Transversal changes, space closure, and efficiency of conventional and self-ligating appliances : A quantitative systematic review.

PubMed

Yang, Xianrui; Xue, Chaoran; He, Yiruo; Zhao, Mengyuan; Luo, Mengqi; Wang, Peiqi; Bai, Ding

2018-01-01

Self-ligating brackets (SLBs) were compared to conventional brackets (CBs) regarding their effectiveness on transversal changes and space closure, as well as the efficiency of alignment and treatment time. All previously published randomized controlled clinical trials (RCTs) dealing with SLBs and CBs were searched via electronic databases, e.g., MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, World Health Organization International Clinical Trials Registry Platform, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. In addition, relevant journals were searched manually. Data extraction was performed independently by two reviewers and assessment of the risk of bias was executed using Cochrane Collaboration's tool. Discrepancies were resolved by discussion with a third reviewer. Meta-analyses were conducted using Review Manager (version 5.3). A total of 976 patients in 17 RCTs were included in the study, of which 11 could be produced quantitatively and 2 showed a low risk of bias. Meta-analyses were found to favor CB for mandibular intercanine width expansion, while passive SLBs were more effective in posterior expansion. Moreover, CBs had an apparent advantage during short treatment periods. However, SLBs and CBs did not differ in closing spaces. Based on current clinical evidence obtained from RCTs, SLBs do not show clinical superiority compared to CBs in expanding transversal dimensions, space closure, or orthodontic efficiency. Further high-level studies involving randomized, controlled, clinical trials are warranted to confirm these results.

Biases encountered in long-term monitoring studies of invertebrates and microflora: Australian examples of protocols, personnel, tools and site location.

PubMed

Greenslade, Penelope; Florentine, Singarayer K; Hansen, Brigita D; Gell, Peter A

2016-08-01

Monitoring forms the basis for understanding ecological change. It relies on repeatability of methods to ensure detected changes accurately reflect the effect of environmental drivers. However, operator bias can influence the repeatability of field and laboratory work. We tested this for invertebrates and diatoms in three trials: (1) two operators swept invertebrates from heath vegetation, (2) four operators picked invertebrates from pyrethrum knockdown samples from tree trunk and (3) diatom identifications by eight operators in three laboratories. In each trial, operators were working simultaneously and their training in the field and laboratory was identical. No variation in catch efficiency was found between the two operators of differing experience using a random number of net sweeps to catch invertebrates when sequence, location and size of sweeps were random. Number of individuals and higher taxa collected by four operators from tree trunks varied significantly between operators and with their 'experience ranking'. Diatom identifications made by eight operators were clustered together according to which of three laboratories they belonged. These three tests demonstrated significant potential bias of operators in both field and laboratory. This is the first documented case demonstrating the significant influence of observer bias on results from invertebrate field-based studies. Examples of two long-term trials are also given that illustrate further operator bias. Our results suggest that long-term ecological studies using invertebrates need to be rigorously audited to ensure that operator bias is accounted for during analysis and interpretation. Further, taxonomic harmonisation remains an important step in merging field and laboratory data collected by different operators.

Silicon solar cell process development, fabrication and analysis

NASA Technical Reports Server (NTRS)

Iles, P. A.; Leung, D. C.

1982-01-01

For UCP Si, randomly selected wafers and wafers cut from two specific ingots were studied. For the randomly selected wafers, a moderate gettering diffusion had little effect. Moreover, an efficiency up to 14% AMI was achieved with advanced processes. For the two specific UCP ingots, ingot #5848-13C displayed severe impurity effects as shown by lower 3sc in the middle of the ingot and low CFF in the top of the ingot. Also the middle portions of this ingot responded to a series of progressively more severe gettering diffusion. Unexplained was the fact that severely gettered samples of this ingot displayed a negative light biased effect on the minority carrier diffusion length while the nongettered or moderately gettered ones had the more conventional positive light biased effect on diffusion length. On the other hand, ingot C-4-21A did not have the problem of ingot 5848-13C and behaved like to the randomly selected wafers. The top half of the ingot was shown to be slightly superior to the bottom half, but moderate gettering helped to narrow the gap.

Exploration properties of biased evanescent random walkers on a one-dimensional lattice

NASA Astrophysics Data System (ADS)

Esguerra, Jose Perico; Reyes, Jelian

2017-08-01

We investigate the combined effects of bias and evanescence on the characteristics of random walks on a one-dimensional lattice. We calculate the time-dependent return probability, eventual return probability, conditional mean return time, and the time-dependent mean number of visited sites of biased immortal and evanescent discrete-time random walkers on a one-dimensional lattice. We then extend the calculations to the case of a continuous-time step-coupled biased evanescent random walk on a one-dimensional lattice with an exponential waiting time distribution.

Both bias and lack of knowledge influence organizational focus on first case of the day starts.

PubMed

Dexter, Elisabeth U; Dexter, Franklin; Masursky, Danielle; Garver, Michael P; Nussmeier, Nancy A

2009-04-01

The economic costs of reducing first case delays are often high, because efforts need to be applied to multiple operating rooms (ORs) simultaneously. Nevertheless, delays in starting first cases of the day are a common topic in OR committee meetings. We added three scientific questions to a 24 question online, anonymous survey performed before the implementation of a new OR information system. The 57 respondents cared sufficiently about OR management at the United States teaching hospital to complete all questions. The survey revealed reasons why personnel may focus on the small reductions in nonoperative time achievable by reducing tardiness in first cases of the day. (A) Respondents lacked knowledge about principles in reducing over-utilized OR time to increase OR efficiency, based on their answering the relevant question correctly at a rate no different from guessing at random. Those results differed from prior findings of responses at a rate worse than random, resulting from a bias on the day of surgery of making decisions that increase clinical work per unit time. (B) Most respondents falsely believed that a 10 min delay at the start of the day causes subsequent cases to start at least 10 min late (P < 0.0001 versus random chance). (C) Most respondents did not know that cases often take less time than scheduled (P = 0.008 versus chance). No one who demonstrated knowledge (C) about cases sometimes taking less time than scheduled applied that information to their response to (B) regarding cases starting late (P = 0.0002). Knowledge of OR efficiency was low among the respondents working in ORs. Nevertheless, the apparent absence of bias shows that education may influence behavior. In contrast, presence of bias on matters of tardiness of start times shows that education may be of no benefit. As the latter results match findings of previous studies of scheduling decisions, interventions to reduce patient and surgeon waiting from start times may depend principally on the application of automation to guide decision-making.

Equipoise, design bias, and randomized controlled trials: the elusive ethics of new drug development.

PubMed

Fries, James F; Krishnan, Eswar

2004-01-01

The concept of 'equipoise', or the 'uncertainty principle', has been represented as a central ethical principle, and holds that a subject may be enrolled in a randomized controlled trial (RCT) only if there is true uncertainty about which of the trial arms is most likely to benefit the patient. We sought to estimate the frequency with which equipoise conditions were met in industry-sponsored RCTs in rheumatology, to explore the reasons for any deviations from equipoise, to examine the concept of 'design bias', and to consider alternative ethical formulations that might improve subject safety and autonomy. We studied abstracts accepted for the 2001 American College of Rheumatology meetings that reported RCTs, acknowledged industry sponsorship, and had clinical end-points (n = 45), and examined the proportion of studies that favored the registration or marketing of the sponsor's drug. In every trial (45/45) results were favorable to the sponsor, indicating that results could have been predicted in advance solely by knowledge of sponsorship (P < 0.0001). Equipoise clearly was being systematically violated. Publication bias appeared to be an incomplete explanation for this dramatic result; this bias occurs after a study is completed. Rather, we hypothesize that 'design bias', in which extensive preliminary data are used to design studies with a high likelihood of being positive, is the major cause of the asymmetric results. Design 'bias' occurs before the trial is begun and is inconsistent with the equipoise principle. However, design bias increases scientific efficiency, decreases drug development costs, and limits the number of subjects required, probably reducing aggregate risks to participants. Conceptual and ethical issues were found with the equipoise principle, which encourages performance of negative studies; ignores patient values, patient autonomy, and social benefits; is applied at a conceptually inappropriate decision point (after randomization rather than before); and is in conflict with the Belmont, Nuremberg, and other sets of ethical principles, as well as with US Food and Drug Administration procedures. We propose a principle of 'positive expected outcomes', which informs the assessment that a trial is ethical, together with a restatement of the priority of personal autonomy.

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects.

PubMed

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called "cluster randomization"). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

A new mean estimator using auxiliary variables for randomized response models

NASA Astrophysics Data System (ADS)

Ozgul, Nilgun; Cingi, Hulya

2013-10-01

Randomized response models are commonly used in surveys dealing with sensitive questions such as abortion, alcoholism, sexual orientation, drug taking, annual income, tax evasion to ensure interviewee anonymity and reduce nonrespondents rates and biased responses. Starting from the pioneering work of Warner [7], many versions of RRM have been developed that can deal with quantitative responses. In this study, new mean estimator is suggested for RRM including quantitative responses. The mean square error is derived and a simulation study is performed to show the efficiency of the proposed estimator to other existing estimators in RRM.

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects

PubMed Central

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies. PMID:28584874

Impact of missing data on the efficiency of homogenisation: experiments with ACMANTv3

NASA Astrophysics Data System (ADS)

Domonkos, Peter; Coll, John

2018-04-01

The impact of missing data on the efficiency of homogenisation with ACMANTv3 is examined with simulated monthly surface air temperature test datasets. The homogeneous database is derived from an earlier benchmarking of daily temperature data in the USA, and then outliers and inhomogeneities (IHs) are randomly inserted into the time series. Three inhomogeneous datasets are generated and used, one with relatively few and small IHs, another one with IHs of medium frequency and size, and a third one with large and frequent IHs. All of the inserted IHs are changes to the means. Most of the IHs are single sudden shifts or pair of shifts resulting in platform-shaped biases. Each test dataset consists of 158 time series of 100 years length, and their mean spatial correlation is 0.68-0.88. For examining the impacts of missing data, seven experiments are performed, in which 18 series are left complete, while variable quantities (10-70%) of the data of the other 140 series are removed. The results show that data gaps have a greater impact on the monthly root mean squared error (RMSE) than the annual RMSE and trend bias. When data with a large ratio of gaps is homogenised, the reduction of the upper 5% of the monthly RMSE is the least successful, but even there, the efficiency remains positive. In terms of reducing the annual RMSE and trend bias, the efficiency is 54-91%. The inclusion of short and incomplete series with sufficient spatial correlation in all cases improves the efficiency of homogenisation with ACMANTv3.

TemperSAT: A new efficient fair-sampling random k-SAT solver

NASA Astrophysics Data System (ADS)

Fang, Chao; Zhu, Zheng; Katzgraber, Helmut G.

The set membership problem is of great importance to many applications and, in particular, database searches for target groups. Recently, an approach to speed up set membership searches based on the NP-hard constraint-satisfaction problem (random k-SAT) has been developed. However, the bottleneck of the approach lies in finding the solution to a large SAT formula efficiently and, in particular, a large number of independent solutions is needed to reduce the probability of false positives. Unfortunately, traditional random k-SAT solvers such as WalkSAT are biased when seeking solutions to the Boolean formulas. By porting parallel tempering Monte Carlo to the sampling of binary optimization problems, we introduce a new algorithm (TemperSAT) whose performance is comparable to current state-of-the-art SAT solvers for large k with the added benefit that theoretically it can find many independent solutions quickly. We illustrate our results by comparing to the currently fastest implementation of WalkSAT, WalkSATlm.

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

PubMed Central

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

A New Filtering and Smoothing Algorithm for Railway Track Surveying Based on Landmark and IMU/Odometer

PubMed Central

Jiang, Qingan; Wu, Wenqi; Jiang, Mingming; Li, Yun

2017-01-01

High-accuracy railway track surveying is essential for railway construction and maintenance. The traditional approaches based on total station equipment are not efficient enough since high precision surveying frequently needs static measurements. This paper proposes a new filtering and smoothing algorithm based on the IMU/odometer and landmarks integration for the railway track surveying. In order to overcome the difficulty of estimating too many error parameters with too few landmark observations, a new model with completely observable error states is established by combining error terms of the system. Based on covariance analysis, the analytical relationship between the railway track surveying accuracy requirements and equivalent gyro drifts including bias instability and random walk noise are established. Experiment results show that the accuracy of the new filtering and smoothing algorithm for railway track surveying can reach 1 mm (1σ) when using a Ring Laser Gyroscope (RLG)-based Inertial Measurement Unit (IMU) with gyro bias instability of 0.03°/h and random walk noise of 0.005°/h while control points of the track control network (CPIII) position observations are provided by the optical total station in about every 60 m interval. The proposed approach can satisfy at the same time the demands of high accuracy and work efficiency for railway track surveying. PMID:28629191

Sampling for Patient Exit Interviews: Assessment of Methods Using Mathematical Derivation and Computer Simulations.

PubMed

Geldsetzer, Pascal; Fink, Günther; Vaikath, Maria; Bärnighausen, Till

2018-02-01

(1) To evaluate the operational efficiency of various sampling methods for patient exit interviews; (2) to discuss under what circumstances each method yields an unbiased sample; and (3) to propose a new, operationally efficient, and unbiased sampling method. Literature review, mathematical derivation, and Monte Carlo simulations. Our simulations show that in patient exit interviews it is most operationally efficient if the interviewer, after completing an interview, selects the next patient exiting the clinical consultation. We demonstrate mathematically that this method yields a biased sample: patients who spend a longer time with the clinician are overrepresented. This bias can be removed by selecting the next patient who enters, rather than exits, the consultation room. We show that this sampling method is operationally more efficient than alternative methods (systematic and simple random sampling) in most primary health care settings. Under the assumption that the order in which patients enter the consultation room is unrelated to the length of time spent with the clinician and the interviewer, selecting the next patient entering the consultation room tends to be the operationally most efficient unbiased sampling method for patient exit interviews. © 2016 The Authors. Health Services Research published by Wiley Periodicals, Inc. on behalf of Health Research and Educational Trust.

A new u-statistic with superior design sensitivity in matched observational studies.

PubMed

Rosenbaum, Paul R

2011-09-01

In an observational or nonrandomized study of treatment effects, a sensitivity analysis indicates the magnitude of bias from unmeasured covariates that would need to be present to alter the conclusions of a naïve analysis that presumes adjustments for observed covariates suffice to remove all bias. The power of sensitivity analysis is the probability that it will reject a false hypothesis about treatment effects allowing for a departure from random assignment of a specified magnitude; in particular, if this specified magnitude is "no departure" then this is the same as the power of a randomization test in a randomized experiment. A new family of u-statistics is proposed that includes Wilcoxon's signed rank statistic but also includes other statistics with substantially higher power when a sensitivity analysis is performed in an observational study. Wilcoxon's statistic has high power to detect small effects in large randomized experiments-that is, it often has good Pitman efficiency-but small effects are invariably sensitive to small unobserved biases. Members of this family of u-statistics that emphasize medium to large effects can have substantially higher power in a sensitivity analysis. For example, in one situation with 250 pair differences that are Normal with expectation 1/2 and variance 1, the power of a sensitivity analysis that uses Wilcoxon's statistic is 0.08 while the power of another member of the family of u-statistics is 0.66. The topic is examined by performing a sensitivity analysis in three observational studies, using an asymptotic measure called the design sensitivity, and by simulating power in finite samples. The three examples are drawn from epidemiology, clinical medicine, and genetic toxicology. © 2010, The International Biometric Society.

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.

Heterodyne efficiency for a coherent laser radar with diffuse or aerosol targets

NASA Technical Reports Server (NTRS)

Frehlich, R. G.

1993-01-01

The performance of a Coherent Laser Radar is determined by the statistics of the coherent Doppler signal. The heterodyne efficiency is an excellent indication of performance because it is an absolute measure of beam alignment and is independent of the transmitter power, the target backscatter coefficient, the atmospheric attenuation, and the detector quantum efficiency and gain. The theoretical calculation of heterodyne efficiency for an optimal monostatic lidar with a circular aperture and Gaussian transmit laser is presented including beam misalignment in the far-field and near-field regimes. The statistical behavior of estimates of the heterodyne efficiency using a calibration hard target are considered. For space based applications, a biased estimate of heterodyne efficiency is proposed that removes the variability due to the random surface return but retains the sensitivity to misalignment. Physical insight is provided by simulation of the fields on the detector surface. The required detector calibration is also discussed.

Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955–2013

PubMed Central

Armijo-Olivo, Susan; Cummings, Greta G.; Amin, Maryam; Flores-Mir, Carlos

2017-01-01

Objectives To examine the risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions and the development of these aspects over time. Methods We included 540 randomized clinical trials from 64 selected systematic reviews. We extracted, in duplicate, details from each of the selected randomized clinical trials with respect to publication and trial characteristics, reporting and methodologic characteristics, and Cochrane risk of bias domains. We analyzed data using logistic regression and Chi-square statistics. Results Sequence generation was assessed to be inadequate (at unclear or high risk of bias) in 68% (n = 367) of the trials, while allocation concealment was inadequate in the majority of trials (n = 464; 85.9%). Blinding of participants and blinding of the outcome assessment were judged to be inadequate in 28.5% (n = 154) and 40.5% (n = 219) of the trials, respectively. A sample size calculation before the initiation of the study was not performed/reported in 79.1% (n = 427) of the trials, while the sample size was assessed as adequate in only 17.6% (n = 95) of the trials. Two thirds of the trials were not described as double blinded (n = 358; 66.3%), while the method of blinding was appropriate in 53% (n = 286) of the trials. We identified a significant decrease over time (1955–2013) in the proportion of trials assessed as having inadequately addressed methodological quality items (P < 0.05) in 30 out of the 40 quality criteria, or as being inadequate (at high or unclear risk of bias) in five domains of the Cochrane risk of bias tool: sequence generation, allocation concealment, incomplete outcome data, other sources of bias, and overall risk of bias. Conclusions The risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions have improved over time; however, further efforts that contribute to the development of more stringent methodology and detailed reporting of trials are still needed. PMID:29272315

Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955-2013.

