Resources Information Center

Micceri, Theodore; Parasher, Pradnya; Waugh, Gordon W.; Herreid, Charlene

2009-01-01

An extensive review of the research literature and a study comparing over 36,000 survey responses with archival true scores indicated that one should expect a minimum of at least three percent random error for the least ambiguous of self-report measures. The Gulliver Effect occurs when a small proportion of error in a sizable subpopulation exerts…

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

PubMed Central

Marchal-Crespo, Laura; Michels, Lars; Jaeger, Lukas; López-Olóriz, Jorge; Riener, Robert

2017-01-01

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation. PMID:29021739

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Study on the Rationality and Validity of Probit Models of Domino Effect to Chemical Process Equipment caused by Overpressure

NASA Astrophysics Data System (ADS)

Sun, Dongliang; Huang, Guangtuan; Jiang, Juncheng; Zhang, Mingguang; Wang, Zhirong

2013-04-01

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Some models considering propagation probability and threshold values of the domino effect caused by overpressure have been proposed in previous study. In order to prove the rationality and validity of the models reported in the reference, two boundary values of three damage degrees reported were considered as random variables respectively in the interval [0, 100%]. Based on the overpressure data for damage to the equipment and the damage state, and the calculation method reported in the references, the mean square errors of the four categories of damage probability models of overpressure were calculated with random boundary values, and then a relationship of mean square error vs. the two boundary value was obtained, the minimum of mean square error was obtained, compared with the result of the present work, mean square error decreases by about 3%. Therefore, the error was in the acceptable range of engineering applications, the models reported can be considered reasonable and valid.

Effect of Random Circuit Fabrication Errors on Small Signal Gain and Phase in Helix Traveling Wave Tubes

NASA Astrophysics Data System (ADS)

Pengvanich, P.; Chernin, D. P.; Lau, Y. Y.; Luginsland, J. W.; Gilgenbach, R. M.

2007-11-01

Motivated by the current interest in mm-wave and THz sources, which use miniature, difficult-to-fabricate circuit components, we evaluate the statistical effects of random fabrication errors on a helix traveling wave tube amplifier's small signal characteristics. The small signal theory is treated in a continuum model in which the electron beam is assumed to be monoenergetic, and axially symmetric about the helix axis. Perturbations that vary randomly along the beam axis are introduced in the dimensionless Pierce parameters b, the beam-wave velocity mismatch, C, the gain parameter, and d, the cold tube circuit loss. Our study shows, as expected, that perturbation in b dominates the other two. The extensive numerical data have been confirmed by our analytic theory. They show in particular that the standard deviation of the output phase is linearly proportional to standard deviation of the individual perturbations in b, C, and d. Simple formulas have been derived which yield the output phase variations in terms of the statistical random manufacturing errors. This work was supported by AFOSR and by ONR.

Effects of learning climate and registered nurse staffing on medication errors.

PubMed

Chang, Yunkyung; Mark, Barbara

2011-01-01

Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.

What errors do peer reviewers detect, and does training improve their ability to detect them?

PubMed

Schroter, Sara; Black, Nick; Evans, Stephen; Godlee, Fiona; Osorio, Lyda; Smith, Richard

2008-10-01

To analyse data from a trial and report the frequencies with which major and minor errors are detected at a general medical journal, the types of errors missed and the impact of training on error detection. 607 peer reviewers at the BMJ were randomized to two intervention groups receiving different types of training (face-to-face training or a self-taught package) and a control group. Each reviewer was sent the same three test papers over the study period, each of which had nine major and five minor methodological errors inserted. BMJ peer reviewers. The quality of review, assessed using a validated instrument, and the number and type of errors detected before and after training. The number of major errors detected varied over the three papers. The interventions had small effects. At baseline (Paper 1) reviewers found an average of 2.58 of the nine major errors, with no notable difference between the groups. The mean number of errors reported was similar for the second and third papers, 2.71 and 3.0, respectively. Biased randomization was the error detected most frequently in all three papers, with over 60% of reviewers rejecting the papers identifying this error. Reviewers who did not reject the papers found fewer errors and the proportion finding biased randomization was less than 40% for each paper. Editors should not assume that reviewers will detect most major errors, particularly those concerned with the context of study. Short training packages have only a slight impact on improving error detection.

Statistical error model for a solar electric propulsion thrust subsystem

NASA Technical Reports Server (NTRS)

Bantell, M. H.

1973-01-01

The solar electric propulsion thrust subsystem statistical error model was developed as a tool for investigating the effects of thrust subsystem parameter uncertainties on navigation accuracy. The model is currently being used to evaluate the impact of electric engine parameter uncertainties on navigation system performance for a baseline mission to Encke's Comet in the 1980s. The data given represent the next generation in statistical error modeling for low-thrust applications. Principal improvements include the representation of thrust uncertainties and random process modeling in terms of random parametric variations in the thrust vector process for a multi-engine configuration.

Quantifying Adventitious Error in a Covariance Structure as a Random Effect

PubMed Central

Wu, Hao; Browne, Michael W.

2017-01-01

We present an approach to quantifying errors in covariance structures in which adventitious error, identified as the process underlying the discrepancy between the population and the structured model, is explicitly modeled as a random effect with a distribution, and the dispersion parameter of this distribution to be estimated gives a measure of misspecification. Analytical properties of the resultant procedure are investigated and the measure of misspecification is found to be related to the RMSEA. An algorithm is developed for numerical implementation of the procedure. The consistency and asymptotic sampling distributions of the estimators are established under a new asymptotic paradigm and an assumption weaker than the standard Pitman drift assumption. Simulations validate the asymptotic sampling distributions and demonstrate the importance of accounting for the variations in the parameter estimates due to adventitious error. Two examples are also given as illustrations. PMID:25813463

Random Versus Nonrandom Peer Review: A Case for More Meaningful Peer Review.

PubMed

Itri, Jason N; Donithan, Adam; Patel, Sohil H

2018-05-10

Random peer review programs are not optimized to discover cases with diagnostic error and thus have inherent limitations with respect to educational and quality improvement value. Nonrandom peer review offers an alternative approach in which diagnostic error cases are targeted for collection during routine clinical practice. The objective of this study was to compare error cases identified through random and nonrandom peer review approaches at an academic center. During the 1-year study period, the number of discrepancy cases and score of discrepancy were determined from each approach. The nonrandom peer review process collected 190 cases, of which 60 were scored as 2 (minor discrepancy), 94 as 3 (significant discrepancy), and 36 as 4 (major discrepancy). In the random peer review process, 1,690 cases were reviewed, of which 1,646 were scored as 1 (no discrepancy), 44 were scored as 2 (minor discrepancy), and none were scored as 3 or 4. Several teaching lessons and quality improvement measures were developed as a result of analysis of error cases collected through the nonrandom peer review process. Our experience supports the implementation of nonrandom peer review as a replacement to random peer review, with nonrandom peer review serving as a more effective method for collecting diagnostic error cases with educational and quality improvement value. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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

Yu, Juan; Beltran, Chris J., E-mail: beltran.chris@mayo.edu; Herman, Michael G.

Purpose: To quantitatively and systematically assess dosimetric effects induced by spot positioning error as a function of spot spacing (SS) on intensity-modulated proton therapy (IMPT) plan quality and to facilitate evaluation of safety tolerance limits on spot position. Methods: Spot position errors (PE) ranging from 1 to 2 mm were simulated. Simple plans were created on a water phantom, and IMPT plans were calculated on two pediatric patients with a brain tumor of 28 and 3 cc, respectively, using a commercial planning system. For the phantom, a uniform dose was delivered to targets located at different depths from 10 tomore » 20 cm with various field sizes from 2{sup 2} to 15{sup 2} cm{sup 2}. Two nominal spot sizes, 4.0 and 6.6 mm of 1 σ in water at isocenter, were used for treatment planning. The SS ranged from 0.5 σ to 1.5 σ, which is 2–6 mm for the small spot size and 3.3–9.9 mm for the large spot size. Various perturbation scenarios of a single spot error and systematic and random multiple spot errors were studied. To quantify the dosimetric effects, percent dose error (PDE) depth profiles and the value of percent dose error at the maximum dose difference (PDE [ΔDmax]) were used for evaluation. Results: A pair of hot and cold spots was created per spot shift. PDE[ΔDmax] is found to be a complex function of PE, SS, spot size, depth, and global spot distribution that can be well defined in simple models. For volumetric targets, the PDE [ΔDmax] is not noticeably affected by the change of field size or target volume within the studied ranges. In general, reducing SS decreased the dose error. For the facility studied, given a single spot error with a PE of 1.2 mm and for both spot sizes, a SS of 1σ resulted in a 2% maximum dose error; a SS larger than 1.25 σ substantially increased the dose error and its sensitivity to PE. A similar trend was observed in multiple spot errors (both systematic and random errors). Systematic PE can lead to noticeable hot spots along the field edges, which may be near critical structures. However, random PE showed minimal dose error. Conclusions: Dose error dependence for PE was quantitatively and systematically characterized and an analytic tool was built to simulate systematic and random errors for patient-specific IMPT. This information facilitates the determination of facility specific spot position error thresholds.« less

Evaluation of some random effects methodology applicable to bird ringing data

USGS Publications Warehouse

Burnham, K.P.; White, Gary C.

2002-01-01

Existing models for ring recovery and recapture data analysis treat temporal variations in annual survival probability (S) as fixed effects. Often there is no explainable structure to the temporal variation in S1,..., Sk; random effects can then be a useful model: Si = E(S) + ??i. Here, the temporal variation in survival probability is treated as random with average value E(??2) = ??2. This random effects model can now be fit in program MARK. Resultant inferences include point and interval estimation for process variation, ??2, estimation of E(S) and var (E??(S)) where the latter includes a component for ??2 as well as the traditional component for v??ar(S??\\S??). Furthermore, the random effects model leads to shrinkage estimates, Si, as improved (in mean square error) estimators of Si compared to the MLE, S??i, from the unrestricted time-effects model. Appropriate confidence intervals based on the Si are also provided. In addition, AIC has been generalized to random effects models. This paper presents results of a Monte Carlo evaluation of inference performance under the simple random effects model. Examined by simulation, under the simple one group Cormack-Jolly-Seber (CJS) model, are issues such as bias of ??s2, confidence interval coverage on ??2, coverage and mean square error comparisons for inference about Si based on shrinkage versus maximum likelihood estimators, and performance of AIC model selection over three models: Si ??? S (no effects), Si = E(S) + ??i (random effects), and S1,..., Sk (fixed effects). For the cases simulated, the random effects methods performed well and were uniformly better than fixed effects MLE for the Si.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies

PubMed Central

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-01-01

Abstract Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. PMID:29106476

Diagnostics of Robust Growth Curve Modeling Using Student's "t" Distribution

ERIC Educational Resources Information Center

Tong, Xin; Zhang, Zhiyong

2012-01-01

Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…

An efficient computational method for characterizing the effects of random surface errors on the average power pattern of reflectors

NASA Technical Reports Server (NTRS)

Rahmat-Samii, Y.

1983-01-01

Based on the works of Ruze (1966) and Vu (1969), a novel mathematical model has been developed to determine efficiently the average power pattern degradations caused by random surface errors. In this model, both nonuniform root mean square (rms) surface errors and nonuniform illumination functions are employed. In addition, the model incorporates the dependence on F/D in the construction of the solution. The mathematical foundation of the model rests on the assumption that in each prescribed annular region of the antenna, the geometrical rms surface value is known. It is shown that closed-form expressions can then be derived, which result in a very efficient computational method for the average power pattern. Detailed parametric studies are performed with these expressions to determine the effects of different random errors and illumination tapers on parameters such as gain loss and sidelobe levels. The results clearly demonstrate that as sidelobe levels decrease, their dependence on the surface rms/wavelength becomes much stronger and, for a specified tolerance level, a considerably smaller rms/wavelength is required to maintain the low sidelobes within the required bounds.

Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes.

PubMed

Lau, Billy T; Ji, Hanlee P

2017-09-21

RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule. To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels. We experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method's performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts. We described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease.

Within-Tunnel Variations in Pressure Data for Three Transonic Wind Tunnels

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2014-01-01

This paper compares the results of pressure measurements made on the same test article with the same test matrix in three transonic wind tunnels. A comparison is presented of the unexplained variance associated with polar replicates acquired in each tunnel. The impact of a significance component of systematic (not random) unexplained variance is reviewed, and the results of analyses of variance are presented to assess the degree of significant systematic error in these representative wind tunnel tests. Total uncertainty estimates are reported for 140 samples of pressure data, quantifying the effects of within-polar random errors and between-polar systematic bias errors.

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

Effects of postexercise ice-water and room-temperature water immersion on the sensory organization of balance control and lower limb proprioception in amateur rugby players: A randomized controlled trial.

PubMed

Chow, Gary C C; Yam, Timothy T T; Chung, Joanne W Y; Fong, Shirley S M

2017-02-01

This single-blinded, three-armed randomized controlled trial aimed to compare the effects of postexercise ice-water immersion (IWI), room-temperature water immersion (RWI), and no water immersion on the balance performance and knee joint proprioception of amateur rugby players. Fifty-three eligible amateur rugby players (mean age ± standard deviation: 21.6 ± 2.9 years) were randomly assigned to the IWI group (5.3 °C), RWI group (25.0 °C), or the no immersion control group. The participants in each group underwent the same fatigue protocol followed by their allocated recovery intervention, which lasted for 1 minute. Measurements were taken before and after the fatigue-recovery intervention. The primary outcomes were the sensory organization test (SOT) composite equilibrium score (ES) and the condition-specific ES, which were measured using a computerized dynamic posturography machine. The secondary outcome was the knee joint repositioning error. Two-way repeated measures analysis of variance was used to test the effect of water immersion on each outcome variable. There were no significant within- and between-group differences in the SOT composite ESs or the condition-specific ESs. However, there was a group-by-time interaction effect on the knee joint repositioning error. It seems that participants in the RWI group had lower errors over time, but those in the IWI and control groups had increased errors over time. The RWI group had significantly lower error score than the IWI group at postintervention. One minute of postexercise IWI or RWI did not impair rugby players' sensory organization of balance control. RWI had a less detrimental effect on knee joint proprioception to IWI at postintervention.

Evaluation of seasonal and spatial variations of lumped water balance model sensitivity to precipitation data errors

NASA Astrophysics Data System (ADS)

Xu, Chong-yu; Tunemar, Liselotte; Chen, Yongqin David; Singh, V. P.

2006-06-01

Sensitivity of hydrological models to input data errors have been reported in the literature for particular models on a single or a few catchments. A more important issue, i.e. how model's response to input data error changes as the catchment conditions change has not been addressed previously. This study investigates the seasonal and spatial effects of precipitation data errors on the performance of conceptual hydrological models. For this study, a monthly conceptual water balance model, NOPEX-6, was applied to 26 catchments in the Mälaren basin in Central Sweden. Both systematic and random errors were considered. For the systematic errors, 5-15% of mean monthly precipitation values were added to the original precipitation to form the corrupted input scenarios. Random values were generated by Monte Carlo simulation and were assumed to be (1) independent between months, and (2) distributed according to a Gaussian law of zero mean and constant standard deviation that were taken as 5, 10, 15, 20, and 25% of the mean monthly standard deviation of precipitation. The results show that the response of the model parameters and model performance depends, among others, on the type of the error, the magnitude of the error, physical characteristics of the catchment, and the season of the year. In particular, the model appears less sensitive to the random error than to the systematic error. The catchments with smaller values of runoff coefficients were more influenced by input data errors than were the catchments with higher values. Dry months were more sensitive to precipitation errors than were wet months. Recalibration of the model with erroneous data compensated in part for the data errors by altering the model parameters.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

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

Elliott, C.J.; McVey, B.; Quimby, D.C.

The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of thesemore » errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.« less

Enhanced orbit determination filter sensitivity analysis: Error budget development

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Burkhart, P. D.

1994-01-01

An error budget analysis is presented which quantifies the effects of different error sources in the orbit determination process when the enhanced orbit determination filter, recently developed, is used to reduce radio metric data. The enhanced filter strategy differs from more traditional filtering methods in that nearly all of the principal ground system calibration errors affecting the data are represented as filter parameters. Error budget computations were performed for a Mars Observer interplanetary cruise scenario for cases in which only X-band (8.4-GHz) Doppler data were used to determine the spacecraft's orbit, X-band ranging data were used exclusively, and a combined set in which the ranging data were used in addition to the Doppler data. In all three cases, the filter model was assumed to be a correct representation of the physical world. Random nongravitational accelerations were found to be the largest source of error contributing to the individual error budgets. Other significant contributors, depending on the data strategy used, were solar-radiation pressure coefficient uncertainty, random earth-orientation calibration errors, and Deep Space Network (DSN) station location uncertainty.

Center of mass perception and inertial frames of reference.

PubMed

Bingham, G P; Muchisky, M M

1993-11-01

Center of mass perception was investigated by varying the shape, size, and orientation of planar objects. Shape was manipulated to investigate symmetries as information. The number of reflective symmetry axes, the amount of rotational symmetry, and the presence of radial symmetry were varied. Orientation affected systematic errors. Judgments tended to undershoot the center of mass. Random errors increased with size and decreased with symmetry. Size had no effect on random errors for maximally symmetric objects, although orientation did. The spatial distributions of judgments were elliptical. Distribution axes were found to align with the principle moments of inertia. Major axes tended to align with gravity in maximally symmetric objects. A functional and physical account was given in terms of the repercussions of error. Overall, judgments were very accurate.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

The influence of different error estimates in the detection of postoperative cognitive dysfunction using reliable change indices with correction for practice effects.

PubMed

Lewis, Matthew S; Maruff, Paul; Silbert, Brendan S; Evered, Lis A; Scott, David A

2007-02-01

The reliable change index (RCI) expresses change relative to its associated error, and is useful in the identification of postoperative cognitive dysfunction (POCD). This paper examines four common RCIs that each account for error in different ways. Three rules incorporate a constant correction for practice effects and are contrasted with the standard RCI that had no correction for practice. These rules are applied to 160 patients undergoing coronary artery bypass graft (CABG) surgery who completed neuropsychological assessments preoperatively and 1 week postoperatively using error and reliability data from a comparable healthy nonsurgical control group. The rules all identify POCD in a similar proportion of patients, but the use of the within-subject standard deviation (WSD), expressing the effects of random error, as an error estimate is a theoretically appropriate denominator when a constant error correction, removing the effects of systematic error, is deducted from the numerator in a RCI.

POLICY IMPLICATIONS OF ADJUSTING RANDOMIZED TRIAL DATA FOR ECONOMIC EVALUATIONS: A DEMONSTRATION FROM THE ASCUS-LSIL TRIAGE STUDY

PubMed Central

Campos, Nicole G.; Castle, Philip E.; Schiffman, Mark; Kim, Jane J.

2013-01-01

Background Although the randomized controlled trial (RCT) is widely considered the most reliable method for evaluation of health care interventions, challenges to both internal and external validity exist. Thus, the efficacy of an intervention in a trial setting does not necessarily represent the real-world performance that decision makers seek to inform comparative effectiveness studies and economic evaluations. Methods Using data from the ASCUS-LSIL Triage Study (ALTS), we performed a simplified economic evaluation of age-based management strategies to detect cervical intraepithelial neoplasia grade 3 (CIN3) among women who were referred to the study with low-grade squamous intraepithelial lesions (LSIL). We used data from the trial itself to adjust for 1) potential lead time bias and random error that led to variation in the observed prevalence of CIN3 by study arm, and 2) potential ascertainment bias among providers in the most aggressive management arm. Results We found that using unadjusted RCT data may result in counterintuitive cost-effectiveness results when random error and/or bias are present. Following adjustment, the rank order of management strategies changed for two of the three age groups we considered. Conclusion Decision analysts need to examine study design, available trial data and cost-effectiveness results closely in order to detect evidence of potential bias. Adjustment for random error and bias in RCTs may yield different policy conclusions relative to unadjusted trial data. PMID:22147881

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies.

PubMed

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-11-01

Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Experiential Teaching Increases Medication Calculation Accuracy Among Baccalaureate Nursing Students.

PubMed

Hurley, Teresa V

Safe medication administration is an international goal. Calculation errors cause patient harm despite education. The research purpose was to evaluate the effectiveness of an experiential teaching strategy to reduce errors in a sample of 78 baccalaureate nursing students at a Northeastern college. A pretest-posttest design with random assignment into equal-sized groups was used. The experiential strategy was more effective than the traditional method (t = -0.312, df = 37, p = .004, 95% CI) with a reduction in calculation errors. Evaluations of error type and teaching strategies are indicated to facilitate course and program changes.

A Method of Reducing Random Drift in the Combined Signal of an Array of Inertial Sensors

DTIC Science & Technology

2015-09-30

stability of the collective output, Bayard et al, US Patent 6,882,964. The prior art methods rely upon the use of Kalman filtering and averaging...including scale-factor errors, quantization effects, temperature effects, random drift, and additive noise. A comprehensive account of all of these

FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

PubMed

Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

2016-07-12

In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

Large Uncertainty in Estimating pCO2 From Carbonate Equilibria in Lakes

NASA Astrophysics Data System (ADS)

Golub, Malgorzata; Desai, Ankur R.; McKinley, Galen A.; Remucal, Christina K.; Stanley, Emily H.

2017-11-01

Most estimates of carbon dioxide (CO2) evasion from freshwaters rely on calculating partial pressure of aquatic CO2 (pCO2) from two out of three CO2-related parameters using carbonate equilibria. However, the pCO2 uncertainty has not been systematically evaluated across multiple lake types and equilibria. We quantified random errors in pH, dissolved inorganic carbon, alkalinity, and temperature from the North Temperate Lakes Long-Term Ecological Research site in four lake groups across a broad gradient of chemical composition. These errors were propagated onto pCO2 calculated from three carbonate equilibria, and for overlapping observations, compared against uncertainties in directly measured pCO2. The empirical random errors in CO2-related parameters were mostly below 2% of their median values. Resulting random pCO2 errors ranged from ±3.7% to ±31.5% of the median depending on alkalinity group and choice of input parameter pairs. Temperature uncertainty had a negligible effect on pCO2. When compared with direct pCO2 measurements, all parameter combinations produced biased pCO2 estimates with less than one third of total uncertainty explained by random pCO2 errors, indicating that systematic uncertainty dominates over random error. Multidecadal trend of pCO2 was difficult to reconstruct from uncertain historical observations of CO2-related parameters. Given poor precision and accuracy of pCO2 estimates derived from virtually any combination of two CO2-related parameters, we recommend direct pCO2 measurements where possible. To achieve consistently robust estimates of CO2 emissions from freshwater components of terrestrial carbon balances, future efforts should focus on improving accuracy and precision of CO2-related parameters (including direct pCO2) measurements and associated pCO2 calculations.

A multifaceted program for improving quality of care in intensive care units: IATROREF study.

PubMed

Garrouste-Orgeas, Maite; Soufir, Lilia; Tabah, Alexis; Schwebel, Carole; Vesin, Aurelien; Adrie, Christophe; Thuong, Marie; Timsit, Jean Francois

2012-02-01

To test the effects of three multifaceted safety programs designed to decrease insulin administration errors, anticoagulant prescription and administration errors, and errors leading to accidental removal of endotracheal tubes and central venous catheters, respectively. Medical errors and adverse events are associated with increased mortality in intensive care patients, indicating an urgent need for prevention programs. Multicenter cluster-randomized study. One medical intensive care unit in a university hospital and two medical-surgical intensive care units in community hospitals belonging to the Outcomerea Study Group. Consecutive patients >18 yrs admitted from January 2007 to January 2008 to the intensive care units. We tested three multifaceted safety programs vs. standard care in random order, each over 2.5 months, after a 1.5-month observation period. Incidence rates of medical errors/1000 patient-days in the multifaceted safety program and standard-care groups were compared using adjusted hierarchical models. In 2117 patients with 15,014 patient-days, 8520 medical errors (567.5/1000 patient-days) were reported, including 1438 adverse events (16.9%, 95.8/1000 patient-days). The insulin multifaceted safety program significantly decreased errors during implementation (risk ratio 0.65; 95% confidence interval [CI] 0.52-0.82; p = .0003) and after implementation (risk ratio 0.51; 95% CI 0.35-0.73; p = .0004). A significant Hawthorne effect was found. The accidental tube/catheter removal multifaceted safety program decreased errors significantly during implementation (odds ratio [OR] 0.34; 95% CI 0.15-0.81; p = .01]) and nonsignificantly after implementation (OR 1.65; 95% CI 0.78-3.48). The anticoagulation multifaceted safety program was not significantly effective (OR 0.64; 95% CI 0.26-1.59) but produced a significant Hawthorne effect. A multifaceted program was effective in preventing insulin errors and accidental tube/catheter removal. Significant Hawthorne effects occurred, emphasizing the need for appropriately designed studies before definitively implementing strategies. clinicaltrials.gov Identifier: NCT00461461.

Statistics of the epoch of reionization 21-cm signal - I. Power spectrum error-covariance

NASA Astrophysics Data System (ADS)

Mondal, Rajesh; Bharadwaj, Somnath; Majumdar, Suman

2016-02-01

The non-Gaussian nature of the epoch of reionization (EoR) 21-cm signal has a significant impact on the error variance of its power spectrum P(k). We have used a large ensemble of seminumerical simulations and an analytical model to estimate the effect of this non-Gaussianity on the entire error-covariance matrix {C}ij. Our analytical model shows that {C}ij has contributions from two sources. One is the usual variance for a Gaussian random field which scales inversely of the number of modes that goes into the estimation of P(k). The other is the trispectrum of the signal. Using the simulated 21-cm Signal Ensemble, an ensemble of the Randomized Signal and Ensembles of Gaussian Random Ensembles we have quantified the effect of the trispectrum on the error variance {C}II. We find that its relative contribution is comparable to or larger than that of the Gaussian term for the k range 0.3 ≤ k ≤ 1.0 Mpc-1, and can be even ˜200 times larger at k ˜ 5 Mpc-1. We also establish that the off-diagonal terms of {C}ij have statistically significant non-zero values which arise purely from the trispectrum. This further signifies that the error in different k modes are not independent. We find a strong correlation between the errors at large k values (≥0.5 Mpc-1), and a weak correlation between the smallest and largest k values. There is also a small anticorrelation between the errors in the smallest and intermediate k values. These results are relevant for the k range that will be probed by the current and upcoming EoR 21-cm experiments.

A quarter of a century of the DBQ: some supplementary notes on its validity with regard to accidents.

PubMed

de Winter, Joost C F; Dodou, Dimitra; Stanton, Neville A

2015-01-01

This article synthesises the latest information on the relationship between the Driver Behaviour Questionnaire (DBQ) and accidents. We show by means of computer simulation that correlations with accidents are necessarily small because accidents are rare events. An updated meta-analysis on the zero-order correlations between the DBQ and self-reported accidents yielded an overall r of .13 (fixed-effect and random-effects models) for violations (57,480 participants; 67 samples) and .09 (fixed-effect and random-effects models) for errors (66,028 participants; 56 samples). An analysis of a previously published DBQ dataset (975 participants) showed that by aggregating across four measurement occasions, the correlation coefficient with self-reported accidents increased from .14 to .24 for violations and from .11 to .19 for errors. Our meta-analysis also showed that DBQ violations (r = .24; 6353 participants; 20 samples) but not DBQ errors (r = - .08; 1086 participants; 16 samples) correlated with recorded vehicle speed. Practitioner Summary: The DBQ is probably the most widely used self-report questionnaire in driver behaviour research. This study shows that DBQ violations and errors correlate moderately with self-reported traffic accidents.

Analysis of space telescope data collection system

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Schoggen, W. O.

1982-01-01

An analysis of the expected performance for the Multiple Access (MA) system is provided. The analysis covers the expected bit error rate performance, the effects of synchronization loss, the problem of self-interference, and the problem of phase ambiguity. The problem of false acceptance of a command word due to data inversion is discussed. A mathematical determination of the probability of accepting an erroneous command word due to a data inversion is presented. The problem is examined for three cases: (1) a data inversion only, (2) a data inversion and a random error within the same command word, and a block (up to 256 48-bit words) containing both a data inversion and a random error.

An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

PubMed

Dodd, Lori E; Korn, Edward L; Freidlin, Boris; Gu, Wenjuan; Abrams, Jeffrey S; Bushnell, William D; Canetta, Renzo; Doroshow, James H; Gray, Robert J; Sridhara, Rajeshwari

2013-10-01

Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

Errors in causal inference: an organizational schema for systematic error and random error.

PubMed

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

Documentation of study medication dispensing in a prospective large randomized clinical trial: experiences from the ARISTOTLE Trial.

PubMed

Alexander, John H; Levy, Elliott; Lawrence, Jack; Hanna, Michael; Waclawski, Anthony P; Wang, Junyuan; Califf, Robert M; Wallentin, Lars; Granger, Christopher B

2013-09-01

In ARISTOTLE, apixaban resulted in a 21% reduction in stroke, a 31% reduction in major bleeding, and an 11% reduction in death. However, approval of apixaban was delayed to investigate a statement in the clinical study report that "7.3% of subjects in the apixaban group and 1.2% of subjects in the warfarin group received, at some point during the study, a container of the wrong type." Rates of study medication dispensing error were characterized through reviews of study medication container tear-off labels in 6,520 participants from randomly selected study sites. The potential effect of dispensing errors on study outcomes was statistically simulated in sensitivity analyses in the overall population. The rate of medication dispensing error resulting in treatment error was 0.04%. Rates of participants receiving at least 1 incorrect container were 1.04% (34/3,273) in the apixaban group and 0.77% (25/3,247) in the warfarin group. Most of the originally reported errors were data entry errors in which the correct medication container was dispensed but the wrong container number was entered into the case report form. Sensitivity simulations in the overall trial population showed no meaningful effect of medication dispensing error on the main efficacy and safety outcomes. Rates of medication dispensing error were low and balanced between treatment groups. The initially reported dispensing error rate was the result of data recording and data management errors and not true medication dispensing errors. These analyses confirm the previously reported results of ARISTOTLE. © 2013.

A Gompertzian model with random effects to cervical cancer growth

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

Mazlan, Mazma Syahidatul Ayuni; Rosli, Norhayati

2015-05-15

In this paper, a Gompertzian model with random effects is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via maximum likehood estimation. We apply 4-stage Runge-Kutta (SRK4) for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of the cervical cancer growth. Low values of root mean-square error (RMSE) of Gompertzian model with random effect indicate good fits.

Random access to mobile networks with advanced error correction

NASA Technical Reports Server (NTRS)

Dippold, Michael

1990-01-01

A random access scheme for unreliable data channels is investigated in conjunction with an adaptive Hybrid-II Automatic Repeat Request (ARQ) scheme using Rate Compatible Punctured Codes (RCPC) Forward Error Correction (FEC). A simple scheme with fixed frame length and equal slot sizes is chosen and reservation is implicit by the first packet transmitted randomly in a free slot, similar to Reservation Aloha. This allows the further transmission of redundancy if the last decoding attempt failed. Results show that a high channel utilization and superior throughput can be achieved with this scheme that shows a quite low implementation complexity. For the example of an interleaved Rayleigh channel and soft decision utilization and mean delay are calculated. A utilization of 40 percent may be achieved for a frame with the number of slots being equal to half the station number under high traffic load. The effects of feedback channel errors and some countermeasures are discussed.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

CONTEXTUAL INTERFERENCE AND INTROVERSION/EXTRAVERSION IN MOTOR LEARNING.

PubMed

Meira, Cassio M; Fairbrother, Jeffrey T; Perez, Carlos R

2015-10-01

The Introversion/Extraversion dimension may interact with contextual interference, as random and blocked practice schedules imply distinct levels of variation. This study investigated the effect of different practice schedules in the acquisition of a motor skill in extraverts and introverts. Forty male undergraduate students (M = 24.3 yr., SD = 5.6) were classified as extraverts (n = 20) and introverts (n = 20) by the Eysenck Personality Questionnaire and allocated in one of two practice schedules with different levels of contextual interference: blocked (low contextual interference) and random (high contextual interference). Half of each group was assigned to a blocked practice schedule, and the other half was assigned to a random practice schedule. The design had two phases: acquisition and transfer (5 min. and 24 hr.). The participants learned variations of a sequential timing keypressing task. Each variation required the same sequence but different timing; three variations were used in acquisition, and one variation of intermediate length was used in transfer. Results for absolute error and overall timing error (root mean square error) indicated that the contextual interference effect was more pronounced for introverts. In addition, introverts who practiced according to the blocked schedule committed more errors during the 24-hr. transfer, suggesting that introverts did not appear to be challenged by a low contextual interference practice schedule.

Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

PubMed

Vetter, Thomas R; Mascha, Edward J

2017-09-01

Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of the association or treatment effect. Interaction among variables, also known as effect modification, exists when the effect of 1 explanatory variable on the outcome depends on the particular level or value of another explanatory variable. Bias and confounding are common potential explanations for statistically significant associations between exposure and outcome when the true relationship is noncausal. Understanding interactions is vital to proper interpretation of treatment effects. These complex concepts should be consistently and appropriately considered whenever one is not only designing but also analyzing and interpreting data from a randomized trial or observational study.

Decorrelation of the true and estimated classifier errors in high-dimensional settings.

PubMed

Hanczar, Blaise; Hua, Jianping; Dougherty, Edward R

2007-01-01

The aim of many microarray experiments is to build discriminatory diagnosis and prognosis models. Given the huge number of features and the small number of examples, model validity which refers to the precision of error estimation is a critical issue. Previous studies have addressed this issue via the deviation distribution (estimated error minus true error), in particular, the deterioration of cross-validation precision in high-dimensional settings where feature selection is used to mitigate the peaking phenomenon (overfitting). Because classifier design is based upon random samples, both the true and estimated errors are sample-dependent random variables, and one would expect a loss of precision if the estimated and true errors are not well correlated, so that natural questions arise as to the degree of correlation and the manner in which lack of correlation impacts error estimation. We demonstrate the effect of correlation on error precision via a decomposition of the variance of the deviation distribution, observe that the correlation is often severely decreased in high-dimensional settings, and show that the effect of high dimensionality on error estimation tends to result more from its decorrelating effects than from its impact on the variance of the estimated error. We consider the correlation between the true and estimated errors under different experimental conditions using both synthetic and real data, several feature-selection methods, different classification rules, and three error estimators commonly used (leave-one-out cross-validation, k-fold cross-validation, and .632 bootstrap). Moreover, three scenarios are considered: (1) feature selection, (2) known-feature set, and (3) all features. Only the first is of practical interest; however, the other two are needed for comparison purposes. We will observe that the true and estimated errors tend to be much more correlated in the case of a known feature set than with either feature selection or using all features, with the better correlation between the latter two showing no general trend, but differing for different models.

Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China).

PubMed

Zhao, Qilong; Strykowski, Gabriel; Li, Jiancheng; Pan, Xiong; Xu, Xinyu

2017-05-25

Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3-5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems.

Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China)

PubMed Central

Zhao, Qilong; Strykowski, Gabriel; Li, Jiancheng; Pan, Xiong; Xu, Xinyu

2017-01-01

Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3–5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems. PMID:28587086

Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China)

NASA Astrophysics Data System (ADS)

Zhao, Q.

2017-12-01

Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3-5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems.

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

The Effectiveness of Two Grammar Treatment Procedures for Children with SLI: A Randomized Clinical Trial

ERIC Educational Resources Information Center

Smith-Lock, Karen M.; Leitão, Suze; Prior, Polly; Nickels, Lyndsey

2015-01-01

Purpose: This study compared the effectiveness of two grammar treatment procedures for children with specific language impairment. Method: A double-blind superiority trial with cluster randomization was used to compare a cueing procedure, designed to elicit a correct production following an initial error, to a recasting procedure, which required…

Random Measurement Error Does Not Bias the Treatment Effect Estimate in the Regression-Discontinuity Design. II. When an Interaction Effect Is Present.

ERIC Educational Resources Information Center

Trochim, William M. K.; And Others

1991-01-01

The regression-discontinuity design involving a treatment interaction effect (TIE), pretest-posttest functional form specification, and choice of point-of-estimation of the TIE are examined. Formulas for controlling the magnitude of TIE in simulations can be used for simulating the randomized experimental case where estimation is not at the…

Disclosure of Medical Errors: What Factors Influence How Patients Respond?

PubMed Central

Mazor, Kathleen M; Reed, George W; Yood, Robert A; Fischer, Melissa A; Baril, Joann; Gurwitz, Jerry H

2006-01-01

BACKGROUND Disclosure of medical errors is encouraged, but research on how patients respond to specific practices is limited. OBJECTIVE This study sought to determine whether full disclosure, an existing positive physician-patient relationship, an offer to waive associated costs, and the severity of the clinical outcome influenced patients' responses to medical errors. PARTICIPANTS Four hundred and seven health plan members participated in a randomized experiment in which they viewed video depictions of medical error and disclosure. DESIGN Subjects were randomly assigned to experimental condition. Conditions varied in type of medication error, level of disclosure, reference to a prior positive physician-patient relationship, an offer to waive costs, and clinical outcome. MEASURES Self-reported likelihood of changing physicians and of seeking legal advice; satisfaction, trust, and emotional response. RESULTS Nondisclosure increased the likelihood of changing physicians, and reduced satisfaction and trust in both error conditions. Nondisclosure increased the likelihood of seeking legal advice and was associated with a more negative emotional response in the missed allergy error condition, but did not have a statistically significant impact on seeking legal advice or emotional response in the monitoring error condition. Neither the existence of a positive relationship nor an offer to waive costs had a statistically significant impact. CONCLUSIONS This study provides evidence that full disclosure is likely to have a positive effect or no effect on how patients respond to medical errors. The clinical outcome also influences patients' responses. The impact of an existing positive physician-patient relationship, or of waiving costs associated with the error remains uncertain. PMID:16808770

Some practical problems in implementing randomization.

PubMed

Downs, Matt; Tucker, Kathryn; Christ-Schmidt, Heidi; Wittes, Janet

2010-06-01

While often theoretically simple, implementing randomization to treatment in a masked, but confirmable, fashion can prove difficult in practice. At least three categories of problems occur in randomization: (1) bad judgment in the choice of method, (2) design and programming errors in implementing the method, and (3) human error during the conduct of the trial. This article focuses on these latter two types of errors, dealing operationally with what can go wrong after trial designers have selected the allocation method. We offer several case studies and corresponding recommendations for lessening the frequency of problems in allocating treatment or for mitigating the consequences of errors. Recommendations include: (1) reviewing the randomization schedule before starting a trial, (2) being especially cautious of systems that use on-demand random number generators, (3) drafting unambiguous randomization specifications, (4) performing thorough testing before entering a randomization system into production, (5) maintaining a dataset that captures the values investigators used to randomize participants, thereby allowing the process of treatment allocation to be reproduced and verified, (6) resisting the urge to correct errors that occur in individual treatment assignments, (7) preventing inadvertent unmasking to treatment assignments in kit allocations, and (8) checking a sample of study drug kits to allow detection of errors in drug packaging and labeling. Although we performed a literature search of documented randomization errors, the examples that we provide and the resultant recommendations are based largely on our own experience in industry-sponsored clinical trials. We do not know how representative our experience is or how common errors of the type we have seen occur. Our experience underscores the importance of verifying the integrity of the treatment allocation process before and during a trial. Clinical Trials 2010; 7: 235-245. http://ctj.sagepub.com.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

Development of a Tablet-based symbol digit modalities test for reliably assessing information processing speed in patients with stroke.

PubMed

Tung, Li-Chen; Yu, Wan-Hui; Lin, Gong-Hong; Yu, Tzu-Ying; Wu, Chien-Te; Tsai, Chia-Yin; Chou, Willy; Chen, Mei-Hsiang; Hsieh, Ching-Lin

2016-09-01

To develop a Tablet-based Symbol Digit Modalities Test (T-SDMT) and to examine the test-retest reliability and concurrent validity of the T-SDMT in patients with stroke. The study had two phases. In the first phase, six experts, nine college students and five outpatients participated in the development and testing of the T-SDMT. In the second phase, 52 outpatients were evaluated twice (2 weeks apart) with the T-SDMT and SDMT to examine the test-retest reliability and concurrent validity of the T-SDMT. The T-SDMT was developed via expert input and college student/patient feedback. Regarding test-retest reliability, the practise effects of the T-SDMT and SDMT were both trivial (d=0.12) but significant (p≦0.015). The improvement in the T-SDMT (4.7%) was smaller than that in the SDMT (5.6%). The minimal detectable changes (MDC%) of the T-SDMT and SDMT were 6.7 (22.8%) and 10.3 (32.8%), respectively. The T-SDMT and SDMT were highly correlated with each other at the two time points (Pearson's r=0.90-0.91). The T-SDMT demonstrated good concurrent validity with the SDMT. Because the T-SDMT had a smaller practise effect and less random measurement error (superior test-retest reliability), it is recommended over the SDMT for assessing information processing speed in patients with stroke. Implications for Rehabilitation The Symbol Digit Modalities Test (SDMT), a common measure of information processing speed, showed a substantial practise effect and considerable random measurement error in patients with stroke. The Tablet-based SDMT (T-SDMT) has been developed to reduce the practise effect and random measurement error of the SDMT in patients with stroke. The T-SDMT had smaller practise effect and random measurement error than the SDMT, which can provide more reliable assessments of information processing speed.

Sun compass error model

NASA Technical Reports Server (NTRS)

Blucker, T. J.; Ferry, W. W.

1971-01-01

An error model is described for the Apollo 15 sun compass, a contingency navigational device. Field test data are presented along with significant results of the test. The errors reported include a random error resulting from tilt in leveling the sun compass, a random error because of observer sighting inaccuracies, a bias error because of mean tilt in compass leveling, a bias error in the sun compass itself, and a bias error because the device is leveled to the local terrain slope.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

Effect of phase errors in stepped-frequency radar systems

NASA Astrophysics Data System (ADS)

Vanbrundt, H. E.

1988-04-01

Stepped-frequency waveforms are being considered for inverse synthetic aperture radar (ISAR) imaging from ship and airborne platforms and for detailed radar cross section (RCS) measurements of ships and aircraft. These waveforms make it possible to achieve resolutions of 1.0 foot by using existing radar designs and processing technology. One problem not yet fully resolved in using stepped-frequency waveform for ISAR imaging is the deterioration in signal level caused by random frequency error. Random frequency error of the stepped-frequency source results in reduced peak responses and increased null responses. The resulting reduced signal-to-noise ratio is range dependent. Two of the major concerns addressed in this report are radar range limitations for ISAR and the error in calibration for RCS measurements caused by differences in range between a passive reflector used for an RCS reference and the target to be measured. In addressing these concerns, NOSC developed an analysis to assess the tolerable frequency error in terms of resulting power loss in signal power and signal-to-phase noise.

Random errors in interferometry with the least-squares method

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

Wang Qi

2011-01-20

This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Covariate Imbalance and Precision in Measuring Treatment Effects

ERIC Educational Resources Information Center

Liu, Xiaofeng Steven

2011-01-01

Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…

Insight into organic reactions from the direct random phase approximation and its corrections

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

Ruzsinszky, Adrienn; Zhang, Igor Ying; Scheffler, Matthias

2015-10-14

The performance of the random phase approximation (RPA) and beyond-RPA approximations for the treatment of electron correlation is benchmarked on three different molecular test sets. The test sets are chosen to represent three typical sources of error which can contribute to the failure of most density functional approximations in chemical reactions. The first test set (atomization and n-homodesmotic reactions) offers a gradually increasing balance of error from the chemical environment. The second test set (Diels-Alder reaction cycloaddition = DARC) reflects more the effect of weak dispersion interactions in chemical reactions. Finally, the third test set (self-interaction error 11 = SIE11)more » represents reactions which are exposed to noticeable self-interaction errors. This work seeks to answer whether any one of the many-body approximations considered here successfully addresses all these challenges.« less

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Comment on 3PL IRT Adjustment for Guessing

ERIC Educational Resources Information Center

Chiu, Ting-Wei; Camilli, Gregory

2013-01-01

Guessing behavior is an issue discussed widely with regard to multiple choice tests. Its primary effect is on number-correct scores for examinees at lower levels of proficiency. This is a systematic error or bias, which increases observed test scores. Guessing also can inflate random error variance. Correction or adjustment for guessing formulas…

The Effects of Observation Errors on the Attack Vulnerability of Complex Networks

DTIC Science & Technology

2012-11-01

more detail, to construct a true network we select a topology (erdos- renyi (Erdos & Renyi , 1959), scale-free (Barabási & Albert, 1999), small world...Efficiency of Scale-Free Networks: Error and Attack Tolerance. Physica A, Volume 320, pp. 622-642. 6. Erdos, P. & Renyi , A., 1959. On Random Graphs, I

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-10-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining data sets from several analysers and using simulations, we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time lag eliminates these effects (provided the time lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-03-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. We are here applying a consistent approach based on auto- and cross-covariance functions to quantifying the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time-lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time-lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining datasets from several analysers and using simulations we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time-lag eliminates these effects (provided the time-lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time-lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

NASA Technical Reports Server (NTRS)

Ramirez, Daniel Perez; Whiteman, David N.; Veselovskii, Igor; Kolgotin, Alexei; Korenskiy, Michael; Alados-Arboledas, Lucas

2013-01-01

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

Random safety auditing, root cause analysis, failure mode and effects analysis.

PubMed

Ursprung, Robert; Gray, James

2010-03-01

Improving quality and safety in health care is a major concern for health care providers, the general public, and policy makers. Errors and quality issues are leading causes of morbidity and mortality across the health care industry. There is evidence that patients in the neonatal intensive care unit (NICU) are at high risk for serious medical errors. To facilitate compliance with safe practices, many institutions have established quality-assurance monitoring procedures. Three techniques that have been found useful in the health care setting are failure mode and effects analysis, root cause analysis, and random safety auditing. When used together, these techniques are effective tools for system analysis and redesign focused on providing safe delivery of care in the complex NICU system. Copyright 2010 Elsevier Inc. All rights reserved.

Encouraging the Flight of Error: Ethical Standards, Evidence Standards, and Randomized Trials

ERIC Educational Resources Information Center

Boruch, Robert

2007-01-01

Thomas Jefferson recognized the value of reason and scientific experimentation in the eighteenth century. This chapter extends the idea in contemporary ways to standards that may be used to judge the ethical propriety of randomized trials and the dependability of evidence on effects of social interventions.

A comparison between the original and Tablet-based Symbol Digit Modalities Test in patients with schizophrenia: Test-retest agreement, random measurement error, practice effect, and ecological validity.

PubMed

Tang, Shih-Fen; Chen, I-Hui; Chiang, Hsin-Yu; Wu, Chien-Te; Hsueh, I-Ping; Yu, Wan-Hui; Hsieh, Ching-Lin

2017-11-27

We aimed to compare the test-retest agreement, random measurement error, practice effect, and ecological validity of the original and Tablet-based Symbol Digit Modalities Test (T-SDMT) over five serial assessments, and to examine the concurrent validity of the T-SDMT in patients with schizophrenia. Sixty patients with chronic schizophrenia completed five serial assessments (one week apart) of the SDMT and T-SDMT and one assessment of the Activities of Daily Living Rating Scale III at the first time point. Both measures showed high test-retest agreement, similar levels of random measurement error over five serial assessments. Moreover, the practice effects of the two measures did not reach a plateau phase after five serial assessments in young and middle-aged participants. Nevertheless, only the practice effect of the T-SDMT became trivial after the first assessment. Like the SDMT, the T-SDMT had good ecological validity. The T-SDMT also had good concurrent validity with the SDMT. In addition, only the T-SDMT had discriminative validity to discriminate processing speed in young and middle-aged participants. Compared to the SDMT, the T-SDMT had overall slightly better psychometric properties, so it can be an alternative measure to the SDMT for assessing processing speed in patients with schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of Oral Reading Errors between Contextual Sentences and Random Words among Schoolchildren

ERIC Educational Resources Information Center

Khalid, Nursyairah Mohd; Buari, Noor Halilah; Chen, Ai-Hong

2017-01-01

This paper compares the oral reading errors between the contextual sentences and random words among schoolchildren. Two sets of reading materials were developed to test the oral reading errors in 30 schoolchildren (10.00±1.44 years). Set A was comprised contextual sentences while Set B encompassed random words. The schoolchildren were asked to…

Bandwagon effects and error bars in particle physics

NASA Astrophysics Data System (ADS)

Jeng, Monwhea

2007-02-01

We study historical records of experiments on particle masses, lifetimes, and widths, both for signs of expectation bias, and to compare actual errors with reported error bars. We show that significant numbers of particle properties exhibit "bandwagon effects": reported values show trends and clustering as a function of the year of publication, rather than random scatter about the mean. While the total amount of clustering is significant, it is also fairly small; most individual particle properties do not display obvious clustering. When differences between experiments are compared with the reported error bars, the deviations do not follow a normal distribution, but instead follow an exponential distribution for up to ten standard deviations.

The Expected Sample Variance of Uncorrelated Random Variables with a Common Mean and Some Applications in Unbalanced Random Effects Models

ERIC Educational Resources Information Center

Vardeman, Stephen B.; Wendelberger, Joanne R.

2005-01-01

There is a little-known but very simple generalization of the standard result that for uncorrelated random variables with common mean [mu] and variance [sigma][superscript 2], the expected value of the sample variance is [sigma][superscript 2]. The generalization justifies the use of the usual standard error of the sample mean in possibly…

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Evaluation and optimization of sampling errors for the Monte Carlo Independent Column Approximation

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Barker, W. Howard

2004-07-01

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average broadband radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. McICA's sampling errors are evaluated here using a global climate model (GCM) dataset and a correlated-k distribution (CKD) radiation scheme. Two approaches to reduce McICA's sampling variance are discussed. The first is to simply restrict all of McICA's samples to cloudy regions. This avoids wasting precious few samples on essentially homogeneous clear skies. Clear-sky fluxes need to be computed separately for this approach, but this is usually done in GCMs for diagnostic purposes anyway. Second, accuracy can be improved by repeated sampling, and averaging those CKD terms with large cloud radiative effects. Although this naturally increases computational costs over the standard CKD model, random errors for fluxes and heating rates are reduced by typically 50% to 60%, for the present radiation code, when the total number of samples is increased by 50%. When both variance reduction techniques are applied simultaneously, globally averaged flux and heating rate random errors are reduced by a factor of #3.

Adjusting for multiple prognostic factors in the analysis of randomised trials

PubMed Central

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size. PMID:23898993

Radar error statistics for the space shuttle

NASA Technical Reports Server (NTRS)

Lear, W. M.

1979-01-01

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Analysis of the impact of error detection on computer performance

NASA Technical Reports Server (NTRS)

Shin, K. C.; Lee, Y. H.

1983-01-01

Conventionally, reliability analyses either assume that a fault/error is detected immediately following its occurrence, or neglect damages caused by latent errors. Though unrealistic, this assumption was imposed in order to avoid the difficulty of determining the respective probabilities that a fault induces an error and the error is then detected in a random amount of time after its occurrence. As a remedy for this problem a model is proposed to analyze the impact of error detection on computer performance under moderate assumptions. Error latency, the time interval between occurrence and the moment of detection, is used to measure the effectiveness of a detection mechanism. This model is used to: (1) predict the probability of producing an unreliable result, and (2) estimate the loss of computation due to fault and/or error.

Random-access algorithms for multiuser computer communication networks. Doctoral thesis, 1 September 1986-31 August 1988

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

Papantoni-Kazakos, P.; Paterakis, M.

1988-07-01

For many communication applications with time constraints (e.g., transmission of packetized voice messages), a critical performance measure is the percentage of messages transmitted within a given amount of time after their generation at the transmitting station. This report presents a random-access algorithm (RAA) suitable for time-constrained applications. Performance analysis demonstrates that significant message-delay improvement is attained at the expense of minimal traffic loss. Also considered is the case of noisy channels. The noise effect appears at erroneously observed channel feedback. Error sensitivity analysis shows that the proposed random-access algorithm is insensitive to feedback channel errors. Window Random-Access Algorithms (RAAs) aremore » considered next. These algorithms constitute an important subclass of Multiple-Access Algorithms (MAAs); they are distributive, and they attain high throughput and low delays by controlling the number of simultaneously transmitting users.« less

Enhancement of cooperation in the spatial prisoner's dilemma with a coherence-resonance effect through annealed randomness at a cooperator-defector boundary; comparison of two variant models

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2016-11-01

Inspired by the commonly observed real-world fact that people tend to behave in a somewhat random manner after facing interim equilibrium to break a stalemate situation whilst seeking a higher output, we established two models of the spatial prisoner's dilemma. One presumes that an agent commits action errors, while the other assumes that an agent refers to a payoff matrix with an added random noise instead of an original payoff matrix. A numerical simulation revealed that mechanisms based on the annealing of randomness due to either the action error or the payoff noise could significantly enhance the cooperation fraction. In this study, we explain the detailed enhancement mechanism behind the two models by referring to the concepts that we previously presented with respect to evolutionary dynamic processes under the names of enduring and expanding periods.

A general method for the definition of margin recipes depending on the treatment technique applied in helical tomotherapy prostate plans.

PubMed

Sevillano, David; Mínguez, Cristina; Sánchez, Alicia; Sánchez-Reyes, Alberto

2016-01-01

To obtain specific margin recipes that take into account the dosimetric characteristics of the treatment plans used in a single institution. We obtained dose-population histograms (DPHs) of 20 helical tomotherapy treatment plans for prostate cancer by simulating the effects of different systematic errors (Σ) and random errors (σ) on these plans. We obtained dosimetric margins and margin reductions due to random errors (random margins) by fitting the theoretical results of coverages for Gaussian distributions with coverages of the planned D99% obtained from the DPHs. The dosimetric margins obtained for helical tomotherapy prostate treatments were 3.3 mm, 3 mm, and 1 mm in the lateral (Lat), anterior-posterior (AP), and superior-inferior (SI) directions. Random margins showed parabolic dependencies, yielding expressions of 0.16σ(2), 0.13σ(2), and 0.15σ(2) for the Lat, AP, and SI directions, respectively. When focusing on values up to σ = 5 mm, random margins could be fitted considering Gaussian penumbras with standard deviations (σp) equal to 4.5 mm Lat, 6 mm AP, and 5.5 mm SI. Despite complex dose distributions in helical tomotherapy treatment plans, we were able to simplify the behaviour of our plans against treatment errors to single values of dosimetric and random margins for each direction. These margins allowed us to develop specific margin recipes for the respective treatment technique. The method is general and could be used for any treatment technique provided that DPHs can be obtained. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

A Strategy to Use Soft Data Effectively in Randomized Controlled Clinical Trials.

ERIC Educational Resources Information Center

Kraemer, Helena Chmura; Thiemann, Sue

1989-01-01

Sees soft data, measures having substantial intrasubject variability due to errors of measurement or response inconsistency, as important measures of response in randomized clinical trials. Shows that using intensive design and slope of response on time as outcome measure maximizes sample retention and decreases within-group variability, thus…

Analysis on pseudo excitation of random vibration for structure of time flight counter

NASA Astrophysics Data System (ADS)

Wu, Qiong; Li, Dapeng

2015-03-01

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure. Pseudo Excitation Method(PEM) is an effective method for calculation of random vibration. Due to complicated and coupling random vibration in rocket or shuttle launching, the new staging white noise mathematical model is deduced according to the practical launch environment. This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter(ToFC). The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level. Considering stiffness of fixture structure, the random vibration experiments are conducted in three directions to compare with the revised PEM. The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained. The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results. The maximum error is within 9%. The reasons of errors are analyzed to improve reliability of calculation. This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

Stochastic characterization of phase detection algorithms in phase-shifting interferometry

DOE PAGES

Munteanu, Florin

2016-11-01

Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here,more » we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.« less

Influence of age, sex, technique, and exercise program on movement patterns after an anterior cruciate ligament injury prevention program in youth soccer players.

PubMed

DiStefano, Lindsay J; Padua, Darin A; DiStefano, Michael J; Marshall, Stephen W

2009-03-01

Anterior cruciate ligament (ACL) injury prevention programs show promising results with changing movement; however, little information exists regarding whether a program designed for an individual's movements may be effective or how baseline movements may affect outcomes. A program designed to change specific movements would be more effective than a "one-size-fits-all" program. Greatest improvement would be observed among individuals with the most baseline error. Subjects of different ages and sexes respond similarly. Randomized controlled trial; Level of evidence, 1. One hundred seventy-three youth soccer players from 27 teams were randomly assigned to a generalized or stratified program. Subjects were videotaped during jump-landing trials before and after the program and were assessed using the Landing Error Scoring System (LESS), which is a valid clinical movement analysis tool. A high LESS score indicates more errors. Generalized players performed the same exercises, while the stratified players performed exercises to correct their initial movement errors. Change scores were compared between groups of varying baseline errors, ages, sexes, and programs. Subjects with the highest baseline LESS score improved the most (95% CI, -3.4 to -2.0). High school subjects (95% CI, -1.7 to -0.98) improved their technique more than pre-high school subjects (95% CI, -1.0 to -0.4). There was no difference between the programs or sexes. Players with the greatest amount of movement errors experienced the most improvement. A program's effectiveness may be enhanced if this population is targeted.

Network problem threshold

NASA Technical Reports Server (NTRS)

Gejji, Raghvendra, R.

1992-01-01

Network transmission errors such as collisions, CRC errors, misalignment, etc. are statistical in nature. Although errors can vary randomly, a high level of errors does indicate specific network problems, e.g. equipment failure. In this project, we have studied the random nature of collisions theoretically as well as by gathering statistics, and established a numerical threshold above which a network problem is indicated with high probability.

Reference-free error estimation for multiple measurement methods.

PubMed

Madan, Hennadii; Pernuš, Franjo; Špiclin, Žiga

2018-01-01

We present a computational framework to select the most accurate and precise method of measurement of a certain quantity, when there is no access to the true value of the measurand. A typical use case is when several image analysis methods are applied to measure the value of a particular quantitative imaging biomarker from the same images. The accuracy of each measurement method is characterized by systematic error (bias), which is modeled as a polynomial in true values of measurand, and the precision as random error modeled with a Gaussian random variable. In contrast to previous works, the random errors are modeled jointly across all methods, thereby enabling the framework to analyze measurement methods based on similar principles, which may have correlated random errors. Furthermore, the posterior distribution of the error model parameters is estimated from samples obtained by Markov chain Monte-Carlo and analyzed to estimate the parameter values and the unknown true values of the measurand. The framework was validated on six synthetic and one clinical dataset containing measurements of total lesion load, a biomarker of neurodegenerative diseases, which was obtained with four automatic methods by analyzing brain magnetic resonance images. The estimates of bias and random error were in a good agreement with the corresponding least squares regression estimates against a reference.

Teaching Common Errors in Applying a Procedure. IDD&E Working Paper No. 18.

ERIC Educational Resources Information Center

Garduno, Alberto O.; And Others

The purpose of this study was to replicate the Bentti, Golden, and Reigeluth study (1983), which explored the use of nonexamples to teach common errors as an effective strategy in teaching a procedure. A total of 24 undergraduate students enrolled in the Syracuse University Symphonic Band were randomly assigned to an experimental group and a…

Is the Intergenerational Transmission of High Cultural Activities Biased by the Retrospective Measurement of Parental High Cultural Activities?

ERIC Educational Resources Information Center

de Vries, Jannes; de Graaf, Paul M.

2008-01-01

In this article we study the bias caused by the conventional retrospective measurement of parental high cultural activities in the effects of parental high cultural activities and educational attainment on son's or daughter's high cultural activities. Multi-informant data show that there is both random measurement error and correlated error in the…

Measurement Error and Bias in Value-Added Models. Research Report. ETS RR-17-25

ERIC Educational Resources Information Center

Kane, Michael T.

2017-01-01

By aggregating residual gain scores (the differences between each student's current score and a predicted score based on prior performance) for a school or a teacher, value-added models (VAMs) can be used to generate estimates of school or teacher effects. It is known that random errors in the prior scores will introduce bias into predictions of…

The Impact of Short-Term Science Teacher Professional Development on the Evaluation of Student Understanding and Errors Related to Natural Selection

ERIC Educational Resources Information Center

Buschang, Rebecca Ellen

2012-01-01

This study evaluated the effects of a short-term professional development session. Forty volunteer high school biology teachers were randomly assigned to one of two professional development conditions: (a) developing deep content knowledge (i.e., control condition) or (b) evaluating student errors and understanding in writing samples (i.e.,…

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

Scattering from binary optics

NASA Technical Reports Server (NTRS)

Ricks, Douglas W.

1993-01-01

There are a number of sources of scattering in binary optics: etch depth errors, line edge errors, quantization errors, roughness, and the binary approximation to the ideal surface. These sources of scattering can be systematic (deterministic) or random. In this paper, scattering formulas for both systematic and random errors are derived using Fourier optics. These formulas can be used to explain the results of scattering measurements and computer simulations.

The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

PubMed Central

Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

2016-01-01

Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Effects of postexercise ice-water and room-temperature water immersion on the sensory organization of balance control and lower limb proprioception in amateur rugby players

PubMed Central

Chow, Gary C.C.; Yam, Timothy T.T.; Chung, Joanne W.Y.; Fong, Shirley S.M.

2017-01-01

Abstract Background: This single-blinded, three-armed randomized controlled trial aimed to compare the effects of postexercise ice-water immersion (IWI), room-temperature water immersion (RWI), and no water immersion on the balance performance and knee joint proprioception of amateur rugby players. Methods: Fifty-three eligible amateur rugby players (mean age ± standard deviation: 21.6 ± 2.9 years) were randomly assigned to the IWI group (5.3 °C), RWI group (25.0 °C), or the no immersion control group. The participants in each group underwent the same fatigue protocol followed by their allocated recovery intervention, which lasted for 1 minute. Measurements were taken before and after the fatigue-recovery intervention. The primary outcomes were the sensory organization test (SOT) composite equilibrium score (ES) and the condition-specific ES, which were measured using a computerized dynamic posturography machine. The secondary outcome was the knee joint repositioning error. Two-way repeated measures analysis of variance was used to test the effect of water immersion on each outcome variable. Results: There were no significant within- and between-group differences in the SOT composite ESs or the condition-specific ESs. However, there was a group-by-time interaction effect on the knee joint repositioning error. It seems that participants in the RWI group had lower errors over time, but those in the IWI and control groups had increased errors over time. The RWI group had significantly lower error score than the IWI group at postintervention. Conclusion: One minute of postexercise IWI or RWI did not impair rugby players’ sensory organization of balance control. RWI had a less detrimental effect on knee joint proprioception to IWI at postintervention. PMID:28207546

Test-retest reliability of jump execution variables using mechanography: a comparison of jump protocols.

PubMed

Fitzgerald, John S; Johnson, LuAnn; Tomkinson, Grant; Stein, Jesse; Roemmich, James N

2018-05-01

Mechanography during the vertical jump may enhance screening and determining mechanistic causes underlying physical performance changes. Utility of jump mechanography for evaluation is limited by scant test-retest reliability data on force-time variables. This study examined the test-retest reliability of eight jump execution variables assessed from mechanography. Thirty-two women (mean±SD: age 20.8 ± 1.3 yr) and 16 men (age 22.1 ± 1.9 yr) attended a familiarization session and two testing sessions, all one week apart. Participants performed two variations of the squat jump with squat depth self-selected and controlled using a goniometer to 80º knee flexion. Test-retest reliability was quantified as the systematic error (using effect size between jumps), random error (using coefficients of variation), and test-retest correlations (using intra-class correlation coefficients). Overall, jump execution variables demonstrated acceptable reliability, evidenced by small systematic errors (mean±95%CI: 0.2 ± 0.07), moderate random errors (mean±95%CI: 17.8 ± 3.7%), and very strong test-retest correlations (range: 0.73-0.97). Differences in random errors between controlled and self-selected protocols were negligible (mean±95%CI: 1.3 ± 2.3%). Jump execution variables demonstrated acceptable reliability, with no meaningful differences between the controlled and self-selected jump protocols. To simplify testing, a self-selected jump protocol can be used to assess force-time variables with negligible impact on measurement error.

[Efficacy of motivational interviewing for reducing medication errors in chronic patients over 65 years with polypharmacy: Results of a cluster randomized trial].

PubMed

Pérula de Torres, Luis Angel; Pulido Ortega, Laura; Pérula de Torres, Carlos; González Lama, Jesús; Olaya Caro, Inmaculada; Ruiz Moral, Roger

2014-10-21

To evaluate the effectiveness of an intervention based on motivational interviewing to reduce medication errors in chronic patients over 65 with polypharmacy. Cluster randomized trial that included doctors and nurses of 16 Primary Care centers and chronic patients with polypharmacy over 65 years. The professionals were assigned to the experimental or the control group using stratified randomization. Interventions consisted of training of professionals and revision of patient treatments, application of motivational interviewing in the experimental group and also the usual approach in the control group. The primary endpoint (medication error) was analyzed at individual level, and was estimated with the absolute risk reduction (ARR), relative risk reduction (RRR), number of subjects to treat (NNT) and by multiple logistic regression analysis. Thirty-two professionals were randomized (19 doctors and 13 nurses), 27 of them recruited 154 patients consecutively (13 professionals in the experimental group recruited 70 patients and 14 professionals recruited 84 patients in the control group) and completed 6 months of follow-up. The mean age of patients was 76 years (68.8% women). A decrease in the average of medication errors was observed along the period. The reduction was greater in the experimental than in the control group (F=5.109, P=.035). RRA 29% (95% confidence interval [95% CI] 15.0-43.0%), RRR 0.59 (95% CI:0.31-0.76), and NNT 3.5 (95% CI 2.3-6.8). Motivational interviewing is more efficient than the usual approach to reduce medication errors in patients over 65 with polypharmacy. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

DOE PAGES

Ye, Xin; Garikapati, Venu M.; You, Daehyun; ...

2017-11-08

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

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

Ye, Xin; Garikapati, Venu M.; You, Daehyun

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates.

PubMed

Fottrell, Edward; Byass, Peter; Berhane, Yemane

2008-03-25

As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.

The Impact of Short-Term Science Teacher Professional Development on the Evaluation of Student Understanding and Errors Related to Natural Selection. CRESST Report 822

ERIC Educational Resources Information Center

Buschang, Rebecca E.

2012-01-01

This study evaluated the effects of a short-term professional development session. Forty volunteer high school biology teachers were randomly assigned to one of two professional development conditions: (a) developing deep content knowledge (i.e., control condition) or (b) evaluating student errors and understanding in writing samples (i.e.,…

Meta-analysis inside and outside particle physics: two traditions that should converge?

PubMed

Baker, Rose D; Jackson, Dan

2013-06-01

The use of meta-analysis in medicine and epidemiology really took off in the 1970s. However, in high-energy physics, the Particle Data Group has been carrying out meta-analyses of measurements of particle masses and other properties since 1957. Curiously, there has been virtually no interaction between those working inside and outside particle physics. In this paper, we use statistical models to study two major differences in practice. The first is the usefulness of systematic errors, which physicists are now beginning to quote in addition to statistical errors. The second is whether it is better to treat heterogeneity by scaling up errors as do the Particle Data Group or by adding a random effect as does the rest of the community. Besides fitting models, we derive and use an exact test of the error-scaling hypothesis. We also discuss the other methodological differences between the two streams of meta-analysis. Our conclusion is that systematic errors are not currently very useful and that the conventional random effects model, as routinely used in meta-analysis, has a useful role to play in particle physics. The moral we draw for statisticians is that we should be more willing to explore 'grassroots' areas of statistical application, so that good statistical practice can flow both from and back to the statistical mainstream. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model

NASA Astrophysics Data System (ADS)

Zou, Guang'an; Wang, Qiang; Mu, Mu

2016-09-01

Sensitive areas for prediction of the Kuroshio large meander using a 1.5-layer, shallow-water ocean model were investigated using the conditional nonlinear optimal perturbation (CNOP) and first singular vector (FSV) methods. A series of sensitivity experiments were designed to test the sensitivity of sensitive areas within the numerical model. The following results were obtained: (1) the eff ect of initial CNOP and FSV patterns in their sensitive areas is greater than that of the same patterns in randomly selected areas, with the eff ect of the initial CNOP patterns in CNOP sensitive areas being the greatest; (2) both CNOP- and FSV-type initial errors grow more quickly than random errors; (3) the eff ect of random errors superimposed on the sensitive areas is greater than that of random errors introduced into randomly selected areas, and initial errors in the CNOP sensitive areas have greater eff ects on final forecasts. These results reveal that the sensitive areas determined using the CNOP are more sensitive than those of FSV and other randomly selected areas. In addition, ideal hindcasting experiments were conducted to examine the validity of the sensitive areas. The results indicate that reduction (or elimination) of CNOP-type errors in CNOP sensitive areas at the initial time has a greater forecast benefit than the reduction (or elimination) of FSV-type errors in FSV sensitive areas. These results suggest that the CNOP method is suitable for determining sensitive areas in the prediction of the Kuroshio large-meander path.

Portable and Error-Free DNA-Based Data Storage.

PubMed

Yazdi, S M Hossein Tabatabaei; Gabrys, Ryan; Milenkovic, Olgica

2017-07-10

DNA-based data storage is an emerging nonvolatile memory technology of potentially unprecedented density, durability, and replication efficiency. The basic system implementation steps include synthesizing DNA strings that contain user information and subsequently retrieving them via high-throughput sequencing technologies. Existing architectures enable reading and writing but do not offer random-access and error-free data recovery from low-cost, portable devices, which is crucial for making the storage technology competitive with classical recorders. Here we show for the first time that a portable, random-access platform may be implemented in practice using nanopore sequencers. The novelty of our approach is to design an integrated processing pipeline that encodes data to avoid costly synthesis and sequencing errors, enables random access through addressing, and leverages efficient portable sequencing via new iterative alignment and deletion error-correcting codes. Our work represents the only known random access DNA-based data storage system that uses error-prone nanopore sequencers, while still producing error-free readouts with the highest reported information rate/density. As such, it represents a crucial step towards practical employment of DNA molecules as storage media.

CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests.

PubMed

Ma, Li; Fan, Suohai

2017-03-14

The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. We propose the CURE-SMOTE algorithm for the imbalanced data classification problem. Experiments on imbalanced UCI data reveal that the combination of Clustering Using Representatives (CURE) enhances the original synthetic minority oversampling technique (SMOTE) algorithms effectively compared with the classification results on the original data using random sampling, Borderline-SMOTE1, safe-level SMOTE, C-SMOTE, and k-means-SMOTE. Additionally, the hybrid RF (random forests) algorithm has been proposed for feature selection and parameter optimization, which uses the minimum out of bag (OOB) data error as its objective function. Simulation results on binary and higher-dimensional data indicate that the proposed hybrid RF algorithms, hybrid genetic-random forests algorithm, hybrid particle swarm-random forests algorithm and hybrid fish swarm-random forests algorithm can achieve the minimum OOB error and show the best generalization ability. The training set produced from the proposed CURE-SMOTE algorithm is closer to the original data distribution because it contains minimal noise. Thus, better classification results are produced from this feasible and effective algorithm. Moreover, the hybrid algorithm's F-value, G-mean, AUC and OOB scores demonstrate that they surpass the performance of the original RF algorithm. Hence, this hybrid algorithm provides a new way to perform feature selection and parameter optimization.

Response Surface Analysis of Experiments with Random Blocks

DTIC Science & Technology

1988-09-01

partitioned into a lack of fit sum of squares, SSLOF, and a pure error sum of squares, SSPE . The latter is obtained by pooling the pure error sums of squares...from the blocks. Tests concerning the polynomial effects can then proceed using SSPE as the error term in the denominators of the F test statistics. 3.2...the center point in each of the three blocks is equal to SSPE = 2.0127 with 5 degrees of freedom. Hence, the lack of fit sum of squares is SSLoF

Neither fixed nor random: weighted least squares meta-regression.

PubMed

Stanley, T D; Doucouliagos, Hristos

2017-03-01

Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Opposite effects of cannabis and cocaine on performance monitoring.

PubMed

Spronk, Desirée B; Verkes, Robbert J; Cools, Roshan; Franke, Barbara; Van Wel, Janelle H P; Ramaekers, Johannes G; De Bruijn, Ellen R A

2016-07-01

Drug use is often associated with risky and unsafe behavior. However, the acute effects of cocaine and cannabis on performance monitoring processes have not been systematically investigated. The aim of the current study was to investigate how administration of these drugs alters performance monitoring processes, as reflected in the error-related negativity (ERN), the error positivity (Pe) and post-error slowing. A double-blind placebo-controlled randomized three-way crossover design was used. Sixty-one subjects completed a Flanker task while EEG measures were obtained. Subjects showed diminished ERN and Pe amplitudes after cannabis administration and increased ERN and Pe amplitudes after administration of cocaine. Neither drug affected post-error slowing. These results demonstrate diametrically opposing effects on the early and late phases of performance monitoring of the two most commonly used illicit drugs of abuse. Conversely, the behavioral adaptation phase of performance monitoring remained unaltered by the drugs. Copyright © 2016. Published by Elsevier B.V.

Multilevel Modeling with Correlated Effects

ERIC Educational Resources Information Center

Kim, Jee-Seon; Frees, Edward W.

2007-01-01

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized…

A proposed method to investigate reliability throughout a questionnaire.

PubMed

Wentzel-Larsen, Tore; Norekvål, Tone M; Ulvik, Bjørg; Nygård, Ottar; Pripp, Are H

2011-10-05

Questionnaires are used extensively in medical and health care research and depend on validity and reliability. However, participants may differ in interest and awareness throughout long questionnaires, which can affect reliability of their answers. A method is proposed for "screening" of systematic change in random error, which could assess changed reliability of answers. A simulation study was conducted to explore whether systematic change in reliability, expressed as changed random error, could be assessed using unsupervised classification of subjects by cluster analysis (CA) and estimation of intraclass correlation coefficient (ICC). The method was also applied on a clinical dataset from 753 cardiac patients using the Jalowiec Coping Scale. The simulation study showed a relationship between the systematic change in random error throughout a questionnaire and the slope between the estimated ICC for subjects classified by CA and successive items in a questionnaire. This slope was proposed as an awareness measure--to assessing if respondents provide only a random answer or one based on a substantial cognitive effort. Scales from different factor structures of Jalowiec Coping Scale had different effect on this awareness measure. Even though assumptions in the simulation study might be limited compared to real datasets, the approach is promising for assessing systematic change in reliability throughout long questionnaires. Results from a clinical dataset indicated that the awareness measure differed between scales.

Development of multiple-eye PIV using mirror array

NASA Astrophysics Data System (ADS)

Maekawa, Akiyoshi; Sakakibara, Jun

2018-06-01

In order to reduce particle image velocimetry measurement error, we manufactured an ellipsoidal polyhedral mirror and placed it between a camera and flow target to capture n images of identical particles from n (=80 maximum) different directions. The 3D particle positions were determined from the ensemble average of n C2 intersecting points of a pair of line-of-sight back-projected points from a particle found in any combination of two images in the n images. The method was then applied to a rigid-body rotating flow and a turbulent pipe flow. In the former measurement, bias error and random error fell in a range of  ±0.02 pixels and 0.02–0.05 pixels, respectively; additionally, random error decreased in proportion to . In the latter measurement, in which the measured value was compared to direct numerical simulation, bias error was reduced and random error also decreased in proportion to .

Learning by (video) example: a randomized study of communication skills training for end-of-life and error disclosure family care conferences.

PubMed

Schmitz, Connie C; Braman, Jonathan P; Turner, Norman; Heller, Stephanie; Radosevich, David M; Yan, Yelena; Miller, Jane; Chipman, Jeffrey G

2016-11-01

Teaching residents to lead end of life (EOL) and error disclosure (ED) conferences is important. We developed and tested an intervention using videotapes of EOL and error disclosure encounters from previous Objective Structured Clinical Exams. Residents (n = 72) from general and orthopedic surgery programs at 2 sites were enrolled. Using a prospective, pre-post, block group design with stratified randomization, we hypothesized the treatment group would outperform the control on EOL and ED cases. We also hypothesized that online course usage would correlate positively with post-test scores. All residents improved (pre-post). At the group level, treatment effects were insignificant, and post-test performance was unrelated to course usage. At the subgroup level for EOL, low performers assigned to treatment scored higher than controls at post-test; and within the treatment group, post graduate year 3 residents outperformed post graduate year ​1 residents. To be effective, online curricula illustrating communication behaviors need face-to-face interaction, individual role play with feedback and discussion. Copyright © 2016 Elsevier Inc. All rights reserved.

Power collection reduction by mirror surface nonflatness and tracking error for a central receiver solar power system.

PubMed

McFee, R H

1975-07-01

The effects of random waviness, curvature, and tracking error of plane-mirror heliostats in a rectangular array around a central-receiver solar power system are determined by subdividing each mirror into 484 elements, assuming the slope of each element to be representative of the surface slope average at its location, and summing the contributions of all elements and then of all mirrors in the array. Total received power and flux density distribution are computed for a given sun location and set of array parameter values. Effects of shading and blocking by adjacent mirrors are included in the calculation. Alt-azimuth mounting of the heliostats is assumed. Representative curves for two receiver diameters and two sun locations indicate a power loss of 20% for random waviness, curvature, and tracking error of 0.1 degrees rms, 0.002 m(-1), and 0.5 degrees , 3sigma, respectively, for an 18.2-m diam receiver and 0.3 degrees rms, 0.005 m(-1), and greater than 1 degrees , respectively, for a 30.4-m diam receiver.

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

PubMed

Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

2014-08-01

To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Combined influence of CT random noise and HU-RSP calibration curve nonlinearities on proton range systematic errors

NASA Astrophysics Data System (ADS)

Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.

2017-11-01

Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.

At least some errors are randomly generated (Freud was wrong)

NASA Technical Reports Server (NTRS)

Sellen, A. J.; Senders, J. W.

1986-01-01

An experiment was carried out to expose something about human error generating mechanisms. In the context of the experiment, an error was made when a subject pressed the wrong key on a computer keyboard or pressed no key at all in the time allotted. These might be considered, respectively, errors of substitution and errors of omission. Each of seven subjects saw a sequence of three digital numbers, made an easily learned binary judgement about each, and was to press the appropriate one of two keys. Each session consisted of 1,000 presentations of randomly permuted, fixed numbers broken into 10 blocks of 100. One of two keys should have been pressed within one second of the onset of each stimulus. These data were subjected to statistical analyses in order to probe the nature of the error generating mechanisms. Goodness of fit tests for a Poisson distribution for the number of errors per 50 trial interval and for an exponential distribution of the length of the intervals between errors were carried out. There is evidence for an endogenous mechanism that may best be described as a random error generator. Furthermore, an item analysis of the number of errors produced per stimulus suggests the existence of a second mechanism operating on task driven factors producing exogenous errors. Some errors, at least, are the result of constant probability generating mechanisms with error rate idiosyncratically determined for each subject.

On the Calculation of Uncertainty Statistics with Error Bounds for CFD Calculations Containing Random Parameters and Fields

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2016-01-01

This chapter discusses the ongoing development of combined uncertainty and error bound estimates for computational fluid dynamics (CFD) calculations subject to imposed random parameters and random fields. An objective of this work is the construction of computable error bound formulas for output uncertainty statistics that guide CFD practitioners in systematically determining how accurately CFD realizations should be approximated and how accurately uncertainty statistics should be approximated for output quantities of interest. Formal error bounds formulas for moment statistics that properly account for the presence of numerical errors in CFD calculations and numerical quadrature errors in the calculation of moment statistics have been previously presented in [8]. In this past work, hierarchical node-nested dense and sparse tensor product quadratures are used to calculate moment statistics integrals. In the present work, a framework has been developed that exploits the hierarchical structure of these quadratures in order to simplify the calculation of an estimate of the quadrature error needed in error bound formulas. When signed estimates of realization error are available, this signed error may also be used to estimate output quantity of interest probability densities as a means to assess the impact of realization error on these density estimates. Numerical results are presented for CFD problems with uncertainty to demonstrate the capabilities of this framework.

Setup deviations for whole-breast radiotherapy with TomoDirect: A comparison of weekly and biweekly image-guided protocols

NASA Astrophysics Data System (ADS)

Jung, Jae Hong; Jung, Joo-Young; Bae, Sun Hyun; Moon, Seong Kwon; Cho, Kwang Hwan

2016-10-01

The purpose of this study was to compare patient setup deviations for different image-guided protocols (weekly vs. biweekly) that are used in TomoDirect three-dimensional conformal radiotherapy (TD-3DCRT) for whole-breast radiation therapy (WBRT). A total of 138 defined megavoltage computed tomography (MVCT) image sets from 46 breast cancer cases were divided into two groups based on the imaging acquisition times: weekly or biweekly. The mean error, three-dimensional setup displacement error (3D-error), systematic error (Σ), and random error (σ) were calculated for each group. The 3D-errors were 4.29 ± 1.11 mm and 5.02 ± 1.85 mm for the weekly and biweekly groups, respectively; the biweekly error was 14.6% higher than the weekly error. The systematic errors in the roll angle and the x, y, and z directions were 0.48°, 1.72 mm, 2.18 mm, and 1.85 mm for the weekly protocol and 0.21°, 1.24 mm, 1.39 mm, and 1.85 mm for the biweekly protocol. Random errors in the roll angle and the x, y, and z directions were 25.7%, 40.6%, 40.0%, and 40.8% higher in the biweekly group than in the weekly group. For the x, y, and z directions, the distributions of the treatment frequency at less than 5 mm were 98.6%, 91.3%, and 94.2% in the weekly group and 94.2%, 89.9%, and 82.6% in the biweekly group. Moreover, the roll angles with 0 - 1° were 79.7% and 89.9% in the weekly and the biweekly groups, respectively. Overall, the evaluation of setup deviations for the two protocols revealed no significant differences (p > 0.05). Reducing the frequency of MVCT imaging could have promising effects on imaging doses and machine times during treatment. However, the biweekly protocol was associated with increased random setup deviations in the treatment. We have demonstrated a biweekly protocol of TD-3DCRT for WBRT, and we anticipate that our method may provide an alternative approach for considering the uncertainties in the patient setup.

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

Effect of magnesium added to local anesthetics for caudal anesthesia on postoperative pain in pediatric surgical patients: A systematic review and meta-analysis with Trial Sequential Analysis.

PubMed

Kawakami, Hiromasa; Mihara, Takahiro; Nakamura, Nobuhito; Ka, Koui; Goto, Takahisa

2018-01-01

Magnesium has been investigated as an adjuvant for neuraxial anesthesia, but the effect of caudal magnesium on postoperative pain is inconsistent. The aim of this systematic review and meta-analysis was to evaluate the analgesic effect of caudal magnesium. We searched six databases, including trial registration sites. Randomized clinical trials reporting the effect of caudal magnesium on postoperative pain after general anesthesia were eligible. The risk ratio for use of rescue analgesics after surgery was combined using a random-effects model. We also assessed adverse events. The I2 statistic was used to assess heterogeneity. We assessed risk of bias with Cochrane domains. We controlled type I and II errors due to sparse data and repetitive testing with Trial Sequential Analysis. We assessed the quality of evidence with GRADE. Four randomized controlled trials (247 patients) evaluated the need for rescue analgesics. In all four trials, 50 mg of magnesium was administered with caudal ropivacaine. The results suggested that the need for rescue analgesia was reduced significantly by caudal magnesium administration (risk ratio 0.45; 95% confidence interval 0.24-0.86). There was considerable heterogeneity as indicated by an I2 value of 62.5%. The Trial Sequential Analysis-adjusted confidence interval was 0.04-5.55, indicating that further trials are required. The quality of evidence was very low. The rate of adverse events was comparable between treatment groups. Caudal magnesium may reduce the need for rescue analgesia after surgery, but further randomized clinical trials with a low risk of bias and a low risk of random errors are necessary to assess the effect of caudal magnesium on postoperative pain and adverse events. University Hospital Medical Information Network Clinical Trials Registry UMIN000025344.

SU-F-T-288: Impact of Trajectory Log Files for Clarkson-Based Independent Dose Verification of IMRT and VMAT

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

Takahashi, R; Kamima, T; Tachibana, H

2016-06-15

Purpose: To investigate the effect of the trajectory files from linear accelerator for Clarkson-based independent dose verification in IMRT and VMAT plans. Methods: A CT-based independent dose verification software (Simple MU Analysis: SMU, Triangle Products, Japan) with a Clarksonbased algorithm was modified to calculate dose using the trajectory log files. Eclipse with the three techniques of step and shoot (SS), sliding window (SW) and Rapid Arc (RA) was used as treatment planning system (TPS). In this study, clinically approved IMRT and VMAT plans for prostate and head and neck (HN) at two institutions were retrospectively analyzed to assess the dosemore » deviation between DICOM-RT plan (PL) and trajectory log file (TJ). An additional analysis was performed to evaluate MLC error detection capability of SMU when the trajectory log files was modified by adding systematic errors (0.2, 0.5, 1.0 mm) and random errors (5, 10, 30 mm) to actual MLC position. Results: The dose deviations for prostate and HN in the two sites were 0.0% and 0.0% in SS, 0.1±0.0%, 0.1±0.1% in SW and 0.6±0.5%, 0.7±0.9% in RA, respectively. The MLC error detection capability shows the plans for HN IMRT were the most sensitive and 0.2 mm of systematic error affected 0.7% dose deviation on average. Effect of the MLC random error did not affect dose error. Conclusion: The use of trajectory log files including actual information of MLC location, gantry angle, etc should be more effective for an independent verification. The tolerance level for the secondary check using the trajectory file may be similar to that of the verification using DICOM-RT plan file. From the view of the resolution of MLC positional error detection, the secondary check could detect the MLC position error corresponding to the treatment sites and techniques. This research is partially supported by Japan Agency for Medical Research and Development (AMED)« less

Dynamically corrected gates for singlet-triplet spin qubits with control-dependent errors

NASA Astrophysics Data System (ADS)

Jacobson, N. Tobias; Witzel, Wayne M.; Nielsen, Erik; Carroll, Malcolm S.

2013-03-01

Magnetic field inhomogeneity due to random polarization of quasi-static local magnetic impurities is a major source of environmentally induced error for singlet-triplet double quantum dot (DQD) spin qubits. Moreover, for singlet-triplet qubits this error may depend on the applied controls. This effect is significant when a static magnetic field gradient is applied to enable full qubit control. Through a configuration interaction analysis, we observe that the dependence of the field inhomogeneity-induced error on the DQD bias voltage can vary systematically as a function of the controls for certain experimentally relevant operating regimes. To account for this effect, we have developed a straightforward prescription for adapting dynamically corrected gate sequences that assume control-independent errors into sequences that compensate for systematic control-dependent errors. We show that accounting for such errors may lead to a substantial increase in gate fidelities. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. DOE's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Random forests of interaction trees for estimating individualized treatment effects in randomized trials.

PubMed

Su, Xiaogang; Peña, Annette T; Liu, Lei; Levine, Richard A

2018-04-29

Assessing heterogeneous treatment effects is a growing interest in advancing precision medicine. Individualized treatment effects (ITEs) play a critical role in such an endeavor. Concerning experimental data collected from randomized trials, we put forward a method, termed random forests of interaction trees (RFIT), for estimating ITE on the basis of interaction trees. To this end, we propose a smooth sigmoid surrogate method, as an alternative to greedy search, to speed up tree construction. The RFIT outperforms the "separate regression" approach in estimating ITE. Furthermore, standard errors for the estimated ITE via RFIT are obtained with the infinitesimal jackknife method. We assess and illustrate the use of RFIT via both simulation and the analysis of data from an acupuncture headache trial. Copyright © 2018 John Wiley & Sons, Ltd.

Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

NASA Technical Reports Server (NTRS)

Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)

2001-01-01

A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

PubMed

Zhou, Tony; Dickson, Jennifer L; Geoffrey Chase, J

2018-01-01

Continuous glucose monitoring (CGM) devices have been effective in managing diabetes and offer potential benefits for use in the intensive care unit (ICU). Use of CGM devices in the ICU has been limited, primarily due to the higher point accuracy errors over currently used traditional intermittent blood glucose (BG) measures. General models of CGM errors, including drift and random errors, are lacking, but would enable better design of protocols to utilize these devices. This article presents an autoregressive (AR) based modeling method that separately characterizes the drift and random noise of the GlySure CGM sensor (GlySure Limited, Oxfordshire, UK). Clinical sensor data (n = 33) and reference measurements were used to generate 2 AR models to describe sensor drift and noise. These models were used to generate 100 Monte Carlo simulations based on reference blood glucose measurements. These were then compared to the original CGM clinical data using mean absolute relative difference (MARD) and a Trend Compass. The point accuracy MARD was very similar between simulated and clinical data (9.6% vs 9.9%). A Trend Compass was used to assess trend accuracy, and found simulated and clinical sensor profiles were similar (simulated trend index 11.4° vs clinical trend index 10.9°). The model and method accurately represents cohort sensor behavior over patients, providing a general modeling approach to any such sensor by separately characterizing each type of error that can arise in the data. Overall, it enables better protocol design based on accurate expected CGM sensor behavior, as well as enabling the analysis of what level of each type of sensor error would be necessary to obtain desired glycemic control safety and performance with a given protocol.

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

PubMed Central

Regoui, Chaouki; Durand, Guillaume; Belliveau, Luc; Léger, Serge

2013-01-01

This paper presents a novel hybrid DNA encryption (HyDEn) approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach. PMID:23984392

The effect of covariate mean differences on the standard error and confidence interval for the comparison of treatment means.

PubMed

Liu, Xiaofeng Steven

2011-05-01

The use of covariates is commonly believed to reduce the unexplained error variance and the standard error for the comparison of treatment means, but the reduction in the standard error is neither guaranteed nor uniform over different sample sizes. The covariate mean differences between the treatment conditions can inflate the standard error of the covariate-adjusted mean difference and can actually produce a larger standard error for the adjusted mean difference than that for the unadjusted mean difference. When the covariate observations are conceived of as randomly varying from one study to another, the covariate mean differences can be related to a Hotelling's T(2) . Using this Hotelling's T(2) statistic, one can always find a minimum sample size to achieve a high probability of reducing the standard error and confidence interval width for the adjusted mean difference. ©2010 The British Psychological Society.

Antioxidant supplements and mortality.

PubMed

Bjelakovic, Goran; Nikolova, Dimitrinka; Gluud, Christian

2014-01-01

Oxidative damage to cells and tissues is considered involved in the aging process and in the development of chronic diseases in humans, including cancer and cardiovascular diseases, the leading causes of death in high-income countries. This has stimulated interest in the preventive potential of antioxidant supplements. Today, more than one half of adults in high-income countries ingest antioxidant supplements hoping to improve their health, oppose unhealthy behaviors, and counteract the ravages of aging. Older observational studies and some randomized clinical trials with high risks of systematic errors ('bias') have suggested that antioxidant supplements may improve health and prolong life. A number of randomized clinical trials with adequate methodologies observed neutral or negative results of antioxidant supplements. Recently completed large randomized clinical trials with low risks of bias and systematic reviews of randomized clinical trials taking systematic errors ('bias') and risks of random errors ('play of chance') into account have shown that antioxidant supplements do not seem to prevent cancer, cardiovascular diseases, or death. Even more, beta-carotene, vitamin A, and vitamin E may increase mortality. Some recent large observational studies now support these findings. According to recent dietary guidelines, there is no evidence to support the use of antioxidant supplements in the primary prevention of chronic diseases or mortality. Antioxidant supplements do not possess preventive effects and may be harmful with unwanted consequences to our health, especially in well-nourished populations. The optimal source of antioxidants seems to come from our diet, not from antioxidant supplements in pills or tablets.

The random coding bound is tight for the average code.

NASA Technical Reports Server (NTRS)

Gallager, R. G.

1973-01-01

The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upperbounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.

A Comparison of Four Approaches to Account for Method Effects in Latent State-Trait Analyses

ERIC Educational Resources Information Center

Geiser, Christian; Lockhart, Ginger

2012-01-01

Latent state-trait (LST) analysis is frequently applied in psychological research to determine the degree to which observed scores reflect stable person-specific effects, effects of situations and/or person-situation interactions, and random measurement error. Most LST applications use multiple repeatedly measured observed variables as indicators…

Inference of median difference based on the Box-Cox model in randomized clinical trials.

PubMed

Maruo, K; Isogawa, N; Gosho, M

2015-05-10

In randomized clinical trials, many medical and biological measurements are not normally distributed and are often skewed. The Box-Cox transformation is a powerful procedure for comparing two treatment groups for skewed continuous variables in terms of a statistical test. However, it is difficult to directly estimate and interpret the location difference between the two groups on the original scale of the measurement. We propose a helpful method that infers the difference of the treatment effect on the original scale in a more easily interpretable form. We also provide statistical analysis packages that consistently include an estimate of the treatment effect, covariance adjustments, standard errors, and statistical hypothesis tests. The simulation study that focuses on randomized parallel group clinical trials with two treatment groups indicates that the performance of the proposed method is equivalent to or better than that of the existing non-parametric approaches in terms of the type-I error rate and power. We illustrate our method with cluster of differentiation 4 data in an acquired immune deficiency syndrome clinical trial. Copyright © 2015 John Wiley & Sons, Ltd.

Causal Inference for fMRI Time Series Data with Systematic Errors of Measurement in a Balanced On/Off Study of Social Evaluative Threat.

PubMed

Sobel, Michael E; Lindquist, Martin A

2014-07-01

Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.

Systematic reviews of randomised clinical trials examining the effects of psychotherapeutic interventions versus "no intervention" for acute major depressive disorder and a randomised trial examining the effects of "third wave" cognitive therapy versus mentalization-based treatment for acute major depressive disorder.