PubMed

Saltaji, Humam; Armijo-Olivo, Susan; Cummings, Greta G; Amin, Maryam; Flores-Mir, Carlos

2017-01-01

To examine the risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions and the development of these aspects over time. We included 540 randomized clinical trials from 64 selected systematic reviews. We extracted, in duplicate, details from each of the selected randomized clinical trials with respect to publication and trial characteristics, reporting and methodologic characteristics, and Cochrane risk of bias domains. We analyzed data using logistic regression and Chi-square statistics. Sequence generation was assessed to be inadequate (at unclear or high risk of bias) in 68% (n = 367) of the trials, while allocation concealment was inadequate in the majority of trials (n = 464; 85.9%). Blinding of participants and blinding of the outcome assessment were judged to be inadequate in 28.5% (n = 154) and 40.5% (n = 219) of the trials, respectively. A sample size calculation before the initiation of the study was not performed/reported in 79.1% (n = 427) of the trials, while the sample size was assessed as adequate in only 17.6% (n = 95) of the trials. Two thirds of the trials were not described as double blinded (n = 358; 66.3%), while the method of blinding was appropriate in 53% (n = 286) of the trials. We identified a significant decrease over time (1955-2013) in the proportion of trials assessed as having inadequately addressed methodological quality items (P < 0.05) in 30 out of the 40 quality criteria, or as being inadequate (at high or unclear risk of bias) in five domains of the Cochrane risk of bias tool: sequence generation, allocation concealment, incomplete outcome data, other sources of bias, and overall risk of bias. The risks of bias, risks of random errors, reporting quality, and methodological quality of randomized clinical trials of oral health interventions have improved over time; however, further efforts that contribute to the development of more stringent methodology and detailed reporting of trials are still needed.

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.

Modeling the Overalternating Bias with an Asymmetric Entropy Measure

PubMed Central

Gronchi, Giorgio; Raglianti, Marco; Noventa, Stefano; Lazzeri, Alessandro; Guazzini, Andrea

2016-01-01

Psychological research has found that human perception of randomness is biased. In particular, people consistently show the overalternating bias: they rate binary sequences of symbols (such as Heads and Tails in coin flipping) with an excess of alternation as more random than prescribed by the normative criteria of Shannon's entropy. Within data mining for medical applications, Marcellin proposed an asymmetric measure of entropy that can be ideal to account for such bias and to quantify subjective randomness. We fitted Marcellin's entropy and Renyi's entropy (a generalized form of uncertainty measure comprising many different kinds of entropies) to experimental data found in the literature with the Differential Evolution algorithm. We observed a better fit for Marcellin's entropy compared to Renyi's entropy. The fitted asymmetric entropy measure also showed good predictive properties when applied to different datasets of randomness-related tasks. We concluded that Marcellin's entropy can be a parsimonious and effective measure of subjective randomness that can be useful in psychological research about randomness perception. PMID:27458418

Directional Bias and Pheromone for Discovery and Coverage on Networks

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

Fink, Glenn A.; Berenhaut, Kenneth S.; Oehmen, Christopher S.

2012-09-11

Natural multi-agent systems often rely on “correlated random walks” (random walks that are biased toward a current heading) to distribute their agents over a space (e.g., for foraging, search, etc.). Our contribution involves creation of a new movement and pheromone model that applies the concept of heading bias in random walks to a multi-agent, digital-ants system designed for cyber-security monitoring. We examine the relative performance effects of both pheromone and heading bias on speed of discovery of a target and search-area coverage in a two-dimensional network layout. We found that heading bias was unexpectedly helpful in reducing search time andmore » that it was more influential than pheromone for improving coverage. We conclude that while pheromone is very important for rapid discovery, heading bias can also greatly improve both performance metrics.« less

Blinded interpretation of study results can feasibly and effectively diminish interpretation bias.

PubMed

Järvinen, Teppo L N; Sihvonen, Raine; Bhandari, Mohit; Sprague, Sheila; Malmivaara, Antti; Paavola, Mika; Schünemann, Holger J; Guyatt, Gordon H

2014-07-01

Controversial and misleading interpretation of data from randomized trials is common. How to avoid misleading interpretation has received little attention. Herein, we describe two applications of an approach that involves blinded interpretation of the results by study investigators. The approach involves developing two interpretations of the results on the basis of a blinded review of the primary outcome data (experimental treatment A compared with control treatment B). One interpretation assumes that A is the experimental intervention and another assumes that A is the control. After agreeing that there will be no further changes, the investigators record their decisions and sign the resulting document. The randomization code is then broken, the correct interpretation chosen, and the manuscript finalized. Review of the document by an external authority before finalization can provide another safeguard against interpretation bias. We found the blinded preparation of a summary of data interpretation described in this article practical, efficient, and useful. Blinded data interpretation may decrease the frequency of misleading data interpretation. Widespread adoption of blinded data interpretation would be greatly facilitated were it added to the minimum set of recommendations outlining proper conduct of randomized controlled trials (eg, the Consolidated Standards of Reporting Trials statement). Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Economical analysis of saturation mutagenesis experiments

PubMed Central

Acevedo-Rocha, Carlos G.; Reetz, Manfred T.; Nov, Yuval

2015-01-01

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced. PMID:26190439

An integrate-over-temperature approach for enhanced sampling.

PubMed

Gao, Yi Qin

2008-02-14

A simple method is introduced to achieve efficient random walking in the energy space in molecular dynamics simulations which thus enhances the sampling over a large energy range. The approach is closely related to multicanonical and replica exchange simulation methods in that it allows configurations of the system to be sampled in a wide energy range by making use of Boltzmann distribution functions at multiple temperatures. A biased potential is quickly generated using this method and is then used in accelerated molecular dynamics simulations.

Evolutionarily stable and convergent stable strategies in reaction-diffusion models for conditional dispersal.

PubMed

Lam, King-Yeung; Lou, Yuan

2014-02-01

We consider a mathematical model of two competing species for the evolution of conditional dispersal in a spatially varying, but temporally constant environment. Two species are different only in their dispersal strategies, which are a combination of random dispersal and biased movement upward along the resource gradient. In the absence of biased movement or advection, Hastings showed that the mutant can invade when rare if and only if it has smaller random dispersal rate than the resident. When there is a small amount of biased movement or advection, we show that there is a positive random dispersal rate that is both locally evolutionarily stable and convergent stable. Our analysis of the model suggests that a balanced combination of random and biased movement might be a better habitat selection strategy for populations.

A novel application of the Intent to Attend assessment to reduce bias due to missing data in a randomized controlled clinical trial

PubMed Central

Rabideau, Dustin J; Nierenberg, Andrew A; Sylvia, Louisa G; Friedman, Edward S.; Bowden, Charles L.; Thase, Michael E.; Ketter, Terence; Ostacher, Michael J.; Reilly-Harrington, Noreen; Iosifescu, Dan V.; Calabrese, Joseph R.; Leon, Andrew C.; Schoenfeld, David A

2014-01-01

Background Missing data are unavoidable in most randomized controlled clinical trials, especially when measurements are taken repeatedly. If strong assumptions about the missing data are not accurate, crude statistical analyses are biased and can lead to false inferences. Furthermore, if we fail to measure all predictors of missing data, we may not be able to model the missing data process sufficiently. In longitudinal randomized trials, measuring a patient's intent to attend future study visits may help to address both of these problems. Leon et al. developed and included the Intent to Attend assessment in the Lithium Treatment—Moderate dose Use Study (LiTMUS), aiming to remove bias due to missing data from the primary study hypothesis [1]. Purpose The purpose of this study is to assess the performance of the Intent to Attend assessment with regard to its use in a sensitivity analysis of missing data. Methods We fit marginal models to assess whether a patient's self-rated intent predicted actual study adherence. We applied inverse probability of attrition weighting (IPAW) coupled with patient intent to assess whether there existed treatment group differences in response over time. We compared the IPAW results to those obtained using other methods. Results Patient-rated intent predicted missed study visits, even when adjusting for other predictors of missing data. On average, the hazard of retention increased by 19% for every one-point increase in intent. We also found that more severe mania, male gender, and a previously missed visit predicted subsequent absence. Although we found no difference in response between the randomized treatment groups, IPAW increased the estimated group difference over time. Limitations LiTMUS was designed to limit missed study visits, which may have attenuated the effects of adjusting for missing data. Additionally, IPAW can be less efficient and less powerful than maximum likelihood or Bayesian estimators, given that the parametric model is well-specified. Conclusions In LiTMUS, the Intent to Attend assessment predicted missed study visits. This item was incorporated into our IPAW models and helped reduce bias due to informative missing data. This analysis should both encourage and facilitate future use of the Intent to Attend assessment along with IPAW to address missing data in a randomized trial. PMID:24872362

Attentional bias modification training for insomnia: A double-blind placebo controlled randomized trial

PubMed Central

Lancee, Jaap; Yasiney, Samya L.; Brendel, Ruben S.; Boffo, Marilisa; Clarke, Patrick J. F.; Salemink, Elske

2017-01-01

Background Attentional bias toward sleep-related information is believed to play a key role in insomnia. If attentional bias is indeed of importance, changing this bias should then in turn have effects on insomnia complaints. In this double-blind placebo controlled randomized trial we investigated the efficacy of attentional bias modification training in the treatment of insomnia. Method We administered baseline, post-test, and one-week follow-up measurements of insomnia severity, sleep-related worry, depression, and anxiety. Participants meeting DSM-5 criteria for insomnia were randomized into an attentional bias training group (n = 67) or a placebo training group (n = 70). Both groups received eight training sessions over the course of two weeks. All participants kept a sleep diary for four consecutive weeks (one week before until one week after the training sessions). Results There was no additional benefit for the attentional bias training over the placebo training on sleep-related indices/outcome measures. Conclusions The absence of the effect may be explained by the fact that there was neither attentional bias at baseline nor any reduction in the bias after the training. Either way, this study gives no support for attentional bias modification training as a stand-alone intervention for ameliorating insomnia complaints. PMID:28423038

On Measuring and Reducing Selection Bias with a Quasi-Doubly Randomized Preference Trial

ERIC Educational Resources Information Center

Joyce, Ted; Remler, Dahlia K.; Jaeger, David A.; Altindag, Onur; O'Connell, Stephen D.; Crockett, Sean

2017-01-01

Randomized experiments provide unbiased estimates of treatment effects, but are costly and time consuming. We demonstrate how a randomized experiment can be leveraged to measure selection bias by conducting a subsequent observational study that is identical in every way except that subjects choose their treatment--a quasi-doubly randomized…

Weighted re-randomization tests for minimization with unbalanced allocation.

PubMed

Han, Baoguang; Yu, Menggang; McEntegart, Damian

2013-01-01

Re-randomization test has been considered as a robust alternative to the traditional population model-based methods for analyzing randomized clinical trials. This is especially so when the clinical trials are randomized according to minimization, which is a popular covariate-adaptive randomization method for ensuring balance among prognostic factors. Among various re-randomization tests, fixed-entry-order re-randomization is advocated as an effective strategy when a temporal trend is suspected. Yet when the minimization is applied to trials with unequal allocation, fixed-entry-order re-randomization test is biased and thus compromised in power. We find that the bias is due to non-uniform re-allocation probabilities incurred by the re-randomization in this case. We therefore propose a weighted fixed-entry-order re-randomization test to overcome the bias. The performance of the new test was investigated in simulation studies that mimic the settings of a real clinical trial. The weighted re-randomization test was found to work well in the scenarios investigated including the presence of a strong temporal trend. Copyright © 2013 John Wiley & Sons, Ltd.

Data-Driven Benchmarking of Building Energy Efficiency Utilizing Statistical Frontier Models

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

Kavousian, A; Rajagopal, R

2014-01-01

Frontier methods quantify the energy efficiency of buildings by forming an efficient frontier (best-practice technology) and by comparing all buildings against that frontier. Because energy consumption fluctuates over time, the efficiency scores are stochastic random variables. Existing applications of frontier methods in energy efficiency either treat efficiency scores as deterministic values or estimate their uncertainty by resampling from one set of measurements. Availability of smart meter data (repeated measurements of energy consumption of buildings) enables using actual data to estimate the uncertainty in efficiency scores. Additionally, existing applications assume a linear form for an efficient frontier; i.e.,they assume that themore » best-practice technology scales up and down proportionally with building characteristics. However, previous research shows that buildings are nonlinear systems. This paper proposes a statistical method called stochastic energy efficiency frontier (SEEF) to estimate a bias-corrected efficiency score and its confidence intervals from measured data. The paper proposes an algorithm to specify the functional form of the frontier, identify the probability distribution of the efficiency score of each building using measured data, and rank buildings based on their energy efficiency. To illustrate the power of SEEF, this paper presents the results from applying SEEF on a smart meter data set of 307 residential buildings in the United States. SEEF efficiency scores are used to rank individual buildings based on energy efficiency, to compare subpopulations of buildings, and to identify irregular behavior of buildings across different time-of-use periods. SEEF is an improvement to the energy-intensity method (comparing kWh/sq.ft.): whereas SEEF identifies efficient buildings across the entire spectrum of building sizes, the energy-intensity method showed bias toward smaller buildings. The results of this research are expected to assist researchers and practitioners compare and rank (i.e.,benchmark) buildings more robustly and over a wider range of building types and sizes. Eventually, doing so is expected to result in improved resource allocation in energy-efficiency programs.« less

Development of n+-in-p planar pixel sensors for extremely high radiation environments, designed to retain high efficiency after irradiation

NASA Astrophysics Data System (ADS)

Unno, Y.; Kamada, S.; Yamamura, K.; Ikegami, Y.; Nakamura, K.; Takubo, Y.; Takashima, R.; Tojo, J.; Kono, T.; Hanagaki, K.; Yajima, K.; Yamauchi, Y.; Hirose, M.; Homma, Y.; Jinnouchi, O.; Kimura, K.; Motohashi, K.; Sato, S.; Sawai, H.; Todome, K.; Yamaguchi, D.; Hara, K.; Sato, Kz.; Sato, Kj.; Hagihara, M.; Iwabuchi, S.

2016-09-01

We have developed n+-in-p pixel sensors to obtain highly radiation tolerant sensors for extremely high radiation environments such as those found at the high-luminosity LHC. We have designed novel pixel structures to eliminate the sources of efficiency loss under the bias rails after irradiation by removing the bias rail out of the boundary region and routing the bias resistors inside the area of the pixel electrodes. After irradiation by protons with the fluence of approximately 3 ×1015neq /cm2, the pixel structure with the polysilicon bias resistor and the bias rails removed far away from the boundary shows an efficiency loss of < 0.5 % per pixel at the boundary region, which is as efficient as the pixel structure without a biasing structure. The pixel structure with the bias rails at the boundary and the widened p-stop's underneath the bias rail also exhibits an improved loss of approximately 1% per pixel at the boundary region. We have elucidated the physical mechanisms behind the efficiency loss under the bias rail with TCAD simulations. The efficiency loss is due to the interplay of the bias rail acting as a charge collecting electrode with the region of low electric field in the silicon near the surface at the boundary. The region acts as a "shield" for the electrode. After irradiation, the strong applied electric field nearly eliminates the region. The TCAD simulations have shown that wide p-stop and large Si-SiO2 interface charge (inversion layer, specifically) act to shield the weighting potential. The pixel sensor of the old design irradiated by γ-rays at 2.4 MGy is confirmed to exhibit only a slight efficiency loss at the boundary.

The persistence of the attentional bias to regularities in a changing environment.

PubMed

Yu, Ru Qi; Zhao, Jiaying

2015-10-01

The environment often is stable, but some aspects may change over time. The challenge for the visual system is to discover and flexibly adapt to the changes. We examined how attention is shifted in the presence of changes in the underlying structure of the environment. In six experiments, observers viewed four simultaneous streams of objects while performing a visual search task. In the first half of each experiment, the stream in the structured location contained regularities, the shapes in the random location were randomized, and gray squares appeared in two neutral locations. In the second half, the stream in the structured or the random location may change. In the first half of all experiments, visual search was facilitated in the structured location, suggesting that attention was consistently biased toward regularities. In the second half, this bias persisted in the structured location when no change occurred (Experiment 1), when the regularities were removed (Experiment 2), or when new regularities embedded in the original or novel stimuli emerged in the previously random location (Experiments 3 and 6). However, visual search was numerically but no longer reliably faster in the structured location when the initial regularities were removed and new regularities were introduced in the previously random location (Experiment 4), or when novel random stimuli appeared in the random location (Experiment 5). This suggests that the attentional bias was weakened. Overall, the results demonstrate that the attentional bias to regularities was persistent but also sensitive to changes in the environment.

Computer-aided system of evaluation for population-based all-in-one service screening (CASE-PASS): from study design to outcome analysis with bias adjustment.

PubMed

Chen, Li-Sheng; Yen, Amy Ming-Fang; Duffy, Stephen W; Tabar, Laszlo; Lin, Wen-Chou; Chen, Hsiu-Hsi

2010-10-01

Population-based routine service screening has gained popularity following an era of randomized controlled trials. The evaluation of these service screening programs is subject to study design, data availability, and the precise data analysis for adjusting bias. We developed a computer-aided system that allows the evaluation of population-based service screening to unify these aspects and facilitate and guide the program assessor to efficiently perform an evaluation. This system underpins two experimental designs: the posttest-only non-equivalent design and the one-group pretest-posttest design and demonstrates the type of data required at both the population and individual levels. Three major analyses were developed that included a cumulative mortality analysis, survival analysis with lead-time adjustment, and self-selection bias adjustment. We used SAS AF software to develop a graphic interface system with a pull-down menu style. We demonstrate the application of this system with data obtained from a Swedish population-based service screen and a population-based randomized controlled trial for the screening of breast, colorectal, and prostate cancer, and one service screening program for cervical cancer with Pap smears. The system provided automated descriptive results based on the various sources of available data and cumulative mortality curves corresponding to the study designs. The comparison of cumulative survival between clinically and screen-detected cases without a lead-time adjustment are also demonstrated. The intention-to-treat and noncompliance analysis with self-selection bias adjustments are also shown to assess the effectiveness of the population-based service screening program. Model validation was composed of a comparison between our adjusted self-selection bias estimates and the empirical results on effectiveness reported in the literature. We demonstrate a computer-aided system allowing the evaluation of population-based service screening programs with an adjustment for self-selection and lead-time bias. This is achieved by providing a tutorial guide from the study design to the data analysis, with bias adjustment. Copyright © 2010 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

A partially reflecting random walk on spheres algorithm for electrical impedance tomography

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

Maire, Sylvain, E-mail: maire@univ-tln.fr; Simon, Martin, E-mail: simon@math.uni-mainz.de

2015-12-15

In this work, we develop a probabilistic estimator for the voltage-to-current map arising in electrical impedance tomography. This novel so-called partially reflecting random walk on spheres estimator enables Monte Carlo methods to compute the voltage-to-current map in an embarrassingly parallel manner, which is an important issue with regard to the corresponding inverse problem. Our method uses the well-known random walk on spheres algorithm inside subdomains where the diffusion coefficient is constant and employs replacement techniques motivated by finite difference discretization to deal with both mixed boundary conditions and interface transmission conditions. We analyze the global bias and the variance ofmore » the new estimator both theoretically and experimentally. Subsequently, the variance of the new estimator is considerably reduced via a novel control variate conditional sampling technique which yields a highly efficient hybrid forward solver coupling probabilistic and deterministic algorithms.« less

[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.