PubMed

Jakobsen, Janus Christian

2014-10-01

Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy and psychodynamic therapy may be effective treatment options for major depressive disorder, but the effects have only had limited assessment in systematic reviews. The two modern forms of psychotherapy, "third wave" cognitive therapy and mentalization-based treatment, have both gained some ground as treatments of psychiatric disorders. No randomised trial has compared the effects of these two interventions for major depressive disorder. We performed two systematic reviews with meta-analyses and trial sequential analyses using The Cochrane Collaboration methodology examining the effects of cognitive therapy and psycho-dynamic therapy for major depressive disorder. We developed a thorough treatment protocol for a randomised trial with low risks of bias (systematic error) and low risks of random errors ("play of chance") examining the effects of third wave' cognitive therapy versus mentalization-based treatment for major depressive disorder. We conducted a randomised trial according to good clinical practice examining the effects of "third wave" cognitive therapy versus mentalisation-based treatment for major depressive disorder. The first systematic review included five randomised trials examining the effects of psychodynamic therapy versus "no intervention' for major depressive disorder. Altogether the five trials randomised 365 participants who in each trial received similar antidepressants as co-interventions. All trials had high risk of bias. Four trials assessed "interpersonal psychotherapy" and one trial "short psychodynamic supportive psychotherapy". Both of these interventions are different forms of psychodynamic therapy. Meta-analysis showed that psychodynamic therapy significantly reduced depressive symptoms on the Hamilton Depression Rating Scale (HDRS) compared with "no intervention" (mean difference -3.01 (95% confidence interval -3.98 to -2.03; p = 0.00001), no significant heterogeneity between trials). Trial sequential analysis confirmed this result. The second systematic review included 12 randomised trials examining the effects of cognitive therapy versus "no intervention" for major depressive disorder. Altogether a total of 669 participants were randomised. All trials had high risk of bias. Meta-analysis showed that cognitive therapy significantly reduced depressive symptoms on the HDRS compared with "no intervention" (four trials; mean difference -3.05 (95% confidence interval, -5.23 to -0.87; p = 0.006)). Trial sequential analysis could not confirm this result. The trial protocol showed that it seemed feasible to conduct a randomised trial with low risks of bias and low risks of random errors examining the effects of "third wave" cognitive therapy versus mentalization-based therapy in a setting in the Danish healthcare system. It turned out to be much more difficult to recruit participants in the randomised trial than expected. We only included about half of the planned participants. The results from the randomised trial showed that participants randomised to "third wave" therapy compared with participants randomised to mentalization-based treatment had borderline significantly lower HDRS scores at 18 weeks in an unadjusted analysis (mean difference -4.14 score; 95% CI -8.30 to 0.03; p = 0.051). In the adjusted analysis, the difference was significant (p = 0.039). Five (22.7%) of the participants randomised to "third wave" cognitive therapy had remission at 18 weeks versus none of the participants randomised to mentalization-based treatment (p = 0.049). Sequential analysis showed that these findings could be due to random errors. No significant differences between the two groups was found regarding Beck's Depression Inventory (BDI II), Symptom Checklist 90 Revised (SCL 90-R), and The World Health Organization-Five Well-being Index 1999 (WHO 5). We concluded that cognitive therapy and psychodynamic therapy might be effective interventions for depression measured on HDRS and BDI, but the review results might be erroneous due to risks of bias and random errors. Furthermore, the effects seem relatively small. The trial protocol showed that it was possible to develop a protocol for a randomised trial examining the effects of "third wave" cognitive therapy versus mentalization-based treatment with low risks of bias and low risks of random errors. Our trial results showed that "third wave" cognitive therapy might be a more effective intervention for depressive symptoms measured on the HDRS compared with mentalization-based treatment. The two interventions did not seem to differ significantly regarding BDI II, SCL 90-R, and WHO 5. More randomised trials with low risks of bias and low risks of random errors are needed to assess the effects of cognitive therapy, psychodynamic therapy, "third wave" cognitive therapy, and mentalization-based treatment.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

NASA Astrophysics Data System (ADS)

Herschtal, A.; te Marvelde, L.; Mengersen, K.; Hosseinifard, Z.; Foroudi, F.; Devereux, T.; Pham, D.; Ball, D.; Greer, P. B.; Pichler, P.; Eade, T.; Kneebone, A.; Bell, L.; Caine, H.; Hindson, B.; Kron, T.

2015-02-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

The impact of 3D volume of interest definition on accuracy and precision of activity estimation in quantitative SPECT and planar processing methods

NASA Astrophysics Data System (ADS)

He, Bin; Frey, Eric C.

2010-06-01

Accurate and precise estimation of organ activities is essential for treatment planning in targeted radionuclide therapy. We have previously evaluated the impact of processing methodology, statistical noise and variability in activity distribution and anatomy on the accuracy and precision of organ activity estimates obtained with quantitative SPECT (QSPECT) and planar (QPlanar) processing. Another important factor impacting the accuracy and precision of organ activity estimates is accuracy of and variability in the definition of organ regions of interest (ROI) or volumes of interest (VOI). The goal of this work was thus to systematically study the effects of VOI definition on the reliability of activity estimates. To this end, we performed Monte Carlo simulation studies using randomly perturbed and shifted VOIs to assess the impact on organ activity estimates. The 3D NCAT phantom was used with activities that modeled clinically observed 111In ibritumomab tiuxetan distributions. In order to study the errors resulting from misdefinitions due to manual segmentation errors, VOIs of the liver and left kidney were first manually defined. Each control point was then randomly perturbed to one of the nearest or next-nearest voxels in three ways: with no, inward or outward directional bias, resulting in random perturbation, erosion or dilation, respectively, of the VOIs. In order to study the errors resulting from the misregistration of VOIs, as would happen, e.g. in the case where the VOIs were defined using a misregistered anatomical image, the reconstructed SPECT images or projections were shifted by amounts ranging from -1 to 1 voxels in increments of with 0.1 voxels in both the transaxial and axial directions. The activity estimates from the shifted reconstructions or projections were compared to those from the originals, and average errors were computed for the QSPECT and QPlanar methods, respectively. For misregistration, errors in organ activity estimations were linear in the shift for both the QSPECT and QPlanar methods. QPlanar was less sensitive to object definition perturbations than QSPECT, especially for dilation and erosion cases. Up to 1 voxel misregistration or misdefinition resulted in up to 8% error in organ activity estimates, with the largest errors for small or low uptake organs. Both types of VOI definition errors produced larger errors in activity estimates for a small and low uptake organs (i.e. -7.5% to 5.3% for the left kidney) than for a large and high uptake organ (i.e. -2.9% to 2.1% for the liver). We observed that misregistration generally had larger effects than misdefinition, with errors ranging from -7.2% to 8.4%. The different imaging methods evaluated responded differently to the errors from misregistration and misdefinition. We found that QSPECT was more sensitive to misdefinition errors, but less sensitive to misregistration errors, as compared to the QPlanar method. Thus, sensitivity to VOI definition errors should be an important criterion in evaluating quantitative imaging methods.

An empirical assessment of taxic paleobiology.

PubMed

Adrain, J M; Westrop, S R

2000-07-07

The analysis of major changes in faunal diversity through time is a central theme of analytical paleobiology. The most important sources of data are literature-based compilations of stratigraphic ranges of fossil taxa. The levels of error in these compilations and the possible effects of such error have often been discussed but never directly assessed. We compared our comprehensive database of trilobites to the equivalent portion of J. J. Sepkoski Jr.'s widely used global genus database. More than 70% of entries in the global database are inaccurate; however, as predicted, the error is randomly distributed and does not introduce bias.

Procedures for dealing with certain types of noise and systematic errors common to many Hadamard transform optical systems

NASA Technical Reports Server (NTRS)

Harwit, M.

1977-01-01

Sources of noise and error correcting procedures characteristic of Hadamard transform optical systems were investigated. Reduction of spectral noise due to noise spikes in the data, the effect of random errors, the relative performance of Fourier and Hadamard transform spectrometers operated under identical detector-noise-limited conditions, and systematic means for dealing with mask defects are among the topics discussed. The distortion in Hadamard transform optical instruments caused by moving Masks, incorrect mask alignment, missing measurements, and diffraction is analyzed and techniques for reducing or eliminating this distortion are described.

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain.

PubMed

Reyes, Jeanette M; Xu, Yadong; Vizuete, William; Serre, Marc L

2017-01-01

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.

Implications of clinical trial design on sample size requirements.

PubMed

Leon, Andrew C

2008-07-01

The primary goal in designing a randomized controlled clinical trial (RCT) is to minimize bias in the estimate of treatment effect. Randomized group assignment, double-blinded assessments, and control or comparison groups reduce the risk of bias. The design must also provide sufficient statistical power to detect a clinically meaningful treatment effect and maintain a nominal level of type I error. An attempt to integrate neurocognitive science into an RCT poses additional challenges. Two particularly relevant aspects of such a design often receive insufficient attention in an RCT. Multiple outcomes inflate type I error, and an unreliable assessment process introduces bias and reduces statistical power. Here we describe how both unreliability and multiple outcomes can increase the study costs and duration and reduce the feasibility of the study. The objective of this article is to consider strategies that overcome the problems of unreliability and multiplicity.

Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation

NASA Astrophysics Data System (ADS)

Li, C.

2012-07-01

POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

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

Winter, Jeff D.; Wong, Raimond; Swaminath, Anand

Purpose: To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials: We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately beforemore » beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results: The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude (r=0.53-0.66, P<.001), whereas only weak correlations existed for correlation errors. Conclusions: Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.« less

A proposed method to investigate reliability throughout a questionnaire

PubMed Central

2011-01-01

Background Questionnaires are used extensively in medical and health care research and depend on validity and reliability. However, participants may differ in interest and awareness throughout long questionnaires, which can affect reliability of their answers. A method is proposed for "screening" of systematic change in random error, which could assess changed reliability of answers. Methods A simulation study was conducted to explore whether systematic change in reliability, expressed as changed random error, could be assessed using unsupervised classification of subjects by cluster analysis (CA) and estimation of intraclass correlation coefficient (ICC). The method was also applied on a clinical dataset from 753 cardiac patients using the Jalowiec Coping Scale. Results The simulation study showed a relationship between the systematic change in random error throughout a questionnaire and the slope between the estimated ICC for subjects classified by CA and successive items in a questionnaire. This slope was proposed as an awareness measure - to assessing if respondents provide only a random answer or one based on a substantial cognitive effort. Scales from different factor structures of Jalowiec Coping Scale had different effect on this awareness measure. Conclusions Even though assumptions in the simulation study might be limited compared to real datasets, the approach is promising for assessing systematic change in reliability throughout long questionnaires. Results from a clinical dataset indicated that the awareness measure differed between scales. PMID:21974842

The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials.

PubMed

Hedden, Sarra L; Woolson, Robert F; Carter, Rickey E; Palesch, Yuko; Upadhyaya, Himanshu P; Malcolm, Robert J

2009-07-01

"Loss to follow-up" can be substantial in substance abuse clinical trials. When extensive losses to follow-up occur, one must cautiously analyze and interpret the findings of a research study. Aims of this project were to introduce the types of missing data mechanisms and describe several methods for analyzing data with loss to follow-up. Furthermore, a simulation study compared Type I error and power of several methods when missing data amount and mechanism varies. Methods compared were the following: Last observation carried forward (LOCF), multiple imputation (MI), modified stratified summary statistics (SSS), and mixed effects models. Results demonstrated nominal Type I error for all methods; power was high for all methods except LOCF. Mixed effect model, modified SSS, and MI are generally recommended for use; however, many methods require that the data are missing at random or missing completely at random (i.e., "ignorable"). If the missing data are presumed to be nonignorable, a sensitivity analysis is recommended.

Effects of monetary reward and punishment on information checking behaviour.

PubMed

Li, Simon Y W; Cox, Anna L; Or, Calvin; Blandford, Ann

2016-03-01

Two experiments were conducted to examine whether checking one's own work can be motivated by monetary reward and punishment. Participants were randomly assigned to one of three conditions: a flat-rate payment for completing the task (Control); payment increased for error-free performance (Reward); payment decreased for error performance (Punishment). Experiment 1 (N = 90) was conducted with liberal arts students, using a general data-entry task. Experiment 2 (N = 90) replicated Experiment 1 with clinical students and a safety-critical 'cover story' for the task. In both studies, Reward and Punishment resulted in significantly fewer errors, more frequent and longer checking, than Control. No such differences were obtained between the Reward and Punishment conditions. It is concluded that error consequences in terms of monetary reward and punishment can result in more accurate task performance and more rigorous checking behaviour than errors without consequences. However, whether punishment is more effective than reward, or vice versa, remains inconclusive. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

Removal of batch effects using distribution-matching residual networks.

PubMed

Shaham, Uri; Stanton, Kelly P; Zhao, Jun; Li, Huamin; Raddassi, Khadir; Montgomery, Ruth; Kluger, Yuval

2017-08-15

Sources of variability in experimentally derived data include measurement error in addition to the physical phenomena of interest. This measurement error is a combination of systematic components, originating from the measuring instrument and random measurement errors. Several novel biological technologies, such as mass cytometry and single-cell RNA-seq (scRNA-seq), are plagued with systematic errors that may severely affect statistical analysis if the data are not properly calibrated. We propose a novel deep learning approach for removing systematic batch effects. Our method is based on a residual neural network, trained to minimize the Maximum Mean Discrepancy between the multivariate distributions of two replicates, measured in different batches. We apply our method to mass cytometry and scRNA-seq datasets, and demonstrate that it effectively attenuates batch effects. our codes and data are publicly available at https://github.com/ushaham/BatchEffectRemoval.git. yuval.kluger@yale.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

An analytic technique for statistically modeling random atomic clock errors in estimation

NASA Technical Reports Server (NTRS)

Fell, P. J.

1981-01-01

Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

Full Bayes Poisson gamma, Poisson lognormal, and zero inflated random effects models: Comparing the precision of crash frequency estimates.

PubMed

Aguero-Valverde, Jonathan

2013-01-01

In recent years, complex statistical modeling approaches have being proposed to handle the unobserved heterogeneity and the excess of zeros frequently found in crash data, including random effects and zero inflated models. This research compares random effects, zero inflated, and zero inflated random effects models using a full Bayes hierarchical approach. The models are compared not just in terms of goodness-of-fit measures but also in terms of precision of posterior crash frequency estimates since the precision of these estimates is vital for ranking of sites for engineering improvement. Fixed-over-time random effects models are also compared to independent-over-time random effects models. For the crash dataset being analyzed, it was found that once the random effects are included in the zero inflated models, the probability of being in the zero state is drastically reduced, and the zero inflated models degenerate to their non zero inflated counterparts. Also by fixing the random effects over time the fit of the models and the precision of the crash frequency estimates are significantly increased. It was found that the rankings of the fixed-over-time random effects models are very consistent among them. In addition, the results show that by fixing the random effects over time, the standard errors of the crash frequency estimates are significantly reduced for the majority of the segments on the top of the ranking. Copyright © 2012 Elsevier Ltd. All rights reserved.

Randomized controlled trial on the effects of training in the use of closed-circuit television on reading performance.

PubMed

Burggraaff, Marloes C; van Nispen, Ruth M A; Hoeben, Frank P; Knol, Dirk L; van Rens, Ger H M B

2012-04-24

To investigate the effectiveness of training in the use of closed-circuit television (CCTV) on reading performance in visually impaired patients. In a multicenter masked randomized controlled trial, 122 patients were randomized either to a treatment group that received usual delivery instructions from the CCTV supplier combined with concise outpatient standardized training, or to a control group that received delivery instructions only. The main outcome measure was reading performance, which was obtained by measuring reading acuity, reading speed, reading errors, column-tracking time, and technical reading, approximately two weeks after patients had received their CCTV and 3 months later. Videotapes of all measurements were rated by two investigators. Training effects were analyzed with linear mixed modeling. There were no statistically significant differences in results between the treatment and control group. However, introducing a CCTV increased reading acuity (mean difference [MD] 0.93 logRAD; P < 0.01) and maximum reading speed (MD 15 wpm; P < 0.01), and decreased the number of errors (MD 0.33; P = 0.04), compared to reading without CCTV. Average reading speed (P = 0.05), number of errors (P = 0.04), and column-tracking time (P = 0.01) improved over time. Prescribing a CCTV and the delivery instructions by the supplier seemed sufficient to improve reading performance. Additional training in the use of this device did not result in further improvement. Based on these results, outpatient low-vision rehabilitation centers may consider reallocating part of the training resources into other evidence-based rehabilitation programs. (trialregister.nl number, NTR1031.).

Beyond alpha: an empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs.

PubMed

Schmidt, Frank L; Le, Huy; Ilies, Remus

2003-06-01

On the basis of an empirical study of measures of constructs from the cognitive domain, the personality domain, and the domain of affective traits, the authors of this study examine the implications of transient measurement error for the measurement of frequently studied individual differences variables. The authors clarify relevant reliability concepts as they relate to transient error and present a procedure for estimating the coefficient of equivalence and stability (L. J. Cronbach, 1947), the only classical reliability coefficient that assesses all 3 major sources of measurement error (random response, transient, and specific factor errors). The authors conclude that transient error exists in all 3 trait domains and is especially large in the domain of affective traits. Their findings indicate that the nearly universal use of the coefficient of equivalence (Cronbach's alpha; L. J. Cronbach, 1951), which fails to assess transient error, leads to overestimates of reliability and undercorrections for biases due to measurement error.

Statistical models for estimating daily streamflow in Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Salehi, Habib

1992-01-01

Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.

Using EHR Data to Detect Prescribing Errors in Rapidly Discontinued Medication Orders.

PubMed

Burlison, Jonathan D; McDaniel, Robert B; Baker, Donald K; Hasan, Murad; Robertson, Jennifer J; Howard, Scott C; Hoffman, James M

2018-01-01

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use. Our objectives were to assess a method to retrospectively detect prescribing errors, to characterize the identified errors, and to identify potential improvement opportunities. Electronically submitted medication orders from 28 randomly selected days that were discontinued within 120 minutes of submission were reviewed and categorized as most likely errors, nonerrors, or not enough information to determine status. Identified errors were evaluated by amount of time elapsed from original submission to discontinuation, error type, staff position, and potential clinical significance. Pearson's chi-square test was used to compare rates of errors across prescriber types. In all, 147 errors were identified in 305 medication orders. The method was most effective for orders that were discontinued within 90 minutes. Duplicate orders were most common; physicians in training had the highest error rate ( p  < 0.001), and 24 errors were potentially clinically significant. None of the errors were voluntarily reported. It is possible to identify prescribing errors in rapidly discontinued medication orders by using retrospective methods that do not require interrupting prescribers to discuss order details. Future research could validate our methods in different clinical settings. Regular use of this measure could help determine the causes of prescribing errors, track performance, and identify and evaluate interventions to improve prescribing systems and processes. Schattauer GmbH Stuttgart.

The immediate effects of therapeutic keyboard music playing for finger training in adults undergoing hand rehabilitation.

PubMed

Zhang, Xiaoying; Liu, Songhuai; Yang, Degang; Du, Liangjie; Wang, Ziyuan

2016-08-01

[Purpose] The purpose of this study was to examine the immediate effects of therapeutic keyboard music playing on the finger function of subjects' hands through measurements of the joint position error test, surface electromyography, probe reaction time, and writing time. [Subjects and Methods] Ten subjects were divided randomly into experimental and control groups. The experimental group used therapeutic keyboard music playing and the control group used grip training. All subjects were assessed and evaluated by the joint position error test, surface electromyography, probe reaction time, and writing time. [Results] After accomplishing therapeutic keyboard music playing and grip training, surface electromyography of the two groups showed no significant change, but joint position error test, probe reaction time, and writing time obviously improved. [Conclusion] These results suggest that therapeutic keyboard music playing is an effective and novel treatment for improving joint position error test scores, probe reaction time, and writing time, and it should be promoted widely in clinics.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Error threshold for color codes and random three-body Ising models.

PubMed

Katzgraber, Helmut G; Bombin, H; Martin-Delgado, M A

2009-08-28

We study the error threshold of color codes, a class of topological quantum codes that allow a direct implementation of quantum Clifford gates suitable for entanglement distillation, teleportation, and fault-tolerant quantum computation. We map the error-correction process onto a statistical mechanical random three-body Ising model and study its phase diagram via Monte Carlo simulations. The obtained error threshold of p(c) = 0.109(2) is very close to that of Kitaev's toric code, showing that enhanced computational capabilities do not necessarily imply lower resistance to noise.

Image guidance in prostate cancer - can offline corrections be an effective substitute for daily online imaging?

PubMed

Prasad, Devleena; Das, Pinaki; Saha, Niladri S; Chatterjee, Sanjoy; Achari, Rimpa; Mallick, Indranil

2014-01-01

This aim of this study was to determine if a less resource-intensive and established offline correction protocol - the No Action Level (NAL) protocol was as effective as daily online corrections of setup deviations in curative high-dose radiotherapy of prostate cancer. A total of 683 daily megavoltage CT (MVCT) or kilovoltage CT (kvCBCT) images of 30 patients with localized prostate cancer treated with intensity modulated radiotherapy were evaluated. Daily image-guidance was performed and setup errors in three translational axes recorded. The NAL protocol was simulated by using the mean shift calculated from the first five fractions and implemented on all subsequent treatments. Using the imaging data from the remaining fractions, the daily residual error (RE) was determined. The proportion of fractions where the RE was greater than 3,5 and 7 mm was calculated, and also the actual PTV margin that would be required if the offline protocol was followed. Using the NAL protocol reduced the systematic but not the random errors. Corrections made using the NAL protocol resulted in small and acceptable RE in the mediolateral (ML) and superoinferior (SI) directions with 46/533 (8.1%) and 48/533 (5%) residual shifts above 5 mm. However; residual errors greater than 5mm in the anteroposterior (AP) direction remained in 181/533 (34%) of fractions. The PTV margins calculated based on residual errors were 5mm, 5mm and 13 mm in the ML, SI and AP directions respectively. Offline correction using the NAL protocol resulted in unacceptably high residual errors in the AP direction, due to random uncertainties of rectal and bladder filling. Daily online imaging and corrections remain the standard image guidance policy for highly conformal radiotherapy of prostate cancer.

Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

PubMed

Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

2017-01-30

In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Random Measurement Error as a Source of Discrepancies between the Reports of Wives and Husbands Concerning Marital Power and Task Allocation.

ERIC Educational Resources Information Center

Quarm, Daisy

1981-01-01

Findings for couples (N=119) show wife's work, money, and spare time low between-spouse correlations are due in part to random measurement error. Suggests that increasing reliability of measures by creating multi-item indices can also increase correlations. Car purchase, vacation, and child discipline were not accounted for by random measurement…

Filtering Drifter Trajectories Sampled at Submesoscale Resolution

DTIC Science & Technology

2015-07-10

interval 5 min and a positioning error 1.5 m, the acceleration error is 4 10 m/s , a value comparable with the typical Coriolis acceleration of a water...10 ms , corresponding to the Coriolis acceleration experi- enced by a water parcel traveling at a speed of 2.2 m/s. This value corresponds to the...computed by integrating the NCOM velocity field contaminated by a random walk process whose effective dispersion coefficient (150 m /s) was specified as the

Alternate methods for FAAT S-curve generation

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

Kaufman, A.M.

The FAAT (Foreign Asset Assessment Team) assessment methodology attempts to derive a probability of effect as a function of incident field strength. The probability of effect is the likelihood that the stress put on a system exceeds its strength. In the FAAT methodology, both the stress and strength are random variables whose statistical properties are estimated by experts. Each random variable has two components of uncertainty: systematic and random. The systematic uncertainty drives the confidence bounds in the FAAT assessment. Its variance can be reduced by improved information. The variance of the random uncertainty is not reducible. The FAAT methodologymore » uses an assessment code called ARES to generate probability of effect curves (S-curves) at various confidence levels. ARES assumes log normal distributions for all random variables. The S-curves themselves are log normal cumulants associated with the random portion of the uncertainty. The placement of the S-curves depends on confidence bounds. The systematic uncertainty in both stress and strength is usually described by a mode and an upper and lower variance. Such a description is not consistent with the log normal assumption of ARES and an unsatisfactory work around solution is used to obtain the required placement of the S-curves at each confidence level. We have looked into this situation and have found that significant errors are introduced by this work around. These errors are at least several dB-W/cm{sup 2} at all confidence levels, but they are especially bad in the estimate of the median. In this paper, we suggest two alternate solutions for the placement of S-curves. To compare these calculational methods, we have tabulated the common combinations of upper and lower variances and generated the relevant S-curves offsets from the mode difference of stress and strength.« less

A comparison of methods for estimating the random effects distribution of a linear mixed model.

PubMed

Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert

2010-12-01

This article reviews various recently suggested approaches to estimate the random effects distribution in a linear mixed model, i.e. (1) the smoothing by roughening approach of Shen and Louis,(1) (2) the semi-non-parametric approach of Zhang and Davidian,(2) (3) the heterogeneity model of Verbeke and Lesaffre( 3) and (4) a flexible approach of Ghidey et al. (4) These four approaches are compared via an extensive simulation study. We conclude that for the considered cases, the approach of Ghidey et al. (4) often shows to have the smallest integrated mean squared error for estimating the random effects distribution. An analysis of a longitudinal dental data set illustrates the performance of the methods in a practical example.

Dynamical decoupling of local transverse random telegraph noise in a two-qubit gate

NASA Astrophysics Data System (ADS)

D'Arrigo, A.; Falci, G.; Paladino, E.

2015-10-01

Achieving high-fidelity universal two-qubit gates is a central requisite of any implementation of quantum information processing. The presence of spurious fluctuators of various physical origin represents a limiting factor for superconducting nanodevices. Operating qubits at optimal points, where the qubit-fluctuator interaction is transverse with respect to the single qubit Hamiltonian, considerably improved single qubit gates. Further enhancement has been achieved by dynamical decoupling (DD). In this article we investigate DD of transverse random telegraph noise acting locally on each of the qubits forming an entangling gate. Our analysis is based on the exact numerical solution of the stochastic Schrödinger equation. We evaluate the gate error under local periodic, Carr-Purcell and Uhrig DD sequences. We find that a threshold value of the number, n, of pulses exists above which the gate error decreases with a sequence-specific power-law dependence on n. Below threshold, DD may even increase the error with respect to the unconditioned evolution, a behaviour reminiscent of the anti-Zeno effect.

Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

NASA Technical Reports Server (NTRS)

Sedlak, J.; Hashmall, J.

1997-01-01

Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

Advanced Water Vapor Lidar Detection System

NASA Technical Reports Server (NTRS)

Elsayed-Ali, Hani

1998-01-01

In the present water vapor lidar system, the detected signal is sent over long cables to a waveform digitizer in a CAMAC crate. This has the disadvantage of transmitting analog signals for a relatively long distance, which is subjected to pickup noise, leading to a decrease in the signal to noise ratio. Generally, errors in the measurement of water vapor with the DIAL method arise from both random and systematic sources. Systematic errors in DIAL measurements are caused by both atmospheric and instrumentation effects. The selection of the on-line alexandrite laser with a narrow linewidth, suitable intensity and high spectral purity, and its operation at the center of the water vapor lines, ensures minimum influence in the DIAL measurement that are caused by the laser spectral distribution and avoid system overloads. Random errors are caused by noise in the detected signal. Variability of the photon statistics in the lidar return signal, noise resulting from detector dark current, and noise in the background signal are the main sources of random error. This type of error can be minimized by maximizing the signal to noise ratio. The increase in the signal to noise ratio can be achieved by several ways. One way is to increase the laser pulse energy, by increasing its amplitude or the pulse repetition rate. Another way, is to use a detector system with higher quantum efficiency and lower noise, on the other hand, the selection of a narrow band optical filter that rejects most of the day background light and retains high optical efficiency is an important issue. Following acquisition of the lidar data, we minimize random errors in the DIAL measurement by averaging the data, but this will result in the reduction of the vertical and horizontal resolutions. Thus, a trade off is necessary to achieve a balance between the spatial resolution and the measurement precision. Therefore, the main goal of this research effort is to increase the signal to noise ratio by a factor of 10 over the current system, using a newly evaluated, very low noise avalanche photo diode detector and constructing a 10 MHz waveform digitizer which will replace the current CAMAC system.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Research on correction algorithm of laser positioning system based on four quadrant detector

NASA Astrophysics Data System (ADS)

Gao, Qingsong; Meng, Xiangyong; Qian, Weixian; Cai, Guixia

2018-02-01

This paper first introduces the basic principle of the four quadrant detector, and a set of laser positioning experiment system is built based on the four quadrant detector. Four quadrant laser positioning system in the actual application, not only exist interference of background light and detector dark current noise, and the influence of random noise, system stability, spot equivalent error can't be ignored, so it is very important to system calibration and correction. This paper analyzes the various factors of system positioning error, and then propose an algorithm for correcting the system error, the results of simulation and experiment show that the modified algorithm can improve the effect of system error on positioning and improve the positioning accuracy.

One-step random mutagenesis by error-prone rolling circle amplification

PubMed Central

Fujii, Ryota; Kitaoka, Motomitsu; Hayashi, Kiyoshi

2004-01-01

In vitro random mutagenesis is a powerful tool for altering properties of enzymes. We describe here a novel random mutagenesis method using rolling circle amplification, named error-prone RCA. This method consists of only one DNA amplification step followed by transformation of the host strain, without treatment with any restriction enzymes or DNA ligases, and results in a randomly mutated plasmid library with 3–4 mutations per kilobase. Specific primers or special equipment, such as a thermal-cycler, are not required. This method permits rapid preparation of randomly mutated plasmid libraries, enabling random mutagenesis to become a more commonly used technique. PMID:15507684

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

Applying Generalizability Theory To Evaluate Treatment Effect in Single-Subject Research.

ERIC Educational Resources Information Center

Lefebvre, Daniel J.; Suen, Hoi K.

An empirical investigation of methodological issues associated with evaluating treatment effect in single-subject research (SSR) designs is presented. This investigation: (1) conducted a generalizability (G) study to identify the sources of systematic and random measurement error (SRME); (2) used an analytic approach based on G theory to integrate…

Noise-Enhanced Eversion Force Sense in Ankles With or Without Functional Instability.

PubMed

Ross, Scott E; Linens, Shelley W; Wright, Cynthia J; Arnold, Brent L

2015-08-01

Force sense impairments are associated with functional ankle instability. Stochastic resonance stimulation (SRS) may have implications for correcting these force sense deficits. To determine if SRS improved force sense. Case-control study. Research laboratory. Twelve people with functional ankle instability (age = 23 ± 3 years, height = 174 ± 8 cm, mass = 69 ± 10 kg) and 12 people with stable ankles (age = 22 ± 2 years, height = 170 ± 7 cm, mass = 64 ± 10 kg). The eversion force sense protocol required participants to reproduce a targeted muscle tension (10% of maximum voluntary isometric contraction). This protocol was assessed under SRSon and SRSoff (control) conditions. During SRSon, random subsensory mechanical noise was applied to the lower leg at a customized optimal intensity for each participant. Constant error, absolute error, and variable error measures quantified accuracy, overall performance, and consistency of force reproduction, respectively. With SRS, we observed main effects for force sense absolute error (SRSoff = 1.01 ± 0.67 N, SRSon = 0.69 ± 0.42 N) and variable error (SRSoff = 1.11 ± 0.64 N, SRSon = 0.78 ± 0.56 N) (P < .05). No other main effects or treatment-by-group interactions were found (P > .05). Although SRS reduced the overall magnitude (absolute error) and variability (variable error) of force sense errors, it had no effect on the directionality (constant error). Clinically, SRS may enhance muscle tension ability, which could have treatment implications for ankle stability.

Analysis of the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery☆

PubMed Central

Arba-Mosquera, Samuel; Aslanides, Ioannis M.

2012-01-01

Purpose To analyze the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery. Methods A comprehensive model, which directly considers eye movements, including saccades, vestibular, optokinetic, vergence, and miniature, as well as, eye-tracker acquisition rate, eye-tracker latency time, scanner positioning time, laser firing rate, and laser trigger delay have been developed. Results Eye-tracker acquisition rates below 100 Hz correspond to pulse positioning errors above 1.5 mm. Eye-tracker latency times to about 15 ms correspond to pulse positioning errors of up to 3.5 mm. Scanner positioning times to about 9 ms correspond to pulse positioning errors of up to 2 mm. Laser firing rates faster than eye-tracker acquisition rates basically duplicate pulse-positioning errors. Laser trigger delays to about 300 μs have minor to no impact on pulse-positioning errors. Conclusions The proposed model can be used for comparison of laser systems used for ablation processes. Due to the pseudo-random nature of eye movements, positioning errors of single pulses are much larger than observed decentrations in the clinical settings. There is no single parameter that ‘alone’ minimizes the positioning error. It is the optimal combination of the several parameters that minimizes the error. The results of this analysis are important to understand the limitations of correcting very irregular ablation patterns.

ATM QoS Experiments Using TCP Applications: Performance of TCP/IP Over ATM in a Variety of Errored Links

NASA Technical Reports Server (NTRS)

Frantz, Brian D.; Ivancic, William D.

2001-01-01

Asynchronous Transfer Mode (ATM) Quality of Service (QoS) experiments using the Transmission Control Protocol/Internet Protocol (TCP/IP) were performed for various link delays. The link delay was set to emulate a Wide Area Network (WAN) and a Satellite Link. The purpose of these experiments was to evaluate the ATM QoS requirements for applications that utilize advance TCP/IP protocols implemented with large windows and Selective ACKnowledgements (SACK). The effects of cell error, cell loss, and random bit errors on throughput were reported. The detailed test plan and test results are presented herein.

Error reduction and parameter optimization of the TAPIR method for fast T1 mapping.

PubMed

Zaitsev, M; Steinhoff, S; Shah, N J

2003-06-01

A methodology is presented for the reduction of both systematic and random errors in T(1) determination using TAPIR, a Look-Locker-based fast T(1) mapping technique. The relations between various sequence parameters were carefully investigated in order to develop recipes for choosing optimal sequence parameters. Theoretical predictions for the optimal flip angle were verified experimentally. Inversion pulse imperfections were identified as the main source of systematic errors in T(1) determination with TAPIR. An effective remedy is demonstrated which includes extension of the measurement protocol to include a special sequence for mapping the inversion efficiency itself. Copyright 2003 Wiley-Liss, Inc.

QUANTIFYING UNCERTAINTY DUE TO RANDOM ERRORS FOR MOMENT ANALYSES OF BREAKTHROUGH CURVES

EPA Science Inventory

The uncertainty in moments calculated from breakthrough curves (BTCs) is investigated as a function of random measurement errors in the data used to define the BTCs. The method presented assumes moments are calculated by numerical integration using the trapezoidal rule, and is t...

Theoretical investigation on the mass loss impact on asteroseismic grid-based estimates of mass, radius, and age for RGB stars

NASA Astrophysics Data System (ADS)

Valle, G.; Dell'Omodarme, M.; Prada Moroni, P. G.; Degl'Innocenti, S.

2018-01-01

Aims: We aim to perform a theoretical evaluation of the impact of the mass loss indetermination on asteroseismic grid based estimates of masses, radii, and ages of stars in the red giant branch (RGB) phase. Methods: We adopted the SCEPtER pipeline on a grid spanning the mass range [0.8; 1.8] M⊙. As observational constraints, we adopted the star effective temperatures, the metallicity [Fe/H], the average large frequency spacing Δν, and the frequency of maximum oscillation power νmax. The mass loss was modelled following a Reimers parametrization with the two different efficiencies η = 0.4 and η = 0.8. Results: In the RGB phase, the average random relative error (owing only to observational uncertainty) on mass and age estimates is about 8% and 30% respectively. The bias in mass and age estimates caused by the adoption of a wrong mass loss parameter in the recovery is minor for the vast majority of the RGB evolution. The biases get larger only after the RGB bump. In the last 2.5% of the RGB lifetime the error on the mass determination reaches 6.5% becoming larger than the random error component in this evolutionary phase. The error on the age estimate amounts to 9%, that is, equal to the random error uncertainty. These results are independent of the stellar metallicity [Fe/H] in the explored range. Conclusions: Asteroseismic-based estimates of stellar mass, radius, and age in the RGB phase can be considered mass loss independent within the range (η ∈ [0.0,0.8]) as long as the target is in an evolutionary phase preceding the RGB bump.

Effects of calcium on the incidence of recurrent colorectal adenomas

PubMed Central

Veettil, Sajesh K.; Ching, Siew Mooi; Lim, Kean Ghee; Saokaew, Surasak; Phisalprapa, Pochamana; Chaiyakunapruk, Nathorn

2017-01-01

Abstract Background: Protective effects of calcium supplementation against colorectal adenomas have been documented in systematic reviews; however, the results have not been conclusive. Our objective was to update and systematically evaluate the evidence for calcium supplementation taking into consideration the risks of systematic and random error and to GRADE the evidence. Methods: The study comprised a systematic review with meta-analysis and trial sequential analysis (TSA) of randomized controlled trials (RCTs). We searched for RCTs published up until September 2016. Retrieved trials were evaluated using risk of bias. Primary outcome measures were the incidences of any recurrent adenomas and of advanced adenomas. Meta-analytic estimates were calculated with the random-effects model and random errors were evaluated with trial sequential analyses (TSAs). Results: Five randomized trials (2234 patients with a history of adenomas) were included. Two of the 5 trials showed either unclear or high risks of bias in most criteria. Meta-analysis of good quality RCTs suggest a moderate protective effect of calcium supplementation on recurrence of adenomas (relative risk [RR], 0.88 [95% CI 0.79–0.99]); however, its effects on advanced adenomas did not show statistical significance (RR, 1.02 [95% CI 0.67–1.55]). Subgroup analyses demonstrated a greater protective effect on recurrence of adenomas with elemental calcium dose ≥1600 mg/day (RR, 0.74 [95% CI 0.56–0.97]) compared to ≤1200 mg/day (RR, 0.84 [95% CI 0.73–0.97]). No major serious adverse events were associated with the use of calcium, but there was an increase in the incidence of hypercalcemia (P = .0095). TSA indicated a lack of firm evidence for a beneficial effect. Concerns with directness and imprecision rated down the quality of the evidence to “low.” Conclusion: The available good quality RCTs suggests a possible beneficial effect of calcium supplementation on the recurrence of adenomas; however, TSA indicated that the accumulated evidence is still inconclusive. Using GRADE-methodology, we conclude that the quality of evidence is low. Large well-designed randomized trials with low risk of bias are needed. PMID:28796047

MacWilliams Identity for M-Spotty Weight Enumerator

NASA Astrophysics Data System (ADS)

Suzuki, Kazuyoshi; Fujiwara, Eiji

M-spotty byte error control codes are very effective for correcting/detecting errors in semiconductor memory systems that employ recent high-density RAM chips with wide I/O data (e.g., 8, 16, or 32bits). In this case, the width of the I/O data is one byte. A spotty byte error is defined as random t-bit errors within a byte of length b bits, where 1 le t ≤ b. Then, an error is called an m-spotty byte error if at least one spotty byte error is present in a byte. M-spotty byte error control codes are characterized by the m-spotty distance, which includes the Hamming distance as a special case for t =1 or t = b. The MacWilliams identity provides the relationship between the weight distribution of a code and that of its dual code. The present paper presents the MacWilliams identity for the m-spotty weight enumerator of m-spotty byte error control codes. In addition, the present paper clarifies that the indicated identity includes the MacWilliams identity for the Hamming weight enumerator as a special case.

Effects of practice schedule and task specificity on the adaptive process of motor learning.

PubMed

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

PubMed

Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A

2013-01-01

Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001). Taking errors into account, SAINT I would have required 24% more subjects than were randomized. We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.

Efficient Measurement of Quantum Gate Error by Interleaved Randomized Benchmarking

NASA Astrophysics Data System (ADS)

Magesan, Easwar; Gambetta, Jay M.; Johnson, B. R.; Ryan, Colm A.; Chow, Jerry M.; Merkel, Seth T.; da Silva, Marcus P.; Keefe, George A.; Rothwell, Mary B.; Ohki, Thomas A.; Ketchen, Mark B.; Steffen, M.

2012-08-01

We describe a scalable experimental protocol for estimating the average error of individual quantum computational gates. This protocol consists of interleaving random Clifford gates between the gate of interest and provides an estimate as well as theoretical bounds for the average error of the gate under test, so long as the average noise variation over all Clifford gates is small. This technique takes into account both state preparation and measurement errors and is scalable in the number of qubits. We apply this protocol to a superconducting qubit system and find a bounded average error of 0.003 [0,0.016] for the single-qubit gates Xπ/2 and Yπ/2. These bounded values provide better estimates of the average error than those extracted via quantum process tomography.

Efficacy of Visual-Acoustic Biofeedback Intervention for Residual Rhotic Errors: A Single-Subject Randomization Study

ERIC Educational Resources Information Center

Byun, Tara McAllister

2017-01-01

Purpose: This study documented the efficacy of visual-acoustic biofeedback intervention for residual rhotic errors, relative to a comparison condition involving traditional articulatory treatment. All participants received both treatments in a single-subject experimental design featuring alternating treatments with blocked randomization of…

Statistical Analysis Experiment for Freshman Chemistry Lab.

ERIC Educational Resources Information Center

Salzsieder, John C.

1995-01-01

Describes a laboratory experiment dissolving zinc from galvanized nails in which data can be gathered very quickly for statistical analysis. The data have sufficient significant figures and the experiment yields a nice distribution of random errors. Freshman students can gain an appreciation of the relationships between random error, number of…

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

Analysis of the “naming game” with learning errors in communications

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong

2015-07-01

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Analysis of the "naming game" with learning errors in communications.

PubMed

Lou, Yang; Chen, Guanrong

2015-07-16

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Determination of the precision error of the pulmonary artery thermodilution catheter using an in vitro continuous flow test rig.

PubMed

Yang, Xiao-Xing; Critchley, Lester A; Joynt, Gavin M

2011-01-01

Thermodilution cardiac output using a pulmonary artery catheter is the reference method against which all new methods of cardiac output measurement are judged. However, thermodilution lacks precision and has a quoted precision error of ± 20%. There is uncertainty about its true precision and this causes difficulty when validating new cardiac output technology. Our aim in this investigation was to determine the current precision error of thermodilution measurements. A test rig through which water circulated at different constant rates with ports to insert catheters into a flow chamber was assembled. Flow rate was measured by an externally placed transonic flowprobe and meter. The meter was calibrated by timed filling of a cylinder. Arrow and Edwards 7Fr thermodilution catheters, connected to a Siemens SC9000 cardiac output monitor, were tested. Thermodilution readings were made by injecting 5 mL of ice-cold water. Precision error was divided into random and systematic components, which were determined separately. Between-readings (random) variability was determined for each catheter by taking sets of 10 readings at different flow rates. Coefficient of variation (CV) was calculated for each set and averaged. Between-catheter systems (systematic) variability was derived by plotting calibration lines for sets of catheters. Slopes were used to estimate the systematic component. Performances of 3 cardiac output monitors were compared: Siemens SC9000, Siemens Sirecust 1261, and Philips MP50. Five Arrow and 5 Edwards catheters were tested using the Siemens SC9000 monitor. Flow rates between 0.7 and 7.0 L/min were studied. The CV (random error) for Arrow was 5.4% and for Edwards was 4.8%. The random precision error was ± 10.0% (95% confidence limits). CV (systematic error) was 5.8% and 6.0%, respectively. The systematic precision error was ± 11.6%. The total precision error of a single thermodilution reading was ± 15.3% and ± 13.0% for triplicate readings. Precision error increased by 45% when using the Sirecust monitor and 100% when using the Philips monitor. In vitro testing of pulmonary artery catheters enabled us to measure both the random and systematic error components of thermodilution cardiac output measurement, and thus calculate the precision error. Using the Siemens monitor, we established a precision error of ± 15.3% for single and ± 13.0% for triplicate reading, which was similar to the previous estimate of ± 20%. However, this precision error was significantly worsened by using the Sirecust and Philips monitors. Clinicians should recognize that the precision error of thermodilution cardiac output is dependent on the selection of catheter and monitor model.

Effect of magnesium added to local anesthetics for caudal anesthesia on postoperative pain in pediatric surgical patients: A systematic review and meta-analysis with Trial Sequential Analysis

PubMed Central

Mihara, Takahiro; Nakamura, Nobuhito; Ka, Koui; Goto, Takahisa

2018-01-01

Background Magnesium has been investigated as an adjuvant for neuraxial anesthesia, but the effect of caudal magnesium on postoperative pain is inconsistent. The aim of this systematic review and meta-analysis was to evaluate the analgesic effect of caudal magnesium. Methods We searched six databases, including trial registration sites. Randomized clinical trials reporting the effect of caudal magnesium on postoperative pain after general anesthesia were eligible. The risk ratio for use of rescue analgesics after surgery was combined using a random-effects model. We also assessed adverse events. The I2 statistic was used to assess heterogeneity. We assessed risk of bias with Cochrane domains. We controlled type I and II errors due to sparse data and repetitive testing with Trial Sequential Analysis. We assessed the quality of evidence with GRADE. Results Four randomized controlled trials (247 patients) evaluated the need for rescue analgesics. In all four trials, 50 mg of magnesium was administered with caudal ropivacaine. The results suggested that the need for rescue analgesia was reduced significantly by caudal magnesium administration (risk ratio 0.45; 95% confidence interval 0.24–0.86). There was considerable heterogeneity as indicated by an I2 value of 62.5%. The Trial Sequential Analysis-adjusted confidence interval was 0.04–5.55, indicating that further trials are required. The quality of evidence was very low. The rate of adverse events was comparable between treatment groups. Conclusion Caudal magnesium may reduce the need for rescue analgesia after surgery, but further randomized clinical trials with a low risk of bias and a low risk of random errors are necessary to assess the effect of caudal magnesium on postoperative pain and adverse events. Trial registration University Hospital Medical Information Network Clinical Trials Registry UMIN000025344. PMID:29293586

Atomoxetine could improve intra-individual variability in drug-naïve adults with attention-deficit/hyperactivity disorder comparably with methylphenidate: A head-to-head randomized clinical trial.

PubMed

Ni, Hsing-Chang; Hwang Gu, Shoou-Lian; Lin, Hsiang-Yuan; Lin, Yu-Ju; Yang, Li-Kuang; Huang, Hui-Chun; Gau, Susan Shur-Fen

2016-05-01

Intra-individual variability in reaction time (IIV-RT) is common in individuals with attention-deficit/hyperactivity disorder (ADHD). It can be improved by stimulants. However, the effects of atomoxetine on IIV-RT are inconclusive. We aimed to investigate the effects of atomoxetine on IIV-RT, and directly compared its efficacy with methylphenidate in adults with ADHD. An 8-10 week, open-label, head-to-head, randomized clinical trial was conducted in 52 drug-naïve adults with ADHD, who were randomly assigned to two treatment groups: immediate-release methylphenidate (n=26) thrice daily (10-20 mg per dose) and atomoxetine once daily (n=26) (0.5-1.2 mg/kg/day). IIV-RT, derived from the Conners' continuous performance test (CCPT), was represented by the Gaussian (reaction time standard error, RTSE) and ex-Gaussian models (sigma and tau). Other neuropsychological functions, including response errors and mean of reaction time, were also measured. Participants received CCPT assessments at baseline and week 8-10 (60.4±6.3 days). We found comparable improvements in performances of CCPT between the immediate-release methylphenidate- and atomoxetine-treated groups. Both medications significantly improved IIV-RT in terms of reducing tau values with comparable efficacy. In addition, both medications significantly improved inhibitory control by reducing commission errors. Our results provide evidence to support that atomoxetine could improve IIV-RT and inhibitory control, of comparable efficacy with immediate-release methylphenidate, in drug-naïve adults with ADHD. Shared and unique mechanisms underpinning these medication effects on IIV-RT awaits further investigation. © The Author(s) 2016.

On-board error correction improves IR earth sensor accuracy

NASA Astrophysics Data System (ADS)

Alex, T. K.; Kasturirangan, K.; Shrivastava, S. K.

1989-10-01

Infra-red earth sensors are used in satellites for attitude sensing. Their accuracy is limited by systematic and random errors. The sources of errors in a scanning infra-red earth sensor are analyzed in this paper. The systematic errors arising from seasonal variation of infra-red radiation, oblate shape of the earth, ambient temperature of sensor, changes in scan/spin rates have been analyzed. Simple relations are derived using least square curve fitting for on-board correction of these errors. Random errors arising out of noise from detector and amplifiers, instability of alignment and localized radiance anomalies are analyzed and possible correction methods are suggested. Sun and Moon interference on earth sensor performance has seriously affected a number of missions. The on-board processor detects Sun/Moon interference and corrects the errors on-board. It is possible to obtain eight times improvement in sensing accuracy, which will be comparable with ground based post facto attitude refinement.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

Peak-locking centroid bias in Shack-Hartmann wavefront sensing

NASA Astrophysics Data System (ADS)

Anugu, Narsireddy; Garcia, Paulo J. V.; Correia, Carlos M.

2018-05-01

Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ˜7 to values of ≲ 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

Modelling exoplanet detection with the LUVOIR Coronagraph: aberration sensitivity and error tolerances

NASA Astrophysics Data System (ADS)

Juanola-Parramon, Roser; Zimmerman, Neil; Bolcar, Matthew R.; Rizzo, Maxime; Roberge, Aki

2018-01-01

The Coronagraph is a key instrument on the Large UV-Optical-Infrared (LUVOIR) Surveyor mission concept. The Apodized Pupil Lyot Coronagraph (APLC) is one of the baselined mask technologies to enable 1E10 contrast observations in the habitable zones of nearby stars. Both the LUVOIR architectures A and B present a segmented aperture as input pupil, introducing a set of random tip/tilt and piston errors, among others, that greatly affect the performance of the coronagraph instrument by increasing the wavefront errors hence reducing the instrument sensitivity. In this poster we present the latest results of the simulation of these effects for different working angle regions and discuss the achieved contrast for exoplanet detection and characterization, including simulated observations under these circumstances, setting boundaries for the tolerance of such errors.

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

Chengqiang, L; Yin, Y; Chen, L

Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans.more » Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.« less

Multilevel Multidimensional Item Response Model with a Multilevel Latent Covariate

ERIC Educational Resources Information Center

Cho, Sun-Joo; Bottge, Brian A.

2015-01-01

In a pretest-posttest cluster-randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre-test scores and other related covariates while estimating an intervention effect at post-test. In many applications in education, the total post-test and pre-test scores that ignores measurement error in the…

Effectiveness of Semantic Therapy for Word-Finding Difficulties in Pupils with Persistent Language Impairments: A Randomized Control Trial

ERIC Educational Resources Information Center

Ebbels, Susan H.; Nicoll, Hilary; Clark, Becky; Eachus, Beth; Gallagher, Aoife L.; Horniman, Karen; Jennings, Mary; McEvoy, Kate; Nimmo, Liz; Turner, Gail

2012-01-01

Background: Word-finding difficulties (WFDs) in children have been hypothesized to be caused at least partly by poor semantic knowledge. Therefore, improving semantic knowledge should decrease word-finding errors. Previous studies of semantic therapy for WFDs are inconclusive. Aims: To investigate the effectiveness of semantic therapy for…

Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

ERIC Educational Resources Information Center

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…

Factors effective on medication errors: A nursing view.

PubMed

Shahrokhi, Akram; Ebrahimpour, Fatemeh; Ghodousi, Arash

2013-01-01

Medication errors are the most common medical errors, which may result in some complications for patients. This study was carried out to investigate what influence medication errors by nurses from their viewpoint. In this descriptive study, 150 nurses who were working in Qazvin Medical University teaching hospitals were selected by proportional random sampling, and data were collected by means of a researcher-made questionnaire including demographic attributes (age, gender, working experience,…), and contributing factors in medication errors (in three categories including nurse-related, management-related, and environment-related factors). The mean age of the participant nurses was 30.7 ± 6.5 years. Most of them (87.1%) were female with a Bachelor of Sciences degree (86.7%) in nursing. The mean of their overtime working was 64.8 ± 38 h/month. The results showed that the nurse-related factors are the most effective factors (55.44 ± 9.14) while the factors related to the management system (52.84 ± 11.24) and the ward environment (44.0 ± 10.89) are respectively less effective. The difference between these three groups was significant (P = 0.000). In each aforementioned category, the most effective factor on medication error (ranked from the most effective to the least effective) were as follow: The nurse's inadequate attention (98.7%), the errors occurring in the transfer of medication orders from the patient's file to kardex (96.6%) and the ward's heavy workload (86.7%). In this study nurse-related factors were the most effective factors on medication errors, but nurses are one of the members of health-care providing team, so their performance must be considered in the context of the health-care system like work force condition, rules and regulations, drug manufacturing that might impact nurses performance, so it could not be possible to prevent medication errors without paying attention to our health-care system in a holistic approach.

Factors effective on medication errors: A nursing view

PubMed Central

Shahrokhi, Akram; Ebrahimpour, Fatemeh; Ghodousi, Arash

2013-01-01

Objective: Medication errors are the most common medical errors, which may result in some complications for patients. This study was carried out to investigate what influence medication errors by nurses from their viewpoint. Methods: In this descriptive study, 150 nurses who were working in Qazvin Medical University teaching hospitals were selected by proportional random sampling, and data were collected by means of a researcher-made questionnaire including demographic attributes (age, gender, working experience,…), and contributing factors in medication errors (in three categories including nurse-related, management-related, and environment-related factors). Findings: The mean age of the participant nurses was 30.7 ± 6.5 years. Most of them (87.1%) were female with a Bachelor of Sciences degree (86.7%) in nursing. The mean of their overtime working was 64.8 ± 38 h/month. The results showed that the nurse-related factors are the most effective factors (55.44 ± 9.14) while the factors related to the management system (52.84 ± 11.24) and the ward environment (44.0 ± 10.89) are respectively less effective. The difference between these three groups was significant (P = 0.000). In each aforementioned category, the most effective factor on medication error (ranked from the most effective to the least effective) were as follow: The nurse's inadequate attention (98.7%), the errors occurring in the transfer of medication orders from the patient's file to kardex (96.6%) and the ward's heavy workload (86.7%). Conclusion: In this study nurse-related factors were the most effective factors on medication errors, but nurses are one of the members of health-care providing team, so their performance must be considered in the context of the health-care system like work force condition, rules and regulations, drug manufacturing that might impact nurses performance, so it could not be possible to prevent medication errors without paying attention to our health-care system in a holistic approach. PMID:24991599

Error Mitigation for Short-Depth Quantum Circuits

NASA Astrophysics Data System (ADS)

Temme, Kristan; Bravyi, Sergey; Gambetta, Jay M.

2017-11-01

Two schemes are presented that mitigate the effect of errors and decoherence in short-depth quantum circuits. The size of the circuits for which these techniques can be applied is limited by the rate at which the errors in the computation are introduced. Near-term applications of early quantum devices, such as quantum simulations, rely on accurate estimates of expectation values to become relevant. Decoherence and gate errors lead to wrong estimates of the expectation values of observables used to evaluate the noisy circuit. The two schemes we discuss are deliberately simple and do not require additional qubit resources, so to be as practically relevant in current experiments as possible. The first method, extrapolation to the zero noise limit, subsequently cancels powers of the noise perturbations by an application of Richardson's deferred approach to the limit. The second method cancels errors by resampling randomized circuits according to a quasiprobability distribution.

Error correcting coding-theory for structured light illumination systems

NASA Astrophysics Data System (ADS)

Porras-Aguilar, Rosario; Falaggis, Konstantinos; Ramos-Garcia, Ruben

2017-06-01

Intensity discrete structured light illumination systems project a series of projection patterns for the estimation of the absolute fringe order using only the temporal grey-level sequence at each pixel. This work proposes the use of error-correcting codes for pixel-wise correction of measurement errors. The use of an error correcting code is advantageous in many ways: it allows reducing the effect of random intensity noise, it corrects outliners near the border of the fringe commonly present when using intensity discrete patterns, and it provides a robustness in case of severe measurement errors (even for burst errors where whole frames are lost). The latter aspect is particular interesting in environments with varying ambient light as well as in critical safety applications as e.g. monitoring of deformations of components in nuclear power plants, where a high reliability is ensured even in case of short measurement disruptions. A special form of burst errors is the so-called salt and pepper noise, which can largely be removed with error correcting codes using only the information of a given pixel. The performance of this technique is evaluated using both simulations and experiments.

Randomness increases self-reported anxiety and neurophysiological correlates of performance monitoring

PubMed Central

Kay, Aaron C.; Inzlicht, Michael

2015-01-01

Several prominent theories spanning clinical, social and developmental psychology suggest that people are motivated to see the world as a sensible orderly place. These theories presuppose that randomness is aversive because it is associated with unpredictability. If this is the case, thinking that the world is random should lead to increased anxiety and heightened monitoring of one’s actions and their consequences. Here, we conduct experimental tests of both of these ideas. Participants read one of three passages: (i) comprehensible order, (ii) incomprehensible order and (iii) randomness. In Study 1, we examined the effects of these passages on self-reported anxiety. In Study 2, we examined the effects of the same manipulation on the error-related negativity (ERN), an event-related brain potential associated with performance monitoring. We found that messages about randomness increased self-reported anxiety and ERN amplitude relative to comprehensible order, whereas incomprehensible order had intermediate effects. These results lend support to the theoretically important idea that randomness is unsettling because it implies that the world is unpredictable. PMID:25062840

What Randomized Benchmarking Actually Measures

DOE PAGES

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin; ...

2017-09-28

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.

Prediction of antenna array performance from subarray measurements

NASA Technical Reports Server (NTRS)

Huisjen, M. A.

1978-01-01

Computer runs were used to determine the effect of mechanical distortions on array pattern performance. Subarray gain data, along with feed network insertion loss, and insertion phase data were combined with the analysis of Ruze on random errors to predict gain of a full array.

Computer-Based Linguistic Analysis.

ERIC Educational Resources Information Center

Wright, James R.

Noam Chomsky's transformational-generative grammar model may effectively be translated into an equivalent computer model. Phrase-structure rules and transformations are tested as to their validity and ordering by the computer via the process of random lexical substitution. Errors appearing in the grammar are detected and rectified, and formal…

Random errors of oceanic monthly rainfall derived from SSM/I using probability distribution functions

NASA Technical Reports Server (NTRS)

Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.

1993-01-01

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.

Effects of input device and motion type on a cursor-positioning task.

PubMed

Yau, Yi-Jan; Hwang, Sheue-Ling; Chao, Chin-Jung

2008-02-01

Many studies have investigated the performance of using nonkey-board input devices under static situations, but few have considered the effects of motion type on manipulating these input devices. In this study comparison of 12 mens' performance using four input devices (three trackballs: currently used, trackman wheel, and erectly held trackballs, as well as a touch screen) under five motion types of static, heave, roll, pitch, and random movements was conducted. The input device and motion type significantly affected movement speed and accuracy, and their interaction significantly affected the movement speed. The touch screen was the fastest but the least accurate input device. The erectly held trackball was the slowest, whereas the error rate of the currently used trackball was the lowest. Impairments of the random motion on movement time and error rate were larger than those of other motion types. Considering objective and subjective evaluations, the trackman wheel and currently used trackball were more efficient in operation than the erectly held trackball and touch screen under the motion environments.

A Systematic Error Correction Method for TOVS Radiances

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Rokke, Laurie; Einaudi, Franco (Technical Monitor)

2000-01-01

Treatment of systematic errors is crucial for the successful use of satellite data in a data assimilation system. Systematic errors in TOVS radiance measurements and radiative transfer calculations can be as large or larger than random instrument errors. The usual assumption in data assimilation is that observational errors are unbiased. If biases are not effectively removed prior to assimilation, the impact of satellite data will be lessened and can even be detrimental. Treatment of systematic errors is important for short-term forecast skill as well as the creation of climate data sets. A systematic error correction algorithm has been developed as part of a 1D radiance assimilation. This scheme corrects for spectroscopic errors, errors in the instrument response function, and other biases in the forward radiance calculation for TOVS. Such algorithms are often referred to as tuning of the radiances. The scheme is able to account for the complex, air-mass dependent biases that are seen in the differences between TOVS radiance observations and forward model calculations. We will show results of systematic error correction applied to the NOAA 15 Advanced TOVS as well as its predecessors. We will also discuss the ramifications of inter-instrument bias with a focus on stratospheric measurements.

Comparison of random regression models with Legendre polynomials and linear splines for production traits and somatic cell score of Canadian Holstein cows.

PubMed

Bohmanova, J; Miglior, F; Jamrozik, J; Misztal, I; Sullivan, P G

2008-09-01

A random regression model with both random and fixed regressions fitted by Legendre polynomials of order 4 was compared with 3 alternative models fitting linear splines with 4, 5, or 6 knots. The effects common for all models were a herd-test-date effect, fixed regressions on days in milk (DIM) nested within region-age-season of calving class, and random regressions for additive genetic and permanent environmental effects. Data were test-day milk, fat and protein yields, and SCS recorded from 5 to 365 DIM during the first 3 lactations of Canadian Holstein cows. A random sample of 50 herds consisting of 96,756 test-day records was generated to estimate variance components within a Bayesian framework via Gibbs sampling. Two sets of genetic evaluations were subsequently carried out to investigate performance of the 4 models. Models were compared by graphical inspection of variance functions, goodness of fit, error of prediction of breeding values, and stability of estimated breeding values. Models with splines gave lower estimates of variances at extremes of lactations than the model with Legendre polynomials. Differences among models in goodness of fit measured by percentages of squared bias, correlations between predicted and observed records, and residual variances were small. The deviance information criterion favored the spline model with 6 knots. Smaller error of prediction and higher stability of estimated breeding values were achieved by using spline models with 5 and 6 knots compared with the model with Legendre polynomials. In general, the spline model with 6 knots had the best overall performance based upon the considered model comparison criteria.

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

NASA Astrophysics Data System (ADS)

Lychak, Oleh V.; Holyns'kiy, Ivan S.

2016-03-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.

Improved methods for the measurement and analysis of stellar magnetic fields

NASA Technical Reports Server (NTRS)

Saar, Steven H.

1988-01-01

The paper presents several improved methods for the measurement of magnetic fields on cool stars which take into account simple radiative transfer effects and the exact Zeeman patterns. Using these methods, high-resolution, low-noise data can be fitted with theoretical line profiles to determine the mean magnetic field strength in stellar active regions and a model-dependent fraction of the stellar surface (filling factor) covered by these regions. Random errors in the derived field strength and filling factor are parameterized in terms of signal-to-noise ratio, wavelength, spectral resolution, stellar rotation rate, and the magnetic parameters themselves. Weak line blends, if left uncorrected, can have significant systematic effects on the derived magnetic parameters, and thus several methods are developed to compensate partially for them. The magnetic parameters determined by previous methods likely have systematic errors because of such line blends and because of line saturation effects. Other sources of systematic error are explored in detail. These sources of error currently make it difficult to determine the magnetic parameters of individual stars to better than about + or - 20 percent.

Correction of a Technical Error in the Golf Swing: Error Amplification Versus Direct Instruction.

PubMed

Milanese, Chiara; Corte, Stefano; Salvetti, Luca; Cavedon, Valentina; Agostini, Tiziano

2016-01-01

Performance errors drive motor learning for many tasks. The authors' aim was to determine which of two strategies, method of amplification of error (MAE) or direct instruction (DI), would be more beneficial for error correction during a full golfing swing with a driver. Thirty-four golfers were randomly assigned to one of three training conditions (MAE, DI, and control). Participants were tested in a practice session in which each golfer performed 7 pretraining trials, 6 training-intervention trials, and 7 posttraining trials; and a retention test after 1 week. An optoeletronic motion capture system was used to measure the kinematic parameters of each golfer's performance. Results showed that MAE is an effective strategy for correcting the technical errors leading to a rapid improvement in performance. These findings could have practical implications for sport psychology and physical education because, while practice is obviously necessary for improving learning, the efficacy of the learning process is essential in enhancing learners' motivation and sport enjoyment.

Light Scattered from Polished Optical Surfaces: Wings of the Point Spread Function

NASA Technical Reports Server (NTRS)

Kenknight, C. E.

1984-01-01

Random figure errors from the polishing process plus particles on the main mirrors in a telescope cause an extended point spread function (PSF) declining approximately as the inverse square of the sine of the angle from a star from about 100 micro-rad to a right angle. The decline in at least one case, and probably in general, proceeds as the inverse cube at smaller angles where the usual focal plane aperture radius is chosen. The photometric error due to misalignment by one Airy ring spacing with an aperture of n rings depends on the net variance in the figure. It is approximately 60/(n+1)(3) when using the data of Kormendy (1973). A typical value is 6 x 10 to the -5th power per ring of misalignment with n = 100 rings. The encircled power may be modulated on a time scale of hours by parts per thousand in a wavelength dependent manner due to relative humidity effects on mirror dust. The scattering according to an inverse power law is due to a random walk in aberration height caused by a multitude of facets and slope errors left by the polishing process. A deviation from such a law at grazing emergence may permit monitoring the dust effects.

An empirical understanding of triple collocation evaluation measure

NASA Astrophysics Data System (ADS)

Scipal, Klaus; Doubkova, Marcela; Hegyova, Alena; Dorigo, Wouter; Wagner, Wolfgang

2013-04-01

Triple collocation method is an advanced evaluation method that has been used in the soil moisture field for only about half a decade. The method requires three datasets with an independent error structure that represent an identical phenomenon. The main advantages of the method are that it a) doesn't require a reference dataset that has to be considered to represent the truth, b) limits the effect of random and systematic errors of other two datasets, and c) simultaneously assesses the error of three datasets. The objective of this presentation is to assess the triple collocation error (Tc) of the ASAR Global Mode Surface Soil Moisture (GM SSM 1) km dataset and highlight problems of the method related to its ability to cancel the effect of error of ancillary datasets. In particular, the goal is to a) investigate trends in Tc related to the change in spatial resolution from 5 to 25 km, b) to investigate trends in Tc related to the choice of a hydrological model, and c) to study the relationship between Tc and other absolute evaluation methods (namely RMSE and Error Propagation EP). The triple collocation method is implemented using ASAR GM, AMSR-E, and a model (either AWRA-L, GLDAS-NOAH, or ERA-Interim). First, the significance of the relationship between the three soil moisture datasets was tested that is a prerequisite for the triple collocation method. Second, the trends in Tc related to the choice of the third reference dataset and scale were assessed. For this purpose the triple collocation is repeated replacing AWRA-L with two different globally available model reanalysis dataset operating at different spatial resolution (ERA-Interim and GLDAS-NOAH). Finally, the retrieved results were compared to the results of the RMSE and EP evaluation measures. Our results demonstrate that the Tc method does not eliminate the random and time-variant systematic errors of the second and the third dataset used in the Tc. The possible reasons include the fact a) that the TC method could not fully function with datasets acting at very different spatial resolutions, or b) that the errors were not fully independent as initially assumed.

Uncertainty Propagation in OMFIT

NASA Astrophysics Data System (ADS)

Smith, Sterling; Meneghini, Orso; Sung, Choongki

2017-10-01

A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.

Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

NASA Astrophysics Data System (ADS)

Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

2017-08-01

We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

Testing the Recognition and Perception of Errors in Context

ERIC Educational Resources Information Center

Brandenburg, Laura C.

2015-01-01

This study tests the recognition of errors in context and whether the presence of errors affects the reader's perception of the writer's ethos. In an experimental, posttest only design, participants were randomly assigned a memo to read in an online survey: one version with errors and one version without. Of the six intentional errors in version…

Exploring Measurement Error with Cookies: A Real and Virtual Approach via Interactive Excel

ERIC Educational Resources Information Center

Sinex, Scott A; Gage, Barbara A.; Beck, Peggy J.

2007-01-01

A simple, guided-inquiry investigation using stacked sandwich cookies is employed to develop a simple linear mathematical model and to explore measurement error by incorporating errors as part of the investigation. Both random and systematic errors are presented. The model and errors are then investigated further by engaging with an interactive…

Nicotine-induced activation of caudate and anterior cingulate cortex in response to errors in schizophrenia.

PubMed

Moran, Lauren V; Stoeckel, Luke E; Wang, Kristina; Caine, Carolyn E; Villafuerte, Rosemond; Calderon, Vanessa; Baker, Justin T; Ongur, Dost; Janes, Amy C; Evins, A Eden; Pizzagalli, Diego A

2018-03-01

Nicotine improves attention and processing speed in individuals with schizophrenia. Few studies have investigated the effects of nicotine on cognitive control. Prior functional magnetic resonance imaging (fMRI) research demonstrates blunted activation of dorsal anterior cingulate cortex (dACC) and rostral anterior cingulate cortex (rACC) in response to error and decreased post-error slowing in schizophrenia. Participants with schizophrenia (n = 13) and healthy controls (n = 12) participated in a randomized, placebo-controlled, crossover study of the effects of transdermal nicotine on cognitive control. For each drug condition, participants underwent fMRI while performing the stop signal task where participants attempt to inhibit prepotent responses to "go (motor activation)" signals when an occasional "stop (motor inhibition)" signal appears. Error processing was evaluated by comparing "stop error" trials (failed response inhibition) to "go" trials. Resting-state fMRI data were collected prior to the task. Participants with schizophrenia had increased nicotine-induced activation of right caudate in response to errors compared to controls (DRUG × GROUP effect: p corrected  < 0.05). Both groups had significant nicotine-induced activation of dACC and rACC in response to errors. Using right caudate activation to errors as a seed for resting-state functional connectivity analysis, relative to controls, participants with schizophrenia had significantly decreased connectivity between the right caudate and dACC/bilateral dorsolateral prefrontal cortices. In sum, we replicated prior findings of decreased post-error slowing in schizophrenia and found that nicotine was associated with more adaptive (i.e., increased) post-error reaction time (RT). This proof-of-concept pilot study suggests a role for nicotinic agents in targeting cognitive control deficits in schizophrenia.

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts

PubMed Central

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2018-01-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments. PMID:29375930

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

PubMed

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

Estimation of population mean in the presence of measurement error and non response under stratified random sampling

PubMed Central

Shabbir, Javid

2018-01-01

In the present paper we propose an improved class of estimators in the presence of measurement error and non-response under stratified random sampling for estimating the finite population mean. The theoretical and numerical studies reveal that the proposed class of estimators performs better than other existing estimators. PMID:29401519

Perceptions of Randomness: Why Three Heads Are Better than Four

ERIC Educational Resources Information Center

Hahn, Ulrike; Warren, Paul A.

2009-01-01

A long tradition of psychological research has lamented the systematic errors and biases in people's perception of the characteristics of sequences generated by a random mechanism such as a coin toss. It is proposed that once the likely nature of people's actual experience of such processes is taken into account, these "errors" and "biases"…

Adaptive box filters for removal of random noise from digital images

USGS Publications Warehouse

Eliason, E.M.; McEwen, A.S.

1990-01-01

We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors

Statistical model for speckle pattern optimization.

PubMed

Su, Yong; Zhang, Qingchuan; Gao, Zeren

2017-11-27

Image registration is the key technique of optical metrologies such as digital image correlation (DIC), particle image velocimetry (PIV), and speckle metrology. Its performance depends critically on the quality of image pattern, and thus pattern optimization attracts extensive attention. In this article, a statistical model is built to optimize speckle patterns that are composed of randomly positioned speckles. It is found that the process of speckle pattern generation is essentially a filtered Poisson process. The dependence of measurement errors (including systematic errors, random errors, and overall errors) upon speckle pattern generation parameters is characterized analytically. By minimizing the errors, formulas of the optimal speckle radius are presented. Although the primary motivation is from the field of DIC, we believed that scholars in other optical measurement communities, such as PIV and speckle metrology, will benefit from these discussions.

The decline and fall of Type II error rates

Treesearch

Steve Verrill; Mark Durst

2005-01-01

For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.

Asymmetric Memory Circuit Would Resist Soft Errors

NASA Technical Reports Server (NTRS)

Buehler, Martin G.; Perlman, Marvin

1990-01-01

Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.

Using Propensity Score Matching Methods to Improve Generalization from Randomized Experiments

ERIC Educational Resources Information Center

Tipton, Elizabeth

2011-01-01

The main result of an experiment is typically an estimate of the average treatment effect (ATE) and its standard error. In most experiments, the number of covariates that may be moderators is large. One way this issue is typically skirted is by interpreting the ATE as the average effect for "some" population. Cornfield and Tukey (1956)…

Effects of clear aligners on sleep bruxism: randomized controlled trial.

PubMed

Castroflorio, T; Bargellini, A; Lucchese, A; Manuelli, M; Casasco, F; Cugliari, G; Cioffi, I; Deregibus, A

2018-01-01

The possible effects on sleep bruxism (SB) of clear aligners in orthodontics are unknown. This study was conducted to analyze the effects of clear aligners on SB. Sixty subjects needing orthodontic treatment and affected by SB (33 m, 27 f, 20±;5 years) were enrolled in the study and randomly assigned to one of the following three groups: 20 were given clear aligners (CAT) (12 m, 8 f, 19±5 years), 20 occlusal splint (MOS) (9 m, 11 f, 22±5 years) and 20 a placebo splint (PMS) (12 m, 8 f, 24±3 years). All groups were followed for 6 consecutive months and monitored for SB with a portable electromyographic-electrocardiographic (EMG-ECG) device (Bruxoff®, OT Bioelettronica, Torino, Italy). MOS subjects reduced masseter contractions after 6 months of treatment (t3) (MD=-29.11, std. error 11.74, p=0.017) but increased phasic contractions related to SB after 3 months of treatment (t2) (MD=4.73, std. error 2.36, p=0.048) and tonic contractions related to SB during all the six months of treatment (t1, t2, t3) when compared to PMS. CAT subjects increased phasic contractions related to SB during the first (t1) (MD=3.94, std. error 2.27, p=0.04) and the third month (t2) of treatment (MD=4.62, std. error 2.36, p=0.046) when compared to PMS. No significant differences were found for SB index at any time for all the three groups. Although MOS and CAT affected EMG signals during sleep time differently, they did not influence the overall SB index.

When do latent class models overstate accuracy for diagnostic and other classifiers in the absence of a gold standard?

PubMed

Spencer, Bruce D

2012-06-01

Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. The error rates according to the latent class model differ from the true error rates, however, and empirical comparisons with a gold standard suggest the true error rates often are larger. We investigate conditions under which the true type I and type II error rates are larger than those provided by the latent class models. Results from Uebersax (1988, Psychological Bulletin 104, 405-416) are extended to accommodate random effects and covariates affecting the responses. The results are important for interpreting the results of latent class analyses. An error decomposition is presented that incorporates an error component from invalidity of the latent class model. © 2011, The International Biometric Society.

The role of model errors represented by nonlinear forcing singular vector tendency error in causing the "spring predictability barrier" within ENSO predictions

NASA Astrophysics Data System (ADS)

Duan, Wansuo; Zhao, Peng

2017-04-01

Within the Zebiak-Cane model, the nonlinear forcing singular vector (NFSV) approach is used to investigate the role of model errors in the "Spring Predictability Barrier" (SPB) phenomenon within ENSO predictions. NFSV-related errors have the largest negative effect on the uncertainties of El Niño predictions. NFSV errors can be classified into two types: the first is characterized by a zonal dipolar pattern of SST anomalies (SSTA), with the western poles centered in the equatorial central-western Pacific exhibiting positive anomalies and the eastern poles in the equatorial eastern Pacific exhibiting negative anomalies; and the second is characterized by a pattern almost opposite the first type. The first type of error tends to have the worst effects on El Niño growth-phase predictions, whereas the latter often yields the largest negative effects on decaying-phase predictions. The evolution of prediction errors caused by NFSV-related errors exhibits prominent seasonality, with the fastest error growth in the spring and/or summer seasons; hence, these errors result in a significant SPB related to El Niño events. The linear counterpart of NFSVs, the (linear) forcing singular vector (FSV), induces a less significant SPB because it contains smaller prediction errors. Random errors cannot generate a SPB for El Niño events. These results show that the occurrence of an SPB is related to the spatial patterns of tendency errors. The NFSV tendency errors cause the most significant SPB for El Niño events. In addition, NFSVs often concentrate these large value errors in a few areas within the equatorial eastern and central-western Pacific, which likely represent those areas sensitive to El Niño predictions associated with model errors. Meanwhile, these areas are also exactly consistent with the sensitive areas related to initial errors determined by previous studies. This implies that additional observations in the sensitive areas would not only improve the accuracy of the initial field but also promote the reduction of model errors to greatly improve ENSO forecasts.

Detecting Spatial Patterns in Biological Array Experiments

PubMed Central

ROOT, DAVID E.; KELLEY, BRIAN P.; STOCKWELL, BRENT R.

2005-01-01

Chemical genetic screening and DNA and protein microarrays are among a number of increasingly important and widely used biological research tools that involve large numbers of parallel experiments arranged in a spatial array. It is often difficult to ensure that uniform experimental conditions are present throughout the entire array, and as a result, one often observes systematic spatially correlated errors, especially when array experiments are performed using robots. Here, the authors apply techniques based on the discrete Fourier transform to identify and quantify spatially correlated errors superimposed on a spatially random background. They demonstrate that these techniques are effective in identifying common spatially systematic errors in high-throughput 384-well microplate assay data. In addition, the authors employ a statistical test to allow for automatic detection of such errors. Software tools for using this approach are provided. PMID:14567791

Geodetic positioning using a global positioning system of satellites

NASA Technical Reports Server (NTRS)

Fell, P. J.

1980-01-01

Geodetic positioning using range, integrated Doppler, and interferometric observations from a constellation of twenty-four Global Positioning System satellites is analyzed. A summary of the proposals for geodetic positioning and baseline determination is given which includes a description of measurement techniques and comments on rank deficiency and error sources. An analysis of variance comparison of range, Doppler, and interferometric time delay to determine their relative geometric strength for baseline determination is included. An analytic examination to the effect of a priori constraints on positioning using simultaneous observations from two stations is presented. Dynamic point positioning and baseline determination using range and Doppler is examined in detail. Models for the error sources influencing dynamic positioning are developed. Included is a discussion of atomic clock stability, and range and Doppler observation error statistics based on random correlated atomic clock error are derived.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.

2004-01-01

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

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

Wang, Yueqi; Lava, Pascal; Reu, Phillip

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE PAGES

Wang, Yueqi; Lava, Pascal; Reu, Phillip; ...

2015-12-23

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros

2004-01-01

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

The use of self checks and voting in software error detection - An empirical study

NASA Technical Reports Server (NTRS)

Leveson, Nancy G.; Cha, Stephen S.; Knight, John C.; Shimeall, Timothy J.

1990-01-01

The results of an empirical study of software error detection using self checks and N-version voting are presented. Working independently, each of 24 programmers first prepared a set of self checks using just the requirements specification of an aerospace application, and then each added self checks to an existing implementation of that specification. The modified programs were executed to measure the error-detection performance of the checks and to compare this with error detection using simple voting among multiple versions. The analysis of the checks revealed that there are great differences in the ability of individual programmers to design effective checks. It was found that some checks that might have been effective failed to detect an error because they were badly placed, and there were numerous instances of checks signaling nonexistent errors. In general, specification-based checks alone were not as effective as specification-based checks combined with code-based checks. Self checks made it possible to identify faults that had not been detected previously by voting 28 versions of the program over a million randomly generated inputs. This appeared to result from the fact that the self checks could examine the internal state of the executing program, whereas voting examines only final results of computations. If internal states had to be identical in N-version voting systems, then there would be no reason to write multiple versions.

Coordinate based random effect size meta-analysis of neuroimaging studies.

PubMed

Tench, C R; Tanasescu, Radu; Constantinescu, C S; Auer, D P; Cottam, W J

2017-06-01

Low power in neuroimaging studies can make them difficult to interpret, and Coordinate based meta-analysis (CBMA) may go some way to mitigating this issue. CBMA has been used in many analyses to detect where published functional MRI or voxel-based morphometry studies testing similar hypotheses report significant summary results (coordinates) consistently. Only the reported coordinates and possibly t statistics are analysed, and statistical significance of clusters is determined by coordinate density. Here a method of performing coordinate based random effect size meta-analysis and meta-regression is introduced. The algorithm (ClusterZ) analyses both coordinates and reported t statistic or Z score, standardised by the number of subjects. Statistical significance is determined not by coordinate density, but by a random effects meta-analyses of reported effects performed cluster-wise using standard statistical methods and taking account of censoring inherent in the published summary results. Type 1 error control is achieved using the false cluster discovery rate (FCDR), which is based on the false discovery rate. This controls both the family wise error rate under the null hypothesis that coordinates are randomly drawn from a standard stereotaxic space, and the proportion of significant clusters that are expected under the null. Such control is necessary to avoid propagating and even amplifying the very issues motivating the meta-analysis in the first place. ClusterZ is demonstrated on both numerically simulated data and on real data from reports of grey matter loss in multiple sclerosis (MS) and syndromes suggestive of MS, and of painful stimulus in healthy controls. The software implementation is available to download and use freely. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Error Analysis of Indirect Broadband Monitoring of Multilayer Optical Coatings using Computer Simulations

NASA Astrophysics Data System (ADS)

Semenov, Z. V.; Labusov, V. A.

2017-11-01

Results of studying the errors of indirect monitoring by means of computer simulations are reported. The monitoring method is based on measuring spectra of reflection from additional monitoring substrates in a wide spectral range. Special software (Deposition Control Simulator) is developed, which allows one to estimate the influence of the monitoring system parameters (noise of the photodetector array, operating spectral range of the spectrometer and errors of its calibration in terms of wavelengths, drift of the radiation source intensity, and errors in the refractive index of deposited materials) on the random and systematic errors of deposited layer thickness measurements. The direct and inverse problems of multilayer coatings are solved using the OptiReOpt library. Curves of the random and systematic errors of measurements of the deposited layer thickness as functions of the layer thickness are presented for various values of the system parameters. Recommendations are given on using the indirect monitoring method for the purpose of reducing the layer thickness measurement error.

Error analysis and algorithm implementation for an improved optical-electric tracking device based on MEMS

NASA Astrophysics Data System (ADS)

Sun, Hong; Wu, Qian-zhong

2013-09-01

In order to improve the precision of optical-electric tracking device, proposing a kind of improved optical-electric tracking device based on MEMS, in allusion to the tracking error of gyroscope senor and the random drift, According to the principles of time series analysis of random sequence, establish AR model of gyro random error based on Kalman filter algorithm, then the output signals of gyro are multiple filtered with Kalman filter. And use ARM as micro controller servo motor is controlled by fuzzy PID full closed loop control algorithm, and add advanced correction and feed-forward links to improve response lag of angle input, Free-forward can make output perfectly follow input. The function of lead compensation link is to shorten the response of input signals, so as to reduce errors. Use the wireless video monitor module and remote monitoring software (Visual Basic 6.0) to monitor servo motor state in real time, the video monitor module gathers video signals, and the wireless video module will sent these signals to upper computer, so that show the motor running state in the window of Visual Basic 6.0. At the same time, take a detailed analysis to the main error source. Through the quantitative analysis of the errors from bandwidth and gyro sensor, it makes the proportion of each error in the whole error more intuitive, consequently, decrease the error of the system. Through the simulation and experiment results shows the system has good following characteristic, and it is very valuable for engineering application.

Record statistics of a strongly correlated time series: random walks and Lévy flights

NASA Astrophysics Data System (ADS)

Godrèche, Claude; Majumdar, Satya N.; Schehr, Grégory

2017-08-01

We review recent advances on the record statistics of strongly correlated time series, whose entries denote the positions of a random walk or a Lévy flight on a line. After a brief survey of the theory of records for independent and identically distributed random variables, we focus on random walks. During the last few years, it was indeed realized that random walks are a very useful ‘laboratory’ to test the effects of correlations on the record statistics. We start with the simple one-dimensional random walk with symmetric jumps (both continuous and discrete) and discuss in detail the statistics of the number of records, as well as of the ages of the records, i.e. the lapses of time between two successive record breaking events. Then we review the results that were obtained for a wide variety of random walk models, including random walks with a linear drift, continuous time random walks, constrained random walks (like the random walk bridge) and the case of multiple independent random walkers. Finally, we discuss further observables related to records, like the record increments, as well as some questions raised by physical applications of record statistics, like the effects of measurement error and noise.

Error Sources in Asteroid Astrometry

NASA Technical Reports Server (NTRS)

Owen, William M., Jr.

2000-01-01

Asteroid astrometry, like any other scientific measurement process, is subject to both random and systematic errors, not all of which are under the observer's control. To design an astrometric observing program or to improve an existing one requires knowledge of the various sources of error, how different errors affect one's results, and how various errors may be minimized by careful observation or data reduction techniques.

Memory consolidation and contextual interference effects with computer games.

PubMed

Shewokis, Patricia A

2003-10-01

Some investigators of the contextual interference effect contend that there is a direct relation between the amount of practice and the contextual interference effect based on the prediction that the improvement in learning tasks in a random practice schedule, compared to a blocked practice schedule, increases in magnitude as the amount of practice during acquisition on the tasks increases. Research using computer games in contextual interference studies has yielded a large effect (f = .50) with a random practice schedule advantage during transfer. These investigations had a total of 36 and 72 acquisition trials, respectively. The present study tested this prediction by having 72 college students, who were randomly assigned to a blocked or random practice schedule, practice 102 trials of three computer-game tasks across three days. After a 24-hr. interval, 6 retention and 5 transfer trials were performed. Dependent variables were time to complete an event in seconds and number of errors. No significant differences were found for retention and transfer. These results are discussed in terms of how the amount of practice, task-related factors, and memory consolidation mediate the contextual interference effect.

A statistical model for analyzing the rotational error of single isocenter for multiple targets technique.

PubMed

Chang, Jenghwa

2017-06-01

To develop a statistical model that incorporates the treatment uncertainty from the rotational error of the single isocenter for multiple targets technique, and calculates the extra PTV (planning target volume) margin required to compensate for this error. The random vector for modeling the setup (S) error in the three-dimensional (3D) patient coordinate system was assumed to follow a 3D normal distribution with a zero mean, and standard deviations of σ x , σ y , σ z . It was further assumed that the rotation of clinical target volume (CTV) about the isocenter happens randomly and follows a three-dimensional (3D) independent normal distribution with a zero mean and a uniform standard deviation of σ δ . This rotation leads to a rotational random error (R), which also has a 3D independent normal distribution with a zero mean and a uniform standard deviation of σ R equal to the product of σδπ180 and dI⇔T, the distance between the isocenter and CTV. Both (S and R) random vectors were summed, normalized, and transformed to the spherical coordinates to derive the Chi distribution with three degrees of freedom for the radial coordinate of S+R. PTV margin was determined using the critical value of this distribution for a 0.05 significance level so that 95% of the time the treatment target would be covered by the prescription dose. The additional PTV margin required to compensate for the rotational error was calculated as a function of σ R and dI⇔T. The effect of the rotational error is more pronounced for treatments that require high accuracy/precision like stereotactic radiosurgery (SRS) or stereotactic body radiotherapy (SBRT). With a uniform 2-mm PTV margin (or σ x = σ y = σ z = 0.715 mm), a σ R = 0.328 mm will decrease the CTV coverage probability from 95.0% to 90.9%, or an additional 0.2-mm PTV margin is needed to prevent this loss of coverage. If we choose 0.2 mm as the threshold, any σ R > 0.328 mm will lead to an extra PTV margin that cannot be ignored, and the maximal σ δ that can be ignored is 0.45° (or 0.0079 rad ) for dI⇔T = 50 mm or 0.23° (or 0.004 rad ) for dI⇔T = 100 mm. The rotational error cannot be ignored for high-accuracy/-precision treatments like SRS/SBRT, particularly when the distance between the isocenter and target is large. © 2017 American Association of Physicists in Medicine.

A theoretical basis for the analysis of redundant software subject to coincident errors

NASA Technical Reports Server (NTRS)

Eckhardt, D. E., Jr.; Lee, L. D.

1985-01-01

Fundamental to the development of redundant software techniques fault-tolerant software, is an understanding of the impact of multiple-joint occurrences of coincident errors. A theoretical basis for the study of redundant software is developed which provides a probabilistic framework for empirically evaluating the effectiveness of the general (N-Version) strategy when component versions are subject to coincident errors, and permits an analytical study of the effects of these errors. The basic assumptions of the model are: (1) independently designed software components are chosen in a random sample; and (2) in the user environment, the system is required to execute on a stationary input series. The intensity of coincident errors, has a central role in the model. This function describes the propensity to introduce design faults in such a way that software components fail together when executing in the user environment. The model is used to give conditions under which an N-Version system is a better strategy for reducing system failure probability than relying on a single version of software. A condition which limits the effectiveness of a fault-tolerant strategy is studied, and it is posted whether system failure probability varies monotonically with increasing N or whether an optimal choice of N exists.

Health plan auditing: 100-percent-of-claims vs. random-sample audits.

PubMed

Sillup, George P; Klimberg, Ronald K

2011-01-01

The objective of this study was to examine the relative efficacy of two different methodologies for auditing self-funded medical claim expenses: 100-percent-of-claims auditing versus random-sampling auditing. Multiple data sets of claim errors or 'exceptions' from two Fortune-100 corporations were analysed and compared to 100 simulated audits of 300- and 400-claim random samples. Random-sample simulations failed to identify a significant number and amount of the errors that ranged from $200,000 to $750,000. These results suggest that health plan expenses of corporations could be significantly reduced if they audited 100% of claims and embraced a zero-defect approach.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Correction of stream quality trends for the effects of laboratory measurement bias

USGS Publications Warehouse

Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.

1993-01-01

We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Does Mckuer's Law Hold for Heart Rate Control via Biofeedback Display?

NASA Technical Reports Server (NTRS)

Courter, B. J.; Jex, H. R.

1984-01-01

Some persons can control their pulse rate with the aid of a biofeedback display. If the biofeedback display is modified to show the error between a command pulse-rate and the measured rate, a compensatory (error correcting) heart rate tracking control loop can be created. The dynamic response characteristics of this control loop when subjected to step and quasi-random disturbances were measured. The control loop includes a beat-to-beat cardiotachmeter differenced with a forcing function from a quasi-random input generator; the resulting error pulse-rate is displayed as feedback. The subject acts to null the displayed pulse-rate error, thereby closing a compensatory control loop. McRuer's Law should hold for this case. A few subjects already skilled in voluntary pulse-rate control were tested for heart-rate control response. Control-law properties are derived, such as: crossover frequency, stability margins, and closed-loop bandwidth. These are evaluated for a range of forcing functions and for step as well as random disturbances.

Synthesis of hover autopilots for rotary-wing VTOL aircraft

NASA Technical Reports Server (NTRS)

Hall, W. E.; Bryson, A. E., Jr.

1972-01-01

The practical situation is considered where imperfect information on only a few rotor and fuselage state variables is available. Filters are designed to estimate all the state variables from noisy measurements of fuselage pitch/roll angles and from noisy measurements of both fuselage and rotor pitch/roll angles. The mean square response of the vehicle to a very gusty, random wind is computed using various filter/controllers and is found to be quite satisfactory although, of course, not so good as when one has perfect information (idealized case). The second part of the report considers precision hover over a point on the ground. A vehicle model without rotor dynamics is used and feedback signals in position and integral of position error are added. The mean square response of the vehicle to a very gusty, random wind is computed, assuming perfect information feedback, and is found to be excellent. The integral error feedback gives zero position error for a steady wind, and smaller position error for a random wind.

Selecting Statistical Quality Control Procedures for Limiting the Impact of Increases in Analytical Random Error on Patient Safety.

PubMed

Yago, Martín

2017-05-01

QC planning based on risk management concepts can reduce the probability of harming patients due to an undetected out-of-control error condition. It does this by selecting appropriate QC procedures to decrease the number of erroneous results reported. The selection can be easily made by using published nomograms for simple QC rules when the out-of-control condition results in increased systematic error. However, increases in random error also occur frequently and are difficult to detect, which can result in erroneously reported patient results. A statistical model was used to construct charts for the 1 ks and X /χ 2 rules. The charts relate the increase in the number of unacceptable patient results reported due to an increase in random error with the capability of the measurement procedure. They thus allow for QC planning based on the risk of patient harm due to the reporting of erroneous results. 1 ks Rules are simple, all-around rules. Their ability to deal with increases in within-run imprecision is minimally affected by the possible presence of significant, stable, between-run imprecision. X /χ 2 rules perform better when the number of controls analyzed during each QC event is increased to improve QC performance. Using nomograms simplifies the selection of statistical QC procedures to limit the number of erroneous patient results reported due to an increase in analytical random error. The selection largely depends on the presence or absence of stable between-run imprecision. © 2017 American Association for Clinical Chemistry.

Neurochemical enhancement of conscious error awareness.

PubMed

Hester, Robert; Nandam, L Sanjay; O'Connell, Redmond G; Wagner, Joe; Strudwick, Mark; Nathan, Pradeep J; Mattingley, Jason B; Bellgrove, Mark A

2012-02-22

How the brain monitors ongoing behavior for performance errors is a central question of cognitive neuroscience. Diminished awareness of performance errors limits the extent to which humans engage in corrective behavior and has been linked to loss of insight in a number of psychiatric syndromes (e.g., attention deficit hyperactivity disorder, drug addiction). These conditions share alterations in monoamine signaling that may influence the neural mechanisms underlying error processing, but our understanding of the neurochemical drivers of these processes is limited. We conducted a randomized, double-blind, placebo-controlled, cross-over design of the influence of methylphenidate, atomoxetine, and citalopram on error awareness in 27 healthy participants. The error awareness task, a go/no-go response inhibition paradigm, was administered to assess the influence of monoaminergic agents on performance errors during fMRI data acquisition. A single dose of methylphenidate, but not atomoxetine or citalopram, significantly improved the ability of healthy volunteers to consciously detect performance errors. Furthermore, this behavioral effect was associated with a strengthening of activation differences in the dorsal anterior cingulate cortex and inferior parietal lobe during the methylphenidate condition for errors made with versus without awareness. Our results have implications for the understanding of the neurochemical underpinnings of performance monitoring and for the pharmacological treatment of a range of disparate clinical conditions that are marked by poor awareness of errors.

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

George, Brandon J.; Beasley, T. Mark; Brown, Andrew W.; Dawson, John; Dimova, Rositsa; Divers, Jasmin; Goldsby, TaShauna U.; Heo, Moonseong; Kaiser, Kathryn A.; Keith, Scott; Kim, Mimi Y.; Li, Peng; Mehta, Tapan; Oakes, J. Michael; Skinner, Asheley; Stuart, Elizabeth; Allison, David B.

2015-01-01

We identify 10 common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research and discuss how they can be avoided. The 10 topics are: 1) misinterpretation of statistical significance, 2) inappropriate testing against baseline values, 3) excessive and undisclosed multiple testing and “p-value hacking,” 4) mishandling of clustering in cluster randomized trials, 5) misconceptions about nonparametric tests, 6) mishandling of missing data, 7) miscalculation of effect sizes, 8) ignoring regression to the mean, 9) ignoring confirmation bias, and 10) insufficient statistical reporting. We hope that discussion of these errors can improve the quality of obesity research by helping researchers to implement proper statistical practice and to know when to seek the help of a statistician. PMID:27028280

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

The Effects of Classic and Web-Designed Conceptual Change Texts on the Subject of Water Chemistry

ERIC Educational Resources Information Center

Tas, Erol; Gülen, Salih; Öner, Zeynep; Özyürek, Cengiz

2015-01-01

The purpose of this study is to research the effects of traditional and web-assisted conceptual change texts for the subject of water chemistry on the success, conceptual errors and permanent learning of students. A total of 37 8th graders in a secondary school of Samsun participated in this study which had a random experimental design with…

The Psychological Effect of Errors in Standardized Language Test Items on EFL Students' Responses to the Following Item

ERIC Educational Resources Information Center

Khaksefidi, Saman

2017-01-01

This study investigates the psychological effect of a wrong question with wrong items on answering to the next question in a test of structure. Forty students selected through stratified random sampling are given 15 questions of a standardized test namely a TOEFL structure test in which questions number 7 and number 11 are wrong and their answers…

Validity of the Omron HJ-112 pedometer during treadmill walking.