SYRCLE’s risk of bias tool for animal studies

PubMed Central

2014-01-01

Background Systematic Reviews (SRs) of experimental animal studies are not yet common practice, but awareness of the merits of conducting such SRs is steadily increasing. As animal intervention studies differ from randomized clinical trials (RCT) in many aspects, the methodology for SRs of clinical trials needs to be adapted and optimized for animal intervention studies. The Cochrane Collaboration developed a Risk of Bias (RoB) tool to establish consistency and avoid discrepancies in assessing the methodological quality of RCTs. A similar initiative is warranted in the field of animal experimentation. Methods We provide an RoB tool for animal intervention studies (SYRCLE’s RoB tool). This tool is based on the Cochrane RoB tool and has been adjusted for aspects of bias that play a specific role in animal intervention studies. To enhance transparency and applicability, we formulated signalling questions to facilitate judgment. Results The resulting RoB tool for animal studies contains 10 entries. These entries are related to selection bias, performance bias, detection bias, attrition bias, reporting bias and other biases. Half these items are in agreement with the items in the Cochrane RoB tool. Most of the variations between the two tools are due to differences in design between RCTs and animal studies. Shortcomings in, or unfamiliarity with, specific aspects of experimental design of animal studies compared to clinical studies also play a role. Conclusions SYRCLE’s RoB tool is an adapted version of the Cochrane RoB tool. Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies. This may subsequently enhance the efficiency of translating animal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies. PMID:24667063

Exchange bias mechanism in FM/FM/AF spin valve systems in the presence of random unidirectional anisotropy field at the AF interface: The role played by the interface roughness due to randomness

NASA Astrophysics Data System (ADS)

Yüksel, Yusuf

2018-05-01

We propose an atomistic model and present Monte Carlo simulation results regarding the influence of FM/AF interface structure on the hysteresis mechanism and exchange bias behavior for a spin valve type FM/FM/AF magnetic junction. We simulate perfectly flat and roughened interface structures both with uncompensated interfacial AF moments. In order to simulate rough interface effect, we introduce the concept of random exchange anisotropy field induced at the interface, and acting on the interface AF spins. Our results yield that different types of the random field distributions of anisotropy field may lead to different behavior of exchange bias.

An Assessment of the Risk of Bias in Randomized Controlled Trial Reports Published in Prosthodontic and Implant Dentistry Journals.

PubMed

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-01-01

The objective of this study was to assess the risk of bias of randomized controlled trials (RCTs) published in prosthodontic and implant dentistry journals. The last 30 issues of 9 journals in the field of prosthodontic and implant dentistry (Clinical Implant Dentistry and Related Research, Clinical Oral Implants Research, Implant Dentistry, International Journal of Oral & Maxillofacial Implants, International Journal of Periodontics and Restorative Dentistry, International Journal of Prosthodontics, Journal of Dentistry, Journal of Oral Rehabilitation, and Journal of Prosthetic Dentistry) were hand-searched for RCTs. Risk of bias was assessed using the Cochrane Collaboration's risk of bias tool and analyzed descriptively. From the 3,667 articles screened, a total of 147 RCTs were identified and included. The number of published RCTs increased with time. The overall distribution of a high risk of bias assessment varied across the domains of the Cochrane risk of bias tool: 8% for random sequence generation, 18% for allocation concealment, 41% for masking, 47% for blinding of outcome assessment, 7% for incomplete outcome data, 12% for selective reporting, and 41% for other biases. The distribution of high risk of bias for RCTs published in the selected prosthodontic and implant dentistry journals varied among journals and ranged from 8% to 47%, which can be considered as substantial.

Generalized essential energy space random walks to more effectively accelerate solute sampling in aqueous environment

NASA Astrophysics Data System (ADS)

Lv, Chao; Zheng, Lianqing; Yang, Wei

2012-01-01

Molecular dynamics sampling can be enhanced via the promoting of potential energy fluctuations, for instance, based on a Hamiltonian modified with the addition of a potential-energy-dependent biasing term. To overcome the diffusion sampling issue, which reveals the fact that enlargement of event-irrelevant energy fluctuations may abolish sampling efficiency, the essential energy space random walk (EESRW) approach was proposed earlier. To more effectively accelerate the sampling of solute conformations in aqueous environment, in the current work, we generalized the EESRW method to a two-dimension-EESRW (2D-EESRW) strategy. Specifically, the essential internal energy component of a focused region and the essential interaction energy component between the focused region and the environmental region are employed to define the two-dimensional essential energy space. This proposal is motivated by the general observation that in different conformational events, the two essential energy components have distinctive interplays. Model studies on the alanine dipeptide and the aspartate-arginine peptide demonstrate sampling improvement over the original one-dimension-EESRW strategy; with the same biasing level, the present generalization allows more effective acceleration of the sampling of conformational transitions in aqueous solution. The 2D-EESRW generalization is readily extended to higher dimension schemes and employed in more advanced enhanced-sampling schemes, such as the recent orthogonal space random walk method.

Chromosome Segregation Is Biased by Kinetochore Size.

PubMed

Drpic, Danica; Almeida, Ana C; Aguiar, Paulo; Renda, Fioranna; Damas, Joana; Lewin, Harris A; Larkin, Denis M; Khodjakov, Alexey; Maiato, Helder

2018-05-07

Chromosome missegregation during mitosis or meiosis is a hallmark of cancer and the main cause of prenatal death in humans. The gain or loss of specific chromosomes is thought to be random, with cell viability being essentially determined by selection. Several established pathways including centrosome amplification, sister-chromatid cohesion defects, or a compromised spindle assembly checkpoint can lead to chromosome missegregation. However, how specific intrinsic features of the kinetochore-the critical chromosomal interface with spindle microtubules-impact chromosome segregation remains poorly understood. Here we used the unique cytological attributes of female Indian muntjac, the mammal with the lowest known chromosome number (2n = 6), to characterize and track individual chromosomes with distinct kinetochore size throughout mitosis. We show that centromere and kinetochore functional layers scale proportionally with centromere size. Measurement of intra-kinetochore distances, serial-section electron microscopy, and RNAi against key kinetochore proteins confirmed a standard structural and functional organization of the Indian muntjac kinetochores and revealed that microtubule binding capacity scales with kinetochore size. Surprisingly, we found that chromosome segregation in this species is not random. Chromosomes with larger kinetochores bi-oriented more efficiently and showed a 2-fold bias to congress to the equator in a motor-independent manner. Despite robust correction mechanisms during unperturbed mitosis, chromosomes with larger kinetochores were also strongly biased to establish erroneous merotelic attachments and missegregate during anaphase. This bias was impervious to the experimental attenuation of polar ejection forces on chromosome arms by RNAi against the chromokinesin Kif4a. Thus, kinetochore size is an important determinant of chromosome segregation fidelity. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Diffusion with social reinforcement: The role of individual preferences

NASA Astrophysics Data System (ADS)

Tur, Elena M.; Zeppini, Paolo; Frenken, Koen

2018-02-01

The debate on diffusion in social networks has traditionally focused on the structure of the network to understand the efficiency of a network in terms of diffusion. Recently, the role of social reinforcement has been added to the debate, as it has been proposed that simple contagions diffuse better in random networks and complex contagions diffuse better in regular networks. In this paper, we show that individual preferences cannot be overlooked: complex contagions diffuse better in regular networks only if the large majority of the population is biased against adoption.

Not all numbers are equal: preferences and biases among children and adults when generating random sequences.

PubMed

Towse, John N; Loetscher, Tobias; Brugger, Peter

2014-01-01

We investigate the number preferences of children and adults when generating random digit sequences. Previous research has shown convincingly that adults prefer smaller numbers when randomly choosing between responses 1-6. We analyze randomization choices made by both children and adults, considering a range of experimental studies and task configurations. Children - most of whom are between 8 and 11~years - show a preference for relatively large numbers when choosing numbers 1-10. Adults show a preference for small numbers with the same response set. We report a modest association between children's age and numerical bias. However, children also exhibit a small number bias with a smaller response set available, and they show a preference specifically for the numbers 1-3 across many datasets. We argue that number space demonstrates both continuities (numbers 1-3 have a distinct status) and change (a developmentally emerging bias toward the left side of representational space or lower numbers).

"Fair Play": A Videogame Designed to Address Implicit Race Bias Through Active Perspective Taking.

PubMed

Gutierrez, Belinda; Kaatz, Anna; Chu, Sarah; Ramirez, Dennis; Samson-Samuel, Clem; Carnes, Molly

2014-12-01

Having diverse faculty in academic health centers will help diversify the healthcare workforce and reduce health disparities. Implicit race bias is one factor that contributes to the underrepresentation of Black faculty. We designed the videogame "Fair Play" in which players assume the role of a Black graduate student named Jamal Davis. As Jamal, players experience subtle race bias while completing "quests" to obtain a science degree. We hypothesized that participants randomly assigned to play the game would have greater empathy for Jamal and lower implicit race bias than participants randomized to read narrative text describing Jamal's experience. University of Wisconsin-Madison graduate students were recruited via e-mail and randomly assigned to play "Fair Play" or read narrative text through an online link. Upon completion, participants took an Implicit Association Test to measure implicit bias and answered survey questions assessing empathy toward Jamal and awareness of bias. As hypothesized, gameplayers showed the least implicit bias but only when they also showed high empathy for Jamal (P=0.013). Gameplayers did not show greater empathy than text readers, and women in the text condition reported the greatest empathy for Jamal (P=0.008). However, high empathy only predicted lower levels of implicit bias among those who actively took Jamal's perspective through gameplay (P=0.014). A videogame in which players experience subtle race bias as a Black graduate student has the potential to reduce implicit bias, possibly because of a game's ability to foster empathy through active perspective taking.

Animal research as a basis for clinical trials.

PubMed

Faggion, Clovis M

2015-04-01

Animal experiments are critical for the development of new human therapeutics because they provide mechanistic information, as well as important information on efficacy and safety. Some evidence suggests that authors of animal research in dentistry do not observe important methodological issues when planning animal experiments, for example sample-size calculation. Low-quality animal research directly interferes with development of the research process in which multiple levels of research are interconnected. For example, high-quality animal experiments generate sound information for the further planning and development of randomized controlled trials in humans. These randomized controlled trials are the main source for the development of systematic reviews and meta-analyses, which will generate the best evidence for the development of clinical guidelines. Therefore, adequate planning of animal research is a sine qua non condition for increasing efficacy and efficiency in research. Ethical concerns arise when animal research is not performed with high standards. This Focus article presents the latest information on the standards of animal research in dentistry, more precisely in the field of implant dentistry. Issues on precision and risk of bias are discussed, and strategies to reduce risk of bias in animal research are reported. © 2015 Eur J Oral Sci.

Selection of core animals in the Algorithm for Proven and Young using a simulation model.

PubMed

Bradford, H L; Pocrnić, I; Fragomeni, B O; Lourenco, D A L; Misztal, I

2017-12-01

The Algorithm for Proven and Young (APY) enables the implementation of single-step genomic BLUP (ssGBLUP) in large, genotyped populations by separating genotyped animals into core and non-core subsets and creating a computationally efficient inverse for the genomic relationship matrix (G). As APY became the choice for large-scale genomic evaluations in BLUP-based methods, a common question is how to choose the animals in the core subset. We compared several core definitions to answer this question. Simulations comprised a moderately heritable trait for 95,010 animals and 50,000 genotypes for animals across five generations. Genotypes consisted of 25,500 SNP distributed across 15 chromosomes. Genotyping errors and missing pedigree were also mimicked. Core animals were defined based on individual generations, equal representation across generations, and at random. For a sufficiently large core size, core definitions had the same accuracies and biases, even if the core animals had imperfect genotypes. When genotyped animals had unknown parents, accuracy and bias were significantly better (p ≤ .05) for random and across generation core definitions. © 2017 The Authors. Journal of Animal Breeding and Genetics Published by Blackwell Verlag GmbH.

Is using multiple imputation better than complete case analysis for estimating a prevalence (risk) difference in randomized controlled trials when binary outcome observations are missing?

PubMed

Mukaka, Mavuto; White, Sarah A; Terlouw, Dianne J; Mwapasa, Victor; Kalilani-Phiri, Linda; Faragher, E Brian

2016-07-22

Missing outcomes can seriously impair the ability to make correct inferences from randomized controlled trials (RCTs). Complete case (CC) analysis is commonly used, but it reduces sample size and is perceived to lead to reduced statistical efficiency of estimates while increasing the potential for bias. As multiple imputation (MI) methods preserve sample size, they are generally viewed as the preferred analytical approach. We examined this assumption, comparing the performance of CC and MI methods to determine risk difference (RD) estimates in the presence of missing binary outcomes. We conducted simulation studies of 5000 simulated data sets with 50 imputations of RCTs with one primary follow-up endpoint at different underlying levels of RD (3-25 %) and missing outcomes (5-30 %). For missing at random (MAR) or missing completely at random (MCAR) outcomes, CC method estimates generally remained unbiased and achieved precision similar to or better than MI methods, and high statistical coverage. Missing not at random (MNAR) scenarios yielded invalid inferences with both methods. Effect size estimate bias was reduced in MI methods by always including group membership even if this was unrelated to missingness. Surprisingly, under MAR and MCAR conditions in the assessed scenarios, MI offered no statistical advantage over CC methods. While MI must inherently accompany CC methods for intention-to-treat analyses, these findings endorse CC methods for per protocol risk difference analyses in these conditions. These findings provide an argument for the use of the CC approach to always complement MI analyses, with the usual caveat that the validity of the mechanism for missingness be thoroughly discussed. More importantly, researchers should strive to collect as much data as possible.

Randomization in clinical trials in orthodontics: its significance in research design and methods to achieve it.

PubMed

Pandis, Nikolaos; Polychronopoulou, Argy; Eliades, Theodore

2011-12-01

Randomization is a key step in reducing selection bias during the treatment allocation phase in randomized clinical trials. The process of randomization follows specific steps, which include generation of the randomization list, allocation concealment, and implementation of randomization. The phenomenon in the dental and orthodontic literature of characterizing treatment allocation as random is frequent; however, often the randomization procedures followed are not appropriate. Randomization methods assign, at random, treatment to the trial arms without foreknowledge of allocation by either the participants or the investigators thus reducing selection bias. Randomization entails generation of random allocation, allocation concealment, and the actual methodology of implementing treatment allocation randomly and unpredictably. Most popular randomization methods include some form of restricted and/or stratified randomization. This article introduces the reasons, which make randomization an integral part of solid clinical trial methodology, and presents the main randomization schemes applicable to clinical trials in orthodontics.

Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form.

PubMed

Torres, Sergio N; Pezoa, Jorge E; Hayat, Majeed M

2003-10-10

What is to our knowledge a new scene-based algorithm for nonuniformity correction in infrared focal-plane array sensors has been developed. The technique is based on the inverse covariance form of the Kalman filter (KF), which has been reported previously and used in estimating the gain and bias of each detector in the array from scene data. The gain and the bias of each detector in the focal-plane array are assumed constant within a given sequence of frames, corresponding to a certain time and operational conditions, but they are allowed to randomly drift from one sequence to another following a discrete-time Gauss-Markov process. The inverse covariance form filter estimates the gain and the bias of each detector in the focal-plane array and optimally updates them as they drift in time. The estimation is performed with considerably higher computational efficiency than the equivalent KF. The ability of the algorithm in compensating for fixed-pattern noise in infrared imagery and in reducing the computational complexity is demonstrated by use of both simulated and real data.

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.

Nature of magnetization and lateral spin-orbit interaction in gated semiconductor nanowires.

PubMed

Karlsson, H; Yakimenko, I I; Berggren, K-F

2018-05-31

Semiconductor nanowires are interesting candidates for realization of spintronics devices. In this paper we study electronic states and effects of lateral spin-orbit coupling (LSOC) in a one-dimensional asymmetrically biased nanowire using the Hartree-Fock method with Dirac interaction. We have shown that spin polarization can be triggered by LSOC at finite source-drain bias,as a result of numerical noise representing a random magnetic field due to wiring or a random background magnetic field by Earth magnetic field, for instance. The electrons spontaneously arrange into spin rows in the wire due to electron interactions leading to a finite spin polarization. The direction of polarization is, however, random at zero source-drain bias. We have found that LSOC has an effect on orientation of spin rows only in the case when source-drain bias is applied.

Nature of magnetization and lateral spin–orbit interaction in gated semiconductor nanowires

NASA Astrophysics Data System (ADS)

Karlsson, H.; Yakimenko, I. I.; Berggren, K.-F.

2018-05-01

Semiconductor nanowires are interesting candidates for realization of spintronics devices. In this paper we study electronic states and effects of lateral spin–orbit coupling (LSOC) in a one-dimensional asymmetrically biased nanowire using the Hartree–Fock method with Dirac interaction. We have shown that spin polarization can be triggered by LSOC at finite source-drain bias,as a result of numerical noise representing a random magnetic field due to wiring or a random background magnetic field by Earth magnetic field, for instance. The electrons spontaneously arrange into spin rows in the wire due to electron interactions leading to a finite spin polarization. The direction of polarization is, however, random at zero source-drain bias. We have found that LSOC has an effect on orientation of spin rows only in the case when source-drain bias is applied.

A mathematical model of case-ascertainment bias: Applied to case-control studies nested within a randomized screening trial.