PubMed

Hasson, Rebecca E; Haller, Jeannie; Pober, David M; Staudenmayer, John; Freedson, Patty S

2009-04-01

The purpose of this investigation was to examine the validity of step counts measured with the Omron HJ-112 pedometer and to assess the effect of pedometer placement. Ninety-two subjects (44 males and 48 females; 71 with body mass index [BMI] <30 kg.m and 21 with BMI >or=30 kg.m) completed three, 12-min bouts of treadmill walking at speeds of 1.12, 1.34, and 1.56 mxs. A subset (21 males and 23 females; 38 BMI <30 kg.m and 6 BMI >or=30 kg.m) completed a variable walking condition. For all conditions, participants wore an Omron HJ-112 pedometer on the hip, in the pants pocket, in the chest shirt pocket, and around the neck. Hip pedometer placement was alternated between right and left sides with the Yamax Digiwalker SW-701. During each walk, an investigator recorded actual steps with a manual hand counter. There was no substantial bias with the Omron in any speed condition (-0.1% to 0.5%). Bias was larger with the Yamax (-3.6% to 2.0%). The largest random error for the Omron was 3.7% in the variable-speed condition for the BMI <30 kg.m group, whereas random errors for the Yamax were larger and up to 20%. None of the Omron placement positions produced statistically significant bias. Hip mounting produced the smallest random error (1.2%), followed by shirt pocket (1.7%), neck (2.2%), and pants pocket (5.8%). The Omron HJ-112 pedometer validly assesses steps in different BMI groups during constant- and variable-speed walking; other than that in the pants pocket, placement of the pedometer has little effect on validity.

Classification of echolocation clicks from odontocetes in the Southern California Bight.

PubMed

Roch, Marie A; Klinck, Holger; Baumann-Pickering, Simone; Mellinger, David K; Qui, Simon; Soldevilla, Melissa S; Hildebrand, John A

2011-01-01

This study presents a system for classifying echolocation clicks of six species of odontocetes in the Southern California Bight: Visually confirmed bottlenose dolphins, short- and long-beaked common dolphins, Pacific white-sided dolphins, Risso's dolphins, and presumed Cuvier's beaked whales. Echolocation clicks are represented by cepstral feature vectors that are classified by Gaussian mixture models. A randomized cross-validation experiment is designed to provide conditions similar to those found in a field-deployed system. To prevent matched conditions from inappropriately lowering the error rate, echolocation clicks associated with a single sighting are never split across the training and test data. Sightings are randomly permuted before assignment to folds in the experiment. This allows different combinations of the training and test data to be used while keeping data from each sighting entirely in the training or test set. The system achieves a mean error rate of 22% across 100 randomized three-fold cross-validation experiments. Four of the six species had mean error rates lower than the overall mean, with the presumed Cuvier's beaked whale clicks showing the best performance (<2% error rate). Long-beaked common and bottlenose dolphins proved the most difficult to classify, with mean error rates of 53% and 68%, respectively.

Extension of sonic anemometry to high subsonic Mach number flows

NASA Astrophysics Data System (ADS)

Otero, R.; Lowe, K. T.; Ng, W. F.

2017-03-01

In the literature, the application of sonic anemometry has been limited to low subsonic Mach number, near-incompressible flow conditions. To the best of the authors’ knowledge, this paper represents the first time a sonic anemometry approach has been used to characterize flow velocity beyond Mach 0.3. Using a high speed jet, flow velocity was measured using a modified sonic anemometry technique in flow conditions up to Mach 0.83. A numerical study was conducted to identify the effects of microphone placement on the accuracy of the measured velocity. Based on estimated error strictly due to uncertainty in time-of-acoustic flight, a random error of +/- 4 m s-1 was identified for the configuration used in this experiment. Comparison with measurements from a Pitot probe indicated a velocity RMS error of +/- 9 m s-1. The discrepancy in error is attributed to a systematic error which may be calibrated out in future work. Overall, the experimental results from this preliminary study support the use of acoustics for high subsonic flow characterization.

Characterization of the International Linear Collider damping ring optics

NASA Astrophysics Data System (ADS)

Shanks, J.; Rubin, D. L.; Sagan, D.

2014-10-01

A method is presented for characterizing the emittance dilution and dynamic aperture for an arbitrary closed lattice that includes guide field magnet errors, multipole errors and misalignments. This method, developed and tested at the Cornell Electron Storage Ring Test Accelerator (CesrTA), has been applied to the damping ring lattice for the International Linear Collider (ILC). The effectiveness of beam based emittance tuning is limited by beam position monitor (BPM) measurement errors, number of corrector magnets and their placement, and correction algorithm. The specifications for damping ring magnet alignment, multipole errors, number of BPMs, and precision in BPM measurements are shown to be consistent with the required emittances and dynamic aperture. The methodology is then used to determine the minimum number of position monitors that is required to achieve the emittance targets, and how that minimum depends on the location of the BPMs. Similarly, the maximum tolerable multipole errors are evaluated. Finally, the robustness of each BPM configuration with respect to random failures is explored.

The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis

PubMed Central

2014-01-01

Background The Health Information Technology for Economic and Clinical Health (HITECH) Act subsidizes implementation by hospitals of electronic health records with computerized provider order entry (CPOE), which may reduce patient injuries caused by medication errors (preventable adverse drug events, pADEs). Effects on pADEs have not been rigorously quantified, and effects on medication errors have been variable. The objectives of this analysis were to assess the effectiveness of CPOE at reducing pADEs in hospital-related settings, and examine reasons for heterogeneous effects on medication errors. Methods Articles were identified using MEDLINE, Cochrane Library, Econlit, web-based databases, and bibliographies of previous systematic reviews (September 2013). Eligible studies compared CPOE with paper-order entry in acute care hospitals, and examined diverse pADEs or medication errors. Studies on children or with limited event-detection methods were excluded. Two investigators extracted data on events and factors potentially associated with effectiveness. We used random effects models to pool data. Results Sixteen studies addressing medication errors met pooling criteria; six also addressed pADEs. Thirteen studies used pre-post designs. Compared with paper-order entry, CPOE was associated with half as many pADEs (pooled risk ratio (RR) = 0.47, 95% CI 0.31 to 0.71) and medication errors (RR = 0.46, 95% CI 0.35 to 0.60). Regarding reasons for heterogeneous effects on medication errors, five intervention factors and two contextual factors were sufficiently reported to support subgroup analyses or meta-regression. Differences between commercial versus homegrown systems, presence and sophistication of clinical decision support, hospital-wide versus limited implementation, and US versus non-US studies were not significant, nor was timing of publication. Higher baseline rates of medication errors predicted greater reductions (P < 0.001). Other context and implementation variables were seldom reported. Conclusions In hospital-related settings, implementing CPOE is associated with a greater than 50% decline in pADEs, although the studies used weak designs. Decreases in medication errors are similar and robust to variations in important aspects of intervention design and context. This suggests that CPOE implementation, as subsidized under the HITECH Act, may benefit public health. More detailed reporting of the context and process of implementation could shed light on factors associated with greater effectiveness. PMID:24894078

A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes

Treesearch

Andrew D. Richardson; David Y. Hollinger; George G. Burba; Kenneth J. Davis; Lawrence B. Flanagan; Gabriel G. Katul; J. William Munger; Daniel M. Ricciuto; Paul C. Stoy; Andrew E. Suyker; Shashi B. Verma; Steven C. Wofsy; Steven C. Wofsy

2006-01-01

Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the ``true?? flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include ``tall tower?? instrumentation), one grassland site, and one...

Far field beam pattern of one MW combined beam of laser diode array amplifiers for space power transmission

NASA Technical Reports Server (NTRS)

Kwon, Jin H.; Lee, Ja H.

1989-01-01

The far-field beam pattern and the power-collection efficiency are calculated for a multistage laser-diode-array amplifier consisting of about 200,000 5-W laser diode arrays with random distributions of phase and orientation errors and random diode failures. From the numerical calculation it is found that the far-field beam pattern is little affected by random failures of up to 20 percent of the laser diodes with reference of 80 percent receiving efficiency in the center spot. The random differences in phases among laser diodes due to probable manufacturing errors is allowed to about 0.2 times the wavelength. The maximum allowable orientation error is about 20 percent of the diffraction angle of a single laser diode aperture (about 1 cm). The preliminary results indicate that the amplifier could be used for space beam-power transmission with an efficiency of about 80 percent for a moderate-size (3-m-diameter) receiver placed at a distance of less than 50,000 km.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Induced mood and selective attention.

PubMed

Brand, N; Verspui, L; Oving, A

1997-04-01

Subjects (N = 60) were randomly assigned to an elated, depressed, or neutral mood-induction condition to assess the effect of mood state on cognitive functioning. In the elated condition film fragments expressing happiness and euphoria were shown. In the depressed condition some frightening and distressing film fragments were presented. The neutral group watched no film. Mood states were measured using the Profile of Mood States, and a Stroop task assessed selective attention. Both were presented by computer. The induction groups differed significantly in the expected direction on the mood subscales Anger, Tension, Depression, Vigour, and Fatigue, and also in the mean scale response times, i.e., slower responses for the depressed condition and faster for the elated one. Differences between conditions were found in the errors on the Stroop: in the depressed condition were the fewest errors and significantly longer error reaction times. Speed of error was associated with self-reported fatigue.

Using multivariate generalizability theory to assess the effect of content stratification on the reliability of a performance assessment.

PubMed

Keller, Lisa A; Clauser, Brian E; Swanson, David B

2010-12-01

In recent years, demand for performance assessments has continued to grow. However, performance assessments are notorious for lower reliability, and in particular, low reliability resulting from task specificity. Since reliability analyses typically treat the performance tasks as randomly sampled from an infinite universe of tasks, these estimates of reliability may not be accurate. For tests built according to a table of specifications, tasks are randomly sampled from different strata (content domains, skill areas, etc.). If these strata remain fixed in the test construction process, ignoring this stratification in the reliability analysis results in an underestimate of "parallel forms" reliability, and an overestimate of the person-by-task component. This research explores the effect of representing and misrepresenting the stratification appropriately in estimation of reliability and the standard error of measurement. Both multivariate and univariate generalizability studies are reported. Results indicate that the proper specification of the analytic design is essential in yielding the proper information both about the generalizability of the assessment and the standard error of measurement. Further, illustrative D studies present the effect under a variety of situations and test designs. Additional benefits of multivariate generalizability theory in test design and evaluation are also discussed.

On the Hedges Correction for a "t"-Test

ERIC Educational Resources Information Center

VanHoudnos, Nathan M.; Greenhouse, Joel B.

2016-01-01

When cluster randomized experiments are analyzed as if units were independent, test statistics for treatment effects can be anticonservative. Hedges proposed a correction for such tests by scaling them to control their Type I error rate. This article generalizes the Hedges correction from a posttest-only experimental design to more common designs…

NON-RANDOM CELL KILLING IN CRYOPRESERVATION: IMPLICATIONS FOR PERFORMANCE OF THE BATTERY OF LEUKOCYTE TESTS (BLT) - I. TOXIC AND IMMUNOTOXIC EFFECTS

EPA Science Inventory

To eliminate between-tests error in longitudinal studies, for specimen sharing, convenient scheduling, etc., it is necessary to freeze freshly separated leukocytes as well as non-transformed, continuous T lymphocyte (CTL) lines. o test the efficacy of a programmable reezer (tempe...

On the Determinants of the Conjunction Fallacy: Probability versus Inductive Confirmation

ERIC Educational Resources Information Center

Tentori, Katya; Crupi, Vincenzo; Russo, Selena

2013-01-01

Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such…

Inadequate Self-Discipline as a Causal Factor in Human Error Accidents

DTIC Science & Technology

1991-03-01

reasons for the effectiveness of the stimuli or incentives used are unknown. Moreover, Gebers and Peck (1987) conclude on the basis of a random sample...Research. 13, 141-156. 234 Gebers , M. A., & Peck, R. C. (1987). Basic California traffic conviction and accident record facts. (Report No. CAL-DMV- RSS

Bias analysis applied to Agricultural Health Study publications to estimate non-random sources of uncertainty.

PubMed

Lash, Timothy L

2007-11-26

The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a qualitative description of study limitations. The latter approach is likely to lead to overconfidence regarding the potential for causal associations, whereas the former safeguards against such overinterpretations. Furthermore, such analyses, once programmed, allow rapid implementation of alternative assignments of probability distributions to the bias parameters, so elevate the plane of discussion regarding study bias from characterizing studies as "valid" or "invalid" to a critical and quantitative discussion of sources of uncertainty.

Physical layer one-time-pad data encryption through synchronized semiconductor laser networks

NASA Astrophysics Data System (ADS)

Argyris, Apostolos; Pikasis, Evangelos; Syvridis, Dimitris

2016-02-01

Semiconductor lasers (SL) have been proven to be a key device in the generation of ultrafast true random bit streams. Their potential to emit chaotic signals under conditions with desirable statistics, establish them as a low cost solution to cover various needs, from large volume key generation to real-time encrypted communications. Usually, only undemanding post-processing is needed to convert the acquired analog timeseries to digital sequences that pass all established tests of randomness. A novel architecture that can generate and exploit these true random sequences is through a fiber network in which the nodes are semiconductor lasers that are coupled and synchronized to central hub laser. In this work we show experimentally that laser nodes in such a star network topology can synchronize with each other through complex broadband signals that are the seed to true random bit sequences (TRBS) generated at several Gb/s. The potential for each node to access real-time generated and synchronized with the rest of the nodes random bit streams, through the fiber optic network, allows to implement an one-time-pad encryption protocol that mixes the synchronized true random bit sequence with real data at Gb/s rates. Forward-error correction methods are used to reduce the errors in the TRBS and the final error rate at the data decoding level. An appropriate selection in the sampling methodology and properties, as well as in the physical properties of the chaotic seed signal through which network locks in synchronization, allows an error free performance.

A randomized trial comparing INR monitoring devices in patients with anticoagulation self-management: evaluation of a novel error-grid approach.

PubMed

Hemkens, Lars G; Hilden, Kristian M; Hartschen, Stephan; Kaiser, Thomas; Didjurgeit, Ulrike; Hansen, Roland; Bender, Ralf; Sawicki, Peter T

2008-08-01

In addition to the metrological quality of international normalized ratio (INR) monitoring devices used in patients' self-management of long-term anticoagulation, the effectiveness of self-monitoring with such devices has to be evaluated under real-life conditions with a focus on clinical implications. An approach to evaluate the clinical significance of inaccuracies is the error-grid analysis as already established in self-monitoring of blood glucose. Two anticoagulation monitors were compared in a real-life setting and a novel error-grid instrument for oral anticoagulation has been evaluated. In a randomized crossover study 16 patients performed self-management of anticoagulation using the INRatio and the CoaguChek S system. Main outcome measures were clinically relevant INR differences according to established criteria and to the error-grid approach. A lower rate of clinically relevant disagreements according to Anderson's criteria was found with CoaguChek S than with INRatio without statistical significance (10.77% vs. 12.90%; P = 0.787). Using the error-grid we found principally consistent results: More measurement pairs with discrepancies of no or low clinical relevance were found with CoaguChek S, whereas with INRatio we found more differences with a moderate clinical relevance. A high rate of patients' satisfaction with both of the point of care devices was found with only marginal differences. A principal appropriateness of the investigated point-of-care devices to adequately monitor the INR is shown. The error-grid is useful for comparing monitoring methods with a focus on clinical relevance under real-life conditions beyond assessing the pure metrological quality, but we emphasize that additional trials using this instrument with larger patient populations are needed to detect differences in clinically relevant disagreements.

An Emprical Point Error Model for Tls Derived Point Clouds

NASA Astrophysics Data System (ADS)

Ozendi, Mustafa; Akca, Devrim; Topan, Hüseyin

2016-06-01

The random error pattern of point clouds has significant effect on the quality of final 3D model. The magnitude and distribution of random errors should be modelled numerically. This work aims at developing such an anisotropic point error model, specifically for the terrestrial laser scanner (TLS) acquired 3D point clouds. A priori precisions of basic TLS observations, which are the range, horizontal angle and vertical angle, are determined by predefined and practical measurement configurations, performed at real-world test environments. A priori precision of horizontal (𝜎𝜃) and vertical (𝜎𝛼) angles are constant for each point of a data set, and can directly be determined through the repetitive scanning of the same environment. In our practical tests, precisions of the horizontal and vertical angles were found as 𝜎𝜃=±36.6𝑐𝑐 and 𝜎𝛼=±17.8𝑐𝑐, respectively. On the other hand, a priori precision of the range observation (𝜎𝜌) is assumed to be a function of range, incidence angle of the incoming laser ray, and reflectivity of object surface. Hence, it is a variable, and computed for each point individually by employing an empirically developed formula varying as 𝜎𝜌=±2-12 𝑚𝑚 for a FARO Focus X330 laser scanner. This procedure was followed by the computation of error ellipsoids of each point using the law of variance-covariance propagation. The direction and size of the error ellipsoids were computed by the principal components transformation. The usability and feasibility of the model was investigated in real world scenarios. These investigations validated the suitability and practicality of the proposed method.

Geometric Accuracy Analysis of Worlddem in Relation to AW3D30, Srtm and Aster GDEM2

NASA Astrophysics Data System (ADS)

Bayburt, S.; Kurtak, A. B.; Büyüksalih, G.; Jacobsen, K.

2017-05-01

In a project area close to Istanbul the quality of WorldDEM, AW3D30, SRTM DSM and ASTER GDEM2 have been analyzed in relation to a reference aerial LiDAR DEM and to each other. The random and the systematic height errors have been separated. The absolute offset for all height models in X, Y and Z is within the expectation. The shifts have been respected in advance for a satisfying estimation of the random error component. All height models are influenced by some tilts, different in size. In addition systematic deformations can be seen not influencing the standard deviation too much. The delivery of WorldDEM includes information about the height error map which is based on the interferometric phase errors, and the number and location of coverage's from different orbits. A dependency of the height accuracy from the height error map information and the number of coverage's can be seen, but it is smaller as expected. WorldDEM is more accurate as the other investigated height models and with 10 m point spacing it includes more morphologic details, visible at contour lines. The morphologic details are close to the details based on the LiDAR digital surface model (DSM). As usual a dependency of the accuracy from the terrain slope can be seen. In forest areas the canopy definition of InSAR X- and C-band height models as well as for the height models based on optical satellite images is not the same as the height definition by LiDAR. In addition the interferometric phase uncertainty over forest areas is larger. Both effects lead to lower height accuracy in forest areas, also visible in the height error map.

A predictability study of Lorenz's 28-variable model as a dynamical system

NASA Technical Reports Server (NTRS)

Krishnamurthy, V.

1993-01-01

The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

Liquid Medication Dosing Errors by Hispanic Parents: Role of Health Literacy and English Proficiency

PubMed Central

Harris, Leslie M.; Dreyer, Benard; Mendelsohn, Alan; Bailey, Stacy C.; Sanders, Lee M.; Wolf, Michael S.; Parker, Ruth M.; Patel, Deesha A.; Kim, Kwang Youn A.; Jimenez, Jessica J.; Jacobson, Kara; Smith, Michelle; Yin, H. Shonna

2016-01-01

Objective Hispanic parents in the US are disproportionately affected by low health literacy and limited English proficiency (LEP). We examined associations between health literacy, LEP, and liquid medication dosing errors in Hispanic parents. Methods Cross-sectional analysis of data from a multisite randomized controlled experiment to identify best practices for the labeling/dosing of pediatric liquid medications (SAFE Rx for Kids study); 3 urban pediatric clinics. Analyses were limited to Hispanic parents of children <8 years, with health literacy and LEP data (n=1126). Parents were randomized to 5 groups that varied by pairing of units of measurement on the label/dosing tool. Each parent measured 9 doses [3 amounts (2.5,5,7.5 mL) using 3 tools (2 syringes (0.2,0.5 mL increment), 1 cup)] in random order. Dependent variable: Dosing error=>20% dose deviation. Predictor variables: health literacy (Newest Vital Sign) [limited=0–3; adequate=4–6], LEP (speaks English less than “very well”). Results 83.1% made dosing errors (mean(SD) errors/parent=2.2(1.9)). Parents with limited health literacy and LEP had the greatest odds of making a dosing error compared to parents with adequate health literacy who were English proficient (% trials with errors/parent=28.8 vs. 12.9%; AOR=2.2[1.7–2.8]). Parents with limited health literacy who were English proficient were also more likely to make errors (% trials with errors/parent=18.8%; AOR=1.4[1.1–1.9]). Conclusion Dosing errors are common among Hispanic parents; those with both LEP and limited health literacy are at particular risk. Further study is needed to examine how the redesign of medication labels and dosing tools could reduce literacy and language-associated disparities in dosing errors. PMID:28477800

Combinatorial neural codes from a mathematical coding theory perspective.

PubMed

Curto, Carina; Itskov, Vladimir; Morrison, Katherine; Roth, Zachary; Walker, Judy L

2013-07-01

Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes do not support accurate error correction, although the error-correcting performance of receptive field codes catches up to that of random comparison codes when a small tolerance to error is introduced. However, receptive field codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Regression dilution bias: tools for correction methods and sample size calculation.

PubMed

Berglund, Lars

2012-08-01

Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

[Ultrasonic scissors. New vs resterilized instruments].

PubMed

Gärtner, D; Münz, K; Hückelheim, E; Hesse, U

2008-02-01

The aim of this study was to compare reliability in handling and function of resterilized and single-use disposable ultrasonic scissors. In a prospective randomized study, the surgeon blindly tested new and resterilized ultrasonographic scissors. The parameters were force of activation, cutting effect, coagulation effect, error messages, and disturbing generator noise. Fifty-one new and 49 resterilized instruments in 94 operations were evaluated. The differences in force of activation, cutting effect, and coagulation were not significant. Error messages and disturbing noises were rare in both groups. Six new instruments and two resterilized instruments had to be exchanged because of problems during surgery. This study demonstrates comparable reliability in function and handling of resterilized and new ultrasonic scissors. The use of resterilized instruments leads to distinctly reduced costs and could contribute to efficiency in laparoscopic surgery.

Effects of Random Shadings, Phasing Errors, and Element Failures on the Beam Patterns of Linear and Planar Arrays

DTIC Science & Technology

1980-03-14

failure Sigmar (Or) in line 50, the standard deviation of the relative error of the weights Sigmap (o) in line 60, the standard deviation of the phase...200, the weight structures in the x and y coordinates Q in line 210, the probability of element failure Sigmar (Or) in line 220, the standard...NUMBER OF ELEMENTS =u;2*H 120 PRINT "Pr’obability of elemenit failure al;O 130 PRINT "Standard dtvi&t ion’ oe r.1&tive ýrror of wl; Sigmar 14 0 PRINT

The (mis)reporting of statistical results in psychology journals.

PubMed

Bakker, Marjan; Wicherts, Jelte M

2011-09-01

In order to study the prevalence, nature (direction), and causes of reporting errors in psychology, we checked the consistency of reported test statistics, degrees of freedom, and p values in a random sample of high- and low-impact psychology journals. In a second study, we established the generality of reporting errors in a random sample of recent psychological articles. Our results, on the basis of 281 articles, indicate that around 18% of statistical results in the psychological literature are incorrectly reported. Inconsistencies were more common in low-impact journals than in high-impact journals. Moreover, around 15% of the articles contained at least one statistical conclusion that proved, upon recalculation, to be incorrect; that is, recalculation rendered the previously significant result insignificant, or vice versa. These errors were often in line with researchers' expectations. We classified the most common errors and contacted authors to shed light on the origins of the errors.

Pricing Employee Stock Options (ESOs) with Random Lattice

NASA Astrophysics Data System (ADS)

Chendra, E.; Chin, L.; Sukmana, A.

2018-04-01

Employee Stock Options (ESOs) are stock options granted by companies to their employees. Unlike standard options that can be traded by typical institutional or individual investors, employees cannot sell or transfer their ESOs to other investors. The sale restrictions may induce the ESO’s holder to exercise them earlier. In much cited paper, Hull and White propose a binomial lattice in valuing ESOs which assumes that employees will exercise voluntarily their ESOs if the stock price reaches a horizontal psychological barrier. Due to nonlinearity errors, the numerical pricing results oscillate significantly so they may lead to large pricing errors. In this paper, we use the random lattice method to price the Hull-White ESOs model. This method can reduce the nonlinearity error by aligning a layer of nodes of the random lattice with a psychological barrier.

The influence of random element displacement on DOA estimates obtained with (Khatri-Rao-)root-MUSIC.

PubMed

Inghelbrecht, Veronique; Verhaevert, Jo; van Hecke, Tanja; Rogier, Hendrik

2014-11-11

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri-Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case.

OROS-methylphenidate efficacy on specific executive functioning deficits in adults with ADHD: a randomized, placebo-controlled cross-over study.

PubMed

Bron, Tannetje I; Bijlenga, Denise; Boonstra, A Marije; Breuk, Minda; Pardoen, Willem F H; Beekman, Aartjan T F; Kooij, J J Sandra

2014-04-01

Attention-deficit/hyperactivity disorder (ADHD) is linked to impaired executive functioning (EF). This is the first study to objectively investigate the effects of a long-acting methylphenidate on neurocognitive test performance of adults with ADHD. Twenty-two adults with ADHD participated in a 6-weeks study examining the effect of osmotic-release oral system methylphenidate (OROS-mph) on continuous performance tests (CPTs; objective measures), and on the self-reported ADHD rating scale (subjective measure) using a randomized, double-blind, placebo-controlled cross-over design. OROS-mph significantly improved reaction time variability (RTV), commission errors (CE) and d-prime (DP) as compared to baseline (Cohen's d>.50), but did not affect hit reaction time (HRT) or omission errors (OE). Compared to placebo, OROS-mph only significantly influenced RTV on one of two CPTs (p<.050). Linear regression analyses showed predictive ability of more beneficial OROS-mph effects in ADHD patients with higher EF severity (RTV: β=.670, t=2.097, p=.042; omission errors (OE): β=-.098, t=-4.759, p<.001), and with more severe ADHD symptoms (RTV: F=6.363, p=.019; HRT: F=3.914, p=.061). Side effects rates were substantially but non-significantly greater for OROS-mph compared to placebo (77% vs. 46%, p=.063). OROS-mph effects indicated RTV as the most sensitive parameter for measuring both neuropsychological and behavioral deficits in adults with ADHD. These findings suggest RTV as an endophenotypic parameter for ADHD symptomatology, and propose CPTs as an objective method for monitoring methylphenidate titration. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

A technique for reducing patient setup uncertainties by aligning and verifying daily positioning of a moving tumor using implanted fiducials

PubMed Central

Balter, Peter; Morice, Rodolfo C.; Choi, Bum; Kudchadker, Rajat J.; Bucci, Kara; Chang, Joe Y.; Dong, Lei; Tucker, Susan; Vedam, Sastry; Briere, Tina; Starkschall, George

2008-01-01

This study aimed to validate and implement a methodology in which fiducials implanted in the periphery of lung tumors can be used to reduce uncertainties in tumor location. Alignment software that matches marker positions on two‐dimensional (2D) kilovoltage portal images to positions on three‐dimensional (3D) computed tomography data sets was validated using static and moving phantoms. This software also was used to reduce uncertainties in tumor location in a patient with fiducials implanted in the periphery of a lung tumor. Alignment of fiducial locations in orthogonal projection images with corresponding fiducial locations in 3D data sets can position both static and moving phantoms with an accuracy of 1 mm. In a patient, alignment based on fiducial locations reduced systematic errors in the left–right direction by 3 mm and random errors by 2 mm, and random errors in the superior–inferior direction by 3 mm as measured by anterior–posterior cine images. Software that matches fiducial markers on 2D and 3D images is effective for aligning both static and moving fiducials before treatment and can be implemented to reduce patient setup uncertainties. PACS number: 81.40.Wx

Identifying treatment effect heterogeneity in clinical trials using subpopulations of events: STEPP.

PubMed

Lazar, Ann A; Bonetti, Marco; Cole, Bernard F; Yip, Wai-Ki; Gelber, Richard D

2016-04-01

Investigators conducting randomized clinical trials often explore treatment effect heterogeneity to assess whether treatment efficacy varies according to patient characteristics. Identifying heterogeneity is central to making informed personalized healthcare decisions. Treatment effect heterogeneity can be investigated using subpopulation treatment effect pattern plot (STEPP), a non-parametric graphical approach that constructs overlapping patient subpopulations with varying values of a characteristic. Procedures for statistical testing using subpopulation treatment effect pattern plot when the endpoint of interest is survival remain an area of active investigation. A STEPP analysis was used to explore patterns of absolute and relative treatment effects for varying levels of a breast cancer biomarker, Ki-67, in the phase III Breast International Group 1-98 randomized clinical trial, comparing letrozole to tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer. Absolute treatment effects were measured by differences in 4-year cumulative incidence of breast cancer recurrence, while relative effects were measured by the subdistribution hazard ratio in the presence of competing risks using O-E (observed-minus-expected) methodology, an intuitive non-parametric method. While estimation of hazard ratio values based on O-E methodology has been shown, a similar development for the subdistribution hazard ratio has not. Furthermore, we observed that the subpopulation treatment effect pattern plot analysis may not produce results, even with 100 patients within each subpopulation. After further investigation through simulation studies, we observed inflation of the type I error rate of the traditional test statistic and sometimes singular variance-covariance matrix estimates that may lead to results not being produced. This is due to the lack of sufficient number of events within the subpopulations, which we refer to as instability of the subpopulation treatment effect pattern plot analysis. We introduce methodology designed to improve stability of the subpopulation treatment effect pattern plot analysis and generalize O-E methodology to the competing risks setting. Simulation studies were designed to assess the type I error rate of the tests for a variety of treatment effect measures, including subdistribution hazard ratio based on O-E estimation. This subpopulation treatment effect pattern plot methodology and standard regression modeling were used to evaluate heterogeneity of Ki-67 in the Breast International Group 1-98 randomized clinical trial. We introduce methodology that generalizes O-E methodology to the competing risks setting and that improves stability of the STEPP analysis by pre-specifying the number of events across subpopulations while controlling the type I error rate. The subpopulation treatment effect pattern plot analysis of the Breast International Group 1-98 randomized clinical trial showed that patients with high Ki-67 percentages may benefit most from letrozole, while heterogeneity was not detected using standard regression modeling. The STEPP methodology can be used to study complex patterns of treatment effect heterogeneity, as illustrated in the Breast International Group 1-98 randomized clinical trial. For the subpopulation treatment effect pattern plot analysis, we recommend a minimum of 20 events within each subpopulation. © The Author(s) 2015.

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

PubMed

Blaya, J A; Shin, S S; Yale, G; Suarez, C; Asencios, L; Contreras, C; Rodriguez, P; Kim, J; Cegielski, P; Fraser, H S F

2010-08-01

To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P < 0.001, OR 0.13, 95%CI 0.07-0.24), than control HCs. Preventing missing results through online viewing accounted for at least 72% of all errors. e-Chasqui users sent on average three electronic error reports per week to the laboratories. e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

[Exploration of the concept of genetic drift in genetics teaching of undergraduates].

PubMed

Wang, Chun-ming

2016-01-01

Genetic drift is one of the difficulties in teaching genetics due to its randomness and probability which could easily cause conceptual misunderstanding. The “sampling error" in its definition is often misunderstood because of the research method of “sampling", which disturbs the results and causes the random changes in allele frequency. I analyzed and compared the definitions of genetic drift in domestic and international genetic textbooks, and found that the definitions containing “sampling error" are widely adopted but are interpreted correctly in only a few textbooks. Here, the history of research on genetic drift, i.e., the contributions of Wright, Fisher and Kimura, is introduced. Moreover, I particularly describe two representative articles recently published about genetic drift teaching of undergraduates, which point out that misconceptions are inevitable for undergraduates during the studying process and also provide a preliminary solution. Combined with my own teaching practice, I suggest that the definition of genetic drift containing “sampling error" can be adopted with further interpretation, i.e., “sampling error" is random sampling among gametes when generating the next generation of alleles which is equivalent to a random sampling of all gametes participating in mating in gamete pool and has no relationship with artificial sampling in general genetics studies. This article may provide some help in genetics teaching.

Unitary n -designs via random quenches in atomic Hubbard and spin models: Application to the measurement of Rényi entropies

NASA Astrophysics Data System (ADS)

Vermersch, B.; Elben, A.; Dalmonte, M.; Cirac, J. I.; Zoller, P.

2018-02-01

We present a general framework for the generation of random unitaries based on random quenches in atomic Hubbard and spin models, forming approximate unitary n -designs, and their application to the measurement of Rényi entropies. We generalize our protocol presented in Elben et al. [Phys. Rev. Lett. 120, 050406 (2018), 10.1103/PhysRevLett.120.050406] to a broad class of atomic and spin-lattice models. We further present an in-depth numerical and analytical study of experimental imperfections, including the effect of decoherence and statistical errors, and discuss connections of our approach with many-body quantum chaos.

Critical side channel effects in random bit generation with multiple semiconductor lasers in a polarization-based quantum key distribution system.

PubMed

Ko, Heasin; Choi, Byung-Seok; Choe, Joong-Seon; Kim, Kap-Joong; Kim, Jong-Hoi; Youn, Chun Ju

2017-08-21

Most polarization-based BB84 quantum key distribution (QKD) systems utilize multiple lasers to generate one of four polarization quantum states randomly. However, random bit generation with multiple lasers can potentially open critical side channels that significantly endangers the security of QKD systems. In this paper, we show unnoticed side channels of temporal disparity and intensity fluctuation, which possibly exist in the operation of multiple semiconductor laser diodes. Experimental results show that the side channels can enormously degrade security performance of QKD systems. An important system issue for the improvement of quantum bit error rate (QBER) related with laser driving condition is further addressed with experimental results.

Combined Uncertainty and A-Posteriori Error Bound Estimates for General CFD Calculations: Theory and Software Implementation

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2014-01-01

This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.

Evaluation of Bayesian Sequential Proportion Estimation Using Analyst Labels

NASA Technical Reports Server (NTRS)

Lennington, R. K.; Abotteen, K. M. (Principal Investigator)

1980-01-01

The author has identified the following significant results. A total of ten Large Area Crop Inventory Experiment Phase 3 blind sites and analyst-interpreter labels were used in a study to compare proportional estimates obtained by the Bayes sequential procedure with estimates obtained from simple random sampling and from Procedure 1. The analyst error rate using the Bayes technique was shown to be no greater than that for the simple random sampling. Also, the segment proportion estimates produced using this technique had smaller bias and mean squared errors than the estimates produced using either simple random sampling or Procedure 1.

Multilevel Models for Intensive Longitudinal Data with Heterogeneous Autoregressive Errors: The Effect of Misspecification and Correction with Cholesky Transformation

PubMed Central

Jahng, Seungmin; Wood, Phillip K.

2017-01-01

Intensive longitudinal studies, such as ecological momentary assessment studies using electronic diaries, are gaining popularity across many areas of psychology. Multilevel models (MLMs) are most widely used analytical tools for intensive longitudinal data (ILD). Although ILD often have individually distinct patterns of serial correlation of measures over time, inferences of the fixed effects, and random components in MLMs are made under the assumption that all variance and autocovariance components are homogenous across individuals. In the present study, we introduced a multilevel model with Cholesky transformation to model ILD with individually heterogeneous covariance structure. In addition, the performance of the transformation method and the effects of misspecification of heterogeneous covariance structure were investigated through a Monte Carlo simulation. We found that, if individually heterogeneous covariances are incorrectly assumed as homogenous independent or homogenous autoregressive, MLMs produce highly biased estimates of the variance of random intercepts and the standard errors of the fixed intercept and the fixed effect of a level 2 covariate when the average autocorrelation is high. For intensive longitudinal data with individual specific residual covariance, the suggested transformation method showed lower bias in those estimates than the misspecified models when the number of repeated observations within individuals is 50 or more. PMID:28286490

Modeling and Prediction of Solvent Effect on Human Skin Permeability using Support Vector Regression and Random Forest.

PubMed

Baba, Hiromi; Takahara, Jun-ichi; Yamashita, Fumiyoshi; Hashida, Mitsuru

2015-11-01

The solvent effect on skin permeability is important for assessing the effectiveness and toxicological risk of new dermatological formulations in pharmaceuticals and cosmetics development. The solvent effect occurs by diverse mechanisms, which could be elucidated by efficient and reliable prediction models. However, such prediction models have been hampered by the small variety of permeants and mixture components archived in databases and by low predictive performance. Here, we propose a solution to both problems. We first compiled a novel large database of 412 samples from 261 structurally diverse permeants and 31 solvents reported in the literature. The data were carefully screened to ensure their collection under consistent experimental conditions. To construct a high-performance predictive model, we then applied support vector regression (SVR) and random forest (RF) with greedy stepwise descriptor selection to our database. The models were internally and externally validated. The SVR achieved higher performance statistics than RF. The (externally validated) determination coefficient, root mean square error, and mean absolute error of SVR were 0.899, 0.351, and 0.268, respectively. Moreover, because all descriptors are fully computational, our method can predict as-yet unsynthesized compounds. Our high-performance prediction model offers an attractive alternative to permeability experiments for pharmaceutical and cosmetic candidate screening and optimizing skin-permeable topical formulations.

Impact of monetary incentives on cognitive performance and error monitoring following sleep deprivation.

PubMed

Hsieh, Shulan; Li, Tzu-Hsien; Tsai, Ling-Ling

2010-04-01

To examine whether monetary incentives attenuate the negative effects of sleep deprivation on cognitive performance in a flanker task that requires higher-level cognitive-control processes, including error monitoring. Twenty-four healthy adults aged 18 to 23 years were randomly divided into 2 subject groups: one received and the other did not receive monetary incentives for performance accuracy. Both subject groups performed a flanker task and underwent electroencephalographic recordings for event-related brain potentials after normal sleep and after 1 night of total sleep deprivation in a within-subject, counterbalanced, repeated-measures study design. Monetary incentives significantly enhanced the response accuracy and reaction time variability under both normal sleep and sleep-deprived conditions, and they reduced the effects of sleep deprivation on the subjective effort level, the amplitude of the error-related negativity (an error-related event-related potential component), and the latency of the P300 (an event-related potential variable related to attention processes). However, monetary incentives could not attenuate the effects of sleep deprivation on any measures of behavior performance, such as the response accuracy, reaction time variability, or posterror accuracy adjustments; nor could they reduce the effects of sleep deprivation on the amplitude of the Pe, another error-related event-related potential component. This study shows that motivation incentives selectively reduce the effects of total sleep deprivation on some brain activities, but they cannot attenuate the effects of sleep deprivation on performance decrements in tasks that require high-level cognitive-control processes. Thus, monetary incentives and sleep deprivation may act through both common and different mechanisms to affect cognitive performance.

The Systematics of Strong Lens Modeling Quantified: The Effects of Constraint Selection and Redshift Information on Magnification, Mass, and Multiple Image Predictability

NASA Astrophysics Data System (ADS)

Johnson, Traci L.; Sharon, Keren

2016-11-01

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.

A path planning method used in fluid jet polishing eliminating lightweight mirror imprinting effect

NASA Astrophysics Data System (ADS)

Li, Wenzong; Fan, Bin; Shi, Chunyan; Wang, Jia; Zhuo, Bin

2014-08-01

With the development of space technology, the design of optical system tends to large aperture lightweight mirror with high dimension-thickness ratio. However, when the lightweight mirror PV value is less than λ/10 , the surface will show wavy imprinting effect obviously. Imprinting effect introduced by head-tool pressure has become a technological barrier in high-precision lightweight mirror manufacturing. Fluid jet polishing can exclude outside pressure. Presently, machining tracks often used are grating type path, screw type path and pseudo-random path. On the edge of imprinting error, the speed of adjacent path points changes too fast, which causes the machine hard to reflect quickly, brings about new path error, and increases the polishing time due to superfluous path. This paper presents a new planning path method to eliminate imprinting effect. Simulation results show that the path of the improved grating path can better eliminate imprinting effect compared to the general path.

Serial position effects in semantic memory: reconstructing the order of verses of hymns.

PubMed

Maylor, Elizabeth A

2002-12-01

Serial position effects (primacy and recency) have been consistently demonstrated in both short- and long-term episodic memory tasks. The search for corresponding effects in semantic memory tasks (e.g., reconstructing the order of U.S. presidents) has been confounded by factors such as differential exposure to stimuli. In the present study, the stimuli were six-verse hymns that would have been sung from the first to the last verse by churchgoers on numerous occasions. Participants were presented with the verses of each hymn in random order and were required to reconstruct the correct order. Primacy and recency effects were significantly more evident for churchgoers than for nonchurchgoers. Moreover, error gradients were steeper than chance for churchgoers but not for nonchurchgoers; in other words, churchgoers' errors were more likely to be close to the correct position than further away. These findings provide the first unequivocal demonstration of serial position effects in semantic memory.

The effects of transcutaneous electrical nerve stimulation on joint position sense in patients with knee joint osteoarthritis.

PubMed

Shirazi, Zahra Rojhani; Shafaee, Razieh; Abbasi, Leila

2014-10-01

To study the effects of transcutaneous electrical nerve stimulation (TENS) on joint position sense (JPS) in knee osteoarthritis (OA) subjects. Thirty subjects with knee OA (40-60 years old) using non-random sampling participated in this study. In order to evaluate the absolute error of repositioning of the knee joint, Qualysis Track Manager system was used and sensory electrical stimulation was applied through the TENS device. The mean errors in repositioning of the joint, in two position of the knee joint with 20 and 60 degree angle, after applying the TENS was significantly decreased (p < 0.05). Application of TENS in subjects with knee OA could improve JPS in these subjects.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine.

PubMed

Howard, Jeremy T; Ashwell, Melissa S; Baynes, Ronald E; Brooks, James D; Yeatts, James L; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs ( n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

PubMed Central

Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study. PMID:29487615

Evaluation of drug administration errors in a teaching hospital

PubMed Central

2012-01-01

Background Medication errors can occur at any of the three steps of the medication use process: prescribing, dispensing and administration. We aimed to determine the incidence, type and clinical importance of drug administration errors and to identify risk factors. Methods Prospective study based on disguised observation technique in four wards in a teaching hospital in Paris, France (800 beds). A pharmacist accompanied nurses and witnessed the preparation and administration of drugs to all patients during the three drug rounds on each of six days per ward. Main outcomes were number, type and clinical importance of errors and associated risk factors. Drug administration error rate was calculated with and without wrong time errors. Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects. Results Twenty-eight nurses caring for 108 patients were observed. Among 1501 opportunities for error, 415 administrations (430 errors) with one or more errors were detected (27.6%). There were 312 wrong time errors, ten simultaneously with another type of error, resulting in an error rate without wrong time error of 7.5% (113/1501). The most frequently administered drugs were the cardiovascular drugs (425/1501, 28.3%). The highest risks of error in a drug administration were for dermatological drugs. No potentially life-threatening errors were witnessed and 6% of errors were classified as having a serious or significant impact on patients (mainly omission). In multivariate analysis, the occurrence of errors was associated with drug administration route, drug classification (ATC) and the number of patient under the nurse's care. Conclusion Medication administration errors are frequent. The identification of its determinants helps to undertake designed interventions. PMID:22409837

Evaluation of drug administration errors in a teaching hospital.

PubMed

Berdot, Sarah; Sabatier, Brigitte; Gillaizeau, Florence; Caruba, Thibaut; Prognon, Patrice; Durieux, Pierre

2012-03-12

Medication errors can occur at any of the three steps of the medication use process: prescribing, dispensing and administration. We aimed to determine the incidence, type and clinical importance of drug administration errors and to identify risk factors. Prospective study based on disguised observation technique in four wards in a teaching hospital in Paris, France (800 beds). A pharmacist accompanied nurses and witnessed the preparation and administration of drugs to all patients during the three drug rounds on each of six days per ward. Main outcomes were number, type and clinical importance of errors and associated risk factors. Drug administration error rate was calculated with and without wrong time errors. Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects. Twenty-eight nurses caring for 108 patients were observed. Among 1501 opportunities for error, 415 administrations (430 errors) with one or more errors were detected (27.6%). There were 312 wrong time errors, ten simultaneously with another type of error, resulting in an error rate without wrong time error of 7.5% (113/1501). The most frequently administered drugs were the cardiovascular drugs (425/1501, 28.3%). The highest risks of error in a drug administration were for dermatological drugs. No potentially life-threatening errors were witnessed and 6% of errors were classified as having a serious or significant impact on patients (mainly omission). In multivariate analysis, the occurrence of errors was associated with drug administration route, drug classification (ATC) and the number of patient under the nurse's care. Medication administration errors are frequent. The identification of its determinants helps to undertake designed interventions.

Gene-targeted Random Mutagenesis to Select Heterochromatin-destabilizing Proteasome Mutants in Fission Yeast.

PubMed

Seo, Hogyu David; Lee, Daeyoup

2018-05-15

Random mutagenesis of a target gene is commonly used to identify mutations that yield the desired phenotype. Of the methods that may be used to achieve random mutagenesis, error-prone PCR is a convenient and efficient strategy for generating a diverse pool of mutants (i.e., a mutant library). Error-prone PCR is the method of choice when a researcher seeks to mutate a pre-defined region, such as the coding region of a gene while leaving other genomic regions unaffected. After the mutant library is amplified by error-prone PCR, it must be cloned into a suitable plasmid. The size of the library generated by error-prone PCR is constrained by the efficiency of the cloning step. However, in the fission yeast, Schizosaccharomyces pombe, the cloning step can be replaced by the use of a highly efficient one-step fusion PCR to generate constructs for transformation. Mutants of desired phenotypes may then be selected using appropriate reporters. Here, we describe this strategy in detail, taking as an example, a reporter inserted at centromeric heterochromatin.

Smooth empirical Bayes estimation of observation error variances in linear systems

NASA Technical Reports Server (NTRS)

Martz, H. F., Jr.; Lian, M. W.

1972-01-01

A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

The accuracy of the measurements in Ulugh Beg's star catalogue

NASA Astrophysics Data System (ADS)

Krisciunas, K.

1992-12-01

The star catalogue compiled by Ulugh Beg and his collaborators in Samarkand (ca. 1437) is the only catalogue primarily based on original observations between the times of Ptolemy and Tycho Brahe. Evans (1987) has given convincing evidence that Ulugh Beg's star catalogue was based on measurements made with a zodiacal armillary sphere graduated to 15(') , with interpolation to 0.2 units. He and Shevchenko (1990) were primarily interested in the systematic errors in ecliptic longitude. Shevchenko's analysis of the random errors was limited to the twelve zodiacal constellations. We have analyzed all 843 ecliptic longitudes and latitudes attributed to Ulugh Beg by Knobel (1917). This required multiplying all the longitude errors by the respective values of the cosine of the celestial latitudes. We find a random error of +/- 17minp 7 for ecliptic longitude and +/- 16minp 5 for ecliptic latitude. On the whole, the random errors are largest near the ecliptic, decreasing towards the ecliptic poles. For all of Ulugh Beg's measurements (excluding outliers) the mean systematic error is -10minp 8 +/- 0minp 8 for ecliptic longitude and 7minp 5 +/- 0minp 7 for ecliptic latitude, with the errors in the sense ``computed minus Ulugh Beg''. For the brighter stars (those designated alpha , beta , and gamma in the respective constellations), the mean systematic errors are -11minp 3 +/- 1minp 9 for ecliptic longitude and 9minp 4 +/- 1minp 5 for ecliptic latitude. Within the errors this matches the systematic error in both coordinates for alpha Vir. With greater confidence we may conclude that alpha Vir was the principal reference star in the catalogues of Ulugh Beg and Ptolemy. Evans, J. 1987, J. Hist. Astr. 18, 155. Knobel, E. B. 1917, Ulugh Beg's Catalogue of Stars, Washington, D. C.: Carnegie Institution. Shevchenko, M. 1990, J. Hist. Astr. 21, 187.

MO-FG-CAMPUS-JeP3-01: A Statistical Model for Analyzing the Rotational Error of Single Iso-Center Technique

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

Chang, J; Dept of Radiation Oncology, New York Weill Cornell Medical Ctr, New York, NY

Purpose: To develop a generalized statistical model that incorporates the treatment uncertainty from the rotational error of single iso-center technique, and calculate the additional PTV (planning target volume) margin required to compensate for this error. Methods: The random vectors for setup and additional rotation errors in the three-dimensional (3D) patient coordinate system were assumed to follow the 3D independent normal distribution with zero mean, and standard deviations σx, σy, σz, for setup error and a uniform σR for rotational error. Both random vectors were summed, normalized and transformed to the spherical coordinates to derive the chi distribution with 3 degreesmore » of freedom for the radical distance ρ. PTV margin was determined using the critical value of this distribution for 0.05 significant level so that 95% of the time the treatment target would be covered by ρ. The additional PTV margin required to compensate for the rotational error was calculated as a function of σx, σy, σz and σR. Results: The effect of the rotational error is more pronounced for treatments that requires high accuracy/precision like stereotactic radiosurgery (SRS) or stereotactic body radiotherapy (SBRT). With a uniform 2mm PTV margin (or σx =σy=σz=0.7mm), a σR=0.32mm will decrease the PTV coverage from 95% to 90% of the time, or an additional 0.2mm PTV margin is needed to prevent this loss of coverage. If we choose 0.2 mm as the threshold, any σR>0.3mm will lead to an additional PTV margin that cannot be ignored, and the maximal σR that can be ignored is 0.0064 rad (or 0.37°) for iso-to-target distance=5cm, or 0.0032 rad (or 0.18°) for iso-to-target distance=10cm. Conclusions: The rotational error cannot be ignored for high-accuracy/-precision treatments like SRS/SBRT, particularly when the distance between the iso-center and target is large.« less

A Fast and On-Machine Measuring System Using the Laser Displacement Sensor for the Contour Parameters of the Drill Pipe Thread.

PubMed

Dong, Zhixu; Sun, Xingwei; Chen, Changzheng; Sun, Mengnan

2018-04-13

The inconvenient loading and unloading of a long and heavy drill pipe gives rise to the difficulty in measuring the contour parameters of its threads at both ends. To solve this problem, in this paper we take the SCK230 drill pipe thread-repairing machine tool as a carrier to design and achieve a fast and on-machine measuring system based on a laser probe. This system drives a laser displacement sensor to acquire the contour data of a certain axial section of the thread by using the servo function of a CNC machine tool. To correct the sensor's measurement errors caused by the measuring point inclination angle, an inclination error model is built to compensate data in real time. To better suppress random error interference and ensure real contour information, a new wavelet threshold function is proposed to process data through the wavelet threshold denoising. Discrete data after denoising is segmented according to the geometrical characteristics of the drill pipe thread, and the regression model of the contour data in each section is fitted by using the method of weighted total least squares (WTLS). Then, the thread parameters are calculated in real time to judge the processing quality. Inclination error experiments show that the proposed compensation model is accurate and effective, and it can improve the data acquisition accuracy of a sensor. Simulation results indicate that the improved threshold function is of better continuity and self-adaptability, which makes sure that denoising effects are guaranteed, and, meanwhile, the complete elimination of real data distorted in random errors is avoided. Additionally, NC50 thread-testing experiments show that the proposed on-machine measuring system can complete the measurement of a 25 mm thread in 7.8 s, with a measurement accuracy of ±8 μm and repeatability limit ≤ 4 μm (high repeatability), and hence the accuracy and efficiency of measurement are both improved.

A Fast and On-Machine Measuring System Using the Laser Displacement Sensor for the Contour Parameters of the Drill Pipe Thread

PubMed Central

Sun, Xingwei; Chen, Changzheng; Sun, Mengnan

2018-01-01

The inconvenient loading and unloading of a long and heavy drill pipe gives rise to the difficulty in measuring the contour parameters of its threads at both ends. To solve this problem, in this paper we take the SCK230 drill pipe thread-repairing machine tool as a carrier to design and achieve a fast and on-machine measuring system based on a laser probe. This system drives a laser displacement sensor to acquire the contour data of a certain axial section of the thread by using the servo function of a CNC machine tool. To correct the sensor’s measurement errors caused by the measuring point inclination angle, an inclination error model is built to compensate data in real time. To better suppress random error interference and ensure real contour information, a new wavelet threshold function is proposed to process data through the wavelet threshold denoising. Discrete data after denoising is segmented according to the geometrical characteristics of the drill pipe thread, and the regression model of the contour data in each section is fitted by using the method of weighted total least squares (WTLS). Then, the thread parameters are calculated in real time to judge the processing quality. Inclination error experiments show that the proposed compensation model is accurate and effective, and it can improve the data acquisition accuracy of a sensor. Simulation results indicate that the improved threshold function is of better continuity and self-adaptability, which makes sure that denoising effects are guaranteed, and, meanwhile, the complete elimination of real data distorted in random errors is avoided. Additionally, NC50 thread-testing experiments show that the proposed on-machine measuring system can complete the measurement of a 25 mm thread in 7.8 s, with a measurement accuracy of ±8 μm and repeatability limit ≤ 4 μm (high repeatability), and hence the accuracy and efficiency of measurement are both improved. PMID:29652836

The Effects of Acute Dopamine Precursor Depletion on the Cognitive Control Functions of Performance Monitoring and Conflict Processing: An Event-Related Potential (ERP) Study.

PubMed

Larson, Michael J; Clayson, Peter E; Primosch, Mark; Leyton, Marco; Steffensen, Scott C

2015-01-01

Studies using medications and psychiatric populations implicate dopamine in cognitive control and performance monitoring processes. However, side effects associated with medication or studying psychiatric groups may confound the relationship between dopamine and cognitive control. To circumvent such possibilities, we utilized a randomized, double-blind, placebo-controlled, within-subjects design wherein participants were administered a nutritionally-balanced amino acid mixture (BAL) and an amino acid mixture deficient in the dopamine precursors tyrosine (TYR) and phenylalanine (PHE) on two separate occasions. Order of sessions was randomly assigned. Cognitive control and performance monitoring were assessed using response times (RT), error rates, the N450, an event-related potential (ERP) index of conflict monitoring, the conflict slow potential (conflict SP), an ERP index of conflict resolution, and the error-related negativity (ERN) and error positivity (Pe), ERPs associated with performance monitoring. Participants were twelve males who completed a Stroop color-word task while ERPs were collected four hours following acute PHE and TYR depletion (APTD) or balanced (BAL) mixture ingestion in two separate sessions. N450 and conflict SP ERP amplitudes significantly differentiated congruent from incongruent trials, but did not differ as a function of APTD or BAL mixture ingestion. Similarly, ERN and Pe amplitudes showed significant differences between error and correct trials that were not different between APTD and BAL conditions. Findings indicate that acute dopamine precursor depletion does not significantly alter cognitive control and performance monitoring ERPs. Current results do not preclude the role of dopamine in these processes, but suggest that multiple methods for dopamine-related hypothesis testing are needed.

Effect of inventory method on niche models: random versus systematic error

Treesearch

Heather E. Lintz; Andrew N. Gray; Bruce McCune

2013-01-01

Data from large-scale biological inventories are essential for understanding and managing Earth's ecosystems. The Forest Inventory and Analysis Program (FIA) of the U.S. Forest Service is the largest biological inventory in North America; however, the FIA inventory recently changed from an amalgam of different approaches to a nationally-standardized approach in...

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…

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian, Yudong

2011-01-01

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Sloppy-slotted ALOHA

NASA Technical Reports Server (NTRS)

Crozier, Stewart N.

1990-01-01

Random access signaling, which allows slotted packets to spill over into adjacent slots, is investigated. It is shown that sloppy-slotted ALOHA can always provide higher throughput than conventional slotted ALOHA. The degree of improvement depends on the timing error distribution. Throughput performance is presented for Gaussian timing error distributions, modified to include timing error corrections. A general channel capacity lower bound, independent of the specific timing error distribution, is also presented.

Model studies of the beam-filling error for rain-rate retrieval with microwave radiometers

NASA Technical Reports Server (NTRS)

Ha, Eunho; North, Gerald R.

1995-01-01

Low-frequency (less than 20 GHz) single-channel microwave retrievals of rain rate encounter the problem of beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of the rain field. This means that one may not simply insert the area average of the brightness temperature into the formula for rain rate without incurring both bias and random error. The statistical heterogeneity of the rain-rate field in the footprint of the instrument is key to determining the nature of these errors. This paper makes use of a series of random rain-rate fields to study the size of the bias and random error associated with beam filling. A number of examples are analyzed in detail: the binomially distributed field, the gamma, the Gaussian, the mixed gamma, the lognormal, and the mixed lognormal ('mixed' here means there is a finite probability of no rain rate at a point of space-time). Of particular interest are the applicability of a simple error formula due to Chiu and collaborators and a formula that might hold in the large field of view limit. It is found that the simple formula holds for Gaussian rain-rate fields but begins to fail for highly skewed fields such as the mixed lognormal. While not conclusively demonstrated here, it is suggested that the notionof climatologically adjusting the retrievals to remove the beam-filling bias is a reasonable proposition.

Technical Note: Millimeter precision in ultrasound based patient positioning: Experimental quantification of inherent technical limitations

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

Ballhausen, Hendrik, E-mail: hendrik.ballhausen@med.uni-muenchen.de; Hieber, Sheila; Li, Minglun

2014-08-15

Purpose: To identify the relevant technical sources of error of a system based on three-dimensional ultrasound (3D US) for patient positioning in external beam radiotherapy. To quantify these sources of error in a controlled laboratory setting. To estimate the resulting end-to-end geometric precision of the intramodality protocol. Methods: Two identical free-hand 3D US systems at both the planning-CT and the treatment room were calibrated to the laboratory frame of reference. Every step of the calibration chain was repeated multiple times to estimate its contribution to overall systematic and random error. Optimal margins were computed given the identified and quantified systematicmore » and random errors. Results: In descending order of magnitude, the identified and quantified sources of error were: alignment of calibration phantom to laser marks 0.78 mm, alignment of lasers in treatment vs planning room 0.51 mm, calibration and tracking of 3D US probe 0.49 mm, alignment of stereoscopic infrared camera to calibration phantom 0.03 mm. Under ideal laboratory conditions, these errors are expected to limit ultrasound-based positioning to an accuracy of 1.05 mm radially. Conclusions: The investigated 3D ultrasound system achieves an intramodal accuracy of about 1 mm radially in a controlled laboratory setting. The identified systematic and random errors require an optimal clinical tumor volume to planning target volume margin of about 3 mm. These inherent technical limitations do not prevent clinical use, including hypofractionation or stereotactic body radiation therapy.« less

Statistical characterization of fluctuations of a laser beam transmitted through a random air-water interface: new results from a laboratory experiment

NASA Astrophysics Data System (ADS)

Majumdar, Arun K.; Land, Phillip; Siegenthaler, John

2014-10-01

New results for characterizing laser intensity fluctuation statistics of a laser beam transmitted through a random air-water interface relevant to underwater communications are presented. A laboratory watertank experiment is described to investigate the beam wandering effects of the transmitted beam. Preliminary results from the experiment provide information about histograms of the probability density functions of intensity fluctuations for different wind speeds measured by a CMOS camera for the transmitted beam. Angular displacements of the centroids of the fluctuating laser beam generates the beam wander effects. This research develops a probabilistic model for optical propagation at the random air-water interface for a transmission case under different wind speed conditions. Preliminary results for bit-error-rate (BER) estimates as a function of fade margin for an on-off keying (OOK) optical communication through the air-water interface are presented for a communication system where a random air-water interface is a part of the communication channel.

Discrepancy-based error estimates for Quasi-Monte Carlo III. Error distributions and central limits

NASA Astrophysics Data System (ADS)

Hoogland, Jiri; Kleiss, Ronald

1997-04-01

In Quasi-Monte Carlo integration, the integration error is believed to be generally smaller than in classical Monte Carlo with the same number of integration points. Using an appropriate definition of an ensemble of quasi-random point sets, we derive various results on the probability distribution of the integration error, which can be compared to the standard Central Limit Theorem for normal stochastic sampling. In many cases, a Gaussian error distribution is obtained.

A preliminary taxonomy of medical errors in family practice

PubMed Central

Dovey, S; Meyers, D; Phillips, R; Green, L; Fryer, G; Galliher, J; Kappus, J; Grob, P

2002-01-01

Objective: To develop a preliminary taxonomy of primary care medical errors. Design: Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. Setting: The National Network for Family Practice and Primary Care Research. Participants: Family physicians. Main outcome measures: Medical error category, context, and consequence. Results: Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failures (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. Conclusions: This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors. PMID:12486987

A preliminary taxonomy of medical errors in family practice.

PubMed

Dovey, S M; Meyers, D S; Phillips, R L; Green, L A; Fryer, G E; Galliher, J M; Kappus, J; Grob, P

2002-09-01

To develop a preliminary taxonomy of primary care medical errors. Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. The National Network for Family Practice and Primary Care Research. Family physicians. Medical error category, context, and consequence. Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failure (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors.

A vignette study to examine health care professionals' attitudes towards patient involvement in error prevention.

PubMed

Schwappach, David L B; Frank, Olga; Davis, Rachel E

2013-10-01

Various authorities recommend the participation of patients in promoting patient safety, but little is known about health care professionals' (HCPs') attitudes towards patients' involvement in safety-related behaviours. To investigate how HCPs evaluate patients' behaviours and HCP responses to patient involvement in the behaviour, relative to different aspects of the patient, the involved HCP and the potential error. Cross-sectional fractional factorial survey with seven factors embedded in two error scenarios (missed hand hygiene, medication error). Each survey included two randomized vignettes that described the potential error, a patient's reaction to that error and the HCP response to the patient. Twelve hospitals in Switzerland. A total of 1141 HCPs (response rate 45%). Approval of patients' behaviour, HCP response to the patient, anticipated effects on the patient-HCP relationship, HCPs' support for being asked the question, affective response to the vignettes. Outcomes were measured on 7-point scales. Approval of patients' safety-related interventions was generally high and largely affected by patients' behaviour and correct identification of error. Anticipated effects on the patient-HCP relationship were much less positive, little correlated with approval of patients' behaviour and were mainly determined by the HCP response to intervening patients. HCPs expressed more favourable attitudes towards patients intervening about a medication error than about hand sanitation. This study provides the first insights into predictors of HCPs' attitudes towards patient engagement in safety. Future research is however required to assess the generalizability of the findings into practice before training can be designed to address critical issues. © 2012 John Wiley & Sons Ltd.

Measures of rowing performance.

PubMed

Smith, T Brett; Hopkins, Will G

2012-04-01

Accurate measures of performance are important for assessing competitive athletes in practi~al and research settings. We present here a review of rowing performance measures, focusing on the errors in these measures and the implications for testing rowers. The yardstick for assessing error in a performance measure is the random variation (typical or standard error of measurement) in an elite athlete's competitive performance from race to race: ∼1.0% for time in 2000 m rowing events. There has been little research interest in on-water time trials for assessing rowing performance, owing to logistic difficulties and environmental perturbations in performance time with such tests. Mobile ergometry via instrumented oars or rowlocks should reduce these problems, but the associated errors have not yet been reported. Measurement of boat speed to monitor on-water training performance is common; one device based on global positioning system (GPS) technology contributes negligible extra random error (0.2%) in speed measured over 2000 m, but extra error is substantial (1-10%) with other GPS devices or with an impeller, especially over shorter distances. The problems with on-water testing have led to widespread use of the Concept II rowing ergometer. The standard error of the estimate of on-water 2000 m time predicted by 2000 m ergometer performance was 2.6% and 7.2% in two studies, reflecting different effects of skill, body mass and environment in on-water versus ergometer performance. However, well trained rowers have a typical error in performance time of only ∼0.5% between repeated 2000 m time trials on this ergometer, so such trials are suitable for tracking changes in physiological performance and factors affecting it. Many researchers have used the 2000 m ergometer performance time as a criterion to identify other predictors of rowing performance. Standard errors of the estimate vary widely between studies even for the same predictor, but the lowest errors (~1-2%) have been observed for peak power output in an incremental test, some measures of lactate threshold and measures of 30-second all-out power. Some of these measures also have typical error between repeated tests suitably low for tracking changes. Combining measures via multiple linear regression needs further investigation. In summary, measurement of boat speed, especially with a good GPS device, has adequate precision for monitoring training performance, but adjustment for environmental effects needs to be investigated. Time trials on the Concept II ergometer provide accurate estimates of a rower's physiological ability to output power, and some submaximal and brief maximal ergometer performance measures can be used frequently to monitor changes in this ability. On-water performance measured via instrumented skiffs that determine individual power output may eventually surpass measures derived from the Concept II.

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Lundquist, J. D.; Clark, M. P.

2015-07-01

Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.

Excitation of transverse dipole and quadrupole modes in a pure ion plasma in a linear Paul trap to study collective processes in intense beams

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

Gilson, Erik P.; Davidson, Ronald C.; Efthimion, Philip C.

Transverse dipole and quadrupole modes have been excited in a one-component cesium ion plasma trapped in the Paul Trap Simulator Experiment (PTSX) in order to characterize their properties and understand the effect of their excitation on equivalent long-distance beam propagation. The PTSX device is a compact laboratory Paul trap that simulates the transverse dynamics of a long, intense charge bunch propagating through an alternating-gradient transport system by putting the physicist in the beam's frame of reference. A pair of arbitrary function generators was used to apply trapping voltage waveform perturbations with a range of frequencies and, by changing which electrodesmore » were driven with the perturbation, with either a dipole or quadrupole spatial structure. The results presented in this paper explore the dependence of the perturbation voltage's effect on the perturbation duration and amplitude. Perturbations were also applied that simulate the effect of random lattice errors that exist in an accelerator with quadrupole magnets that are misaligned or have variance in their field strength. The experimental results quantify the growth in the equivalent transverse beam emittance that occurs due to the applied noise and demonstrate that the random lattice errors interact with the trapped plasma through the plasma's internal collective modes. Coherent periodic perturbations were applied to simulate the effects of magnet errors in circular machines such as storage rings. The trapped one component plasma is strongly affected when the perturbation frequency is commensurate with a plasma mode frequency. The experimental results, which help to understand the physics of quiescent intense beam propagation over large distances, are compared with analytic models.« less

SU-E-J-119: What Effect Have the Volume Defined in the Alignment Clipbox for Cervical Cancer Using Automatic Registration Methods for Cone- Beam CT Verification?

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

Wang, W; Yang, H; Wang, Y

2014-06-01

Purpose: To investigate the impact of different clipbox volumes with automated registration techniques using commercially available software with on board volumetric imaging(OBI) for treatment verification in cervical cancer patients. Methods: Fifty cervical cancer patients received daily CBCT scans(on-board imaging v1.5 system, Varian Medical Systems) during the first treatment week and weekly thereafter were included this analysis. A total of 450 CBCT scans were registered to the planning CTscan using pelvic clipbox(clipbox-Pelvic) and around PTV clip box(clipbox- PTV). The translations(anterior-posterior, left-right, superior-inferior) and the rotations(yaw, pitch and roll) errors for each matches were recorded. The setup errors and the systematic andmore » random errors for both of the clip-boxes were calculated. Paired Samples t test was used to analysis the differences between clipbox-Pelvic and clipbox-PTV. Results: . The SD of systematic error(σ) was 1.0mm, 2.0mm,3.2mm and 1.9mm,2.3mm, 3.0mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. The average random error(Σ)was 1.7mm, 2.0mm,4.2mm and 1.7mm,3.4mm, 4.4mm in the AP, LR and SI directions for clipbox-Pelvic and clipbox-PTV, respectively. But, only the SI direction was acquired significantly differences between two image registration volumes(p=0.002,p=0.01 for mean and SD). For rotations, the yaw mean/SD and the pitch SD were acquired significantly differences between clipbox-Pelvic and clipbox-PTV. Conclusion: The defined volume for Image registration is important for cervical cancer when 3D/3D match was used. The alignment clipbox can effect the setup errors obtained. Further analysis is need to determine the optimal defined volume to use the image registration in cervical cancer. Conflict of interest: none.« less

Accuracy of indirect estimation of power output from uphill performance in cycling.

PubMed

Millet, Grégoire P; Tronche, Cyrille; Grappe, Frédéric

2014-09-01

To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

On the apparent insignificance of the randomness of flexible joints on large space truss dynamics

NASA Technical Reports Server (NTRS)

Koch, R. M.; Klosner, J. M.

1993-01-01

Deployable periodic large space structures have been shown to exhibit high dynamic sensitivity to period-breaking imperfections and uncertainties. These can be brought on by manufacturing or assembly errors, structural imperfections, as well as nonlinear and/or nonconservative joint behavior. In addition, the necessity of precise pointing and position capability can require the consideration of these usually negligible and unknown parametric uncertainties and their effect on the overall dynamic response of large space structures. This work describes the use of a new design approach for the global dynamic solution of beam-like periodic space structures possessing parametric uncertainties. Specifically, the effect of random flexible joints on the free vibrations of simply-supported periodic large space trusses is considered. The formulation is a hybrid approach in terms of an extended Timoshenko beam continuum model, Monte Carlo simulation scheme, and first-order perturbation methods. The mean and mean-square response statistics for a variety of free random vibration problems are derived for various input random joint stiffness probability distributions. The results of this effort show that, although joint flexibility has a substantial effect on the modal dynamic response of periodic large space trusses, the effect of any reasonable uncertainty or randomness associated with these joint flexibilities is insignificant.

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 Automatic Quality Control Pipeline for High-Throughput Screening Hit Identification.

PubMed

Zhai, Yufeng; Chen, Kaisheng; Zhong, Yang; Zhou, Bin; Ainscow, Edward; Wu, Ying-Ta; Zhou, Yingyao

2016-09-01

The correction or removal of signal errors in high-throughput screening (HTS) data is critical to the identification of high-quality lead candidates. Although a number of strategies have been previously developed to correct systematic errors and to remove screening artifacts, they are not universally effective and still require fair amount of human intervention. We introduce a fully automated quality control (QC) pipeline that can correct generic interplate systematic errors and remove intraplate random artifacts. The new pipeline was first applied to ~100 large-scale historical HTS assays; in silico analysis showed auto-QC led to a noticeably stronger structure-activity relationship. The method was further tested in several independent HTS runs, where QC results were sampled for experimental validation. Significantly increased hit confirmation rates were obtained after the QC steps, confirming that the proposed method was effective in enriching true-positive hits. An implementation of the algorithm is available to the screening community. © 2016 Society for Laboratory Automation and Screening.

Effects of Mesh Irregularities on Accuracy of Finite-Volume Discretization Schemes

NASA Technical Reports Server (NTRS)

Diskin, Boris; Thomas, James L.

2012-01-01

The effects of mesh irregularities on accuracy of unstructured node-centered finite-volume discretizations are considered. The focus is on an edge-based approach that uses unweighted least-squares gradient reconstruction with a quadratic fit. For inviscid fluxes, the discretization is nominally third order accurate on general triangular meshes. For viscous fluxes, the scheme is an average-least-squares formulation that is nominally second order accurate and contrasted with a common Green-Gauss discretization scheme. Gradient errors, truncation errors, and discretization errors are separately studied according to a previously introduced comprehensive methodology. The methodology considers three classes of grids: isotropic grids in a rectangular geometry, anisotropic grids typical of adapted grids, and anisotropic grids over a curved surface typical of advancing layer grids. The meshes within the classes range from regular to extremely irregular including meshes with random perturbation of nodes. Recommendations are made concerning the discretization schemes that are expected to be least sensitive to mesh irregularities in applications to turbulent flows in complex geometries.

Horizontal plane localization in single-sided deaf adults fitted with a bone-anchored hearing aid (Baha).

PubMed

Grantham, D Wesley; Ashmead, Daniel H; Haynes, David S; Hornsby, Benjamin W Y; Labadie, Robert F; Ricketts, Todd A

2012-01-01

: One purpose of this investigation was to evaluate the effect of a unilateral bone-anchored hearing aid (Baha) on horizontal plane localization performance in single-sided deaf adults who had either a conductive or sensorineural hearing loss in their impaired ear. The use of a 33-loudspeaker array allowed for a finer response measure than has previously been used to investigate localization in this population. In addition, a detailed analysis of error patterns allowed an evaluation of the contribution of random error and bias error to the total rms error computed in the various conditions studied. A second purpose was to investigate the effect of stimulus duration and head-turning on localization performance. : Two groups of single-sided deaf adults were tested in a localization task in which they had to identify the direction of a spoken phrase on each trial. One group had a sensorineural hearing loss (SNHL group; N = 7), and the other group had a conductive hearing loss (CHL group; N = 5). In addition, a control group of four normal-hearing adults was tested. The spoken phrase was either 1250 msec in duration (a male saying "Where am I coming from now?") or 341 msec in duration (the same male saying "Where?"). For the longer-duration phrase, subjects were tested in conditions in which they either were or were not allowed to move their heads before the termination of the phrase. The source came from one of nine positions in the front horizontal plane (from -79° to +79°). The response range included 33 choices (from -90° to +90°, separated by 5.6°). Subjects were tested in all stimulus conditions, both with and without the Baha device. Overall rms error was computed for each condition. Contributions of random error and bias error to the overall error were also computed. : There was considerable intersubject variability in all conditions. However, for the CHL group, the average overall error was significantly smaller when the Baha was on than when it was off. Further analysis of error patterns indicated that this improvement was primarily based on reduced response bias when the device was on; that is, the average response azimuth was nearer to the source azimuth when the device was on than when it was off. The SNHL group, on the other hand, had significantly greater overall error when the Baha was on than when it was off. Collapsed across listening conditions and groups, localization performance was significantly better with the 1250 msec stimulus than with the 341 msec stimulus. However, for the longer-duration stimulus, there was no significant beneficial effect of head-turning. Error scores in all conditions for both groups were considerably larger than those in the normal-hearing control group. : On average, single-sided deaf adults with CHL showed improved localization ability when using the Baha, whereas single-sided deaf adults with SNHL showed a decrement in performance when using the device. These results may have implications for clinical counseling for patients with unilateral hearing impairment.

A confirmation of the general relativistic prediction of the Lense-Thirring effect.

PubMed

Ciufolini, I; Pavlis, E C

2004-10-21

An important early prediction of Einstein's general relativity was the advance of the perihelion of Mercury's orbit, whose measurement provided one of the classical tests of Einstein's theory. The advance of the orbital point-of-closest-approach also applies to a binary pulsar system and to an Earth-orbiting satellite. General relativity also predicts that the rotation of a body like Earth will drag the local inertial frames of reference around it, which will affect the orbit of a satellite. This Lense-Thirring effect has hitherto not been detected with high accuracy, but its detection with an error of about 1 per cent is the main goal of Gravity Probe B--an ongoing space mission using orbiting gyroscopes. Here we report a measurement of the Lense-Thirring effect on two Earth satellites: it is 99 +/- 5 per cent of the value predicted by general relativity; the uncertainty of this measurement includes all known random and systematic errors, but we allow for a total +/- 10 per cent uncertainty to include underestimated and unknown sources of error.

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

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

The effect of divided attention on novices and experts in laparoscopic task performance.

PubMed

Ghazanfar, Mudassar Ali; Cook, Malcolm; Tang, Benjie; Tait, Iain; Alijani, Afshin

2015-03-01

Attention is important for the skilful execution of surgery. The surgeon's attention during surgery is divided between surgery and outside distractions. The effect of this divided attention has not been well studied previously. We aimed to compare the effect of dividing attention of novices and experts on a laparoscopic task performance. Following ethical approval, 25 novices and 9 expert surgeons performed a standardised peg transfer task in a laboratory setup under three randomly assigned conditions: silent as control condition and two standardised auditory distracting tasks requiring response (easy and difficult) as study conditions. Human reliability assessment was used for surgical task analysis. Primary outcome measures were correct auditory responses, task time, number of surgical errors and instrument movements. Secondary outcome measures included error rate, error probability and hand specific differences. Non-parametric statistics were used for data analysis. 21109 movements and 9036 total errors were analysed. Novices had increased mean task completion time (seconds) (171 ± 44SD vs. 149 ± 34, p < 0.05), number of total movements (227 ± 27 vs. 213 ± 26, p < 0.05) and number of errors (127 ± 51 vs. 96 ± 28, p < 0.05) during difficult study conditions compared to control. The correct responses to auditory stimuli were less frequent in experts (68 %) compared to novices (80 %). There was a positive correlation between error rate and error probability in novices (r (2) = 0.533, p < 0.05) but not in experts (r (2) = 0.346, p > 0.05). Divided attention conditions in theatre environment require careful consideration during surgical training as the junior surgeons are less able to focus their attention during these conditions.

Theory of injection locking and rapid start-up of magnetrons, and effects of manufacturing errors in terahertz traveling wave tubes

NASA Astrophysics Data System (ADS)

Pengvanich, Phongphaeth

In this thesis, several contemporary issues on coherent radiation sources are examined. They include the fast startup and the injection locking of microwave magnetrons, and the effects of random manufacturing errors on phase and small signal gain of terahertz traveling wave amplifiers. In response to the rapid startup and low noise magnetron experiments performed at the University of Michigan that employed periodic azimuthal perturbations in the axial magnetic field, a systematic study of single particle orbits is performed for a crossed electric and periodic magnetic field. A parametric instability in the orbits, which brings a fraction of the electrons from the cathode toward the anode, is discovered. This offers an explanation of the rapid startup observed in the experiments. A phase-locking model has been constructed from circuit theory to qualitatively explain various regimes observed in kilowatt magnetron injection-locking experiments, which were performed at the University of Michigan. These experiments utilize two continuous-wave magnetrons; one functions as an oscillator and the other as a driver. Time and frequency domain solutions are developed from the model, allowing investigations into growth, saturation, and frequency response of the output. The model qualitatively recovers many of the phase-locking frequency characteristics observed in the experiments. Effects of frequency chirp and frequency perturbation on the phase and lockability have also been quantified. Development of traveling wave amplifier operating at terahertz is a subject of current interest. The small circuit size has prompted a statistical analysis of the effects of random fabrication errors on phase and small signal gain of these amplifiers. The small signal theory is treated with a continuum model in which the electron beam is monoenergetic. Circuit perturbations that vary randomly along the beam axis are introduced through the dimensionless Pierce parameters describing the beam-wave velocity mismatch (b), the gain parameter (C), and the cold tube circuit loss ( d). Our study shows that perturbation in b dominates the other two in terms of power gain and phase shift. Extensive data show that standard deviation of the output phase is linearly proportional to standard deviation of the individual perturbations in b, C and d.

Effect of Preoperative Warm-up Exercise Before Laparoscopic Gynecological Surgery: A Randomized Trial.

PubMed

Polterauer, Stephan; Husslein, Heinrich; Kranawetter, Marlene; Schwameis, Richard; Reinthaller, Alexander; Heinze, Georg; Grimm, Christoph

2016-01-01

Laparoscopic surgical procedures require a high level of cognitive and psychomotoric skills. Thus, effective training methods to acquire an adequate level of expertise are crucial. The aim of this study was to investigate the effect of preoperative warm up training on surgeon׳s performance during gynecologic laparoscopic surgery. In this randomized controlled trial, surgeons performed a preoperative warm up training using a virtual reality simulator before laparoscopic unilateral salpingo-oophorectomy. Serving as their own controls, each subject performed 2 pairs of laparoscopic cases, each pair consisting of 1 case with and 1 without warm up before surgery. Surgeries were videotaped and psychomotoric skills were rated using objective structured assessment of technical skills (OSATS) and the generic error rating tool by a masked observer. Perioperative complications were assessed. Statistical analysis was performed using a mixed model, and mean OSATS scores were compared between both the groups. In total, data of 10 surgeons and 17 surgeries were available for analysis. No differences between educational level and surgical experiences were observed between the groups. Mean standard error psychomotoric and task-specific OSATS scores of 19.8 (1.7) and 3.7 (0.2) were observed in the warm up group compared with 18.6 (1.7) and 3.8 (0.2) in the no warm up group, respectively (p = 0.51 and p = 0.29). Using generic error rating tool, the total number of errors was 8.75 (2.15) in the warm up group compared with 10.8 (2.18) in the no warm-up group (p = 0.53). Perioperative complications and operating time did not differ between both the groups. The present study suggests that warm-up before laparoscopic salpingo-oophorectomy does not increase psychomotoric skills during surgery. Moreover, it does not influence operating time and complication rates. (Medical University of Vienna-IRB approval number, 1072/2011, ClinicalTrials.gov number, NCT01712607). Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Numerical Error Estimation with UQ

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Korn, Peter; Marotzke, Jochem

2014-05-01

Ocean models are still in need of means to quantify model errors, which are inevitably made when running numerical experiments. The total model error can formally be decomposed into two parts, the formulation error and the discretization error. The formulation error arises from the continuous formulation of the model not fully describing the studied physical process. The discretization error arises from having to solve a discretized model instead of the continuously formulated model. Our work on error estimation is concerned with the discretization error. Given a solution of a discretized model, our general problem statement is to find a way to quantify the uncertainties due to discretization in physical quantities of interest (diagnostics), which are frequently used in Geophysical Fluid Dynamics. The approach we use to tackle this problem is called the "Goal Error Ensemble method". The basic idea of the Goal Error Ensemble method is that errors in diagnostics can be translated into a weighted sum of local model errors, which makes it conceptually based on the Dual Weighted Residual method from Computational Fluid Dynamics. In contrast to the Dual Weighted Residual method these local model errors are not considered deterministically but interpreted as local model uncertainty and described stochastically by a random process. The parameters for the random process are tuned with high-resolution near-initial model information. However, the original Goal Error Ensemble method, introduced in [1], was successfully evaluated only in the case of inviscid flows without lateral boundaries in a shallow-water framework and is hence only of limited use in a numerical ocean model. Our work consists in extending the method to bounded, viscous flows in a shallow-water framework. As our numerical model, we use the ICON-Shallow-Water model. In viscous flows our high-resolution information is dependent on the viscosity parameter, making our uncertainty measures viscosity-dependent. We will show that we can choose a sensible parameter by using the Reynolds-number as a criteria. Another topic, we will discuss is the choice of the underlying distribution of the random process. This is especially of importance in the scope of lateral boundaries. We will present resulting error estimates for different height- and velocity-based diagnostics applied to the Munk gyre experiment. References [1] F. RAUSER: Error Estimation in Geophysical Fluid Dynamics through Learning; PhD Thesis, IMPRS-ESM, Hamburg, 2010 [2] F. RAUSER, J. MAROTZKE, P. KORN: Ensemble-type numerical uncertainty quantification from single model integrations; SIAM/ASA Journal on Uncertainty Quantification, submitted

The detection of problem analytes in a single proficiency test challenge in the absence of the Health Care Financing Administration rule violations.

PubMed

Cembrowski, G S; Hackney, J R; Carey, N

1993-04-01

The Clinical Laboratory Improvement Act of 1988 (CLIA 88) has dramatically changed proficiency testing (PT) practices having mandated (1) satisfactory PT for certain analytes as a condition of laboratory operation, (2) fixed PT limits for many of these "regulated" analytes, and (3) an increased number of PT specimens (n = 5) for each testing cycle. For many of these analytes, the fixed limits are much broader than the previously employed Standard Deviation Index (SDI) criteria. Paradoxically, there may be less incentive to identify and evaluate analytically significant outliers to improve the analytical process. Previously described "control rules" to evaluate these PT results are unworkable as they consider only two or three results. We used Monte Carlo simulations of Kodak Ektachem analyzers participating in PT to determine optimal control rules for the identification of PT results that are inconsistent with those from other laboratories using the same methods. The analysis of three representative analytes, potassium, creatine kinase, and iron was simulated with varying intrainstrument and interinstrument standard deviations (si and sg, respectively) obtained from the College of American Pathologists (Northfield, Ill) Quality Assurance Services data and Proficiency Test data, respectively. Analytical errors were simulated in each of the analytes and evaluated in terms of multiples of the interlaboratory SDI. Simple control rules for detecting systematic and random error were evaluated with power function graphs, graphs of probability of error detected vs magnitude of error. Based on the simulation results, we recommend screening all analytes for the occurrence of two or more observations exceeding the same +/- 1 SDI limit. For any analyte satisfying this condition, the mean of the observations should be calculated. For analytes with sg/si ratios between 1.0 and 1.5, a significant systematic error is signaled by the mean exceeding 1.0 SDI. Significant random error is signaled by one observation exceeding the +/- 3-SDI limit or the range of the observations exceeding 4 SDIs. For analytes with higher sg/si, significant systematic or random error is signaled by violation of the screening rule (having at least two observations exceeding the same +/- 1 SDI limit). Random error can also be signaled by one observation exceeding the +/- 1.5-SDI limit or the range of the observations exceeding 3 SDIs. We present a practical approach to the workup of apparent PT errors.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research-A Behavioral Study.

PubMed

Furlan, Leonardo; Sterr, Annette

2018-01-01

Motor learning studies face the challenge of differentiating between real changes in performance and random measurement error. While the traditional p -value-based analyses of difference (e.g., t -tests, ANOVAs) provide information on the statistical significance of a reported change in performance scores, they do not inform as to the likely cause or origin of that change, that is, the contribution of both real modifications in performance and random measurement error to the reported change. One way of differentiating between real change and random measurement error is through the utilization of the statistics of standard error of measurement (SEM) and minimal detectable change (MDC). SEM is estimated from the standard deviation of a sample of scores at baseline and a test-retest reliability index of the measurement instrument or test employed. MDC, in turn, is estimated from SEM and a degree of confidence, usually 95%. The MDC value might be regarded as the minimum amount of change that needs to be observed for it to be considered a real change, or a change to which the contribution of real modifications in performance is likely to be greater than that of random measurement error. A computer-based motor task was designed to illustrate the applicability of SEM and MDC to motor learning research. Two studies were conducted with healthy participants. Study 1 assessed the test-retest reliability of the task and Study 2 consisted in a typical motor learning study, where participants practiced the task for five consecutive days. In Study 2, the data were analyzed with a traditional p -value-based analysis of difference (ANOVA) and also with SEM and MDC. The findings showed good test-retest reliability for the task and that the p -value-based analysis alone identified statistically significant improvements in performance over time even when the observed changes could in fact have been smaller than the MDC and thereby caused mostly by random measurement error, as opposed to by learning. We suggest therefore that motor learning studies could complement their p -value-based analyses of difference with statistics such as SEM and MDC in order to inform as to the likely cause or origin of any reported changes in performance.

The effect of rainfall measurement uncertainties on rainfall-runoff processes modelling.

PubMed

Stransky, D; Bares, V; Fatka, P

2007-01-01

Rainfall data are a crucial input for various tasks concerning the wet weather period. Nevertheless, their measurement is affected by random and systematic errors that cause an underestimation of the rainfall volume. Therefore, the general objective of the presented work was to assess the credibility of measured rainfall data and to evaluate the effect of measurement errors on urban drainage modelling tasks. Within the project, the methodology of the tipping bucket rain gauge (TBR) was defined and assessed in terms of uncertainty analysis. A set of 18 TBRs was calibrated and the results were compared to the previous calibration. This enables us to evaluate the ageing of TBRs. A propagation of calibration and other systematic errors through the rainfall-runoff model was performed on experimental catchment. It was found that the TBR calibration is important mainly for tasks connected with the assessment of peak values and high flow durations. The omission of calibration leads to up to 30% underestimation and the effect of other systematic errors can add a further 15%. The TBR calibration should be done every two years in order to catch up the ageing of TBR mechanics. Further, the authors recommend to adjust the dynamic test duration proportionally to generated rainfall intensity.

Positivity, discontinuity, finite resources, and nonzero error for arbitrarily varying quantum channels

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

Boche, H., E-mail: boche@tum.de, E-mail: janis.noetzel@tum.de; Nötzel, J., E-mail: boche@tum.de, E-mail: janis.noetzel@tum.de

2014-12-15

This work is motivated by a quite general question: Under which circumstances are the capacities of information transmission systems continuous? The research is explicitly carried out on finite arbitrarily varying quantum channels (AVQCs). We give an explicit example that answers the recent question whether the transmission of messages over AVQCs can benefit from assistance by distribution of randomness between the legitimate sender and receiver in the affirmative. The specific class of channels introduced in that example is then extended to show that the unassisted capacity does have discontinuity points, while it is known that the randomness-assisted capacity is always continuousmore » in the channel. We characterize the discontinuity points and prove that the unassisted capacity is always continuous around its positivity points. After having established shared randomness as an important resource, we quantify the interplay between the distribution of finite amounts of randomness between the legitimate sender and receiver, the (nonzero) probability of a decoding error with respect to the average error criterion and the number of messages that can be sent over a finite number of channel uses. We relate our results to the entanglement transmission capacities of finite AVQCs, where the role of shared randomness is not yet well understood, and give a new sufficient criterion for the entanglement transmission capacity with randomness assistance to vanish.« less

Noise in two-color electronic distance meter measurements revisited

USGS Publications Warehouse

Langbein, J.

2004-01-01

Frequent, high-precision geodetic data have temporally correlated errors. Temporal correlations directly affect both the estimate of rate and its standard error; the rate of deformation is a key product from geodetic measurements made in tectonically active areas. Various models of temporally correlated errors are developed and these provide relations between the power spectral density and the data covariance matrix. These relations are applied to two-color electronic distance meter (EDM) measurements made frequently in California over the past 15-20 years. Previous analysis indicated that these data have significant random walk error. Analysis using the noise models developed here indicates that the random walk model is valid for about 30% of the data. A second 30% of the data can be better modeled with power law noise with a spectral index between 1 and 2, while another 30% of the data can be modeled with a combination of band-pass-filtered plus random walk noise. The remaining 10% of the data can be best modeled as a combination of band-pass-filtered plus power law noise. This band-pass-filtered noise is a product of an annual cycle that leaks into adjacent frequency bands. For time spans of more than 1 year these more complex noise models indicate that the precision in rate estimates is better than that inferred by just the simpler, random walk model of noise.

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2016-01-01

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

Estimating errors in least-squares fitting

NASA Technical Reports Server (NTRS)

Richter, P. H.

1995-01-01

While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random errors in the data. Expressions are derived for the standard error of the fit, as a function of the independent variable, for the general nonlinear and linear fitting problems. Additionally, closed-form expressions are derived for some examples commonly encountered in the scientific and engineering fields, namely ordinary polynomial and Gaussian fitting functions. These results have direct application to the assessment of the antenna gain and system temperature characteristics, in addition to a broad range of problems in data analysis. The effects of the nature of the data and the choice of fitting function on the ability to accurately model the system under study are discussed, and some general rules are deduced to assist workers intent on maximizing the amount of information obtained form a given set of measurements.

Robust vector quantization for noisy channels

NASA Technical Reports Server (NTRS)

Demarca, J. R. B.; Farvardin, N.; Jayant, N. S.; Shoham, Y.

1988-01-01

The paper briefly discusses techniques for making vector quantizers more tolerant to tranmsission errors. Two algorithms are presented for obtaining an efficient binary word assignment to the vector quantizer codewords without increasing the transmission rate. It is shown that about 4.5 dB gain over random assignment can be achieved with these algorithms. It is also proposed to reduce the effects of error propagation in vector-predictive quantizers by appropriately constraining the response of the predictive loop. The constrained system is shown to have about 4 dB of SNR gain over an unconstrained system in a noisy channel, with a small loss of clean-channel performance.

A study of high density bit transition requirements versus the effects on BCH error correcting coding

NASA Technical Reports Server (NTRS)

Ingels, F.; Schoggen, W. O.

1981-01-01

Several methods for increasing bit transition densities in a data stream are summarized, discussed in detail, and compared against constraints imposed by the 2 MHz data link of the space shuttle high rate multiplexer unit. These methods include use of alternate pulse code modulation waveforms, data stream modification by insertion, alternate bit inversion, differential encoding, error encoding, and use of bit scramblers. The psuedo-random cover sequence generator was chosen for application to the 2 MHz data link of the space shuttle high rate multiplexer unit. This method is fully analyzed and a design implementation proposed.

Helical tomotherapy setup variations in canine nasal tumor patients immobilized with a bite block.

PubMed

Kubicek, Lyndsay N; Seo, Songwon; Chappell, Richard J; Jeraj, Robert; Forrest, Lisa J

2012-01-01

The purpose of our study was to compare setup variation in four degrees of freedom (vertical, longitudinal, lateral, and roll) between canine nasal tumor patients immobilized with a mattress and bite block, versus a mattress alone. Our secondary aim was to define a clinical target volume (CTV) to planning target volume (PTV) expansion margin based on our mean systematic error values associated with nasal tumor patients immobilized by a mattress and bite block. We evaluated six parameters for setup corrections: systematic error, random error, patient-patient variation in systematic errors, the magnitude of patient-specific random errors (root mean square [RMS]), distance error, and the variation of setup corrections from zero shift. The variations in all parameters were statistically smaller in the group immobilized by a mattress and bite block. The mean setup corrections in the mattress and bite block group ranged from 0.91 mm to 1.59 mm for the translational errors and 0.5°. Although most veterinary radiation facilities do not have access to Image-guided radiotherapy (IGRT), we identified a need for more rigid fixation, established the value of adding IGRT to veterinary radiation therapy, and define the CTV-PTV setup error margin for canine nasal tumor patients immobilized in a mattress and bite block. © 2012 Veterinary Radiology & Ultrasound.

[Theory, method and application of method R on estimation of (co)variance components].

PubMed

Liu, Wen-Zhong

2004-07-01

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

Bit Error Probability for Maximum Likelihood Decoding of Linear Block Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc P. C.; Rhee, Dojun

1996-01-01

In this paper, the bit error probability P(sub b) for maximum likelihood decoding of binary linear codes is investigated. The contribution of each information bit to P(sub b) is considered. For randomly generated codes, it is shown that the conventional approximation at high SNR P(sub b) is approximately equal to (d(sub H)/N)P(sub s), where P(sub s) represents the block error probability, holds for systematic encoding only. Also systematic encoding provides the minimum P(sub b) when the inverse mapping corresponding to the generator matrix of the code is used to retrieve the information sequence. The bit error performances corresponding to other generator matrix forms are also evaluated. Although derived for codes with a generator matrix randomly generated, these results are shown to provide good approximations for codes used in practice. Finally, for decoding methods which require a generator matrix with a particular structure such as trellis decoding or algebraic-based soft decision decoding, equivalent schemes that reduce the bit error probability are discussed.