PubMed

Jansen, Rick J; Alexander, Bruce H; Hayes, Richard B; Miller, Anthony B; Wacholder, Sholom; Church, Timothy R

2018-01-01

When some individuals are screen-detected before the beginning of the study, but otherwise would have been diagnosed symptomatically during the study, this results in different case-ascertainment probabilities among screened and unscreened participants, referred to here as lead-time-biased case-ascertainment (LTBCA). In fact, this issue can arise even in risk-factor studies nested within a randomized screening trial; even though the screening intervention is randomly allocated to trial arms, there is no randomization to potential risk-factors and uptake of screening can differ by risk-factor strata. Under the assumptions that neither screening nor the risk factor affects underlying incidence and no other forms of bias operate, we simulate and compare the underlying cumulative incidence and that observed in the study due to LTBCA. The example used will be constructed from the randomized Prostate, Lung, Colorectal, and Ovarian cancer screening trial. The derived mathematical model is applied to simulating two nested studies to evaluate the potential for screening bias in observational lung cancer studies. Because of differential screening under plausible assumptions about preclinical incidence and duration, the simulations presented here show that LTBCA due to chest x-ray screening can significantly increase the estimated risk of lung cancer due to smoking by 1% and 50%. Traditional adjustment methods cannot account for this bias, as the influence screening has on observational study estimates involves events outside of the study observation window (enrollment and follow-up) that change eligibility for potential participants, thus biasing case ascertainment.

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

PubMed

Stanley, T D; Doucouliagos, Hristos

2015-06-15

This study challenges two core conventional meta-analysis methods: fixed effect and random effects. We show how and explain why an unrestricted weighted least squares estimator is superior to conventional random-effects meta-analysis when there is publication (or small-sample) bias and better than a fixed-effect weighted average if there is heterogeneity. Statistical theory and simulations of effect sizes, log odds ratios and regression coefficients demonstrate that this unrestricted weighted least squares estimator provides satisfactory estimates and confidence intervals that are comparable to random effects when there is no publication (or small-sample) bias and identical to fixed-effect meta-analysis when there is no heterogeneity. When there is publication selection bias, the unrestricted weighted least squares approach dominates random effects; when there is excess heterogeneity, it is clearly superior to fixed-effect meta-analysis. In practical applications, an unrestricted weighted least squares weighted average will often provide superior estimates to both conventional fixed and random effects. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

PubMed

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J

2015-12-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. (c) 2015 APA, all rights reserved).

Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations

PubMed Central

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J.

2016-01-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. PMID:26389526

Randomization Methods in Emergency Setting Trials: A Descriptive Review

ERIC Educational Resources Information Center

Corbett, Mark Stephen; Moe-Byrne, Thirimon; Oddie, Sam; McGuire, William

2016-01-01

Background: Quasi-randomization might expedite recruitment into trials in emergency care settings but may also introduce selection bias. Methods: We searched the Cochrane Library and other databases for systematic reviews of interventions in emergency medicine or urgent care settings. We assessed selection bias (baseline imbalances) in prognostic…

The Use of Propensity Scores and Observational Data to Estimate Randomized Controlled Trial Generalizability Bias

PubMed Central

Pressler, Taylor R.; Kaizar, Eloise E.

2014-01-01

While randomized controlled trials (RCT) are considered the “gold standard” for clinical studies, the use of exclusion criteria may impact the external validity of the results. It is unknown whether estimators of effect size are biased by excluding a portion of the target population from enrollment. We propose to use observational data to estimate the bias due to enrollment restrictions, which we term generalizability bias. In this paper we introduce a class of estimators for the generalizability bias and use simulation to study its properties in the presence of non-constant treatment effects. We find the surprising result that our estimators can be unbiased for the true generalizability bias even when all potentially confounding variables are not measured. In addition, our proposed doubly robust estimator performs well even for mis-specified models. PMID:23553373

Challenges to inferring causality from viral information dispersion in dynamic social networks

NASA Astrophysics Data System (ADS)

Ternovski, John

2014-06-01

Understanding the mechanism behind large-scale information dispersion through complex networks has important implications for a variety of industries ranging from cyber-security to public health. With the unprecedented availability of public data from online social networks (OSNs) and the low cost nature of most OSN outreach, randomized controlled experiments, the "gold standard" of causal inference methodologies, have been used with increasing regularity to study viral information dispersion. And while these studies have dramatically furthered our understanding of how information disseminates through social networks by isolating causal mechanisms, there are still major methodological concerns that need to be addressed in future research. This paper delineates why modern OSNs are markedly different from traditional sociological social networks and why these differences present unique challenges to experimentalists and data scientists. The dynamic nature of OSNs is particularly troublesome for researchers implementing experimental designs, so this paper identifies major sources of bias arising from network mutability and suggests strategies to circumvent and adjust for these biases. This paper also discusses the practical considerations of data quality and collection, which may adversely impact the efficiency of the estimator. The major experimental methodologies used in the current literature on virality are assessed at length, and their strengths and limits identified. Other, as-yetunsolved threats to the efficiency and unbiasedness of causal estimators--such as missing data--are also discussed. This paper integrates methodologies and learnings from a variety of fields under an experimental and data science framework in order to systematically consolidate and identify current methodological limitations of randomized controlled experiments conducted in OSNs.

Maximum likelihood estimation of correction for dilution bias in simple linear regression using replicates from subjects with extreme first measurements.

PubMed

Berglund, Lars; Garmo, Hans; Lindbäck, Johan; Svärdsudd, Kurt; Zethelius, Björn

2008-09-30

The least-squares estimator of the slope in a simple linear regression model is biased towards zero when the predictor is measured with random error. A corrected slope may be estimated by adding data from a reliability study, which comprises a subset of subjects from the main study. The precision of this corrected slope depends on the design of the reliability study and estimator choice. Previous work has assumed that the reliability study constitutes a random sample from the main study. A more efficient design is to use subjects with extreme values on their first measurement. Previously, we published a variance formula for the corrected slope, when the correction factor is the slope in the regression of the second measurement on the first. In this paper we show that both designs improve by maximum likelihood estimation (MLE). The precision gain is explained by the inclusion of data from all subjects for estimation of the predictor's variance and by the use of the second measurement for estimation of the covariance between response and predictor. The gain of MLE enhances with stronger true relationship between response and predictor and with lower precision in the predictor measurements. We present a real data example on the relationship between fasting insulin, a surrogate marker, and true insulin sensitivity measured by a gold-standard euglycaemic insulin clamp, and simulations, where the behavior of profile-likelihood-based confidence intervals is examined. MLE was shown to be a robust estimator for non-normal distributions and efficient for small sample situations. Copyright (c) 2008 John Wiley & Sons, Ltd.

Randomized controlled trial of attention bias modification in a racially diverse, socially anxious, alcohol dependent sample.

PubMed

Clerkin, Elise M; Magee, Joshua C; Wells, Tony T; Beard, Courtney; Barnett, Nancy P

2016-12-01

Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Adult participants (N = 86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. Copyright © 2016 Elsevier Ltd. All rights reserved.

Randomized Controlled Trial of Attention Bias Modification in a Racially Diverse, Socially Anxious, Alcohol Dependent Sample

PubMed Central

Clerkin, Elise M.; Magee, Joshua C.; Wells, Tony T.; Beard, Courtney; Barnett, Nancy P.

2016-01-01

Objective Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Method Adult participants (N=86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Results Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. Conclusions These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. PMID:27591918

“Fair Play”: A Videogame Designed to Address Implicit Race Bias Through Active Perspective Taking

PubMed Central

Kaatz, Anna; Chu, Sarah; Ramirez, Dennis; Samson-Samuel, Clem; Carnes, Molly

2014-01-01

Abstract Objective: Having diverse faculty in academic health centers will help diversify the healthcare workforce and reduce health disparities. Implicit race bias is one factor that contributes to the underrepresentation of Black faculty. We designed the videogame “Fair Play” in which players assume the role of a Black graduate student named Jamal Davis. As Jamal, players experience subtle race bias while completing “quests” to obtain a science degree. We hypothesized that participants randomly assigned to play the game would have greater empathy for Jamal and lower implicit race bias than participants randomized to read narrative text describing Jamal's experience. Materials and Methods: University of Wisconsin–Madison graduate students were recruited via e-mail and randomly assigned to play “Fair Play” or read narrative text through an online link. Upon completion, participants took an Implicit Association Test to measure implicit bias and answered survey questions assessing empathy toward Jamal and awareness of bias. Results: As hypothesized, gameplayers showed the least implicit bias but only when they also showed high empathy for Jamal (P=0.013). Gameplayers did not show greater empathy than text readers, and women in the text condition reported the greatest empathy for Jamal (P=0.008). However, high empathy only predicted lower levels of implicit bias among those who actively took Jamal's perspective through gameplay (P=0.014). Conclusions: A videogame in which players experience subtle race bias as a Black graduate student has the potential to reduce implicit bias, possibly because of a game's ability to foster empathy through active perspective taking. PMID:26192644

Evaluating the Bias of Alternative Cost Progress Models: Tests Using Aerospace Industry Acquisition Programs

DTIC Science & Technology

1992-12-01

suspect :mat, -n2 extent predict:.on cas jas ccsiziveiv crrei:=e amonc e v:arious models, :he fandom *.;aik, learn ha r ur e, i;<ea- variable and Bemis...Functions, Production Rate Adjustment Model, Learning Curve Model. Random Walk Model. Bemis Model. Evaluating Model Bias, Cost Prediction Bias. Cost...of four cost progress models--a random walk model, the tradiuonai learning curve model, a production rate model Ifixed-variable model). and a model

Health Surveys Using Mobile Phones in Developing Countries: Automated Active Strata Monitoring and Other Statistical Considerations for Improving Precision and Reducing Biases

PubMed Central

Blynn, Emily; Ahmed, Saifuddin; Gibson, Dustin; Pariyo, George; Hyder, Adnan A

2017-01-01

In low- and middle-income countries (LMICs), historically, household surveys have been carried out by face-to-face interviews to collect survey data related to risk factors for noncommunicable diseases. The proliferation of mobile phone ownership and the access it provides in these countries offers a new opportunity to remotely conduct surveys with increased efficiency and reduced cost. However, the near-ubiquitous ownership of phones, high population mobility, and low cost require a re-examination of statistical recommendations for mobile phone surveys (MPS), especially when surveys are automated. As with landline surveys, random digit dialing remains the most appropriate approach to develop an ideal survey-sampling frame. Once the survey is complete, poststratification weights are generally applied to reduce estimate bias and to adjust for selectivity due to mobile ownership. Since weights increase design effects and reduce sampling efficiency, we introduce the concept of automated active strata monitoring to improve representativeness of the sample distribution to that of the source population. Although some statistical challenges remain, MPS represent a promising emerging means for population-level data collection in LMICs. PMID:28476726

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

PubMed

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

The beneficial effects of a positive attention bias amongst children with a history of psychosocial deprivation.

PubMed

Troller-Renfree, Sonya; McLaughlin, Katie A; Sheridan, Margaret A; Nelson, Charles A; Zeanah, Charles H; Fox, Nathan A

2017-01-01

Children raised in institutions experience psychosocial deprivation that has detrimental influences on attention and mental health. The current study examined patterns of attention biases in children from institutions who were randomized at approximately 21.6 months to receive either a high-quality foster care intervention or care-as-usual. At age 12, children performed a dot-probe task and indices of attention bias were calculated. Additionally, children completed a social stress paradigm and cortisol reactivity was computed. Children randomized into foster care (N=40) exhibited an attention bias toward positive stimuli but not threat, whereas children who received care-as-usual (N=40) and a never-institutionalized comparison group (N=47) showed no bias. Stability of foster care placement was related to positive bias, while instability of foster care placement was related to threat bias. The magnitude of the positive bias was associated with fewer internalizing problems and better coping mechanisms. Within the foster care group, positive attention bias was related to less blunted cortisol reactivity. Copyright © 2016 Elsevier B.V. All rights reserved.

Training Anxious Children to Disengage Attention from Threat: A Randomized Controlled Trial

ERIC Educational Resources Information Center

Bar-Haim, Yair; Morag, Inbar; Glickman, Shlomit

2011-01-01

Background: Threat-related attention biases have been implicated in the etiology and maintenance of anxiety disorders. As a result, attention bias modification (ABM) protocols have been employed as treatments for anxious adults. However, they have yet to emerge for children. A randomized, double-blind placebo-controlled trial was conducted to…

An audit strategy for progression-free survival

PubMed Central

Dodd, Lori E.; Korn, Edward L.; Freidlin, Boris; Gray, Robert; Bhattacharya, Suman

2010-01-01

Summary In randomized clinical trials, the use of potentially subjective endpoints has led to frequent use of blinded independent central review (BICR) and event adjudication committees to reduce possible bias in treatment effect estimators based on local evaluations (LE). In oncology trials, progression-free survival (PFS) is one such endpoint. PFS requires image interpretation to determine whether a patient’s cancer has progressed, and BICR has been advocated to reduce the potential for endpoints to be biased by knowledge of treatment assignment. There is current debate, however, about the value of such reviews with time-to-event outcomes like PFS. We propose a BICR audit strategy as an alternative to a complete-case BICR to provide assurance of the presence of a treatment effect. We develop an auxiliary-variable estimator of the log-hazard ratio that is more efficient than simply using the audited (i.e., sampled) BICR data for estimation. Our estimator incorporates information from the LE on all the cases and the audited BICR cases, and is an asymptotically unbiased estimator of the log-hazard ratio from BICR. The estimator offers considerable efficiency gains that improve as the correlation between LE and BICR increases. A two-stage auditing strategy is also proposed and evaluated through simulation studies. The method is applied retrospectively to a large oncology trial that had a complete-case BICR, showing the potential for efficiency improvements. PMID:21210772

Missing Data and Multiple Imputation: An Unbiased Approach

NASA Technical Reports Server (NTRS)

Foy, M.; VanBaalen, M.; Wear, M.; Mendez, C.; Mason, S.; Meyers, V.; Alexander, D.; Law, J.

2014-01-01

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches.

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

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.

Adaptive adjustment of the randomization ratio using historical control data

PubMed Central

Hobbs, Brian P.; Carlin, Bradley P.; Sargent, Daniel J.

2013-01-01

Background Prospective trial design often occurs in the presence of “acceptable” [1] historical control data. Typically this data is only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis. Purpose We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al. [2], succeeded a similar trial reported by Saltz et al. [3], and used a control therapy identical to that tested (and found beneficial) in the Saltz trial. Methods The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS) characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors [4] are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial’s frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial. Results Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure leads to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs. Limitations Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring. Conclusions The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on pre-existing information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare. PMID:23690095

Adaptive adjustment of the randomization ratio using historical control data.

PubMed

Hobbs, Brian P; Carlin, Bradley P; Sargent, Daniel J

2013-01-01

Prospective trial design often occurs in the presence of 'acceptable' historical control data. Typically, these data are only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis. We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al., succeeded a similar trial reported by Saltz et al., and used a control therapy identical to that tested (and found beneficial) in the Saltz trial. The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS), characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial's frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial. Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure lead to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs. Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring. The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on preexisting information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare.

Attack Vulnerability of Network Controllability

PubMed Central

2016-01-01

Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability. PMID:27588941

Attack Vulnerability of Network Controllability.

PubMed

Lu, Zhe-Ming; Li, Xin-Feng

2016-01-01

Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability.

Interpretation Bias Modification for Youth and their Parents: A Novel Treatment for Early Adolescent Social Anxiety

PubMed Central

Reuland, Meg M.; Teachman, Bethany A.

2014-01-01

Social anxiety is the most prevalent anxiety disorder of late adolescence, yet current treatments reach only a minority of youth with the disorder. Effective and easy-to-disseminate treatments are needed. This study pilot tested the efficacy of a novel, online cognitive bias modification for interpretation (CBM-I) intervention for socially anxious youth and their parents. The CBM-I intervention targeted cognitive biases associated with early adolescents’ maladaptive beliefs regarding social situations, and with parents’ intrusive behavior, both of which have been theoretically linked with the maintenance of social anxiety in youth. To investigate the efficacy of intervening with parents and/or children, clinically diagnosed early adolescents (ages 10–15; N = 18) and their mothers were randomly assigned to one of three conditions: the first targeted early adolescents’ cognitive biases related to social anxiety (Child-only condition); the second targeted parents’ biases associated with intrusive behavior (Parent-only condition); and the third targeted both youth and parents’ biases in tandem (Combo condition). The use of a multiple baseline design allowed for the efficient assessment of causal links between the intervention and reduction in social anxiety symptoms in youth. Results provided converging evidence indicating modest support for the efficacy of CBM-I, with no reliable differences across conditions. Taken together, results suggest that online CBM-I with anxious youth and/or their parents holds promise as an effective and easily administered component of treatment for child social anxiety that deserves further evaluation in a larger trial. PMID:25445075

Interpretation bias modification for youth and their parents: a novel treatment for early adolescent social anxiety.

PubMed

Reuland, Meg M; Teachman, Bethany A

2014-12-01

Social anxiety is the most prevalent anxiety disorder of late adolescence, yet current treatments reach only a minority of youth with the disorder. Effective and easy-to-disseminate treatments are needed. This study pilot tested the efficacy of a novel, online cognitive bias modification for interpretation (CBM-I) intervention for socially anxious youth and their parents. The CBM-I intervention targeted cognitive biases associated with early adolescents' maladaptive beliefs regarding social situations, and with parents' intrusive behavior, both of which have been theoretically linked with the maintenance of social anxiety in youth. To investigate the efficacy of intervening with parents and/or children, clinically diagnosed early adolescents (ages 10-15; N=18) and their mothers were randomly assigned to one of three conditions: the first targeted early adolescents' cognitive biases related to social anxiety (Child-only condition); the second targeted parents' biases associated with intrusive behavior (Parent-only condition); and the third targeted both youth and parents' biases in tandem (Combo condition). The use of a multiple baseline design allowed for the efficient assessment of causal links between the intervention and reduction in social anxiety symptoms in youth. Results provided converging evidence indicating modest support for the efficacy of CBM-I, with no reliable differences across conditions. Taken together, results suggest that online CBM-I with anxious youth and/or their parents holds promise as an effective and easily administered component of treatment for child social anxiety that deserves further evaluation in a larger trial. Copyright © 2014 Elsevier Ltd. All rights reserved.