Value stream mapping of the Pap test processing procedure: a lean approach to improve quality and efficiency.

PubMed

Michael, Claire W; Naik, Kalyani; McVicker, Michael

2013-05-01

We developed a value stream map (VSM) of the Papanicolaou test procedure to identify opportunities to reduce waste and errors, created a new VSM, and implemented a new process emphasizing Lean tools. Preimplementation data revealed the following: (1) processing time (PT) for 1,140 samples averaged 54 hours; (2) 27 accessioning errors were detected on review of 357 random requisitions (7.6%); (3) 5 of the 20,060 tests had labeling errors that had gone undetected in the processing stage. Four were detected later during specimen processing but 1 reached the reporting stage. Postimplementation data were as follows: (1) PT for 1,355 samples averaged 31 hours; (2) 17 accessioning errors were detected on review of 385 random requisitions (4.4%); and (3) no labeling errors were undetected. Our results demonstrate that implementation of Lean methods, such as first-in first-out processes and minimizing batch size by staff actively participating in the improvement process, allows for higher quality, greater patient safety, and improved efficiency.

Influence of ultraviolet irradiation on data retention characteristics in resistive random access memory

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

Kimura, K.; Ohmi, K.; Tottori University Electronic Display Research Center, 101 Minami4-chome, Koyama-cho, Tottori-shi, Tottori 680-8551

With increasing density of memory devices, the issue of generating soft errors by cosmic rays is becoming more and more serious. Therefore, the irradiation resistance of resistance random access memory (ReRAM) to cosmic radiation has to be elucidated for practical use. In this paper, we investigated the data retention characteristics of ReRAM against ultraviolet irradiation with a Pt/NiO/ITO structure. Soft errors were confirmed to be caused by ultraviolet irradiation in both low- and high-resistance states. An analysis of the wavelength dependence of light irradiation on data retention characteristics suggested that electronic excitation from the valence to the conduction band andmore » to the energy level generated due to the introduction of oxygen vacancies caused the errors. Based on a statistically estimated soft error rates, the errors were suggested to be caused by the cohesion and dispersion of oxygen vacancies owing to the generation of electron-hole pairs and valence changes by the ultraviolet irradiation.« less

The dependence of crowding on flanker complexity and target-flanker similarity

PubMed Central

Bernard, Jean-Baptiste; Chung, Susana T.L.

2013-01-01

We examined the effects of the spatial complexity of flankers and target-flanker similarity on the performance of identifying crowded letters. On each trial, observers identified the middle character of random strings of three characters (“trigrams”) briefly presented at 10° below fixation. We tested the 26 lowercase letters of the Times-Roman and Courier fonts, a set of 79 characters (letters and non-letters) of the Times-Roman font, and the uppercase letters of two highly complex ornamental fonts, Edwardian and Aristocrat. Spatial complexity of characters was quantified by the length of the morphological skeleton of each character, and target-flanker similarity was defined based on a psychometric similarity matrix. Our results showed that (1) letter identification error rate increases with flanker complexity up to a certain value, beyond which error rate becomes independent of flanker complexity; (2) the increase of error rate is slower for high-complexity target letters; (3) error rate increases with target-flanker similarity; and (4) mislocation error rate increases with target-flanker similarity. These findings, combined with the current understanding of the faulty feature integration account of crowding, provide some constraints of how the feature integration process could cause perceptual errors. PMID:21730225

Quantum Steering Inequality with Tolerance for Measurement-Setting Errors: Experimentally Feasible Signature of Unbounded Violation

NASA Astrophysics Data System (ADS)

Rutkowski, Adam; Buraczewski, Adam; Horodecki, Paweł; Stobińska, Magdalena

2017-01-01

Quantum steering is a relatively simple test for proving that the values of quantum-mechanical measurement outcomes come into being only in the act of measurement. By exploiting quantum correlations, Alice can influence—steer—Bob's physical system in a way that is impossible in classical mechanics, as shown by the violation of steering inequalities. Demonstrating this and similar quantum effects for systems of increasing size, approaching even the classical limit, is a long-standing challenging problem. Here, we prove an experimentally feasible unbounded violation of a steering inequality. We derive its universal form where tolerance for measurement-setting errors is explicitly built in by means of the Deutsch-Maassen-Uffink entropic uncertainty relation. Then, generalizing the mutual unbiasedness, we apply the inequality to the multisinglet and multiparticle bipartite Bell state. However, the method is general and opens the possibility of employing multiparticle bipartite steering for randomness certification and development of quantum technologies, e.g., random access codes.

Event-related potentials reflect impaired temporal interval learning following haloperidol administration.

PubMed

Forster, Sarah E; Zirnheld, Patrick; Shekhar, Anantha; Steinhauer, Stuart R; O'Donnell, Brian F; Hetrick, William P

2017-09-01

Signals carried by the mesencephalic dopamine system and conveyed to anterior cingulate cortex are critically implicated in probabilistic reward learning and performance monitoring. A common evaluative mechanism purportedly subserves both functions, giving rise to homologous medial frontal negativities in feedback- and response-locked event-related brain potentials (the feedback-related negativity (FRN) and the error-related negativity (ERN), respectively), reflecting dopamine-dependent prediction error signals to unexpectedly negative events. Consistent with this model, the dopamine receptor antagonist, haloperidol, attenuates the ERN, but effects on FRN have not yet been evaluated. ERN and FRN were recorded during a temporal interval learning task (TILT) following randomized, double-blind administration of haloperidol (3 mg; n = 18), diphenhydramine (an active control for haloperidol; 25 mg; n = 20), or placebo (n = 21) to healthy controls. Centroparietal positivities, the Pe and feedback-locked P300, were also measured and correlations between ERP measures and behavioral indices of learning, overall accuracy, and post-error compensatory behavior were evaluated. We hypothesized that haloperidol would reduce ERN and FRN, but that ERN would uniquely track automatic, error-related performance adjustments, while FRN would be associated with learning and overall accuracy. As predicted, ERN was reduced by haloperidol and in those exhibiting less adaptive post-error performance; however, these effects were limited to ERNs following fast timing errors. In contrast, the FRN was not affected by drug condition, although increased FRN amplitude was associated with improved accuracy. Significant drug effects on centroparietal positivities were also absent. Our results support a functional and neurobiological dissociation between the ERN and FRN.

Estimation of daily interfractional larynx residual setup error after isocentric alignment for head and neck radiotherapy: Quality-assurance implications for target volume and organ-at-risk margination using daily CT-on-rails imaging

PubMed Central

Baron, Charles A.; Awan, Musaddiq J.; Mohamed, Abdallah S. R.; Akel, Imad; Rosenthal, David I.; Gunn, G. Brandon; Garden, Adam S.; Dyer, Brandon A.; Court, Laurence; Sevak, Parag R; Kocak-Uzel, Esengul; Fuller, Clifton D.

2016-01-01

Larynx may alternatively serve as a target or organ-at-risk (OAR) in head and neck cancer (HNC) image-guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population–based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT-on-rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other 6 points were calculated post-isocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all 6 points for all scans over the course of treatment were calculated. Residual systematic and random error, and the necessary compensatory CTV-to-PTV and OAR-to-PRV margins were calculated, using both observational cohort data and a bootstrap-resampled population estimator. The grand mean displacements for all anatomical points was 5.07mm, with mean systematic error of 1.1mm and mean random setup error of 2.63mm, while bootstrapped POIs grand mean displacement was 5.09mm, with mean systematic error of 1.23mm and mean random setup error of 2.61mm. Required margin for CTV-PTV expansion was 4.6mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9mm. The calculated OAR-to-PRV expansion for the observed residual set-up error was 2.7mm, and bootstrap estimated expansion of 2.9mm. We conclude that the interfractional larynx setup error is a significant source of RT set-up/delivery error in HNC both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5mm to compensate for set up error if the larynx is a target or 3mm if the larynx is an OAR when using a non-laryngeal bony isocenter. PMID:25679151

Estimation of daily interfractional larynx residual setup error after isocentric alignment for head and neck radiotherapy: quality assurance implications for target volume and organs‐at‐risk margination using daily CT on‐rails imaging

PubMed Central

Baron, Charles A.; Awan, Musaddiq J.; Mohamed, Abdallah S.R.; Akel, Imad; Rosenthal, David I.; Gunn, G. Brandon; Garden, Adam S.; Dyer, Brandon A.; Court, Laurence; Sevak, Parag R.; Kocak‐Uzel, Esengul

2014-01-01

Larynx may alternatively serve as a target or organs at risk (OAR) in head and neck cancer (HNC) image‐guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population‐based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT on‐rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior‐anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other six points were calculated postisocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all six points for all scans over the course of treatment was calculated. Residual systematic and random error and the necessary compensatory CTV‐to‐PTV and OAR‐to‐PRV margins were calculated, using both observational cohort data and a bootstrap‐resampled population estimator. The grand mean displacements for all anatomical points was 5.07 mm, with mean systematic error of 1.1 mm and mean random setup error of 2.63 mm, while bootstrapped POIs grand mean displacement was 5.09 mm, with mean systematic error of 1.23 mm and mean random setup error of 2.61 mm. Required margin for CTV‐PTV expansion was 4.6 mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9 mm. The calculated OAR‐to‐PRV expansion for the observed residual setup error was 2.7 mm and bootstrap estimated expansion of 2.9 mm. We conclude that the interfractional larynx setup error is a significant source of RT setup/delivery error in HNC, both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5 mm to compensate for setup error if the larynx is a target, or 3 mm if the larynx is an OAR, when using a nonlaryngeal bony isocenter. PACS numbers: 87.55.D‐, 87.55.Qr

Full-Duplex Bidirectional Secure Communications Under Perfect and Distributionally Ambiguous Eavesdropper's CSI

NASA Astrophysics Data System (ADS)

Li, Qiang; Zhang, Ying; Lin, Jingran; Wu, Sissi Xiaoxiao

2017-09-01

Consider a full-duplex (FD) bidirectional secure communication system, where two communication nodes, named Alice and Bob, simultaneously transmit and receive confidential information from each other, and an eavesdropper, named Eve, overhears the transmissions. Our goal is to maximize the sum secrecy rate (SSR) of the bidirectional transmissions by optimizing the transmit covariance matrices at Alice and Bob. To tackle this SSR maximization (SSRM) problem, we develop an alternating difference-of-concave (ADC) programming approach to alternately optimize the transmit covariance matrices at Alice and Bob. We show that the ADC iteration has a semi-closed-form beamforming solution, and is guaranteed to converge to a stationary solution of the SSRM problem. Besides the SSRM design, this paper also deals with a robust SSRM transmit design under a moment-based random channel state information (CSI) model, where only some roughly estimated first and second-order statistics of Eve's CSI are available, but the exact distribution or other high-order statistics is not known. This moment-based error model is new and different from the widely used bounded-sphere error model and the Gaussian random error model. Under the consider CSI error model, the robust SSRM is formulated as an outage probability-constrained SSRM problem. By leveraging the Lagrangian duality theory and DC programming, a tractable safe solution to the robust SSRM problem is derived. The effectiveness and the robustness of the proposed designs are demonstrated through simulations.

ICP-Forests (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests): Quality Assurance procedure in plant diversity monitoring.

PubMed

Allegrini, Maria-Cristina; Canullo, Roberto; Campetella, Giandiego

2009-04-01

Knowledge of accuracy and precision rates is particularly important for long-term studies. Vegetation assessments include many sources of error related to overlooking and misidentification, that are usually influenced by some factors, such as cover estimate subjectivity, observer biased species lists and experience of the botanist. The vegetation assessment protocol adopted in the Italian forest monitoring programme (CONECOFOR) contains a Quality Assurance programme. The paper presents the different phases of QA, separates the 5 main critical points of the whole protocol as sources of random or systematic errors. Examples of Measurement Quality Objectives (MQOs) expressed as Data Quality Limits (DQLs) are given for vascular plant cover estimates, in order to establish the reproducibility of the data. Quality control activities were used to determine the "distance" between the surveyor teams and the control team. Selected data were acquired during the training and inter-calibration courses. In particular, an index of average cover by species groups was used to evaluate the random error (CV 4%) as the dispersion around the "true values" of the control team. The systematic error in the evaluation of species composition, caused by overlooking or misidentification of species, was calculated following the pseudo-turnover rate; detailed species censuses on smaller sampling units were accepted as the pseudo-turnover which always fell below the 25% established threshold; species density scores recorded at community level (100 m(2) surface) rarely exceeded that limit.

Modeling methodology for MLS range navigation system errors using flight test data

NASA Technical Reports Server (NTRS)

Karmali, M. S.; Phatak, A. V.

1982-01-01

Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.

A practical approach to automate randomized design of experiments for ligand-binding assays.

PubMed

Tsoi, Jennifer; Patel, Vimal; Shih, Judy

2014-03-01

Design of experiments (DOE) is utilized in optimizing ligand-binding assay by modeling factor effects. To reduce the analyst's workload and error inherent with DOE, we propose the integration of automated liquid handlers to perform the randomized designs. A randomized design created from statistical software was imported into custom macro converting the design into a liquid-handler worklist to automate reagent delivery. An optimized assay was transferred to a contract research organization resulting in a successful validation. We developed a practical solution for assay optimization by integrating DOE and automation to increase assay robustness and enable successful method transfer. The flexibility of this process allows it to be applied to a variety of assay designs.

Asteroid thermal modeling in the presence of reflected sunlight

NASA Astrophysics Data System (ADS)

Myhrvold, Nathan

2018-03-01

A new derivation of simple asteroid thermal models is presented, investigating the need to account correctly for Kirchhoff's law of thermal radiation when IR observations contain substantial reflected sunlight. The framework applies to both the NEATM and related thermal models. A new parameterization of these models eliminates the dependence of thermal modeling on visible absolute magnitude H, which is not always available. Monte Carlo simulations are used to assess the potential impact of violating Kirchhoff's law on estimates of physical parameters such as diameter and IR albedo, with an emphasis on NEOWISE results. The NEOWISE papers use ten different models, applied to 12 different combinations of WISE data bands, in 47 different combinations. The most prevalent combinations are simulated and the accuracy of diameter estimates is found to be depend critically on the model and data band combination. In the best case of full thermal modeling of all four band the errors in an idealized model the 1σ (68.27%) confidence interval is -5% to +6%, but this combination is just 1.9% of NEOWISE results. Other combinations representing 42% of the NEOWISE results have about twice the CI at -10% to +12%, before accounting for errors due to irregular shape or other real world effects that are not simulated. The model and data band combinations found for the majority of NEOWISE results have much larger systematic and random errors. Kirchhoff's law violation by NEOWISE models leads to errors in estimation accuracy that are strongest for asteroids with W1, W2 band emissivity ɛ12 in both the lowest (0.605 ≤ɛ12 ≤ 0 . 780), and highest decile (0.969 ≤ɛ12 ≤ 0 . 988), corresponding to the highest and lowest deciles of near-IR albedo pIR. Systematic accuracy error between deciles ranges from a low of 5% to as much as 45%, and there are also differences in the random errors. Kirchhoff's law effects also produce large errors in NEOWISE estimates of pIR, particularly for high values. IR observations of asteroids in bands that have substantial reflected sunlight can largely avoid these problems by adopting the Kirchhoff law compliant modeling framework presented here, which is conceptually straightforward and comes without computational cost.

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

PubMed Central

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test–post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences. PMID:29881032

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses.

PubMed

Cho, Sun-Joo; Preacher, Kristopher J; Bottge, Brian A

2015-11-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test-post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences.

Spatial serial order processing in schizophrenia.

PubMed

Fraser, David; Park, Sohee; Clark, Gina; Yohanna, Daniel; Houk, James C

2004-10-01

The aim of this study was to examine serial order processing deficits in 21 schizophrenia patients and 16 age- and education-matched healthy controls. In a spatial serial order working memory task, one to four spatial targets were presented in a randomized sequence. Subjects were required to remember the locations and the order in which the targets were presented. Patients showed a marked deficit in ability to remember the sequences compared with controls. Increasing the number of targets within a sequence resulted in poorer memory performance for both control and schizophrenia subjects, but the effect was much more pronounced in the patients. Targets presented at the end of a long sequence were more vulnerable to memory error in schizophrenia patients. Performance deficits were not attributable to motor errors, but to errors in target choice. The results support the idea that the memory errors seen in schizophrenia patients may be due to saturating the working memory network at relatively low levels of memory load.

Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

NASA Astrophysics Data System (ADS)

Utegulov, B. B.

2018-02-01

In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

Use of machine learning methods to reduce predictive error of groundwater models.

PubMed

Xu, Tianfang; Valocchi, Albert J; Choi, Jaesik; Amir, Eyal

2014-01-01

Quantitative analyses of groundwater flow and transport typically rely on a physically-based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data-driven models (DDMs) to reduce the predictive error of physically-based groundwater models. Two machine learning techniques, the instance-based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real-world case studies of the Republican River Compact Administration model and the Spokane Valley-Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root-mean-square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically-based model. © 2013, National GroundWater Association.

Linear error analysis of slope-area discharge determinations

USGS Publications Warehouse

Kirby, W.H.

1987-01-01

The slope-area method can be used to calculate peak flood discharges when current-meter measurements are not possible. This calculation depends on several quantities, such as water-surface fall, that are subject to large measurement errors. Other critical quantities, such as Manning's n, are not even amenable to direct measurement but can only be estimated. Finally, scour and fill may cause gross discrepancies between the observed condition of the channel and the hydraulic conditions during the flood peak. The effects of these potential errors on the accuracy of the computed discharge have been estimated by statistical error analysis using a Taylor-series approximation of the discharge formula and the well-known formula for the variance of a sum of correlated random variates. The resultant error variance of the computed discharge is a weighted sum of covariances of the various observational errors. The weights depend on the hydraulic and geometric configuration of the channel. The mathematical analysis confirms the rule of thumb that relative errors in computed discharge increase rapidly when velocity heads exceed the water-surface fall, when the flow field is expanding and when lateral velocity variation (alpha) is large. It also confirms the extreme importance of accurately assessing the presence of scour or fill. ?? 1987.

Interpreting findings from Mendelian randomization using the MR-Egger method.

PubMed

Burgess, Stephen; Thompson, Simon G

2017-05-01

Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption-the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases.

The Effect of Cluster Sampling Design in Survey Research on the Standard Error Statistic.

ERIC Educational Resources Information Center

Wang, Lin; Fan, Xitao

Standard statistical methods are used to analyze data that is assumed to be collected using a simple random sampling scheme. These methods, however, tend to underestimate variance when the data is collected with a cluster design, which is often found in educational survey research. The purposes of this paper are to demonstrate how a cluster design…

Landing Technique and Performance in Youth Athletes After a Single Injury-Prevention Program Session

PubMed Central

Root, Hayley; Trojian, Thomas; Martinez, Jessica; Kraemer, William; DiStefano, Lindsay J.

2015-01-01

Context Injury-prevention programs (IPPs) performed as season-long warm-ups improve injury rates, performance outcomes, and jump-landing technique. However, concerns regarding program adoption exist. Identifying the acute benefits of using an IPP compared with other warm-ups may encourage IPP adoption. Objective To examine the immediate effects of 3 warm-up protocols (IPP, static warm-up [SWU], or dynamic warm-up [DWU]) on jump-landing technique and performance measures in youth athletes. Design Randomized controlled clinical trial. Setting Gymnasiums. Patients or Other Participants Sixty male and 29 female athletes (age = 13 ± 2 years, height = 162.8 ± 12.6 cm, mass = 37.1 ± 13.5 kg) volunteered to participate in a single session. Intervention(s) Participants were stratified by age, sex, and sport and then were randomized into 1 protocol: IPP, SWU, or DWU. The IPP consisted of dynamic flexibility, strengthening, plyometric, and balance exercises and emphasized proper technique. The SWU consisted of jogging and lower extremity static stretching. The DWU consisted of dynamic lower extremity flexibility exercises. Participants were assessed for landing technique and performance measures immediately before (PRE) and after (POST) completing their warm-ups. Main Outcome Measure(s) One rater graded each jump-landing trial using the Landing Error Scoring System. Participants performed a vertical jump, long jump, shuttle run, and jump-landing task in randomized order. The averages of all jump-landing trials and performance variables were used to calculate 1 composite score for each variable at PRE and POST. Change scores were calculated (POST − PRE) for all measures. Separate 1-way (group) analyses of variance were conducted for each dependent variable (α < .05). Results No differences were observed among groups for any performance measures (P > .05). The Landing Error Scoring System scores improved after the IPP (change = −0.40 ± 1.24 errors) compared with the DWU (0.27 ± 1.09 errors) and SWU (0.43 ± 1.35 errors; P = .04). Conclusions An IPP did not impair sport performance and may have reduced injury risk, which supports the use of these programs before sport activity. PMID:26523663

THE SYSTEMATICS OF STRONG LENS MODELING QUANTIFIED: THE EFFECTS OF CONSTRAINT SELECTION AND REDSHIFT INFORMATION ON MAGNIFICATION, MASS, AND MULTIPLE IMAGE PREDICTABILITY

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

Johnson, Traci L.; Sharon, Keren, E-mail: tljohn@umich.edu

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading asmore » to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.« less

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors.

PubMed

El-Diasty, Mohammed; Pagiatakis, Spiros

2009-01-01

In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

A Spanish Pillbox App for Elderly Patients Taking Multiple Medications: Randomized Controlled Trial

PubMed Central

Mira, José Joaquín; Navarro, Isabel; Botella, Federico; Borrás, Fernando; Orozco, Domingo; Iglesias-Alonso, Fuencisla; Pérez-Pérez, Pastora; Lorenzo, Susana; Toro, Nuria

2014-01-01

Background Nonadherence and medication errors are common among patients with complex drug regimens. Apps for smartphones and tablets are effective for improving adherence, but they have not been tested in elderly patients with complex chronic conditions and who typically have less experience with this type of technology. Objective The objective of this study was to design, implement, and evaluate a medication self-management app (called ALICE) for elderly patients taking multiple medications with the intention of improving adherence and safe medication use. Methods A single-blind randomized controlled trial was conducted with a control and an experimental group (N=99) in Spain in 2013. The characteristics of ALICE were specified based on the suggestions of 3 nominal groups with a total of 23 patients and a focus group with 7 professionals. ALICE was designed for Android and iOS to allow for the personalization of prescriptions and medical advice, showing images of each of the medications (the packaging and the medication itself) together with alerts and multiple reminders for each alert. The randomly assigned patients in the control group received oral and written information on the safe use of their medications and the patients in the experimental group used ALICE for 3 months. Pre and post measures included rate of missed doses and medication errors reported by patients, scores from the 4-item Morisky Medication Adherence Scale (MMAS-4), level of independence, self-perceived health status, and biochemical test results. In the experimental group, data were collected on their previous experience with information and communication technologies, their rating of ALICE, and their perception of the level of independence they had achieved. The intergroup intervention effects were calculated by univariate linear models and ANOVA, with the pre to post intervention differences as the dependent variables. Results Data were obtained from 99 patients (48 and 51 in the control and experimental groups, respectively). Patients in the experimental group obtained better MMAS-4 scores (P<.001) and reported fewer missed doses of medication (P=.02). ALICE only helped to significantly reduce medication errors in patients with an initially higher rate of errors (P<.001). Patients with no experience with information and communication technologies reported better adherence (P<.001), fewer missed doses (P<.001), and fewer medication errors (P=.02). The mean satisfaction score for ALICE was 8.5 out of 10. In all, 45 of 51 patients (88%) felt that ALICE improved their independence in managing their medications. Conclusions The ALICE app improves adherence, helps reduce rates of forgetting and of medication errors, and increases perceived independence in managing medication. Elderly patients with no previous experience with information and communication technologies are capable of effectively using an app designed to help them take their medicine more safely. Trial Registration Clinicaltrials.gov NCT02071498; http://clinicaltrials.gov/ct2/show/NCT02071498 (Archived by WebCite at http://www.webcitation.org/6OJjdHVhD). PMID:24705022

A Spanish pillbox app for elderly patients taking multiple medications: randomized controlled trial.

PubMed

Mira, José Joaquín; Navarro, Isabel; Botella, Federico; Borrás, Fernando; Nuño-Solinís, Roberto; Orozco, Domingo; Iglesias-Alonso, Fuencisla; Pérez-Pérez, Pastora; Lorenzo, Susana; Toro, Nuria

2014-04-04

Nonadherence and medication errors are common among patients with complex drug regimens. Apps for smartphones and tablets are effective for improving adherence, but they have not been tested in elderly patients with complex chronic conditions and who typically have less experience with this type of technology. The objective of this study was to design, implement, and evaluate a medication self-management app (called ALICE) for elderly patients taking multiple medications with the intention of improving adherence and safe medication use. A single-blind randomized controlled trial was conducted with a control and an experimental group (N=99) in Spain in 2013. The characteristics of ALICE were specified based on the suggestions of 3 nominal groups with a total of 23 patients and a focus group with 7 professionals. ALICE was designed for Android and iOS to allow for the personalization of prescriptions and medical advice, showing images of each of the medications (the packaging and the medication itself) together with alerts and multiple reminders for each alert. The randomly assigned patients in the control group received oral and written information on the safe use of their medications and the patients in the experimental group used ALICE for 3 months. Pre and post measures included rate of missed doses and medication errors reported by patients, scores from the 4-item Morisky Medication Adherence Scale (MMAS-4), level of independence, self-perceived health status, and biochemical test results. In the experimental group, data were collected on their previous experience with information and communication technologies, their rating of ALICE, and their perception of the level of independence they had achieved. The intergroup intervention effects were calculated by univariate linear models and ANOVA, with the pre to post intervention differences as the dependent variables. Data were obtained from 99 patients (48 and 51 in the control and experimental groups, respectively). Patients in the experimental group obtained better MMAS-4 scores (P<.001) and reported fewer missed doses of medication (P=.02). ALICE only helped to significantly reduce medication errors in patients with an initially higher rate of errors (P<.001). Patients with no experience with information and communication technologies reported better adherence (P<.001), fewer missed doses (P<.001), and fewer medication errors (P=.02). The mean satisfaction score for ALICE was 8.5 out of 10. In all, 45 of 51 patients (88%) felt that ALICE improved their independence in managing their medications. The ALICE app improves adherence, helps reduce rates of forgetting and of medication errors, and increases perceived independence in managing medication. Elderly patients with no previous experience with information and communication technologies are capable of effectively using an app designed to help them take their medicine more safely. Clinicaltrials.gov NCT02071498; http://clinicaltrials.gov/ct2/show/NCT02071498.

Impact of Internally Developed Electronic Prescription on Prescribing Errors at Discharge from the Emergency Department

PubMed Central

Hitti, Eveline; Tamim, Hani; Bakhti, Rinad; Zebian, Dina; Mufarrij, Afif

2017-01-01

Introduction Medication errors are common, with studies reporting at least one error per patient encounter. At hospital discharge, medication errors vary from 15%–38%. However, studies assessing the effect of an internally developed electronic (E)-prescription system at discharge from an emergency department (ED) are comparatively minimal. Additionally, commercially available electronic solutions are cost-prohibitive in many resource-limited settings. We assessed the impact of introducing an internally developed, low-cost E-prescription system, with a list of commonly prescribed medications, on prescription error rates at discharge from the ED, compared to handwritten prescriptions. Methods We conducted a pre- and post-intervention study comparing error rates in a randomly selected sample of discharge prescriptions (handwritten versus electronic) five months pre and four months post the introduction of the E-prescription. The internally developed, E-prescription system included a list of 166 commonly prescribed medications with the generic name, strength, dose, frequency and duration. We included a total of 2,883 prescriptions in this study: 1,475 in the pre-intervention phase were handwritten (HW) and 1,408 in the post-intervention phase were electronic. We calculated rates of 14 different errors and compared them between the pre- and post-intervention period. Results Overall, E-prescriptions included fewer prescription errors as compared to HW-prescriptions. Specifically, E-prescriptions reduced missing dose (11.3% to 4.3%, p <0.0001), missing frequency (3.5% to 2.2%, p=0.04), missing strength errors (32.4% to 10.2%, p <0.0001) and legibility (0.7% to 0.2%, p=0.005). E-prescriptions, however, were associated with a significant increase in duplication errors, specifically with home medication (1.7% to 3%, p=0.02). Conclusion A basic, internally developed E-prescription system, featuring commonly used medications, effectively reduced medication errors in a low-resource setting where the costs of sophisticated commercial electronic solutions are prohibitive. PMID:28874948

Impact of Internally Developed Electronic Prescription on Prescribing Errors at Discharge from the Emergency Department.

PubMed

Hitti, Eveline; Tamim, Hani; Bakhti, Rinad; Zebian, Dina; Mufarrij, Afif

2017-08-01

Medication errors are common, with studies reporting at least one error per patient encounter. At hospital discharge, medication errors vary from 15%-38%. However, studies assessing the effect of an internally developed electronic (E)-prescription system at discharge from an emergency department (ED) are comparatively minimal. Additionally, commercially available electronic solutions are cost-prohibitive in many resource-limited settings. We assessed the impact of introducing an internally developed, low-cost E-prescription system, with a list of commonly prescribed medications, on prescription error rates at discharge from the ED, compared to handwritten prescriptions. We conducted a pre- and post-intervention study comparing error rates in a randomly selected sample of discharge prescriptions (handwritten versus electronic) five months pre and four months post the introduction of the E-prescription. The internally developed, E-prescription system included a list of 166 commonly prescribed medications with the generic name, strength, dose, frequency and duration. We included a total of 2,883 prescriptions in this study: 1,475 in the pre-intervention phase were handwritten (HW) and 1,408 in the post-intervention phase were electronic. We calculated rates of 14 different errors and compared them between the pre- and post-intervention period. Overall, E-prescriptions included fewer prescription errors as compared to HW-prescriptions. Specifically, E-prescriptions reduced missing dose (11.3% to 4.3%, p <0.0001), missing frequency (3.5% to 2.2%, p=0.04), missing strength errors (32.4% to 10.2%, p <0.0001) and legibility (0.7% to 0.2%, p=0.005). E-prescriptions, however, were associated with a significant increase in duplication errors, specifically with home medication (1.7% to 3%, p=0.02). A basic, internally developed E-prescription system, featuring commonly used medications, effectively reduced medication errors in a low-resource setting where the costs of sophisticated commercial electronic solutions are prohibitive.

Effectiveness of a web-based education program to improve vaccine storage conditions in primary care (Keep Cool): study protocol for a randomized controlled trial.

PubMed

Thielmann, Anika; Viehmann, Anja; Weltermann, Birgitta M

2015-07-14

Immunization programs are among the most effective public health strategies worldwide. Adequate vaccine storage is a prerequisite to assure the vaccines' effectiveness and safety. In a questionnaire survey among a random sample of German primary care physicians, we discovered vaccine storage deficits: 16% of physicians had experience with cold chain breaches either as an error or near error, 49 % did not keep a temperature log, and 21 % did not use a separate refrigerator for vaccine storage. In a recent feasibility study of 21 practice refrigerators, we showed that these were outside the target range 10.2% of the total time with some single refrigerators being outside the target range as much as 66.3% of the time. These cooling-chain deficits are consistent with the international medical literature, yet an effective, easy to disseminate, practice-centered intervention to improve storage conditions is lacking. This randomized intervention trial will be conducted in a random sample of primary care practices. Based on continuous temperature recordings over 7 days, all practices with readings outside the target range for vaccine storage (+2 °C to +8 °C) will be randomly allocated to a web-based education program or a waiting list control group. The practice physicians and their teams constitute the target population. Participants will be educated about best practices in vaccine storage and will receive a manual including storage checklists and templates for temperature documentation. In all practices, temperatures of the vaccine refrigerators will be monitored continuously using a data logger with a glycol probe as a surrogate for vaccine vial temperature. The effectiveness of the web-based education program will be determined after 6 months in terms of the proportion of refrigerators with vaccine vial temperatures within the target range (+2 °C to +8 °C) during 7-day temperature logging. Secondary outcome parameters include temperature monitoring, no critically low temperatures (≤ -0.5 °C), compliance with storage recommendations, knowledge of good vaccine storage conditions, and assignment of personnel as vaccine storage manager and backup. Keep Cool will develop and evaluate a web-based education program to improve vaccine storage conditions in primary care and thereby ensure immunization safety and effectiveness. DRKS00006561 (date of registration: 20 February 2015).

Serotonergic antidepressants decrease hedonic signals but leave learning signals in the nucleus accumbens unaffected.

PubMed

Graf, Heiko; Metzger, Coraline D; Walter, Martin; Abler, Birgit

2016-01-06

Investigating the effects of serotonergic antidepressants on neural correlates of visual erotic stimulation revealed decreased reactivity within the dopaminergic reward network along with decreased subjective sexual functioning compared with placebo. However, a global dampening of the reward system under serotonergic drugs is not intuitive considering clinical observations of their beneficial effects in the treatment of depression. Particularly, learning signals as coded in prediction error processing within the dopaminergic reward system can be assumed to be rather enhanced as antidepressant drugs have been demonstrated to facilitate the efficacy of psychotherapeutic interventions relying on learning processes. Within the same study sample, we now explored the effects of serotonergic and dopaminergic/noradrenergic antidepressants on prediction error signals compared with placebo by functional MRI. A total of 17 healthy male participants (mean age: 25.4 years) were investigated under the administration of paroxetine, bupropion and placebo for 7 days each within a randomized, double-blind, within-subject cross-over design. During functional MRI, we used an established monetary incentive task to explore neural prediction error signals within the bilateral nucleus accumbens as region of interest within the dopaminergic reward system. In contrast to diminished neural activations and subjective sexual functioning under the serotonergic agent paroxetine under visual erotic stimulation, we revealed unaffected or even enhanced neural prediction error processing within the nucleus accumbens under this antidepressant along with unaffected behavioural processing. Our study provides evidence that serotonergic antidepressants facilitate prediction error signalling and may support suggestions of beneficial effects of these agents on reinforced learning as an essential element in behavioural psychotherapy.

Nano-metrology: The art of measuring X-ray mirrors with slope errors <100 nrad

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

Alcock, Simon G., E-mail: simon.alcock@diamond.ac.uk; Nistea, Ioana; Sawhney, Kawal

2016-05-15

We present a comprehensive investigation of the systematic and random errors of the nano-metrology instruments used to characterize synchrotron X-ray optics at Diamond Light Source. With experimental skill and careful analysis, we show that these instruments used in combination are capable of measuring state-of-the-art X-ray mirrors. Examples are provided of how Diamond metrology data have helped to achieve slope errors of <100 nrad for optical systems installed on synchrotron beamlines, including: iterative correction of substrates using ion beam figuring and optimal clamping of monochromator grating blanks in their holders. Simulations demonstrate how random noise from the Diamond-NOM’s autocollimator adds intomore » the overall measured value of the mirror’s slope error, and thus predict how many averaged scans are required to accurately characterize different grades of mirror.« less

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.

The Gnomon Experiment

NASA Astrophysics Data System (ADS)

Krisciunas, Kevin

2007-12-01

A gnomon, or vertical pointed stick, can be used to determine the north-south direction at a site, as well as one's latitude. If one has accurate time and knows one's time zone, it is also possible to determine one's longitude. From observations on the first day of winter and the first day of summer one can determine the obliquity of the ecliptic. Since we can obtain accurate geographical coordinates from Google Earth or a GPS device, analysis of set of shadow length measurements can be used by students to learn about astronomical coordinate systems, time systems, systematic errors, and random errors. Systematic latitude errors of student datasets are typically 30 nautical miles (0.5 degree) or more, but with care one can achieve systematic and random errors less than 8 nautical miles. One of the advantages of this experiment is that it can be carried out during the day. Also, it is possible to determine if a student has made up his data.

Biometrics encryption combining palmprint with two-layer error correction codes

NASA Astrophysics Data System (ADS)

Li, Hengjian; Qiu, Jian; Dong, Jiwen; Feng, Guang

2017-07-01

To bridge the gap between the fuzziness of biometrics and the exactitude of cryptography, based on combining palmprint with two-layer error correction codes, a novel biometrics encryption method is proposed. Firstly, the randomly generated original keys are encoded by convolutional and cyclic two-layer coding. The first layer uses a convolution code to correct burst errors. The second layer uses cyclic code to correct random errors. Then, the palmprint features are extracted from the palmprint images. Next, they are fused together by XORing operation. The information is stored in a smart card. Finally, the original keys extraction process is the information in the smart card XOR the user's palmprint features and then decoded with convolutional and cyclic two-layer code. The experimental results and security analysis show that it can recover the original keys completely. The proposed method is more secure than a single password factor, and has higher accuracy than a single biometric factor.

Error-Transparent Quantum Gates for Small Logical Qubit Architectures

NASA Astrophysics Data System (ADS)

Kapit, Eliot

2018-02-01

One of the largest obstacles to building a quantum computer is gate error, where the physical evolution of the state of a qubit or group of qubits during a gate operation does not match the intended unitary transformation. Gate error stems from a combination of control errors and random single qubit errors from interaction with the environment. While great strides have been made in mitigating control errors, intrinsic qubit error remains a serious problem that limits gate fidelity in modern qubit architectures. Simultaneously, recent developments of small error-corrected logical qubit devices promise significant increases in logical state lifetime, but translating those improvements into increases in gate fidelity is a complex challenge. In this Letter, we construct protocols for gates on and between small logical qubit devices which inherit the parent device's tolerance to single qubit errors which occur at any time before or during the gate. We consider two such devices, a passive implementation of the three-qubit bit flip code, and the author's own [E. Kapit, Phys. Rev. Lett. 116, 150501 (2016), 10.1103/PhysRevLett.116.150501] very small logical qubit (VSLQ) design, and propose error-tolerant gate sets for both. The effective logical gate error rate in these models displays superlinear error reduction with linear increases in single qubit lifetime, proving that passive error correction is capable of increasing gate fidelity. Using a standard phenomenological noise model for superconducting qubits, we demonstrate a realistic, universal one- and two-qubit gate set for the VSLQ, with error rates an order of magnitude lower than those for same-duration operations on single qubits or pairs of qubits. These developments further suggest that incorporating small logical qubits into a measurement based code could substantially improve code performance.

Hybrid computer technique yields random signal probability distributions

NASA Technical Reports Server (NTRS)

Cameron, W. D.

1965-01-01

Hybrid computer determines the probability distributions of instantaneous and peak amplitudes of random signals. This combined digital and analog computer system reduces the errors and delays of manual data analysis.

The Effects of Aerobic Exercise and Gaming on Cognitive Performance.

PubMed

Douris, Peter C; Handrakis, John P; Apergis, Demitra; Mangus, Robert B; Patel, Rima; Limtao, Jessica; Platonova, Svetlana; Gregorio, Aladino; Luty, Elliot

2018-03-01

The purpose of our study was to investigate the effects of video gaming, aerobic exercise (biking), and the combination of these two activities on the domains of cognitive performance: selective attention, processing speed, and executive functioning. The study was a randomized clinical trial with 40 subjects (mean age 23.7 ± 1.8 years) randomized to one of four thirty-minute conditions: video gaming, biking, simultaneous gaming and biking, and a control condition. Cognitive performance was measured pre and post condition using the Stroop test and Trails B test. A mixed design was utilized. While video gaming, biking, simultaneous gaming and biking conditions improved selective attention and processing speed (p < 0.05), only the bike condition improved the highest order of cognitive performance, executive function (p < 0.01). There were no changes in cognitive performance for the control condition. Previous studies have shown that if tasks approach the limits of attentional capacity there is an increase in the overall chance for errors, known as the dual-task deficit. Simultaneous biking and gaming may have surpassed attentional capacity limits, ultimately increasing errors during the executive function tests of our cognitive performance battery. The results suggest that the fatiguing effects of a combined physically and mentally challenging task that extends after the exercise cessation may overcome the eventual beneficial cognitive effects derived from the physical exercise.

Continuous Glucose Monitoring in Newborn Infants

PubMed Central

Thomas, Felicity; Signal, Mathew; Harris, Deborah L.; Weston, Philip J.; Harding, Jane E.; Shaw, Geoffrey M.

2014-01-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. PMID:24876618

[Comparative volumetry of human testes using special types of testicular sonography, Prader's orchidometer, Schirren's circle and sliding caliber].

PubMed

Dörnberger, V; Dörnberger, G

1987-01-01

On 99 testes of corpses (death had occurred between 26 und 86 years) comparative volumetry was done. In the left surrounding capsules (without scrotal skin and tunica dartos) the testes were measured via real time sonography in a waterbath (7.5 MHz linear-scan), afterwards length, breadth and height were measured by a sliding calibre, the largest diameter (the length) of the testis was determined by Schirren's circle and finally the size of the testis was measured via Prader's orchidometer. After all the testes were surgically exposed, their volume (by litres) was determined according to Archimedes' principle. As for the Archimedes' principle a random mean error of 7% must be accepted, sonographic determination of the volume showed a random mean error of 15%. Whereas the accuracy of measurement increases with increasing volumes, both methods should be used with caution if the volumes are below 4 ml, since the possibilities of error are rather great. According to Prader's orchidometer the measured volumes on average were higher (+ 27%) with a random mean error of 19.5%. With Schirren's circle the obtained mean value was even higher (+ 52%) in comparison to the "real" volume by Archimedes' principle with a random mean error of 19%. The measurements of the testes in the left capsules by sliding calibre can be optimized, if one applies a correcting factor f (sliding calibre) = 0.39 for calculation of the testis volume corresponding to an ellipsoid. Here you will get the same mean value as in Archimedes' principle with a standard mean error of only 9%. If one applies the correction factor of real time sonography of testis f (sono) = 0.65 the mean value of sliding calibre measurements would be 68.8% too high with a standard mean error of 20.3%. For measurements via sliding calibre the calculation of the testis volume corresponding to an ellipsoid one should apply the smaller factor f (sliding calibre) = 0.39, because in this way the left capsules of testis and the epididymis are considered.

Developing and Validating Path-Dependent Uncertainty Estimates for use with the Regional Seismic Travel Time (RSTT) Model

NASA Astrophysics Data System (ADS)

Begnaud, M. L.; Anderson, D. N.; Phillips, W. S.; Myers, S. C.; Ballard, S.

2016-12-01

The Regional Seismic Travel Time (RSTT) tomography model has been developed to improve travel time predictions for regional phases (Pn, Sn, Pg, Lg) in order to increase seismic location accuracy, especially for explosion monitoring. The RSTT model is specifically designed to exploit regional phases for location, especially when combined with teleseismic arrivals. The latest RSTT model (version 201404um) has been released (http://www.sandia.gov/rstt). Travel time uncertainty estimates for RSTT are determined using one-dimensional (1D), distance-dependent error models, that have the benefit of being very fast to use in standard location algorithms, but do not account for path-dependent variations in error, and structural inadequacy of the RSTTT model (e.g., model error). Although global in extent, the RSTT tomography model is only defined in areas where data exist. A simple 1D error model does not accurately model areas where RSTT has not been calibrated. We are developing and validating a new error model for RSTT phase arrivals by mathematically deriving this multivariate model directly from a unified model of RSTT embedded into a statistical random effects model that captures distance, path and model error effects. An initial method developed is a two-dimensional path-distributed method using residuals. The goals for any RSTT uncertainty method are for it to be both readily useful for the standard RSTT user as well as improve travel time uncertainty estimates for location. We have successfully tested using the new error model for Pn phases and will demonstrate the method and validation of the error model for Sn, Pg, and Lg phases.

Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

PubMed

Thomas, Felicity; Signal, Mathew; Harris, Deborah L; Weston, Philip J; Harding, Jane E; Shaw, Geoffrey M; Chase, J Geoffrey

2014-05-01

Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. © 2014 Diabetes Technology Society.

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

Older driver training using video and global positioning system technology--a randomized controlled trial.

PubMed

Porter, Michelle M

2013-05-01

There is emerging evidence that older driver training programs with on-road instruction are more effective than driver education programs that are conducted only in the classroom. Although most programs have provided this additional in-vehicle training with a driving instructor and a dual-braked vehicle, technology could assist in providing this feedback. It was hypothesized that participants who received video and global positioning system (GPS) feedback (Video group) in addition to classroom education would improve to a greater extent than those who received a classroom-based course alone (Education) or Control participants. Fifty-four participants (32 men and 22 women), 70-89 years old, randomized to one of the three groups, completed the study. All participants underwent pre- and postintervention driving tests, in their own vehicle, on a standardized route, that were recorded with video and GPS equipment. The Video group met with a driving instructor to receive feedback on their driving errors in their preintervention driving test. A blinded assessor scored all driving tests in random order. The Video group significantly reduced their driving errors by 25% (p < .05) following the intervention, whereas the other two groups did not change significantly. Fifty-two percent of participants from the Video group improved their global safety rating, whereas only 5.3% in the Control and 22.2% in the Education groups did. This study suggests that direct driving feedback using video and GPS technology could be an effective and novel means to provide older driver education.

Accounting for dropout bias using mixed-effects models.

PubMed

Mallinckrodt, C H; Clark, W S; David, S R

2001-01-01

Treatment effects are often evaluated by comparing change over time in outcome measures. However, valid analyses of longitudinal data can be problematic when subjects discontinue (dropout) prior to completing the study. This study assessed the merits of likelihood-based repeated measures analyses (MMRM) compared with fixed-effects analysis of variance where missing values were imputed using the last observation carried forward approach (LOCF) in accounting for dropout bias. Comparisons were made in simulated data and in data from a randomized clinical trial. Subject dropout was introduced in the simulated data to generate ignorable and nonignorable missingness. Estimates of treatment group differences in mean change from baseline to endpoint from MMRM were, on average, markedly closer to the true value than estimates from LOCF in every scenario simulated. Standard errors and confidence intervals from MMRM accurately reflected the uncertainty of the estimates, whereas standard errors and confidence intervals from LOCF underestimated uncertainty.

Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials.

PubMed

Brown, Andrew W; Li, Peng; Bohan Brown, Michelle M; Kaiser, Kathryn A; Keith, Scott W; Oakes, J Michael; Allison, David B

2015-08-01

Cluster randomized controlled trials (cRCTs; also known as group randomized trials and community-randomized trials) are multilevel experiments in which units that are randomly assigned to experimental conditions are sets of grouped individuals, whereas outcomes are recorded at the individual level. In human cRCTs, clusters that are randomly assigned are typically families, classrooms, schools, worksites, or counties. With growing interest in community-based, public health, and policy interventions to reduce obesity or improve nutrition, the use of cRCTs has increased. Errors in the design, analysis, and interpretation of cRCTs are unfortunately all too common. This situation seems to stem in part from investigator confusion about how the unit of randomization affects causal inferences and the statistical procedures required for the valid estimation and testing of effects. In this article, we provide a brief introduction and overview of the importance of cRCTs and highlight and explain important considerations for the design, analysis, and reporting of cRCTs by using published examples. © 2015 American Society for Nutrition.

Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements

USGS Publications Warehouse

Tarrab, Leticia; Garcia, Carlos M.; Cantero, Mariano I.; Oberg, Kevin

2012-01-01

This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).

Learning in the Machine: Random Backpropagation and the Deep Learning Channel.

PubMed

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2018-07-01

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement of maintaining symmetric weights in a physical neural system. To better understand random backpropagation, we first connect it to the notions of local learning and learning channels. Through this connection, we derive several alternatives to RBP, including skipped RBP (SRPB), adaptive RBP (ARBP), sparse RBP, and their combinations (e.g. ASRBP) and analyze their computational complexity. We then study their behavior through simulations using the MNIST and CIFAR-10 bechnmark datasets. These simulations show that most of these variants work robustly, almost as well as backpropagation, and that multiplication by the derivatives of the activation functions is important. As a follow-up, we study also the low-end of the number of bits required to communicate error information over the learning channel. We then provide partial intuitive explanations for some of the remarkable properties of RBP and its variations. Finally, we prove several mathematical results, including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.

Differential effects of primary motor cortex and cerebellar transcranial direct current stimulation on motor learning in healthy individuals: A randomized double-blind sham-controlled study.

PubMed

Ehsani, F; Bakhtiary, A H; Jaberzadeh, S; Talimkhani, A; Hajihasani, A

2016-11-01

The purpose of study was to compare the effect of primary motor cortex (M1) and cerebellar anodal transcranial direct current stimulation (a-tDCS) on online and offline motor learning in healthy individuals. Fifty-nine healthy volunteers were randomly divided into three groups (n=20 in two experimental groups and n=19 in sham-control group). One experimental group received M1a-tDCSand another received cerebellar a-tDCS. The main outcome measure were response time (RT) and number of errors during serial response time test (SRTT) which were assessed prior, 35min and 48h after the interventions. Reduction of response time (RT) and error numbers at last block of the test compared to the first block was considered online learning. Comparison of assessments during retention tests was considered as short-term and long-term offline learning. Online RT reduction was not different among groups (P>0.05), while online error reduction was significantly greater in cerebellar a-tDCS than sham-control group (P<0.017). Moreover, a-tDCS on both M1 and cerebellar regions produced more long-term offline learning as compared to sham tDCS (P<0.01), while short-term offline RT reduction was significantly greater in M1a-tDCS than sham-control group (P<0.05). The findings indicated that although cerebellar a-tDCS enhances online learning and M1a-tDCS has more effect on short-term offline learning, both M 1 and cerebellar a-tDCS can be used as a boosting technique for improvement of offline motor learning in healthy individuals. Crown Copyright © 2016. Published by Elsevier Ireland Ltd. All rights reserved.

Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

NASA Astrophysics Data System (ADS)

Baum, Bryan A.; Wielicki, Bruce A.

1994-01-01

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence

NASA Astrophysics Data System (ADS)

Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo

2018-05-01

The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.

The Propagation of Errors in Experimental Data Analysis: A Comparison of Pre-and Post-Test Designs

ERIC Educational Resources Information Center

Gorard, Stephen

2013-01-01

Experimental designs involving the randomization of cases to treatment and control groups are powerful and under-used in many areas of social science and social policy. This paper reminds readers of the pre-and post-test, and the post-test only, designs, before explaining briefly how measurement errors propagate according to error theory. The…

Analysis of Errors Committed by Physics Students in Secondary Schools in Ilorin Metropolis, Nigeria

ERIC Educational Resources Information Center

Omosewo, Esther Ore; Akanbi, Abdulrasaq Oladimeji

2013-01-01

The study attempt to find out the types of error committed and influence of gender on the type of error committed by senior secondary school physics students in metropolis. Six (6) schools were purposively chosen for the study. One hundred and fifty five students' scripts were randomly sampled for the study. Joint Mock physics essay questions…

Two-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

NASA Astrophysics Data System (ADS)

Jun, Brian; Giarra, Matthew; Golz, Brian; Main, Russell; Vlachos, Pavlos

2016-11-01

We present a methodology to mitigate the major sources of error associated with two-dimensional confocal laser scanning microscopy (CLSM) images of nanoparticles flowing through a microfluidic channel. The correlation-based velocity measurements from CLSM images are subject to random error due to the Brownian motion of nanometer-sized tracer particles, and a bias error due to the formation of images by raster scanning. Here, we develop a novel ensemble phase correlation with dynamic optimal filter that maximizes the correlation strength, which diminishes the random error. In addition, we introduce an analytical model of CLSM measurement bias error correction due to two-dimensional image scanning of tracer particles. We tested our technique using both synthetic and experimental images of nanoparticles flowing through a microfluidic channel. We observed that our technique reduced the error by up to a factor of ten compared to ensemble standard cross correlation (SCC) for the images tested in the present work. Subsequently, we will assess our framework further, by interrogating nanoscale flow in the cell culture environment (transport within the lacunar-canalicular system) to demonstrate our ability to accurately resolve flow measurements in a biological system.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

NASA Astrophysics Data System (ADS)

Crevillén-García, D.; Power, H.

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

PubMed

Crevillén-García, D; Power, H

2017-08-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

PubMed Central

Power, H.

2017-01-01

In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error. PMID:28878974

Learning mechanisms to limit medication administration errors.

PubMed

Drach-Zahavy, Anat; Pud, Dorit

2010-04-01

This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.

Error coding simulations in C

NASA Technical Reports Server (NTRS)

Noble, Viveca K.

1994-01-01

When data is transmitted through a noisy channel, errors are produced within the data rendering it indecipherable. Through the use of error control coding techniques, the bit error rate can be reduced to any desired level without sacrificing the transmission data rate. The Astrionics Laboratory at Marshall Space Flight Center has decided to use a modular, end-to-end telemetry data simulator to simulate the transmission of data from flight to ground and various methods of error control. The simulator includes modules for random data generation, data compression, Consultative Committee for Space Data Systems (CCSDS) transfer frame formation, error correction/detection, error generation and error statistics. The simulator utilizes a concatenated coding scheme which includes CCSDS standard (255,223) Reed-Solomon (RS) code over GF(2(exp 8)) with interleave depth of 5 as the outermost code, (7, 1/2) convolutional code as an inner code and CCSDS recommended (n, n-16) cyclic redundancy check (CRC) code as the innermost code, where n is the number of information bits plus 16 parity bits. The received signal-to-noise for a desired bit error rate is greatly reduced through the use of forward error correction techniques. Even greater coding gain is provided through the use of a concatenated coding scheme. Interleaving/deinterleaving is necessary to randomize burst errors which may appear at the input of the RS decoder. The burst correction capability length is increased in proportion to the interleave depth. The modular nature of the simulator allows for inclusion or exclusion of modules as needed. This paper describes the development and operation of the simulator, the verification of a C-language Reed-Solomon code, and the possibility of using Comdisco SPW(tm) as a tool for determining optimal error control schemes.

Improved PPP Ambiguity Resolution Considering the Stochastic Characteristics of Atmospheric Corrections from Regional Networks

PubMed Central

Li, Yihe; Li, Bofeng; Gao, Yang

2015-01-01

With the increased availability of regional reference networks, Precise Point Positioning (PPP) can achieve fast ambiguity resolution (AR) and precise positioning by assimilating the satellite fractional cycle biases (FCBs) and atmospheric corrections derived from these networks. In such processing, the atmospheric corrections are usually treated as deterministic quantities. This is however unrealistic since the estimated atmospheric corrections obtained from the network data are random and furthermore the interpolated corrections diverge from the realistic corrections. This paper is dedicated to the stochastic modelling of atmospheric corrections and analyzing their effects on the PPP AR efficiency. The random errors of the interpolated corrections are processed as two components: one is from the random errors of estimated corrections at reference stations, while the other arises from the atmospheric delay discrepancies between reference stations and users. The interpolated atmospheric corrections are then applied by users as pseudo-observations with the estimated stochastic model. Two data sets are processed to assess the performance of interpolated corrections with the estimated stochastic models. The results show that when the stochastic characteristics of interpolated corrections are properly taken into account, the successful fix rate reaches 93.3% within 5 min for a medium inter-station distance network and 80.6% within 10 min for a long inter-station distance network. PMID:26633400

Improved PPP Ambiguity Resolution Considering the Stochastic Characteristics of Atmospheric Corrections from Regional Networks.

PubMed

Li, Yihe; Li, Bofeng; Gao, Yang

2015-11-30

With the increased availability of regional reference networks, Precise Point Positioning (PPP) can achieve fast ambiguity resolution (AR) and precise positioning by assimilating the satellite fractional cycle biases (FCBs) and atmospheric corrections derived from these networks. In such processing, the atmospheric corrections are usually treated as deterministic quantities. This is however unrealistic since the estimated atmospheric corrections obtained from the network data are random and furthermore the interpolated corrections diverge from the realistic corrections. This paper is dedicated to the stochastic modelling of atmospheric corrections and analyzing their effects on the PPP AR efficiency. The random errors of the interpolated corrections are processed as two components: one is from the random errors of estimated corrections at reference stations, while the other arises from the atmospheric delay discrepancies between reference stations and users. The interpolated atmospheric corrections are then applied by users as pseudo-observations with the estimated stochastic model. Two data sets are processed to assess the performance of interpolated corrections with the estimated stochastic models. The results show that when the stochastic characteristics of interpolated corrections are properly taken into account, the successful fix rate reaches 93.3% within 5 min for a medium inter-station distance network and 80.6% within 10 min for a long inter-station distance network.

Hypothesis-Testing Demands Trustworthy Data—A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy

PubMed Central

Krefeld-Schwalb, Antonia; Witte, Erich H.; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H0-hypothesis to a statistical H1-verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a “pure” Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis. PMID:29740363

Investigation of Optimal Digital Image Correlation Patterns for Deformation Measurement

NASA Technical Reports Server (NTRS)

Bomarito, G. F.; Ruggles, T. J.; Hochhalter, J. D.; Cannon, A. H.

2016-01-01

Digital image correlation (DIC) relies on the surface texture of a specimen to measure deformation. When the specimen itself has little or no texture, a pattern is applied to the surface which deforms with the specimen and acts as an artificial surface texture. Because the applied pattern has an effect on the accuracy of DIC, an ideal pattern is sought for which the error introduced into DIC measurements is minimal. In this work, a study is performed in which several DIC pattern quality metrics from the literature are correlated to DIC measurement error. The resulting correlations give insight on the optimality of DIC patterns in general. Optimizations are then performed to produce patterns which are well suited for DIC. These patterns are tested to show their relative benefits. Chief among these benefits are a reduction in error of approximately 30 with respect to a randomly generated pattern.

Hypothesis-Testing Demands Trustworthy Data-A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy.

PubMed

Krefeld-Schwalb, Antonia; Witte, Erich H; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H 0 -hypothesis to a statistical H 1 -verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a "pure" Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

PubMed

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-02-23

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements

PubMed Central

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-01-01

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472

Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit

NASA Technical Reports Server (NTRS)

Sun, Xiaoli; Skillman, David R.; Hoffman, Evan D.; Mao, Dandan; McGarry, Jan F.; Neumann, Gregory A.; McIntire, Leva; Zellar, Ronald S.; Davidson, Frederic M.; Fong, Wai H.;

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed 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. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Cognitive fatigue effects on physical performance: A systematic review and meta-analysis.

PubMed

McMorris, Terry; Barwood, Martin; Hale, Beverley J; Dicks, Matt; Corbett, Jo

2018-05-01

Recent research has examined the effect that undertaking a cognitively fatiguing task for ≤90 min has on subsequent physical performance. Cognitive fatigue is claimed to affect subsequent physical performance by inducing energy depletion in the brain, depletion of brain catecholamine neurotransmitters or changes in motivation. Observation of the psychophysiology and neurochemistry literature questions the ability of 90 min' cognitive activity to deplete energy or catecholamine resources. The purpose of this study, therefore, was to examine the evidence for cognitive fatigue having an effect on subsequent physical performance. A systematic, meta-analytic review was undertaken. We found a small but significant pooled effect size based on comparison between physical performance post-cognitive fatigue compared to post-control (g = -0.27, SE = -0.12, 95% CI -0.49 to -0.04, Z(10) = -2.283, p < 0.05). However, the results were not heterogenous (Q(10) = 2.789, p > 0.10, Τ 2  < 0.001), suggesting that the pooled effect size does not amount to a real effect and differences are due to random error. No publication bias was evident (Kendall's τ = -0.07, p > 0.05). Thus, the results are somewhat contradictory. The pooled effect size shows a small but significant negative effect of cognitive fatigue, however tests of heterogeneity show that the results are due to random error. Future research should use neuroscientific tests to ensure that cognitive fatigue has been achieved. Copyright © 2018 Elsevier Inc. All rights reserved.

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Assessing representation errors of IAGOS CO2, CO and CH4 profile observations: the impact of spatial variations in near-field emissions

NASA Astrophysics Data System (ADS)

Boschetti, Fabio; Thouret, Valerie; Nedelec, Philippe; Chen, Huilin; Gerbig, Christoph

2015-04-01

Airborne platforms have their main strength in the ability of collecting mixing ratio and meteorological data at different heights across a vertical profile, allowing an insight in the internal structure of the atmosphere. However, rental airborne platforms are usually expensive, limiting the number of flights that can be afforded and hence on the amount of data that can be collected. To avoid this disadvantage, the MOZAIC/IAGOS (Measurements of Ozone and water vapor by Airbus In-service airCraft/In-service Aircraft for a Global Observing System) program makes use of commercial airliners, providing data on a regular basis. It is therefore considered an important tool in atmospheric investigations. However, due to the nature of said platforms, MOZAIC/IAGOS's profiles are located near international airports, which are usually significant emission sources, and are in most cases close to major urban settlements, characterized by higher anthropogenic emissions compared to rural areas. When running transport models at finite resolution, these local emissions can heavily affect measurements resulting in biases in model/observation mismatch. Model/observation mismatch can include different aspects in both horizontal and vertical direction, for example spatial and temporal resolution of the modeled fluxes, or poorly represented convective transport or turbulent mixing in the boundary layer. In the framework of the IGAS (IAGOS for GMES Atmospheric Service) project, whose aim is to improve connections between data collected by MOZAIC/IAGOS and Copernicus Atmospheric Service, the present study is focused on the effect of the spatial resolution of emission fluxes, referred to here as representation error. To investigate this, the Lagrangian transport model STILT (Stochastic Time Inverted Lagrangian Transport) was coupled with EDGAR (Emission Database for Global Atmospheric Research) version-4.3 emission inventory at European regional scale. EDGAR's simulated fluxes for CO, CO2 and CH4 with a spatial resolution of 10x10 km for the time frame 2006-2011 was be aggregated into coarser and coarser grid cells in order to evaluate the representation error at different spatial scales. The dependence of representation error from wind direction and month of the year was evaluated for different location in the European domain, for both random and bias component. The representation error was then validated against the model-data mismatch derived from the comparison of MACC (Monitoring Atmospheric Composition and Climate) reanalysis with IAGOS observations for CO to investigate its suitability for modeling applications. We found that the random and bias components of the representation error show a similar pattern dependent on wind direction. In addition, we found a clear linear relationship between the representation error and the model-data mismatch for both (random and bias) components, indicating that about 50% of the model-data mismatch is related to the representation error. This suggests that the representation error derived using STILT provides useful information for better understanding causes for model-data mismatch.

Evaluating methods of correcting for multiple comparisons implemented in SPM12 in social neuroscience fMRI studies: an example from moral psychology.

PubMed

Han, Hyemin; Glenn, Andrea L

2018-06-01

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social neuroscience that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial and also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in Statistical Parametric Mapping 12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxelwise thresholding with familywise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods.

Application of random effects to the study of resource selection by animals

USGS Publications Warehouse

Gillies, C.S.; Hebblewhite, M.; Nielsen, S.E.; Krawchuk, M.A.; Aldridge, Cameron L.; Frair, J.L.; Saher, D.J.; Stevens, C.E.; Jerde, C.L.

2006-01-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence.2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability.3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed.4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects.5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection.6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Application of random effects to the study of resource selection by animals.

PubMed

Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Optimization of planar PIV-based pressure estimates in laminar and turbulent wakes

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2017-05-01

The performance of four pressure estimation techniques using Eulerian material acceleration estimates from planar, two-component Particle Image Velocimetry (PIV) data were evaluated in a bluff body wake. To allow for the ground truth comparison of the pressure estimates, direct numerical simulations of flow over a circular cylinder were used to obtain synthetic velocity fields. Direct numerical simulations were performed for Re_D = 100, 300, and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A parametric study encompassing a range of temporal and spatial resolutions was performed for each Re_D. The effect of random noise typical of experimental velocity measurements was also evaluated. The results identified optimal temporal and spatial resolutions that minimize the propagation of random and truncation errors to the pressure field estimates. A model derived from linear error propagation through the material acceleration central difference estimators was developed to predict these optima, and showed good agreement with the results from common pressure estimation techniques. The results of the model are also shown to provide acceptable first-order approximations for sampling parameters that reduce error propagation when Lagrangian estimations of material acceleration are employed. For pressure integration based on planar PIV, the effect of flow three-dimensionality was also quantified, and shown to be most pronounced at higher Reynolds numbers downstream of the vortex formation region, where dominant vortices undergo substantial three-dimensional deformations. The results of the present study provide a priori recommendations for the use of pressure estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Validation of self-reported start year of mobile phone use in a Swedish case-control study on radiofrequency fields and acoustic neuroma risk.

PubMed

Pettersson, David; Bottai, Matteo; Mathiesen, Tiit; Prochazka, Michaela; Feychting, Maria

2015-01-01

The possible effect of radiofrequency exposure from mobile phones on tumor risk has been studied since the late 1990s. Yet, empirical information about recall of the start of mobile phone use among adult cases and controls has never been reported. Limited knowledge about recall errors hampers interpretations of the epidemiological evidence. We used network operator data to validate the self-reported start year of mobile phone use in a case-control study of mobile phone use and acoustic neuroma risk. The answers of 96 (29%) cases and 111 (22%) controls could be included in the validation. The larger proportion of cases reflects a more complete and detailed reporting of subscription history. Misclassification was substantial, with large random errors, small systematic errors, and no significant differences between cases and controls. The average difference between self-reported and operator start year was -0.62 (95% confidence interval: -1.42, 0.17) years for cases and -0.71 (-1.50, 0.07) years for controls, standard deviations were 3.92 and 4.17 years, respectively. Agreement between self-reported and operator-recorded data categorized into short, intermediate and long-term use was moderate (kappa statistic: 0.42). Should an association exist, dilution of risk estimates and distortion of exposure-response patterns for time since first mobile phone use could result from the large random errors in self-reported start year. Retrospective collection of operator data likely leads to a selection of "good reporters", with a higher proportion of cases. Thus, differential recall cannot be entirely excluded.

Laboratory issues: use of nutritional biomarkers.

PubMed

Blanck, Heidi Michels; Bowman, Barbara A; Cooper, Gerald R; Myers, Gary L; Miller, Dayton T

2003-03-01

Biomarkers of nutritional status provide alternative measures of dietary intake. Like the error and variation associated with dietary intake measures, the magnitude and impact of both biological (preanalytical) and laboratory (analytical) variability need to be considered when one is using biomarkers. When choosing a biomarker, it is important to understand how it relates to nutritional intake and the specific time frame of exposure it reflects as well as how it is affected by sampling and laboratory procedures. Biological sources of variation that arise from genetic and disease states of an individual affect biomarkers, but they are also affected by nonbiological sources of variation arising from specimen collection and storage, seasonality, time of day, contamination, stability and laboratory quality assurance. When choosing a laboratory for biomarker assessment, researchers should try to make sure random and systematic error is minimized by inclusion of certain techniques such as blinding of laboratory staff to disease status and including external pooled standards to which laboratory staff are blinded. In addition analytic quality control should be ensured by use of internal standards or certified materials over the entire range of possible values to control method accuracy. One must consider the effect of random laboratory error on measurement precision and also understand the method's limit of detection and the laboratory cutpoints. Choosing appropriate cutpoints and reducing error is extremely important in nutritional epidemiology where weak associations are frequent. As part of this review, serum lipids are included as an example of a biomarker whereby collaborative efforts have been put forth to both understand biological sources of variation and standardize laboratory results.

Performance consequences of alternating directional control-response compatibility: evidence from a coal mine shuttle car simulator.

PubMed

Zupanc, Christine M; Burgess-Limerick, Robin J; Wallis, Guy

2007-08-01

To investigate error and reaction time consequences of alternating compatible and incompatible steering arrangements during a simulated obstacle avoidance task. Underground coal mine shuttle cars provide an example of a vehicle in which operators are required to alternate between compatible and incompatible steering configurations. This experiment examines the performance of 48 novice participants in a virtual analogy of an underground coal mine shuttle car. Participants were randomly assigned to a compatible condition, an incompatible condition, an alternating condition in which compatibility alternated within and between hands, or an alternating condition in which compatibility alternated between hands. Participants made fewer steering direction errors and made correct steering responses more quickly in the compatible condition. Error rate decreased over time in the incompatible condition. A compatibility effect for both errors and reaction time was also found when the control-response relationship alternated; however, performance improvements over time were not consistent. Isolating compatibility to a hand resulted in reduced error rate and faster reaction time than when compatibility alternated within and between hands. The consequences of alternating control-response relationships are higher error rates and slower responses, at least in the early stages of learning. This research highlights the importance of ensuring consistently compatible human-machine directional control-response relationships.

Magnetic field errors tolerances of Nuclotron booster

NASA Astrophysics Data System (ADS)

Butenko, Andrey; Kazinova, Olha; Kostromin, Sergey; Mikhaylov, Vladimir; Tuzikov, Alexey; Khodzhibagiyan, Hamlet

2018-04-01

Generation of magnetic field in units of booster synchrotron for the NICA project is one of the most important conditions for getting the required parameters and qualitative accelerator operation. Research of linear and nonlinear dynamics of ion beam 197Au31+ in the booster have carried out with MADX program. Analytical estimation of magnetic field errors tolerance and numerical computation of dynamic aperture of booster DFO-magnetic lattice are presented. Closed orbit distortion with random errors of magnetic fields and errors in layout of booster units was evaluated.

An extended Reed Solomon decoder design

NASA Technical Reports Server (NTRS)

Chen, J.; Owsley, P.; Purviance, J.

1991-01-01

It has previously been shown that the Reed-Solomon (RS) codes can correct errors beyond the Singleton and Rieger Bounds with an arbitrarily small probability of a miscorrect. That is, an (n,k) RS code can correct more than (n-k)/2 errors. An implementation of such an RS decoder is presented in this paper. An existing RS decoder, the AHA4010, is utilized in this work. This decoder is especially useful for errors which are patterned with a long burst plus some random errors.

Research on the method of improving the accuracy of CMM (coordinate measuring machine) testing aspheric surface

NASA Astrophysics Data System (ADS)

Cong, Wang; Xu, Lingdi; Li, Ang

2017-10-01

Large aspheric surface which have the deviation with spherical surface are being used widely in various of optical systems. Compared with spherical surface, Large aspheric surfaces have lots of advantages, such as improving image quality, correcting aberration, expanding field of view, increasing the effective distance and make the optical system compact, lightweight. Especially, with the rapid development of space optics, space sensor resolution is required higher and viewing angle is requred larger. Aspheric surface will become one of the essential components in the optical system. After finishing Aspheric coarse Grinding surface profile error is about Tens of microns[1].In order to achieve the final requirement of surface accuracy,the aspheric surface must be quickly modified, high precision testing is the basement of rapid convergence of the surface error . There many methods on aspheric surface detection[2], Geometric ray detection, hartmann detection, ronchi text, knifeedge method, direct profile test, interferometry, while all of them have their disadvantage[6]. In recent years the measure of the aspheric surface become one of the import factors which are restricting the aspheric surface processing development. A two meter caliber industrial CMM coordinate measuring machine is avaiable, but it has many drawbacks such as large detection error and low repeatability precision in the measurement of aspheric surface coarse grinding , which seriously affects the convergence efficiency during the aspherical mirror processing. To solve those problems, this paper presents an effective error control, calibration and removal method by calibration mirror position of the real-time monitoring and other effective means of error control, calibration and removal by probe correction and the measurement mode selection method to measure the point distribution program development. This method verified by real engineer examples, this method increases the original industrial-grade coordinate system nominal measurement accuracy PV value of 7 microns to 4microns, Which effectively improves the grinding efficiency of aspheric mirrors and verifies the correctness of the method. This paper also investigates the error detection and operation control method, the error calibration of the CMM and the random error calibration of the CMM .

Cardiac examination and the effect of dual-processing instruction in a cardiopulmonary simulator.

PubMed

Sibbald, Matt; McKinney, James; Cavalcanti, Rodrigo B; Yu, Eric; Wood, David A; Nair, Parvathy; Eva, Kevin W; Hatala, Rose

2013-08-01

Use of dual-processing has been widely touted as a strategy to reduce diagnostic error in clinical medicine. However, this strategy has not been tested among medical trainees with complex diagnostic problems. We sought to determine whether dual-processing instruction could reduce diagnostic error across a spectrum of experience with trainees undertaking cardiac physical exam. Three experiments were conducted using a similar design to teach cardiac physical exam using a cardiopulmonary simulator. One experiment was conducted in each of three groups: experienced, intermediate and novice trainees. In all three experiments, participants were randomized to receive undirected or dual-processing verbal instruction during teaching, practice and testing phases. When tested, dual-processing instruction did not change the probability assigned to the correct diagnosis in any of the three experiments. Among intermediates, there was an apparent interaction between the diagnosis tested and the effect of dual-processing instruction. Among relative novices, dual processing instruction may have dampened the harmful effect of a bias away from the correct diagnosis. Further work is needed to define the role of dual-processing instruction to reduce cognitive error. This study suggests that it cannot be blindly applied to complex diagnostic problems such as cardiac physical exam.

Metacontrast masking and attention do not interact.

PubMed

Agaoglu, Sevda; Breitmeyer, Bruno; Ogmen, Haluk

2016-07-01

Visual masking and attention have been known to control the transfer of information from sensory memory to visual short-term memory. A natural question is whether these processes operate independently or interact. Recent evidence suggests that studies that reported interactions between masking and attention suffered from ceiling and/or floor effects. The objective of the present study was to investigate whether metacontrast masking and attention interact by using an experimental design in which saturation effects are avoided. We asked observers to report the orientation of a target bar randomly selected from a display containing either two or six bars. The mask was a ring that surrounded the target bar. Attentional load was controlled by set-size and masking strength by the stimulus onset asynchrony between the target bar and the mask ring. We investigated interactions between masking and attention by analyzing two different aspects of performance: (i) the mean absolute response errors and (ii) the distribution of signed response errors. Our results show that attention affects observers' performance without interacting with masking. Statistical modeling of response errors suggests that attention and metacontrast masking exert their effects by independently modulating the probability of "guessing" behavior. Implications of our findings for models of attention are discussed.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Social contact patterns can buffer costs of forgetting in the evolution of cooperation.

PubMed

Stevens, Jeffrey R; Woike, Jan K; Schooler, Lael J; Lindner, Stefan; Pachur, Thorsten

2018-06-13

Analyses of the evolution of cooperation often rely on two simplifying assumptions: (i) individuals interact equally frequently with all social network members and (ii) they accurately remember each partner's past cooperation or defection. Here, we examine how more realistic, skewed patterns of contact-in which individuals interact primarily with only a subset of their network's members-influence cooperation. In addition, we test whether skewed contact patterns can counteract the decrease in cooperation caused by memory errors (i.e. forgetting). Finally, we compare two types of memory error that vary in whether forgotten interactions are replaced with random actions or with actions from previous encounters. We use evolutionary simulations of repeated prisoner's dilemma games that vary agents' contact patterns, forgetting rates and types of memory error. We find that highly skewed contact patterns foster cooperation and also buffer the detrimental effects of forgetting. The type of memory error used also influences cooperation rates. Our findings reveal previously neglected but important roles of contact pattern, type of memory error and the interaction of contact pattern and memory on cooperation. Although cognitive limitations may constrain the evolution of cooperation, social contact patterns can counteract some of these constraints. © 2018 The Author(s).

Nonconvergence of the Wang-Landau algorithms with multiple random walkers.

PubMed

Belardinelli, R E; Pereyra, V D

2016-05-01

This paper discusses some convergence properties in the entropic sampling Monte Carlo methods with multiple random walkers, particularly in the Wang-Landau (WL) and 1/t algorithms. The classical algorithms are modified by the use of m-independent random walkers in the energy landscape to calculate the density of states (DOS). The Ising model is used to show the convergence properties in the calculation of the DOS, as well as the critical temperature, while the calculation of the number π by multiple dimensional integration is used in the continuum approximation. In each case, the error is obtained separately for each walker at a fixed time, t; then, the average over m walkers is performed. It is observed that the error goes as 1/sqrt[m]. However, if the number of walkers increases above a certain critical value m>m_{x}, the error reaches a constant value (i.e., it saturates). This occurs for both algorithms; however, it is shown that for a given system, the 1/t algorithm is more efficient and accurate than the similar version of the WL algorithm. It follows that it makes no sense to increase the number of walkers above a critical value m_{x}, since it does not reduce the error in the calculation. Therefore, the number of walkers does not guarantee convergence.

Estimating the Standard Error of the Impact Estimator in Individually Randomized Trials with Clustering

ERIC Educational Resources Information Center

Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F.

2016-01-01

In the "individually randomized group treatment" (IRGT) experimental design, individuals are first randomly assigned to a treatment arm or a control arm, but then within each arm, are grouped together (e.g., within classrooms/schools, through shared case managers, in group therapy sessions, through shared doctors, etc.) to receive…

The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method

PubMed Central

2014-01-01

Background The DerSimonian and Laird approach (DL) is widely used for random effects meta-analysis, but this often results in inappropriate type I error rates. The method described by Hartung, Knapp, Sidik and Jonkman (HKSJ) is known to perform better when trials of similar size are combined. However evidence in realistic situations, where one trial might be much larger than the other trials, is lacking. We aimed to evaluate the relative performance of the DL and HKSJ methods when studies of different sizes are combined and to develop a simple method to convert DL results to HKSJ results. Methods We evaluated the performance of the HKSJ versus DL approach in simulated meta-analyses of 2–20 trials with varying sample sizes and between-study heterogeneity, and allowing trials to have various sizes, e.g. 25% of the trials being 10-times larger than the smaller trials. We also compared the number of “positive” (statistically significant at p < 0.05) findings using empirical data of recent meta-analyses with > = 3 studies of interventions from the Cochrane Database of Systematic Reviews. Results The simulations showed that the HKSJ method consistently resulted in more adequate error rates than the DL method. When the significance level was 5%, the HKSJ error rates at most doubled, whereas for DL they could be over 30%. DL, and, far less so, HKSJ had more inflated error rates when the combined studies had unequal sizes and between-study heterogeneity. The empirical data from 689 meta-analyses showed that 25.1% of the significant findings for the DL method were non-significant with the HKSJ method. DL results can be easily converted into HKSJ results. Conclusions Our simulations showed that the HKSJ method consistently results in more adequate error rates than the DL method, especially when the number of studies is small, and can easily be applied routinely in meta-analyses. Even with the HKSJ method, extra caution is needed when there are = <5 studies of very unequal sizes. PMID:24548571

Measurement error in environmental epidemiology and the shape of exposure-response curves.

PubMed

Rhomberg, Lorenz R; Chandalia, Juhi K; Long, Christopher M; Goodman, Julie E

2011-09-01

Both classical and Berkson exposure measurement errors as encountered in environmental epidemiology data can result in biases in fitted exposure-response relationships that are large enough to affect the interpretation and use of the apparent exposure-response shapes in risk assessment applications. A variety of sources of potential measurement error exist in the process of estimating individual exposures to environmental contaminants, and the authors review the evaluation in the literature of the magnitudes and patterns of exposure measurement errors that prevail in actual practice. It is well known among statisticians that random errors in the values of independent variables (such as exposure in exposure-response curves) may tend to bias regression results. For increasing curves, this effect tends to flatten and apparently linearize what is in truth a steeper and perhaps more curvilinear or even threshold-bearing relationship. The degree of bias is tied to the magnitude of the measurement error in the independent variables. It has been shown that the degree of bias known to apply to actual studies is sufficient to produce a false linear result, and that although nonparametric smoothing and other error-mitigating techniques may assist in identifying a threshold, they do not guarantee detection of a threshold. The consequences of this could be great, as it could lead to a misallocation of resources towards regulations that do not offer any benefit to public health.

Acute Effects of Mecamylamine and Varenicline on Cognitive Performance in Non-smokers With and Without Schizophrenia

PubMed Central

Roh, Sungwon; Hoeppner, Susanne S.; Schoenfeld, David; Fullerton, Catherine A.; Stoeckel, Luke E.; Evins, A. Eden

2013-01-01

Rationale Nicotinic acetylcholine receptors (nAChRs) have been implicated in the pathophysiology of cognitive deficits in the domains of attention and memory in schizophrenia. While nicotinic agonists and antagonists have been proposed as smoking cessation aids, few comparisons have been made of these agents on cognitive performance in individuals with schizophrenia. Objectives This study investigated the acute effects of a nAChR antagonist, mecamylamine, and partial agonist, varenicline, on cognitive function in non-smokers with and without schizophrenia. Methods Single oral doses of mecamylamine, 10 mg, varenicline, 1 mg, and placebo were administered, one week apart, in random order to adults with schizophrenia (n=30) and to healthy volunteers (n=41) in a double-blind, crossover design. The primary outcome of interest was sustained attention as assessed with hit reaction time variability (HRT-SD) on the identical pairs continuous performance test (CPT-IP). Results Mecamylamine worsened performance on CPT-IP HRT-SD, a measure of attention, compared to varenicline in both groups. Performance on mecamylamine was worse than performance on both placebo and varenicline on several additional measures of attention, including CPT-IP hit reaction time (HRT) and random errors at various levels of task difficulty. There was a treatment by diagnosis interaction, such that mecamylamine worsened performance on CPT-IP 2-digit HRT, 3-digit random errors, and 4-digit hit rate compared to placebo and varenicline in participants with schizophrenia, effects not observed in controls. Conclusions These findings support a role for nAChR’s in attention and suggest that those with schizophrenia may be particularly sensitive to nAChR blockade. PMID:24114425

a Weighted Closed-Form Solution for Rgb-D Data Registration

NASA Astrophysics Data System (ADS)

Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.

2016-06-01

Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.

Effects of Hip Strengthening on Neuromuscular Control, Hip Strength, and Self-Reported Functional Deficits in Individuals With Chronic Ankle Instability.

PubMed

Smith, Brent I; Curtis, Denice; Docherty, Carrie L

2018-06-12

Deficits in ankle and hip strength and lower-extremity postural control are associated with chronic ankle instability (CAI). Following strength training, muscle groups demonstrate increased strength. This change is partially credited to improved neuromuscular control, and many studies have investigated ankle protocols for subjects with CAI. The effects of isolating hip musculature in strength training protocols in this population are not well understood. To examine the effects of hip strengthening on clinical and self-reported outcomes in patients with CAI. Prospective randomized controlled clinical trial. Athletic training facility. Twenty-six participants with CAI (12 males and 14 females; age = 20.9 [1.5] y, height = 170.0 [12.7] cm, and mass = 77.5 [17.5] kg) were randomly assigned to training or control groups. Participants completed either 4 weeks of supervised hip strengthening (resistance bands 3 times a week) or no intervention. Participants were assessed on 4 clinical measures (Star Excursion Balance Test in the anterior, posteromedial, and posterolateral directions; Balance Error Scoring System; hip external rotation strength; and hip abduction strength) and a patient-reported measure (the Foot and Ankle Ability Measure activities of daily living and sports subscales) before and after the 4-week training period. The training group displayed significantly improved posttest measures compared with the control group for hip abduction strength (training: 446.3 [77.4] N, control: 314.7 [49.6] N, P < .01); hip external rotation strength (training: 222.1 [48.7] N, control: 169.4 [34.6] N, P < .01); Star Excursion Balance Test reach in the anterior (training: 93.1% [7.4%], control: 90.2% [7.9%], P < .01), posteromedial (training: 96.3% [8.9%], control: 88.0% [8.8%], P < .01), and posterolateral (training: 95.4% [11.1%], control: 86.6% [9.6%], P < .01) directions; Balance Error Scoring System total errors (training: 9.9 [6.3] errors, control: 21.2 [6.3] errors, P < .01); and the Foot and Ankle Ability Measure-sports score (training: 88.0 [12.6], control: 84.8 [10.9], P < .01). Improved clinical and patient-reported outcomes in the training group suggest hip strengthening is beneficial in the management and prevention of recurrent symptoms associated with CAI.

Prevalence of medication errors in primary health care at Bahrain Defence Force Hospital – prescription-based study

PubMed Central

Aljasmi, Fatema; Almalood, Fatema

2018-01-01

Background One of the important activities that physicians – particularly general practitioners – perform is prescribing. It occurs in most health care facilities and especially in primary health care (PHC) settings. Objectives This study aims to determine what types of prescribing errors are made in PHC at Bahrain Defence Force (BDF) Hospital, and how common they are. Methods This was a retrospective study of data from PHC at BDF Hospital. The data consisted of 379 prescriptions randomly selected from the pharmacy between March and May 2013, and errors in the prescriptions were classified into five types: major omission, minor omission, commission, integration, and skill-related errors. Results Of the total prescriptions, 54.4% (N=206) were given to male patients and 45.6% (N=173) to female patients; 24.8% were given to patients under the age of 10 years. On average, there were 2.6 drugs per prescription. In the prescriptions, 8.7% of drugs were prescribed by their generic names, and 28% (N=106) of prescriptions included an antibiotic. Out of the 379 prescriptions, 228 had an error, and 44.3% (N=439) of the 992 prescribed drugs contained errors. The proportions of errors were as follows: 9.9% (N=38) were minor omission errors; 73.6% (N=323) were major omission errors; 9.3% (N=41) were commission errors; and 17.1% (N=75) were skill-related errors. Conclusion This study provides awareness of the presence of prescription errors and frequency of the different types of errors that exist in this hospital. Understanding the different types of errors could help future studies explore the causes of specific errors and develop interventions to reduce them. Further research should be conducted to understand the causes of these errors and demonstrate whether the introduction of electronic prescriptions has an effect on patient outcomes. PMID:29445304

Comparison of error-based and errorless learning for people with severe traumatic brain injury: study protocol for a randomized control trial.

PubMed

Ownsworth, Tamara; Fleming, Jennifer; Tate, Robyn; Shum, David H K; Griffin, Janelle; Schmidt, Julia; Lane-Brown, Amanda; Kendall, Melissa; Chevignard, Mathilde

2013-11-05

Poor skills generalization poses a major barrier to successful outcomes of rehabilitation after traumatic brain injury (TBI). Error-based learning (EBL) is a relatively new intervention approach that aims to promote skills generalization by teaching people internal self-regulation skills, or how to anticipate, monitor and correct their own errors. This paper describes the protocol of a study that aims to compare the efficacy of EBL and errorless learning (ELL) for improving error self-regulation, behavioral competency, awareness of deficits and long-term outcomes after TBI. This randomized, controlled trial (RCT) has two arms (EBL and ELL); each arm entails 8 × 2 h training sessions conducted within the participants' homes. The first four sessions involve a meal preparation activity, and the final four sessions incorporate a multitasking errand activity. Based on a sample size estimate, 135 participants with severe TBI will be randomized into either the EBL or ELL condition. The primary outcome measure assesses error self-regulation skills on a task related to but distinct from training. Secondary outcomes include measures of self-monitoring and self-regulation, behavioral competency, awareness of deficits, role participation and supportive care needs. Assessments will be conducted at pre-intervention, post-intervention, and at 6-months post-intervention. This study seeks to determine the efficacy and long-term impact of EBL for training internal self-regulation strategies following severe TBI. In doing so, the study will advance theoretical understanding of the role of errors in task learning and skills generalization. EBL has the potential to reduce the length and costs of rehabilitation and lifestyle support because the techniques could enhance generalization success and lifelong application of strategies after TBI. ACTRN12613000585729.

A meta-analysis of inhibitory-control deficits in patients diagnosed with Alzheimer's dementia.

PubMed

Kaiser, Anna; Kuhlmann, Beatrice G; Bosnjak, Michael

2018-05-10

The authors conducted meta-analyses to determine the magnitude of performance impairments in patients diagnosed with Alzheimer's dementia (AD) compared with healthy aging (HA) controls on eight tasks commonly used to measure inhibitory control. Response time (RT) and error rates from a total of 64 studies were analyzed with random-effects models (overall effects) and mixed-effects models (moderator analyses). Large differences between AD patients and HA controls emerged in the basic inhibition conditions of many of the tasks with AD patients often performing slower, overall d = 1.17, 95% CI [0.88-1.45], and making more errors, d = 0.83 [0.63-1.03]. However, comparably large differences were also present in performance on many of the baseline control-conditions, d = 1.01 [0.83-1.19] for RTs and d = 0.44 [0.19-0.69] for error rates. A standardized derived inhibition score (i.e., control-condition score - inhibition-condition score) suggested no significant mean group difference for RTs, d = -0.07 [-0.22-0.08], and only a small difference for errors, d = 0.24 [-0.12-0.60]. Effects systematically varied across tasks and with AD severity. Although the error rate results suggest a specific deterioration of inhibitory-control abilities in AD, further processes beyond inhibitory control (e.g., a general reduction in processing speed and other, task-specific attentional processes) appear to contribute to AD patients' performance deficits observed on a variety of inhibitory-control tasks. Nonetheless, the inhibition conditions of many of these tasks well discriminate between AD patients and HA controls. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Robust Tomography using Randomized Benchmarking

NASA Astrophysics Data System (ADS)

Silva, Marcus; Kimmel, Shelby; Johnson, Blake; Ryan, Colm; Ohki, Thomas

2013-03-01

Conventional randomized benchmarking (RB) can be used to estimate the fidelity of Clifford operations in a manner that is robust against preparation and measurement errors -- thus allowing for a more accurate and relevant characterization of the average error in Clifford gates compared to standard tomography protocols. Interleaved RB (IRB) extends this result to the extraction of error rates for individual Clifford gates. In this talk we will show how to combine multiple IRB experiments to extract all information about the unital part of any trace preserving quantum process. Consequently, one can compute the average fidelity to any unitary, not just the Clifford group, with tighter bounds than IRB. Moreover, the additional information can be used to design improvements in control. MS, BJ, CR and TO acknowledge support from IARPA under contract W911NF-10-1-0324.

Screening actuator locations for static shape control

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

1990-01-01

Correction of shape distortion due to zero-mean normally distributed errors in structural sizes which are random variables is examined. A bound on the maximum improvement in the expected value of the root-mean-square shape error is obtained. The shape correction associated with the optimal actuators is also characterized. An actuator effectiveness index is developed and shown to be helpful in screening actuator locations in the structure. The results are specialized to a simple form for truss structures composed of nominally identical members. The bound and effectiveness index are tested on a 55-m radiometer antenna truss structure. It is found that previously obtained results for optimum actuators had a performance close to the bound obtained here. Furthermore, the actuators associated with the optimum design are shown to have high effectiveness indices. Since only a small fraction of truss elements tend to have high effectiveness indices, the proposed screening procedure can greatly reduce the number of truss members that need to be considered as actuator sites.

Nutritional therapy in cirrhosis or alcoholic hepatitis: a systematic review and meta-analysis.

PubMed

Fialla, Annette D; Israelsen, Mads; Hamberg, Ole; Krag, Aleksander; Gluud, Lise Lotte

2015-09-01

Patients with cirrhosis and alcoholic hepatitis are often malnourished and have a superimposed stress metabolism, which increases nutritional demands. We performed a systematic review on the effects of nutritional therapy vs. no intervention for patients with cirrhosis or alcoholic hepatitis. We included trials on nutritional therapy designed to fulfil at least 75% of daily nutritional demand. Authors extracted data in an independent manner. Random-effects and fixed-effect meta-analyses were performed and the results expressed as risk ratios (RR) with 95% confidence intervals (CI). Sequential analyses were performed to evaluate the risk of spurious findings because of random and systematic errors. Subgroup and sensitivity analyses were performed to evaluate the risk of bias and sources of between trial heterogeneity. Thirteen randomized controlled trials with 329 allocated to enteral (nine trials) or intravenous (four trials) nutrition and 334 controls. All trials were classed as having a high risk of bias. Random-effects meta-analysis showed that nutritional therapy reduced mortality 0.80 (95% CI, 0.64 to 0.99). The result was not confirmed in sequential analysis. Fixed-effect analysis suggested that nutrition prevented overt hepatic encephalopathy (0.73; 95% CI, 0.55 to 0.96) and infection (0.66; 95% CI, 0.45 to 0.98, respectively), but the results were not confirmed in random-effects analyses. Our review suggests that nutritional therapy may have beneficial effects on clinical outcomes in cirrhosis and alcoholic hepatitis. High-quality trials are needed to verify our findings. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Distributional assumptions in food and feed commodities- development of fit-for-purpose sampling protocols.

PubMed

Paoletti, Claudia; Esbensen, Kim H

2015-01-01

Material heterogeneity influences the effectiveness of sampling procedures. Most sampling guidelines used for assessment of food and/or feed commodities are based on classical statistical distribution requirements, the normal, binomial, and Poisson distributions-and almost universally rely on the assumption of randomness. However, this is unrealistic. The scientific food and feed community recognizes a strong preponderance of non random distribution within commodity lots, which should be a more realistic prerequisite for definition of effective sampling protocols. Nevertheless, these heterogeneity issues are overlooked as the prime focus is often placed only on financial, time, equipment, and personnel constraints instead of mandating acquisition of documented representative samples under realistic heterogeneity conditions. This study shows how the principles promulgated in the Theory of Sampling (TOS) and practically tested over 60 years provide an effective framework for dealing with the complete set of adverse aspects of both compositional and distributional heterogeneity (material sampling errors), as well as with the errors incurred by the sampling process itself. The results of an empirical European Union study on genetically modified soybean heterogeneity, Kernel Lot Distribution Assessment are summarized, as they have a strong bearing on the issue of proper sampling protocol development. TOS principles apply universally in the food and feed realm and must therefore be considered the only basis for development of valid sampling protocols free from distributional constraints.

Defining robustness protocols: a method to include and evaluate robustness in clinical plans

NASA Astrophysics Data System (ADS)

McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.

2015-04-01

We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.

Accounting for unknown foster dams in the genetic evaluation of embryo transfer progeny.

PubMed

Suárez, M J; Munilla, S; Cantet, R J C

2015-02-01

Animals born by embryo transfer (ET) are usually not included in the genetic evaluation of beef cattle for preweaning growth if the recipient dam is unknown. This is primarily to avoid potential bias in the estimation of the unknown age of dam. We present a method that allows including records of calves with unknown age of dam. Assumptions are as follows: (i) foster cows belong to the same breed being evaluated, (ii) there is no correlation between the breeding value (BV) of the calf and the maternal BV of the recipient cow, and (iii) cows of all ages are used as recipients. We examine the issue of bias for the fixed level of unknown age of dam (AOD) and propose an estimator of the effect based on classical measurement error theory (MEM) and a Bayesian approach. Using stochastic simulation under random mating or selection, the MEM estimating equations were compared with BLUP in two situations as follows: (i) full information (FI); (ii) missing AOD information on some dams. Predictions of breeding value (PBV) from the FI situation had the smallest empirical average bias followed by PBV obtained without taking measurement error into account. In turn, MEM displayed the highest bias, although the differences were small. On the other hand, MEM showed the smallest MSEP, for either random mating or selection, followed by FI, whereas ignoring measurement error produced the largest MSEP. As a consequence from the smallest MSEP with a relatively small bias, empirical accuracies of PBV were larger for MEM than those for full information, which in turn showed larger accuracies than the situation ignoring measurement error. It is concluded that MEM equations are a useful alternative for analysing weaning weight data when recipient cows are unknown, as it mitigates the effects of bias in AOD by decreasing MSEP. © 2014 Blackwell Verlag GmbH.