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"…

Mapping ecological systems with a random foret model: tradeoffs between errors and bias

Treesearch

Emilie Grossmann; Janet Ohmann; James Kagan; Heather May; Matthew Gregory

2010-01-01

New methods for predictive vegetation mapping allow improved estimations of plant community composition across large regions. Random Forest (RF) models limit over-fitting problems of other methods, and are known for making accurate classification predictions from noisy, nonnormal data, but can be biased when plot samples are unbalanced. We developed two contrasting...

The Evaluation of Bias of the Weighted Random Effects Model Estimators. Research Report. ETS RR-11-13

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…

Reader reaction on estimation of treatment effects in all-comers randomized clinical trials with a predictive marker.

PubMed

Korn, Edward L; Freidlin, Boris

2017-06-01

For a fallback randomized clinical trial design with a marker, Choai and Matsui (2015, Biometrics 71, 25-32) estimate the bias of the estimator of the treatment effect in the marker-positive subgroup conditional on the treatment effect not being statistically significant in the overall population. This is used to construct and examine conditionally bias-corrected estimators of the treatment effect for the marker-positive subgroup. We argue that it may not be appropriate to correct for conditional bias in this setting. Instead, we consider the unconditional bias of estimators of the treatment effect for marker-positive patients. © 2016, The International Biometric Society.

Biased random walks on Kleinberg's spatial networks

NASA Astrophysics Data System (ADS)

Pan, Gui-Jun; Niu, Rui-Wu

2016-12-01

We investigate the problem of the particle or message that travels as a biased random walk toward a target node in Kleinberg's spatial network which is built from a d-dimensional (d = 2) regular lattice improved by adding long-range shortcuts with probability P(rij) ∼rij-α, where rij is the lattice distance between sites i and j, and α is a variable exponent. Bias is represented as a probability p of the packet to travel at every hop toward the node which has the smallest Manhattan distance to the target node. We study the mean first passage time (MFPT) for different exponent α and the scaling of the MFPT with the size of the network L. We find that there exists a threshold probability pth ≈ 0.5, for p ≥pth the optimal transportation condition is obtained with an optimal transport exponent αop = d, while for 0 < p pth, and increases with L less than a power law and get close to logarithmical law for 0 < p

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.

Attention bias modification augments cognitive-behavioral group therapy for social anxiety disorder: a randomized controlled trial.

PubMed

Lazarov, Amit; Marom, Sofi; Yahalom, Naomi; Pine, Daniel S; Hermesh, Haggai; Bar-Haim, Yair

2017-12-20

Cognitive-behavioral group therapy (CBGT) is a first-line treatment for social anxiety disorder (SAD). However, since many patients remain symptomatic post-treatment, there is a need for augmenting procedures. This randomized controlled trial (RCT) examined the potential augmentation effect of attention bias modification (ABM) for CBGT. Fifty patients with SAD from three therapy groups were randomized to receive an 18-week standard CBGT with either ABM designed to shift attention away from threat (CBGT + ABM), or a placebo protocol not designed to modify threat-related attention (CBGT + placebo). Therapy groups took place in a large mental health center. Clinician and self-report measures of social anxiety and depression were acquired pre-treatment, post-treatment, and at 3-month follow-up. Attention bias was assessed at pre- and post-treatment. Patients randomized to the CBGT + ABM group, relative to those randomized to the CBGT + placebo group, showed greater reductions in clinician-rated SAD symptoms post-treatment, with effects maintained at 3-month follow-up. Group differences were not evident for self-report or attention-bias measures, with similar reductions in both groups. Finally, reduction in attention bias did not mediate the association between group and reduction in Liebowitz Social Anxiety Scale Structured Interview (LSAS) scores. This is the first RCT to examine the possible augmenting effect of ABM added to group-based cognitive-behavioral therapy for adult SAD. Training patients' attention away from threat might augment the treatment response to standard CBGT in SAD, a possibility that could be further evaluated in large-scale RCTs.

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.

Performance comparison of NE213 detectors for their application in moisture measurement

PubMed

Naqvi; Nagadi; Rehman; Kidwai

2000-10-01

The pulse shape discrimination (PSD) characteristic and neutron detection efficiency of NE213 detectors have been measured for their application in moisture measurements using 252Cf and 241Am-Be sources. In PSD studies, neutron peak to valley (Pn/V) ratio and figure of merit M were measured at four different bias values for cylindrical 50, 125 and 250 mm diameter NE213 detectors. The result of this study has shown that better PSD performance with the NE213 detector can be achieved with a smaller volume detector in conjunction with a neutron source with smaller gamma-ray/neutron ratio. The neutron detection efficiency of the 125 mm diameter NE213 detector for 241Am-Be and 252Cf source spectra was determined at 0.85, 1.25 and 1.75 MeV bias energies using the experimental neutron detection efficiency data of the same detector over 0.1-10 MeV energy range. Due to different energy spectra of the 241Am-Be and 252Cf sources, integrated efficiency of the 125 mm diameter NE213 detector for the two sources shows bias dependence. At smaller bias, 252Cf source has larger efficiency but as the bias is increased, the detector has larger efficiency for 241Am-Be source. This study has revealed that NE213 detector has better performance (such as PSD and neutron detection efficiency) in simultaneous detection of neutron and gamma-rays in moisture measurements, if it is used in conjunction with 241Am-Be source at higher detector bias.

Undesirable Choice Biases with Small Differences in the Spatial Structure of Chance Stimulus Sequences.

PubMed

Herrera, David; Treviño, Mario

2015-01-01

In two-alternative discrimination tasks, experimenters usually randomize the location of the rewarded stimulus so that systematic behavior with respect to irrelevant stimuli can only produce chance performance on the learning curves. One way to achieve this is to use random numbers derived from a discrete binomial distribution to create a 'full random training schedule' (FRS). When using FRS, however, sporadic but long laterally-biased training sequences occur by chance and such 'input biases' are thought to promote the generation of laterally-biased choices (i.e., 'output biases'). As an alternative, a 'Gellerman-like training schedule' (GLS) can be used. It removes most input biases by prohibiting the reward from appearing on the same location for more than three consecutive trials. The sequence of past rewards obtained from choosing a particular discriminative stimulus influences the probability of choosing that same stimulus on subsequent trials. Assuming that the long-term average ratio of choices matches the long-term average ratio of reinforcers, we hypothesized that a reduced amount of input biases in GLS compared to FRS should lead to a reduced production of output biases. We compared the choice patterns produced by a 'Rational Decision Maker' (RDM) in response to computer-generated FRS and GLS training sequences. To create a virtual RDM, we implemented an algorithm that generated choices based on past rewards. Our simulations revealed that, although the GLS presented fewer input biases than the FRS, the virtual RDM produced more output biases with GLS than with FRS under a variety of test conditions. Our results reveal that the statistical and temporal properties of training sequences interacted with the RDM to influence the production of output biases. Thus, discrete changes in the training paradigms did not translate linearly into modifications in the pattern of choices generated by a RDM. Virtual RDMs could be further employed to guide the selection of proper training schedules for perceptual decision-making studies.

The effects of noise due to random undetected tilts and paleosecular variation on regional paleomagnetic directions

USGS Publications Warehouse

Calderone, G.J.; Butler, R.F.

1991-01-01

Random tilting of a single paleomagnetic vector produces a distribution of vectors which is not rotationally symmetric about the original vector and therefore not Fisherian. Monte Carlo simulations were performed on two types of vector distributions: 1) distributions of vectors formed by perturbing a single original vector with a Fisher distribution of bedding poles (each defining a tilt correction) and 2) standard Fisher distributions. These simulations demonstrate that inclinations of vectors drawn from both distributions are biased toward shallow inclinations. The Fisher mean direction of the distribution of vectors formed by perturbing a single vector with random undetected tilts is biased toward shallow inclinations, but this bias is insignificant for angular dispersions of bedding poles less than 20??. -from Authors

Using Audit Information to Adjust Parameter Estimates for Data Errors in Clinical Trials

PubMed Central

Shepherd, Bryan E.; Shaw, Pamela A.; Dodd, Lori E.

2013-01-01

Background Audits are often performed to assess the quality of clinical trial data, but beyond detecting fraud or sloppiness, the audit data is generally ignored. In earlier work using data from a non-randomized study, Shepherd and Yu (2011) developed statistical methods to incorporate audit results into study estimates, and demonstrated that audit data could be used to eliminate bias. Purpose In this manuscript we examine the usefulness of audit-based error-correction methods in clinical trial settings where a continuous outcome is of primary interest. Methods We demonstrate the bias of multiple linear regression estimates in general settings with an outcome that may have errors and a set of covariates for which some may have errors and others, including treatment assignment, are recorded correctly for all subjects. We study this bias under different assumptions including independence between treatment assignment, covariates, and data errors (conceivable in a double-blinded randomized trial) and independence between treatment assignment and covariates but not data errors (possible in an unblinded randomized trial). We review moment-based estimators to incorporate the audit data and propose new multiple imputation estimators. The performance of estimators is studied in simulations. Results When treatment is randomized and unrelated to data errors, estimates of the treatment effect using the original error-prone data (i.e., ignoring the audit results) are unbiased. In this setting, both moment and multiple imputation estimators incorporating audit data are more variable than standard analyses using the original data. In contrast, in settings where treatment is randomized but correlated with data errors and in settings where treatment is not randomized, standard treatment effect estimates will be biased. And in all settings, parameter estimates for the original, error-prone covariates will be biased. Treatment and covariate effect estimates can be corrected by incorporating audit data using either the multiple imputation or moment-based approaches. Bias, precision, and coverage of confidence intervals improve as the audit size increases. Limitations The extent of bias and the performance of methods depend on the extent and nature of the error as well as the size of the audit. This work only considers methods for the linear model. Settings much different than those considered here need further study. Conclusions In randomized trials with continuous outcomes and treatment assignment independent of data errors, standard analyses of treatment effects will be unbiased and are recommended. However, if treatment assignment is correlated with data errors or other covariates, naive analyses may be biased. In these settings, and when covariate effects are of interest, approaches for incorporating audit results should be considered. PMID:22848072

Risk of bias reporting in the recent animal focal cerebral ischaemia literature.

PubMed

Bahor, Zsanett; Liao, Jing; Macleod, Malcolm R; Bannach-Brown, Alexandra; McCann, Sarah K; Wever, Kimberley E; Thomas, James; Ottavi, Thomas; Howells, David W; Rice, Andrew; Ananiadou, Sophia; Sena, Emily

2017-10-15

Findings from in vivo research may be less reliable where studies do not report measures to reduce risks of bias. The experimental stroke community has been at the forefront of implementing changes to improve reporting, but it is not known whether these efforts are associated with continuous improvements. Our aims here were firstly to validate an automated tool to assess risks of bias in published works, and secondly to assess the reporting of measures taken to reduce the risk of bias within recent literature for two experimental models of stroke. We developed and used text analytic approaches to automatically ascertain reporting of measures to reduce risk of bias from full-text articles describing animal experiments inducing middle cerebral artery occlusion (MCAO) or modelling lacunar stroke. Compared with previous assessments, there were improvements in the reporting of measures taken to reduce risks of bias in the MCAO literature but not in the lacunar stroke literature. Accuracy of automated annotation of risk of bias in the MCAO literature was 86% (randomization), 94% (blinding) and 100% (sample size calculation); and in the lacunar stroke literature accuracy was 67% (randomization), 91% (blinding) and 96% (sample size calculation). There remains substantial opportunity for improvement in the reporting of animal research modelling stroke, particularly in the lacunar stroke literature. Further, automated tools perform sufficiently well to identify whether studies report blinded assessment of outcome, but improvements are required in the tools to ascertain whether randomization and a sample size calculation were reported. © 2017 The Author(s).

Correction of gene expression data: Performance-dependency on inter-replicate and inter-treatment biases.

PubMed

Darbani, Behrooz; Stewart, C Neal; Noeparvar, Shahin; Borg, Søren

2014-10-20

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies of correction methods are influenced by the inter-treatment bias as well as the inter-replicate variance. Therefore, we recommend inspecting both of the bias sources in order to apply the most efficient correction method. As an alternative correction strategy, sequential application of different correction approaches is also advised. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of Relative Bias, Precision, and Efficiency of Sampling Methods for Natural Enemies of Soybean Aphid (Hemiptera: Aphididae).

PubMed

Bannerman, J A; Costamagna, A C; McCornack, B P; Ragsdale, D W

2015-06-01

Generalist natural enemies play an important role in controlling soybean aphid, Aphis glycines (Hemiptera: Aphididae), in North America. Several sampling methods are used to monitor natural enemy populations in soybean, but there has been little work investigating their relative bias, precision, and efficiency. We compare five sampling methods: quadrats, whole-plant counts, sweep-netting, walking transects, and yellow sticky cards to determine the most practical methods for sampling the three most prominent species, which included Harmonia axyridis (Pallas), Coccinella septempunctata L. (Coleoptera: Coccinellidae), and Orius insidiosus (Say) (Hemiptera: Anthocoridae). We show an important time by sampling method interaction indicated by diverging community similarities within and between sampling methods as the growing season progressed. Similarly, correlations between sampling methods for the three most abundant species over multiple time periods indicated differences in relative bias between sampling methods and suggests that bias is not consistent throughout the growing season, particularly for sticky cards and whole-plant samples. Furthermore, we show that sticky cards produce strongly biased capture rates relative to the other four sampling methods. Precision and efficiency differed between sampling methods and sticky cards produced the most precise (but highly biased) results for adult natural enemies, while walking transects and whole-plant counts were the most efficient methods for detecting coccinellids and O. insidiosus, respectively. Based on bias, precision, and efficiency considerations, the most practical sampling methods for monitoring in soybean include walking transects for coccinellid detection and whole-plant counts for detection of small predators like O. insidiosus. Sweep-netting and quadrat samples are also useful for some applications, when efficiency is not paramount. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

More ethical and more efficient clinical research: multiplex trial design.

PubMed

Keus, Frederik; van der Horst, Iwan C C; Nijsten, Maarten W

2014-08-14

Today's clinical research faces challenges such as a lack of clinical equipoise between treatment arms, reluctance in randomizing for multiple treatments simultaneously, inability to address interactions and increasingly restricted resources. Furthermore, many trials are biased by extensive exclusion criteria, relatively small sample size and less appropriate outcome measures. We propose a 'Multiplex' trial design that preserves clinical equipoise with a continuous and factorial trial design that will also result in more efficient use of resources. This multiplex design accommodates subtrials with appropriate choice of treatment arms within each subtrial. Clinical equipoise should increase consent rates while the factorial design is the best way to identify interactions. The multiplex design may evolve naturally from today's research limitations and challenges, while principal objections seem absent. However this new design poses important infrastructural, organisational and psychological challenges that need in depth consideration.

Scale of reference bias and the evolution of health.

PubMed

Groot, Wim

2003-09-01

The analysis of subjective measures of well-being-such as self-reports by individuals about their health status is frequently hampered by the problem of scale of reference bias. A particular form of scale of reference bias is age norming. In this study we corrected for scale of reference bias by allowing for individual specific effects in an equation on subjective health. A random effects ordered response model was used to analyze scale of reference bias in self-reported health measures. The results indicate that if we do not control for unobservable individual specific effects, the response to a subjective health state measure suffers from age norming. Age norming can be controlled for by a random effects estimation technique using longitudinal data. Further, estimates are presented on the rate of depreciation of health. Finally, simulations of life expectancy indicate that the estimated model provides a reasonably good fit of the true life expectancy.

Balancing the popularity bias of object similarities for personalised recommendation

NASA Astrophysics Data System (ADS)

Hou, Lei; Pan, Xue; Liu, Kecheng

2018-03-01

Network-based similarity measures have found wide applications in recommendation algorithms and made significant contributions for uncovering users' potential interests. However, existing measures are generally biased in terms of popularity, that the popular objects tend to have more common neighbours with others and thus are considered more similar to others. Such popularity bias of similarity quantification will result in the biased recommendations, with either poor accuracy or poor diversity. Based on the bipartite network modelling of the user-object interactions, this paper firstly calculates the expected number of common neighbours of two objects with given popularities in random networks. A Balanced Common Neighbour similarity index is accordingly developed by removing the random-driven common neighbours, estimated as the expected number, from the total number. Recommendation experiments in three data sets show that balancing the popularity bias in a certain degree can significantly improve the recommendations' accuracy and diversity simultaneously.

Student Sorting and Bias in Value Added Estimation: Selection on Observables and Unobservables. NBER Working Paper No. 14666

ERIC Educational Resources Information Center

Rothstein, Jesse

2009-01-01

Non-random assignment of students to teachers can bias value added estimates of teachers' causal effects. Rothstein (2008a, b) shows that typical value added models indicate large counter-factual effects of 5th grade teachers on students' 4th grade learning, indicating that classroom assignments are far from random. This paper quantifies the…

Trial Registration: Understanding and Preventing Reporting Bias in Social Work Research

ERIC Educational Resources Information Center

Harrison, Bronwyn A.; Mayo-Wilson, Evan

2014-01-01

Randomized controlled trials are considered the gold standard for evaluating social work interventions. However, published reports can systematically overestimate intervention effects when researchers selectively report large and significant findings. Publication bias and other types of reporting biases can be minimized through prospective trial…

Social Interpretation Bias in Children and Adolescents with Anxiety Disorders: Psychometric Examination of the Self-report of Ambiguous Social Situations for Youth (SASSY) Scale.

PubMed

Gonzalez, Araceli; Rozenman, Michelle; Langley, Audra K; Kendall, Philip C; Ginsburg, Golda S; Compton, Scott; Walkup, John T; Birmaher, Boris; Albano, Anne Marie; Piacentini, John

2017-06-01

Anxiety disorders are among the most common mental health problems in youth, and faulty interpretation bias has been positively linked to anxiety severity, even within anxiety-disordered youth. Quick, reliable assessment of interpretation bias may be useful in identifying youth with certain types of anxiety or assessing changes on cognitive bias during intervention. This study examined the factor structure, reliability, and validity of the Self-report of Ambiguous Social Situations for Youth (SASSY) scale, a self-report measure developed to assess interpretation bias in youth. Participants (N=488, age 7 to 17) met diagnostic criteria for Social Phobia, Generalized Anxiety Disorder, and/or Separation Anxiety Disorder. An exploratory factor analysis was performed on baseline data from youth participating in a large randomized clinical trial. Exploratory factor analysis yielded two factors (Accusation/Blame, Social Rejection). The SASSY full scale and Social Rejection factor demonstrated adequate internal consistency, convergent validity with social anxiety, and discriminant validity as evidenced by non-significant correlations with measures of non-social anxiety. Further, the SASSY Social Rejection factor accurately distinguished children and adolescents with Social Phobia from those with other anxiety disorders, supporting its criterion validity, and revealed sensitivity to changes with treatment. Given the relevance to youth with social phobia, pre- and post-intervention data were examined for youth social phobia to test sensitivity to treatment effects; results suggested that SASSY scores reduced for treatment responders. Findings suggest the potential utility of the SASSY Social Rejection factor as a quick, reliable, and efficient way of assessing interpretation bias in anxious youth, particularly as related to social concerns, in research and clinical settings.

Translation efficiency is determined by both codon bias and folding energy

PubMed Central

Tuller, Tamir; Waldman, Yedael Y.; Kupiec, Martin; Ruppin, Eytan

2010-01-01

Synonymous mutations do not alter the protein produced yet can have a significant effect on protein levels. The mechanisms by which this effect is achieved are controversial; although some previous studies have suggested that codon bias is the most important determinant of translation efficiency, a recent study suggested that mRNA folding at the beginning of genes is the dominant factor via its effect on translation initiation. Using the Escherichia coli and Saccharomyces cerevisiae transcriptomes, we conducted a genome-scale study aiming at dissecting the determinants of translation efficiency. There is a significant association between codon bias and translation efficiency across all endogenous genes in E. coli and S. cerevisiae but no association between folding energy and translation efficiency, demonstrating the role of codon bias as an important determinant of translation efficiency. However, folding energy does modulate the strength of association between codon bias and translation efficiency, which is maximized at very weak mRNA folding (i.e., high folding energy) levels. We find a strong correlation between the genomic profiles of ribosomal density and genomic profiles of folding energy across mRNA, suggesting that lower folding energies slow down the ribosomes and decrease translation efficiency. Accordingly, we find that selection forces act near uniformly to decrease the folding energy at the beginning of genes. In summary, these findings testify that in endogenous genes, folding energy affects translation efficiency in a global manner that is not related to the expression levels of individual genes, and thus cannot be detected by correlation with their expression levels. PMID:20133581

Health Surveys Using Mobile Phones in Developing Countries: Automated Active Strata Monitoring and Other Statistical Considerations for Improving Precision and Reducing Biases.

PubMed

Labrique, Alain; Blynn, Emily; Ahmed, Saifuddin; Gibson, Dustin; Pariyo, George; Hyder, Adnan A

2017-05-05

In low- and middle-income countries (LMICs), historically, household surveys have been carried out by face-to-face interviews to collect survey data related to risk factors for noncommunicable diseases. The proliferation of mobile phone ownership and the access it provides in these countries offers a new opportunity to remotely conduct surveys with increased efficiency and reduced cost. However, the near-ubiquitous ownership of phones, high population mobility, and low cost require a re-examination of statistical recommendations for mobile phone surveys (MPS), especially when surveys are automated. As with landline surveys, random digit dialing remains the most appropriate approach to develop an ideal survey-sampling frame. Once the survey is complete, poststratification weights are generally applied to reduce estimate bias and to adjust for selectivity due to mobile ownership. Since weights increase design effects and reduce sampling efficiency, we introduce the concept of automated active strata monitoring to improve representativeness of the sample distribution to that of the source population. Although some statistical challenges remain, MPS represent a promising emerging means for population-level data collection in LMICs. ©Alain Labrique, Emily Blynn, Saifuddin Ahmed, Dustin Gibson, George Pariyo, Adnan A Hyder. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.05.2017.

Magnetic Random Access Memory based non-volatile asynchronous Muller cell for ultra-low power autonomous applications

NASA Astrophysics Data System (ADS)

Di Pendina, G.; Zianbetov, E.; Beigne, E.

2015-05-01

Micro and nano electronic integrated circuit domain is today mainly driven by the advent of the Internet of Things for which the constraints are strong, especially in terms of power consumption and autonomy, not only during the computing phases but also during the standby or idle phases. In such ultra-low power applications, the circuit has to meet new constraints mainly linked to its changing energetic environment: long idle phases, automatic wake up, data back-up when the circuit is sporadically turned off, and ultra-low voltage power supply operation. Such circuits have to be completely autonomous regarding their unstable environment, while remaining in an optimum energetic configuration. Therefore, we propose in this paper the first MRAM-based non-volatile asynchronous Muller cell. This cell has been simulated and characterized in a very advanced 28 nm CMOS fully depleted silicon-on-insulator technology, presenting good power performance results due to an extremely efficient body biasing control together with ultra-wide supply voltage range from 160 mV up to 920 mV. The leakage current can be reduced to 154 pA thanks to reverse body biasing. We also propose an efficient standard CMOS bulk version of this cell in order to be compatible with different fabrication processes.

Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome

PubMed Central

Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C

2012-01-01

Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model. PMID:22368390

Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome.

PubMed

Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C

2012-01-01

Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model.

Hypothesis Testing Using Factor Score Regression

PubMed Central

Devlieger, Ines; Mayer, Axel; Rosseel, Yves

2015-01-01

In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and with structural equation modeling (SEM) by using analytic calculations and two Monte Carlo simulation studies to examine their finite sample characteristics. Several performance criteria are used, such as the bias using the unstandardized and standardized parameterization, efficiency, mean square error, standard error bias, type I error rate, and power. The results show that the bias correcting method, with the newly developed standard error, is the only suitable alternative for SEM. While it has a higher standard error bias than SEM, it has a comparable bias, efficiency, mean square error, power, and type I error rate. PMID:29795886

Assessment of the ecological bias of seven aggregate social deprivation indices.

PubMed

Bryere, Josephine; Pornet, Carole; Copin, Nane; Launay, Ludivine; Gusto, Gaëlle; Grosclaude, Pascale; Delpierre, Cyrille; Lang, Thierry; Lantieri, Olivier; Dejardin, Olivier; Launoy, Guy

2017-01-17

In aggregate studies, ecological indices are used to study the influence of socioeconomic status on health. Their main limitation is ecological bias. This study assesses the misclassification of individual socioeconomic status in seven ecological indices. Individual socioeconomic data for a random sample of 10,000 persons came from periodic health examinations conducted in 2006 in 11 French departments. Geographical data came from the 2007 census at the lowest geographical level available in France. The Receiver Operating Characteristics (ROC) curves, the areas under the curves (AUC) for each individual variable, and the distribution of deprived and non-deprived persons in quintiles of each aggregate score were analyzed. The aggregate indices studied are quite good "proxies" for individual deprivation (AUC close to 0.7), and they have similar performance. The indices are more efficient at measuring individual income than education or occupational category and are suitable for measuring of deprivation but not affluence. The study inventoried the aggregate indices available in France and evaluated their assessment of individual SES.

Participation Bias among Suicidal Adults in a Randomized Controlled Trial

ERIC Educational Resources Information Center

Stirman, Shannon Wiltsey; Brown, Gregory K.; Ghahramanlou-Holloway, Marjan; Fox, Allison J.; Chohan, Mariam Zahid; Beck, Aaron T.

2011-01-01

Although individuals who attempt suicide have poor compliance rates with treatment recommendations, the nature and degree of participation bias in clinical treatment research among these individuals is virtually unknown. The purpose of this study was to examine participation bias by comparing the demographic and diagnostic characteristics of adult…

Propensity Score Matching: Retrospective Randomization?

PubMed

Jupiter, Daniel C

Randomized controlled trials are viewed as the optimal study design. In this commentary, we explore the strength of this design and its complexity. We also discuss some situations in which these trials are not possible, or not ethical, or not economical. In such situations, specifically, in retrospective studies, we should make every effort to recapitulate the rigor and strength of the randomized trial. However, we could be faced with an inherent indication bias in such a setting. Thus, we consider the tools available to address that bias. Specifically, we examine matching and introduce and explore a new tool: propensity score matching. This tool allows us to group subjects according to their propensity to be in a particular treatment group and, in so doing, to account for the indication bias. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials.

PubMed

Wang, Sue-Jane; O'Neill, Robert T; Hung, Hm James

2010-10-01

The current practice for seeking genomically favorable patients in randomized controlled clinical trials using genomic convenience samples. To discuss the extent of imbalance, confounding, bias, design efficiency loss, type I error, and type II error that can occur in the evaluation of the convenience samples, particularly when they are small samples. To articulate statistical considerations for a reasonable sample size to minimize the chance of imbalance, and, to highlight the importance of replicating the subgroup finding in independent studies. Four case examples reflecting recent regulatory experiences are used to underscore the problems with convenience samples. Probability of imbalance for a pre-specified subgroup is provided to elucidate sample size needed to minimize the chance of imbalance. We use an example drug development to highlight the level of scientific rigor needed, with evidence replicated for a pre-specified subgroup claim. The convenience samples evaluated ranged from 18% to 38% of the intent-to-treat samples with sample size ranging from 100 to 5000 patients per arm. The baseline imbalance can occur with probability higher than 25%. Mild to moderate multiple confounders yielding the same directional bias in favor of the treated group can make treatment group incomparable at baseline and result in a false positive conclusion that there is a treatment difference. Conversely, if the same directional bias favors the placebo group or there is loss in design efficiency, the type II error can increase substantially. Pre-specification of a genomic subgroup hypothesis is useful only for some degree of type I error control. Complete ascertainment of genomic samples in a randomized controlled trial should be the first step to explore if a favorable genomic patient subgroup suggests a treatment effect when there is no clear prior knowledge and understanding about how the mechanism of a drug target affects the clinical outcome of interest. When stratified randomization based on genomic biomarker status cannot be implemented in designing a pharmacogenomics confirmatory clinical trial, if there is one genomic biomarker prognostic for clinical response, as a general rule of thumb, a sample size of at least 100 patients may be needed to be considered for the lower prevalence genomic subgroup to minimize the chance of an imbalance of 20% or more difference in the prevalence of the genomic marker. The sample size may need to be at least 150, 350, and 1350, respectively, if an imbalance of 15%, 10% and 5% difference is of concern.

Randomized controlled trials in dentistry: common pitfalls and how to avoid them.

PubMed

Fleming, Padhraig S; Lynch, Christopher D; Pandis, Nikolaos

2014-08-01

Clinical trials are used to appraise the effectiveness of clinical interventions throughout medicine and dentistry. Randomized controlled trials (RCTs) are established as the optimal primary design and are published with increasing frequency within the biomedical sciences, including dentistry. This review outlines common pitfalls associated with the conduct of randomized controlled trials in dentistry. Common failings in RCT design leading to various types of bias including selection, performance, detection and attrition bias are discussed in this review. Moreover, methods of minimizing and eliminating bias are presented to ensure that maximal benefit is derived from RCTs within dentistry. Well-designed RCTs have both upstream and downstream uses acting as a template for development and populating systematic reviews to permit more precise estimates of treatment efficacy and effectiveness. However, there is increasing awareness of waste in clinical research, whereby resource-intensive studies fail to provide a commensurate level of scientific evidence. Waste may stem either from inappropriate design or from inadequate reporting of RCTs; the importance of robust conduct of RCTs within dentistry is clear. Optimal reporting of randomized controlled trials within dentistry is necessary to ensure that trials are reliable and valid. Common shortcomings leading to important forms or bias are discussed and approaches to minimizing these issues are outlined. Copyright © 2014 Elsevier Ltd. All rights reserved.

Robust random telegraph conductivity noise in single crystals of the ferromagnetic insulating manganite La0.86Ca0.14MnO3

NASA Astrophysics Data System (ADS)

Przybytek, J.; Fink-Finowicki, J.; Puźniak, R.; Shames, A.; Markovich, V.; Mogilyansky, D.; Jung, G.

2017-03-01

Robust random telegraph conductivity fluctuations have been observed in La0.86Ca0.14MnO3 manganite single crystals. At room temperatures, the spectra of conductivity fluctuations are featureless and follow a 1 /f shape in the entire experimental frequency and bias range. Upon lowering the temperature, clear Lorentzian bias-dependent excess noise appears on the 1 /f background and eventually dominates the spectral behavior. In the time domain, fully developed Lorentzian noise appears as pronounced two-level random telegraph noise with a thermally activated switching rate, which does not depend on bias current and applied magnetic field. The telegraph noise is very robust and persists in the exceptionally wide temperature range of more than 50 K. The amplitude of the telegraph noise decreases exponentially with increasing bias current in exactly the same manner as the sample resistance increases with the current, pointing out the dynamic current redistribution between percolation paths dominated by phase-separated clusters with different conductivity as a possible origin of two-level conductivity fluctuations.

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

PubMed Central

Bakbergenuly, Ilyas; Morgenthaler, Stephan

2016-01-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability p^, both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence. PMID:27192062

Estimating causal contrasts involving intermediate variables in the presence of selection bias.

PubMed

Valeri, Linda; Coull, Brent A

2016-11-20

An important goal across the biomedical and social sciences is the quantification of the role of intermediate factors in explaining how an exposure exerts an effect on an outcome. Selection bias has the potential to severely undermine the validity of inferences on direct and indirect causal effects in observational as well as in randomized studies. The phenomenon of selection may arise through several mechanisms, and we here focus on instances of missing data. We study the sign and magnitude of selection bias in the estimates of direct and indirect effects when data on any of the factors involved in the analysis is either missing at random or not missing at random. Under some simplifying assumptions, the bias formulae can lead to nonparametric sensitivity analyses. These sensitivity analyses can be applied to causal effects on the risk difference and risk-ratio scales irrespectively of the estimation approach employed. To incorporate parametric assumptions, we also develop a sensitivity analysis for selection bias in mediation analysis in the spirit of the expectation-maximization algorithm. The approaches are applied to data from a health disparities study investigating the role of stage at diagnosis on racial disparities in colorectal cancer survival. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

R. A. Fisher and his advocacy of randomization.

PubMed

Hall, Nancy S

2007-01-01

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods.

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

PubMed Central

Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D

2004-01-01

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

PubMed

Zhu, Qiaohao; Carriere, K C

2016-01-01

Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

High efficiency FET microwave detector design

NASA Astrophysics Data System (ADS)

Luglio, Juan; Ishii, Thomas Koryu

1990-12-01

The work is based on an assumption that very little microwave power would be consumed at a negatively biased gate of a microwave FET, yet significant detected signals would be obtained at the drain if the bias is given. By analyzing a Taylor-series expansion of the drain-current equation in the vicinity of a fixed gate-bias voltage, the bias voltage is found to maximize the second derivative of the drain current, the gate-bias voltage characteristic curve for the maximum detected drain current under a given fixed drain-bias voltage. Based on these findings, a high-efficiency microwave detector is designed, fabricated, and tested at 8.6 GHz, and it is shown that the audio power over absorbed microwave power ratio of the detector is 135 percent due to the positive gain.

The Effect of Framing on Surrogate Optimism Bias: A Simulation Study

PubMed Central

Patel, Dev; Cohen, Elan D.; Barnato, Amber E.

2016-01-01

Purpose To explore the effect of emotion priming and physician communication behaviors on optimism bias. Materials and Methods We conducted a 5 × 2 between-subject randomized factorial experiment using a web-based interactive video designed to simulate a family meeting for a critically ill spouse/parent. Eligibility included age ≥ 35 and self-identifying as the surrogate for a spouse/parent. The primary outcome was the surrogate's election of code status. We defined optimism bias as the surrogate's estimate of prognosis with CPR > their recollection of the physician's estimate. Results 256/373 respondents (69%) logged-in and were randomized and 220 (86%) had non-missing data for prognosis. 67/220 (30%) overall, and 56/173 (32%) of those with an accurate recollection of the physician's estimate had optimism bias. Optimism bias correlated with choosing CPR (p<.001). Emotion priming (p=.397), physician attention to emotion (p=.537), and framing of CPR as the social norm (p=.884) did not affect optimism bias. Framing the decision as the patient's vs. the surrogate's (25% vs. 36%, p=.066) and describing the alternative to CPR as “allow natural death” instead of “do not resuscitate” (25% vs. 37%, p =.035) decreased optimism bias. Conclusions Framing of CPR choice during code status conversations may influence surrogates’ optimism bias. PMID:26796950

Correcting Biases in a lower resolution global circulation model with data assimilation

NASA Astrophysics Data System (ADS)

Canter, Martin; Barth, Alexander

2016-04-01

With this work, we aim at developping a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias. First, through a preliminary run, we estimate the bias of the model and its possible sources. Then, we establish a forcing term which is directly added inside the model's equations. We create an ensemble of runs and consider the forcing term as a control variable during the assimilation of observations. We then use this analysed forcing term to correct the bias of the model. Since the forcing is added inside the model, it acts as a source term, unlike external forcings such as wind. This procedure has been developed and successfully tested with a twin experiment on a Lorenz 95 model. It is currently being applied and tested on the sea ice ocean NEMO LIM model, which is used in the PredAntar project. NEMO LIM is a global and low resolution (2 degrees) coupled model (hydrodynamic model and sea ice model) with long time steps allowing simulations over several decades. Due to its low resolution, the model is subject to bias in area where strong currents are present. We aim at correcting this bias by using perturbed current fields from higher resolution models and randomly generated perturbations. The random perturbations need to be constrained in order to respect the physical properties of the ocean, and not create unwanted phenomena. To construct those random perturbations, we first create a random field with the Diva tool (Data-Interpolating Variational Analysis). Using a cost function, this tool penalizes abrupt variations in the field, while using a custom correlation length. It also decouples disconnected areas based on topography. Then, we filter the field to smoothen it and remove small scale variations. We use this field as a random stream function, and take its derivatives to get zonal and meridional velocity fields. We also constrain the stream function along the coasts in order not to have currents perpendicular to the coast. The randomly generated stochastic forcing are then directly injected into the NEMO LIM model's equations in order to force the model at each timestep, and not only during the assimilation step. Results from a twin experiment will be presented. This method is being applied to a real case, with observations on the sea surface height available from the mean dynamic topography of CNES (Centre national d'études spatiales). The model, the bias correction, and more extensive forcings, in particular with a three dimensional structure and a time-varying component, will also be presented.

Cryptographic Boolean Functions with Biased Inputs

DTIC Science & Technology

2015-07-31

theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the

Topology-dependent density optima for efficient simultaneous network exploration

NASA Astrophysics Data System (ADS)

Wilson, Daniel B.; Baker, Ruth E.; Woodhouse, Francis G.

2018-06-01

A random search process in a networked environment is governed by the time it takes to visit every node, termed the cover time. Often, a networked process does not proceed in isolation but competes with many instances of itself within the same environment. A key unanswered question is how to optimize this process: How many concurrent searchers can a topology support before the benefits of parallelism are outweighed by competition for space? Here, we introduce the searcher-averaged parallel cover time (APCT) to quantify these economies of scale. We show that the APCT of the networked symmetric exclusion process is optimized at a searcher density that is well predicted by the spectral gap. Furthermore, we find that nonequilibrium processes, realized through the addition of bias, can support significantly increased density optima. Our results suggest alternative hybrid strategies of serial and parallel search for efficient information gathering in social interaction and biological transport networks.

Survival analysis for the missing censoring indicator model using kernel density estimation techniques

PubMed Central

Subramanian, Sundarraman

2008-01-01

This article concerns asymptotic theory for a new estimator of a survival function in the missing censoring indicator model of random censorship. Specifically, the large sample results for an inverse probability-of-non-missingness weighted estimator of the cumulative hazard function, so far not available, are derived, including an almost sure representation with rate for a remainder term, and uniform strong consistency with rate of convergence. The estimator is based on a kernel estimate for the conditional probability of non-missingness of the censoring indicator. Expressions for its bias and variance, in turn leading to an expression for the mean squared error as a function of the bandwidth, are also obtained. The corresponding estimator of the survival function, whose weak convergence is derived, is asymptotically efficient. A numerical study, comparing the performances of the proposed and two other currently existing efficient estimators, is presented. PMID:18953423

Survival analysis for the missing censoring indicator model using kernel density estimation techniques.

PubMed

Subramanian, Sundarraman

2006-01-01

This article concerns asymptotic theory for a new estimator of a survival function in the missing censoring indicator model of random censorship. Specifically, the large sample results for an inverse probability-of-non-missingness weighted estimator of the cumulative hazard function, so far not available, are derived, including an almost sure representation with rate for a remainder term, and uniform strong consistency with rate of convergence. The estimator is based on a kernel estimate for the conditional probability of non-missingness of the censoring indicator. Expressions for its bias and variance, in turn leading to an expression for the mean squared error as a function of the bandwidth, are also obtained. The corresponding estimator of the survival function, whose weak convergence is derived, is asymptotically efficient. A numerical study, comparing the performances of the proposed and two other currently existing efficient estimators, is presented.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

PubMed

Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Method and apparatus for in-situ characterization of energy storage and energy conversion devices

DOEpatents

Christophersen, Jon P [Idaho Falls, ID; Motloch, Chester G [Idaho Falls, ID; Morrison, John L [Butte, MT; Albrecht, Weston [Layton, UT

2010-03-09

Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.

Estimating the efficacy of Alcoholics Anonymous without self-selection bias: An instrumental variables re-analysis of randomized clinical trials

PubMed Central

Humphreys, Keith; Blodgett, Janet C.; Wagner, Todd H.

2014-01-01

Background Observational studies of Alcoholics Anonymous’ (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study therefore employed an innovative statistical technique to derive a selection bias-free estimate of AA’s impact. Methods Six datasets from 5 National Institutes of Health-funded randomized trials (one with two independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol dependent individuals in one of the datasets (n = 774) were analyzed separately from the rest of sample (n = 1582 individuals pooled from 5 datasets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable. Results Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In five of the six data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = .38, p = .001) and 15-month (B = 0.42, p = .04) follow-up. However, in the remaining dataset, in which pre-existing AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome. Conclusions For most individuals seeking help for alcohol problems, increasing AA attendance leads to short and long term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high pre-existing AA involvement, further increases in AA attendance may have little impact. PMID:25421504

Estimating the efficacy of Alcoholics Anonymous without self-selection bias: an instrumental variables re-analysis of randomized clinical trials.

PubMed

Humphreys, Keith; Blodgett, Janet C; Wagner, Todd H

2014-11-01

Observational studies of Alcoholics Anonymous' (AA) effectiveness are vulnerable to self-selection bias because individuals choose whether or not to attend AA. The present study, therefore, employed an innovative statistical technique to derive a selection bias-free estimate of AA's impact. Six data sets from 5 National Institutes of Health-funded randomized trials (1 with 2 independent parallel arms) of AA facilitation interventions were analyzed using instrumental variables models. Alcohol-dependent individuals in one of the data sets (n = 774) were analyzed separately from the rest of sample (n = 1,582 individuals pooled from 5 data sets) because of heterogeneity in sample parameters. Randomization itself was used as the instrumental variable. Randomization was a good instrument in both samples, effectively predicting increased AA attendance that could not be attributed to self-selection. In 5 of the 6 data sets, which were pooled for analysis, increased AA attendance that was attributable to randomization (i.e., free of self-selection bias) was effective at increasing days of abstinence at 3-month (B = 0.38, p = 0.001) and 15-month (B = 0.42, p = 0.04) follow-up. However, in the remaining data set, in which preexisting AA attendance was much higher, further increases in AA involvement caused by the randomly assigned facilitation intervention did not affect drinking outcome. For most individuals seeking help for alcohol problems, increasing AA attendance leads to short- and long-term decreases in alcohol consumption that cannot be attributed to self-selection. However, for populations with high preexisting AA involvement, further increases in AA attendance may have little impact. Copyright © 2014 by the Research Society on Alcoholism.

Estimation and modeling of electrofishing capture efficiency for fishes in wadeable warmwater streams

USGS Publications Warehouse

Price, A.; Peterson, James T.

2010-01-01

Stream fish managers often use fish sample data to inform management decisions affecting fish populations. Fish sample data, however, can be biased by the same factors affecting fish populations. To minimize the effect of sample biases on decision making, biologists need information on the effectiveness of fish sampling methods. We evaluated single-pass backpack electrofishing and seining combined with electrofishing by following a dual-gear, mark–recapture approach in 61 blocknetted sample units within first- to third-order streams. We also estimated fish movement out of unblocked units during sampling. Capture efficiency and fish abundances were modeled for 50 fish species by use of conditional multinomial capture–recapture models. The best-approximating models indicated that capture efficiencies were generally low and differed among species groups based on family or genus. Efficiencies of single-pass electrofishing and seining combined with electrofishing were greatest for Catostomidae and lowest for Ictaluridae. Fish body length and stream habitat characteristics (mean cross-sectional area, wood density, mean current velocity, and turbidity) also were related to capture efficiency of both methods, but the effects differed among species groups. We estimated that, on average, 23% of fish left the unblocked sample units, but net movement varied among species. Our results suggest that (1) common warmwater stream fish sampling methods have low capture efficiency and (2) failure to adjust for incomplete capture may bias estimates of fish abundance. We suggest that managers minimize bias from incomplete capture by adjusting data for site- and species-specific capture efficiency and by choosing sampling gear that provide estimates with minimal bias and variance. Furthermore, if block nets are not used, we recommend that managers adjust the data based on unconditional capture efficiency.

Lifting the Curtain on the Wizard of Oz: Biased Voice-Based Impressions of Speaker Size

ERIC Educational Resources Information Center

Rendall, Drew; Vokey, John R.; Nemeth, Christie

2007-01-01

The consistent, but often wrong, impressions people form of the size of unseen speakers are not random but rather point to a consistent misattribution bias, one that the advertising, broadcasting, and entertainment industries also routinely exploit. The authors report 3 experiments examining the perceptual basis of this bias. The results indicate…

Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions

ERIC Educational Resources Information Center

Riegg, Stephanie K.

2008-01-01

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college-going. I first describe the problem of self-selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed…

Free energy calculations: an efficient adaptive biasing potential method.

PubMed

Dickson, Bradley M; Legoll, Frédéric; Lelièvre, Tony; Stoltz, Gabriel; Fleurat-Lessard, Paul

2010-05-06

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is computed directly from the population along the coordinates of the free energy. Because of the mollifier, the bias potential is "nonlocal", and its gradient admits a simple analytic expression. A single observation of the reaction coordinate can thus be used to update the approximate free energy at every point within a neighborhood of the observation. This greatly reduces the equilibration time of the adaptive bias potential. This approximation introduces two parameters: strength of mollification and the zero of energy of the bias potential. While we observe that the approximate free energy is a very good estimate of the actual free energy for a large range of mollification strength, we demonstrate that the errors associated with the mollification may be removed via deconvolution. The zero of energy of the bias potential, which is easy to choose, influences the speed of convergence but not the limiting accuracy. This method is simple to apply to free energy or mean force computation in multiple dimensions and does not involve second derivatives of the reaction coordinates, matrix manipulations nor on-the-fly adaptation of parameters. For the alanine dipeptide test case, the new method is found to gain as much as a factor of 10 in efficiency as compared to two basic implementations of the adaptive biasing force methods, and it is shown to be as efficient as well-tempered metadynamics with the postprocess deconvolution giving a clear advantage to the mollified density of states method.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

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

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays.

An Overview of Randomization and Minimization Programs for Randomized Clinical Trials

PubMed Central

Saghaei, Mahmoud

2011-01-01

Randomization is an essential component of sound clinical trials, which prevents selection biases and helps in blinding the allocations. Randomization is a process by which subsequent subjects are enrolled into trial groups only by chance, which essentially eliminates selection biases. A serious consequence of randomization is severe imbalance among the treatment groups with respect to some prognostic factors, which invalidate the trial results or necessitate complex and usually unreliable secondary analysis to eradicate the source of imbalances. Minimization on the other hand tends to allocate in such a way as to minimize the differences among groups, with respect to prognostic factors. Pure minimization is therefore completely deterministic, that is, one can predict the allocation of the next subject by knowing the factor levels of a previously enrolled subject and having the properties of the next subject. To eliminate the predictability of randomization, it is necessary to include some elements of randomness in the minimization algorithms. In this article brief descriptions of randomization and minimization are presented followed by introducing selected randomization and minimization programs. PMID:22606659

Landmark Estimation of Survival and Treatment Effect in a Randomized Clinical Trial

PubMed Central

Parast, Layla; Tian, Lu; Cai, Tianxi

2013-01-01

Summary In many studies with a survival outcome, it is often not feasible to fully observe the primary event of interest. This often leads to heavy censoring and thus, difficulty in efficiently estimating survival or comparing survival rates between two groups. In certain diseases, baseline covariates and the event time of non-fatal intermediate events may be associated with overall survival. In these settings, incorporating such additional information may lead to gains in efficiency in estimation of survival and testing for a difference in survival between two treatment groups. If gains in efficiency can be achieved, it may then be possible to decrease the sample size of patients required for a study to achieve a particular power level or decrease the duration of the study. Most existing methods for incorporating intermediate events and covariates to predict survival focus on estimation of relative risk parameters and/or the joint distribution of events under semiparametric models. However, in practice, these model assumptions may not hold and hence may lead to biased estimates of the marginal survival. In this paper, we propose a semi-nonparametric two-stage procedure to estimate and compare t-year survival rates by incorporating intermediate event information observed before some landmark time, which serves as a useful approach to overcome semi-competing risks issues. In a randomized clinical trial setting, we further improve efficiency through an additional calibration step. Simulation studies demonstrate substantial potential gains in efficiency in terms of estimation and power. We illustrate our proposed procedures using an AIDS Clinical Trial Protocol 175 dataset by estimating survival and examining the difference in survival between two treatment groups: zidovudine and zidovudine plus zalcitabine. PMID:24659838

A Cautious Note on Auxiliary Variables That Can Increase Bias in Missing Data Problems.

PubMed

Thoemmes, Felix; Rose, Norman

2014-01-01

The treatment of missing data in the social sciences has changed tremendously during the last decade. Modern missing data techniques such as multiple imputation and full-information maximum likelihood are used much more frequently. These methods assume that data are missing at random. One very common approach to increase the likelihood that missing at random is achieved consists of including many covariates as so-called auxiliary variables. These variables are either included based on data considerations or in an inclusive fashion; that is, taking all available auxiliary variables. In this article, we point out that there are some instances in which auxiliary variables exhibit the surprising property of increasing bias in missing data problems. In a series of focused simulation studies, we highlight some situations in which this type of biasing behavior can occur. We briefly discuss possible ways how one can avoid selecting bias-inducing covariates as auxiliary variables.

A surface-bound molecule that undergoes optically biased Brownian rotation.

PubMed

Hutchison, James A; Uji-i, Hiroshi; Deres, Ania; Vosch, Tom; Rocha, Susana; Müller, Sibylle; Bastian, Andreas A; Enderlein, Jörg; Nourouzi, Hassan; Li, Chen; Herrmann, Andreas; Müllen, Klaus; De Schryver, Frans; Hofkens, Johan

2014-02-01

Developing molecular systems with functions analogous to those of macroscopic machine components, such as rotors, gyroscopes and valves, is a long-standing goal of nanotechnology. However, macroscopic analogies go only so far in predicting function in nanoscale environments, where friction dominates over inertia. In some instances, ratchet mechanisms have been used to bias the ever-present random, thermally driven (Brownian) motion and drive molecular diffusion in desired directions. Here, we visualize the motions of surface-bound molecular rotors using defocused fluorescence imaging, and observe the transition from hindered to free Brownian rotation by tuning medium viscosity. We show that the otherwise random rotations can be biased by the polarization of the excitation light field, even though the associated optical torque is insufficient to overcome thermal fluctuations. The biased rotation is attributed instead to a fluctuating-friction mechanism in which photoexcitation of the rotor strongly inhibits its diffusion rate.

Explicit Bias Toward High-Income-Country Research: A Randomized, Blinded, Crossover Experiment Of English Clinicians.

PubMed

Harris, Matthew; Marti, Joachim; Watt, Hillary; Bhatti, Yasser; Macinko, James; Darzi, Ara W

2017-11-01

Unconscious bias may interfere with the interpretation of research from some settings, particularly from lower-income countries. Most studies of this phenomenon have relied on indirect outcomes such as article citation counts and publication rates; few have addressed or proven the effect of unconscious bias in evidence interpretation. In this randomized, blinded crossover experiment in a sample of 347 English clinicians, we demonstrate that changing the source of a research abstract from a low- to a high-income country significantly improves how it is viewed, all else being equal. Using fixed-effects models, we measured differences in ratings for strength of evidence, relevance, and likelihood of referral to a peer. Having a high-income-country source had a significant overall impact on respondents' ratings of relevance and recommendation to a peer. Unconscious bias can have far-reaching implications for the diffusion of knowledge and innovations from low-income countries.

Online attentional bias modification training targeting anxiety and depression in unselected adolescents: Short- and long-term effects of a randomized controlled trial.

PubMed

de Voogd, E L; Wiers, R W; Prins, P J M; de Jong, P J; Boendermaker, W J; Zwitser, R J; Salemink, E

2016-12-01

Based on information processing models of anxiety and depression, we investigated the efficacy of multiple sessions of online attentional bias modification training to reduce attentional bias and symptoms of anxiety and depression, and to increase emotional resilience in youth. Unselected adolescents (N = 340, age: 11-18 years) were randomly allocated to eight sessions of a dot-probe, or a visual search-based attentional training, or one of two corresponding placebo control conditions. Cognitive and emotional measures were assessed pre- and post-training; emotional outcome measures also at three, six and twelve months follow-up. Only visual search training enhanced attention for positive information, and this effect was stronger for participants who completed more training sessions. Symptoms of anxiety and depression reduced, whereas emotional resilience improved. However, these effects were not especially pronounced in the active conditions. Thus, this large-scale randomized controlled study provided no support for the efficacy of the current online attentional bias modification training as a preventive intervention to reduce symptoms of anxiety or depression or to increase emotional resilience in unselected adolescents. However, the absence of biased attention related to symptomatology at baseline, and the large drop-out rates at follow-up preclude strong conclusions. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Compositional pressure and translational selection determine codon usage in the extremely GC-poor unicellular eukaryote Entamoeba histolytica.

PubMed

Romero, H; Zavala, A; Musto, H

2000-01-25

It is widely accepted that the compositional pressure is the only factor shaping codon usage in unicellular species displaying extremely biased genomic compositions. This seems to be the case in the prokaryotes Mycoplasma capricolum, Rickettsia prowasekii and Borrelia burgdorferi (GC-poor), and in Micrococcus luteus (GC-rich). However, in the GC-poor unicellular eukaryotes Dictyostelium discoideum and Plasmodium falciparum, there is evidence that selection, acting at the level of translation, influences codon choices. This is a twofold intriguing finding, since (1) the genomic GC levels of the above mentioned eukaryotes are lower than the GC% of any studied bacteria, and (2) bacteria usually have larger effective population sizes than eukaryotes, and hence natural selection is expected to overcome more efficiently the randomizing effects of genetic drift among prokaryotes than among eukaryotes. In order to gain a new insight about this problem, we analysed the patterns of codon preferences of the nuclear genes of Entamoeba histolytica, a unicellular eukaryote characterised by an extremely AT-rich genome (GC = 25%). The overall codon usage is strongly biased towards A and T in the third codon positions, and among the presumed highly expressed sequences, there is an increased relative usage of a subset of codons, many of which are C-ending. Since an increase in C in third codon positions is 'against' the compositional bias, we conclude that codon usage in E. histolytica, as happens in D. discoideum and P. falciparum, is the result of an equilibrium between compositional pressure and selection. These findings raise the question of why strongly compositionally biased eukaryotic cells may be more sensitive to the (presumed) slight differences among synonymous codons than compositionally biased bacteria.

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.

Science faculty's subtle gender biases favor male students.

PubMed

Moss-Racusin, Corinne A; Dovidio, John F; Brescoll, Victoria L; Graham, Mark J; Handelsman, Jo

2012-10-09

Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student-who was randomly assigned either a male or female name-for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants' preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science.

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.

The effect of framing on surrogate optimism bias: A simulation study.

PubMed

Patel, Dev; Cohen, Elan D; Barnato, Amber E

2016-04-01

To explore the effect of emotion priming and physician communication behaviors on optimism bias. We conducted a 5 × 2 between-subject randomized factorial experiment using a Web-based interactive video designed to simulate a family meeting for a critically ill spouse/parent. Eligibility included age at least 35 years and self-identifying as the surrogate for a spouse/parent. The primary outcome was the surrogate's election of code status. We defined optimism bias as the surrogate's estimate of prognosis with cardiopulmonary resuscitation (CPR) > their recollection of the physician's estimate. Of 373 respondents, 256 (69%) logged in and were randomized and 220 (86%) had nonmissing data for prognosis. Sixty-seven (30%) of 220 overall and 56 of (32%) 173 with an accurate recollection of the physician's estimate had optimism bias. Optimism bias correlated with choosing CPR (P < .001). Emotion priming (P = .397), physician attention to emotion (P = .537), and framing of CPR as the social norm (P = .884) did not affect optimism bias. Framing the decision as the patient's vs the surrogate's (25% vs 36%, P = .066) and describing the alternative to CPR as "allow natural death" instead of "do not resuscitate" (25% vs 37%, P = .035) decreased optimism bias. Framing of CPR choice during code status conversations may influence surrogates' optimism bias. Copyright © 2015 Elsevier Inc. All rights reserved.

Magnetic Random Access Memory based non-volatile asynchronous Muller cell for ultra-low power autonomous applications

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

Di Pendina, G., E-mail: gregory.dipendina@cea.fr, E-mail: eldar.zianbetov@cea.fr, E-mail: edith.beigne@cea.fr; Zianbetov, E., E-mail: gregory.dipendina@cea.fr, E-mail: eldar.zianbetov@cea.fr, E-mail: edith.beigne@cea.fr; CNRS, SPINTEC, F-38000 Grenoble

2015-05-07

Micro and nano electronic integrated circuit domain is today mainly driven by the advent of the Internet of Things for which the constraints are strong, especially in terms of power consumption and autonomy, not only during the computing phases but also during the standby or idle phases. In such ultra-low power applications, the circuit has to meet new constraints mainly linked to its changing energetic environment: long idle phases, automatic wake up, data back-up when the circuit is sporadically turned off, and ultra-low voltage power supply operation. Such circuits have to be completely autonomous regarding their unstable environment, while remainingmore » in an optimum energetic configuration. Therefore, we propose in this paper the first MRAM-based non-volatile asynchronous Muller cell. This cell has been simulated and characterized in a very advanced 28 nm CMOS fully depleted silicon-on-insulator technology, presenting good power performance results due to an extremely efficient body biasing control together with ultra-wide supply voltage range from 160 mV up to 920 mV. The leakage current can be reduced to 154 pA thanks to reverse body biasing. We also propose an efficient standard CMOS bulk version of this cell in order to be compatible with different fabrication processes.« less

Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials: overview of published comments and analysis of user practice in Cochrane and non-Cochrane reviews.

PubMed

Jørgensen, Lars; Paludan-Müller, Asger S; Laursen, David R T; Savović, Jelena; Boutron, Isabelle; Sterne, Jonathan A C; Higgins, Julian P T; Hróbjartsson, Asbjørn

2016-05-10

The Cochrane risk of bias tool for randomized clinical trials was introduced in 2008 and has frequently been commented on and used in systematic reviews. We wanted to evaluate the tool by reviewing published comments on its strengths and challenges and by describing and analysing how the tool is applied to both Cochrane and non-Cochrane systematic reviews. A review of published comments (searches in PubMed, The Cochrane Methodology Register and Google Scholar) and an observational study (100 Cochrane and 100 non-Cochrane reviews from 2014). Our review included 68 comments, 15 of which were categorised as major. The main strengths of the tool were considered to be its aim (to assess trial conduct and not reporting), its developmental basis (wide consultation, empirical and theoretical evidence) and its transparent procedures. The challenges of the tool were mainly considered to be its choice of core bias domains (e.g. not involving funding/conflicts of interest) and issues to do with implementation (i.e. modest inter-rater agreement) and terminology. Our observational study found that the tool was used in all Cochrane reviews (100/100) and was the preferred tool in non-Cochrane reviews (31/100). Both types of reviews frequently implemented the tool in non-recommended ways. Most Cochrane reviews planned to use risk of bias assessments as basis for sensitivity analyses (70 %), but only a minority conducted such analyses (19 %) because, in many cases, few trials were assessed as having "low" risk of bias for all standard domains (6 %). The judgement of at least one risk of bias domain as "unclear" was found in 89 % of included randomized clinical trials (1103/1242). The Cochrane tool has become the standard approach to assess risk of bias in randomized clinical trials but is frequently implemented in a non-recommended way. Based on published comments and how it is applied in practice in systematic reviews, the tool may be further improved by a revised structure and more focused guidance.

The Risk of Bias in Randomized Trials in General Dentistry Journals.

PubMed

Hinton, Stephanie; Beyari, Mohammed M; Madden, Kim; Lamfon, Hanadi A

2015-01-01

The use of a randomized controlled trial (RCT) research design is considered the gold standard for conducting evidence-based clinical research. In this present study, we aimed to assess the quality of RCTs in dentistry and create a general foundation for evidence-based dentistry on which to perform subsequent RCTs. We conducted a systematic assessment of bias of RCTs in seven general dentistry journals published between January 2011 and March 2012. We extracted study characteristics in duplicate and assessed each trial's quality using the Cochrane Risk of Bias tool. We compared risk of bias across studies graphically. Among 1,755 studies across seven journals, we identified 67 RCTs. Many included studies were conducted in Europe (39%), with an average sample size of 358 participants. These studies included 52% female participants and the maximum follow-up period was 13 years. Overall, we found a high percentage of unclear risk of bias among included RCTs, indicating poor quality of reporting within the included studies. An overall high proportion of trials with an "unclear risk of bias" suggests the need for better quality of reporting in dentistry. As such, key concepts in dental research and future trials should focus on high-quality reporting.

Dinucleotide controlled null models for comparative RNA gene prediction.

PubMed

Gesell, Tanja; Washietl, Stefan

2008-05-27

Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: http://sourceforge.net/projects/sissiz.

Instruments for Assessing Risk of Bias and Other Methodological Criteria of Published Animal Studies: A Systematic Review

PubMed Central

Krauth, David; Woodruff, Tracey J.

2013-01-01

Background: Results from animal toxicology studies are critical to evaluating the potential harm from exposure to environmental chemicals or the safety of drugs prior to human testing. However, there is significant debate about how to evaluate the methodology and potential biases of the animal studies. There is no agreed-upon approach, and a systematic evaluation of current best practices is lacking. Objective: We performed a systematic review to identify and evaluate instruments for assessing the risk of bias and/or other methodological criteria of animal studies. Method: We searched Medline (January 1966–November 2011) to identify all relevant articles. We extracted data on risk of bias criteria (e.g., randomization, blinding, allocation concealment) and other study design features included in each assessment instrument. Discussion: Thirty distinct instruments were identified, with the total number of assessed risk of bias, methodological, and/or reporting criteria ranging from 2 to 25. The most common criteria assessed were randomization (25/30, 83%), investigator blinding (23/30, 77%), and sample size calculation (18/30, 60%). In general, authors failed to empirically justify why these or other criteria were included. Nearly all (28/30, 93%) of the instruments have not been rigorously tested for validity or reliability. Conclusion: Our review highlights a number of risk of bias assessment criteria that have been empirically tested for animal research, including randomization, concealment of allocation, blinding, and accounting for all animals. In addition, there is a need for empirically testing additional methodological criteria and assessing the validity and reliability of a standard risk of bias assessment instrument. Citation: Krauth D, Woodruff TJ, Bero L. 2013. Instruments for assessing risk of bias and other methodological criteria of published animal studies: a systematic review. Environ Health Perspect 121:985–992 (2013); http://dx.doi.org/10.1289/ehp.1206389 PMID:23771496

Evaluation of bias and logistics in a survey of adults at increased risk for oral health decrements.

PubMed

Gilbert, G H; Duncan, R P; Kulley, A M; Coward, R T; Heft, M W

1997-01-01

Designing research to include sufficient respondents in groups at highest risk for oral health decrements can present unique challenges. Our purpose was to evaluate bias and logistics in this survey of adults at increased risk for oral health decrements. We used a telephone survey methodology that employed both listed numbers and random digit dialing to identify dentate persons 45 years old or older and to oversample blacks, poor persons, and residents of nonmetropolitan counties. At a second stage, a subsample of the respondents to the initial telephone screening was selected for further study, which consisted of a baseline in-person interview and a clinical examination. We assessed bias due to: (1) limiting the sample to households with telephones, (2) using predominantly listed numbers instead of random digit dialing, and (3) nonresponse at two stages of data collection. While this approach apparently created some biases in the sample, they were small in magnitude. Specifically, limiting the sample to households with telephones biased the sample overall toward more females, larger households, and fewer functionally impaired persons. Using predominantly listed numbers led to a modest bias toward selection of persons more likely to be younger, healthier, female, have had a recent dental visit, and reside in smaller households. Blacks who were selected randomly at a second stage were more likely to participate in baseline data gathering than their white counterparts. Comparisons of the data obtained in this survey with those from recent national surveys suggest that this methodology for sampling high-risk groups did not substantively bias the sample with respect to two important dental parameters, prevalence of edentulousness and dental care use, nor were conclusions about multivariate associations with dental care recency substantively affected. This method of sampling persons at high risk for oral health decrements resulted in only modest bias with respect to the population of interest.

Estimating bias in causes of death ascertainment in the Finnish Randomized Study of Screening for Prostate Cancer.

PubMed

Kilpeläinen, Tuomas P; Mäkinen, Tuukka; Karhunen, Pekka J; Aro, Jussi; Lahtela, Jorma; Taari, Kimmo; Talala, Kirsi; Tammela, Teuvo L J; Auvinen, Anssi

2016-12-01

Precise cause of death (CoD) ascertainment is crucial in any cancer screening trial to avoid bias from misclassification due to excessive recording of diagnosed cancer as a CoD in death certificates instead of non-cancer disease that actually caused death. We estimated whether there was bias in CoD determination between screening (SA) and control arms (CA) in a population-based prostate cancer (PCa) screening trial. Our trial is the largest component of the European Randomized Study of Screening for Prostate Cancer with more than 80,000 men. Randomly selected deaths in men with PCa (N=442/2568 cases, 17.2%) were reviewed by an independent CoD committee. Median follow-up was 16.8 years in both arms. Overdiagnosis of PCa was present in the SA as the risk ratio for PCa incidence was 1.19 (95% confidence interval (CI) 1.14-1.24). The hazard ratio (HR) for PCa mortality was 0.94 (95%CI 0.82-1.08) in favor of the SA. Agreement with official CoD registry was 94.6% (κ=0.88) in the SA and 95.4% (κ=0.91) in the CA. Altogether 14 PCa deaths were estimated as false-positive in both arms and exclusion of these resulted in HR 0.92 (95% CI 0.80-1.06). A small differential misclassification bias in ascertainment of CoD was present, most likely due to attribution bias (overdiagnosis in the SA). Maximum precision in CoD ascertainment can only be achieved with independent review of all deaths in the diseased population. However, this is cumbersome and expensive and may provide little benefit compared to random sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring activity-driven network with biased walks

NASA Astrophysics Data System (ADS)

Wang, Yan; Wu, Ding Juan; Lv, Fang; Su, Meng Long

We investigate the concurrent dynamics of biased random walks and the activity-driven network, where the preferential transition probability is in terms of the edge-weighting parameter. We also obtain the analytical expressions for stationary distribution and the coverage function in directed and undirected networks, all of which depend on the weight parameter. Appropriately adjusting this parameter, more effective search strategy can be obtained when compared with the unbiased random walk, whether in directed or undirected networks. Since network weights play a significant role in the diffusion process.

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

PubMed Central

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

Seven Deadly Sins in Trauma Outcomes Research: An Epidemiologic Post-Mortem for Major Causes of Bias

PubMed Central

del Junco, Deborah J.; Fox, Erin E.; Camp, Elizabeth A.; Rahbar, Mohammad H.; Holcomb, John B.

2013-01-01

Background Because randomized clinical trials (RCTs) in trauma outcomes research are expensive and complex, they have rarely been the basis for the clinical care of trauma patients. Most published findings are derived from retrospective and occasionally prospective observational studies that may be particularly susceptible to bias. The sources of bias include some common to other clinical domains, such as heterogeneous patient populations with competing and interdependent short- and long-term outcomes. Other sources of bias are unique to trauma, such as rapidly changing multi-system responses to injury that necessitate highly dynamic treatment regimes like blood product transfusion. The standard research design and analysis strategies applied in published observational studies are often inadequate to address these biases. Methods Drawing on recent experience in the design, data collection, monitoring and analysis of the 10-site observational PROMMTT study, seven common and sometimes overlapping biases are described through examples and resolution strategies. Results Sources of bias in trauma research include ignoring 1) variation in patients’ indications for treatment (indication bias), 2) the dependency of intervention delivery on patient survival (survival bias), 3) time-varying treatment, 4) time-dependent confounding, 5) non-uniform intervention effects over time, 6) non-random missing data mechanisms, and 7) imperfectly defined variables. This list is not exhaustive. Conclusion The mitigation strategies to overcome these threats to validity require epidemiologic and statistical vigilance. Minimizing the highlighted types of bias in trauma research will facilitate clinical translation of more accurate and reproducible findings and improve the evidence-base that clinicians apply in their care of injured patients. PMID:23778519

Control designs for low-loss active magnetic bearings: Theory and implementation

NASA Astrophysics Data System (ADS)

Wilson, Brian Christopher David

Active Magnetic Bearings (AMB) have been proposed for use in Electromechanical Flywheel Batteries. In these devices, kinetic energy is stored in a magnetically levitated flywheel which spins in a vacuum. The AMB eliminates all mechanical losses, however, electrical loss, which is proportional to the square of the magnetic flux, is still significant. For efficient operation, the flux bias, which is typically introduced into the electromagnets to improve the AMB stiffness, must be reduced, preferably to zero. This zero-bias (ZB) mode of operation cripples the classical control techniques which are customarily used and nonlinear control is required. As a compromise between AMB stiffness and efficiency, a new flux bias scheme is proposed called the generalized complementary flux condition (gcfc). A flux-bias dependent trade-off exists between AMB stiffness, power consumption, and power loss. This work theoretically develops and experimentally verifies new low-loss AMB control designs which employ the gcfc condition. Particular attention is paid to the removal of the singularity present in the standard nonlinear control techniques when operating in ZB. Experimental verification is conduced on a 6-DOF AMB reaction wheel. Practical aspects of the gcfc implementation such as flux measurement and flux-bias implementation with voltage mode amplifiers using IR compensation are investigated. Comparisons are made between the gcfc bias technique and the standard constant-flux-sum (cfs) bias method. Under typical operating circumstances, theoretical analysis and experimental data show that the new gcfc bias scheme is more efficient in producing the control flux required for rotor stabilization than the ordinary cfs bias strategy.

Improved Monte Carlo Scheme for Efficient Particle Transfer in Heterogeneous Systems in the Grand Canonical Ensemble: Application to Vapor-Liquid Nucleation.

PubMed

Loeffler, Troy D; Sepehri, Aliasghar; Chen, Bin

2015-09-08

Reformulation of existing Monte Carlo algorithms used in the study of grand canonical systems has yielded massive improvements in efficiency. Here we present an energy biasing scheme designed to address targeting issues encountered in particle swap moves using sophisticated algorithms such as the Aggregation-Volume-Bias and Unbonding-Bonding methods. Specifically, this energy biasing scheme allows a particle to be inserted to (or removed from) a region that is more acceptable. As a result, this new method showed a several-fold increase in insertion/removal efficiency in addition to an accelerated rate of convergence for the thermodynamic properties of the system.

Minimally-invasive glaucoma surgeries (MIGS) for open angle glaucoma: A systematic review and meta-analysis

PubMed Central

Maule, Milena; Ceccarelli, Manuela; Fea, Antonio Maria

2017-01-01

Background MIGS have been developed as a surgical alternative for glaucomatous patients. Purpose To analyze the change in intraocular pressure (IOP) and glaucoma medications using different MIGS devices (Trabectome, iStent, Excimer Laser Trabeculotomy (ELT), iStent Supra, CyPass, XEN, Hydrus, Fugo Blade, Ab interno canaloplasty, Goniscopy-assisted transluminal trabeculotomy) as a solo procedure or in association with phacoemulsification. Methods Randomized control trials (RCT) and non-RCT (non randomized comparative studies, NRS, and before-after studies) were included. Studies with at least one year of follow-up in patients affected by primary open angle glaucoma, pseudoexfoliative glaucoma or pigmentary glaucoma were considered. Risk of Bias assessment was performed using the Cochrane Risk of Bias and the ROBINS-I tools. The main outcome was the effect of MIGS devices compared to medical therapy, cataract surgery, other glaucoma surgeries and other MIGS on both IOP and use of glaucoma medications 12 months after surgery. Outcomes measures were the mean difference in the change of IOP and glaucoma medication compared to baseline at one and two years and all ocular adverse events. The current meta-analysis is registered on PROSPERO (reference n° CRD42016037280). Results Over a total of 3,069 studies, nine RCT and 21 case series with a total of 2.928 eyes were included. Main concerns about risk of bias in RCTs were lack of blinding, allocation concealment and attrition bias while in non-RCTs they were represented by patients’ selection, masking of participants and co-intervention management. Limited evidence was found based on both RCTs and non RCTs that compared MIGS surgery with medical therapy or other MIGS. In before-after series, MIGS surgery seemed effective in lowering both IOP and glaucoma drug use. MIGS showed a good safety profile: IOP spikes were the most frequent complications and no cases of infection or BCVA loss due to glaucoma were reported. Conclusions Although MIGS seem efficient in the reduction of the IOP and glaucoma medication and show good safety profile, this evidence is mainly derived from non-comparative studies and further, good quality RCTs are warranted. PMID:28850575

Minimally-invasive glaucoma surgeries (MIGS) for open angle glaucoma: A systematic review and meta-analysis.

PubMed

Lavia, Carlo; Dallorto, Laura; Maule, Milena; Ceccarelli, Manuela; Fea, Antonio Maria

2017-01-01

MIGS have been developed as a surgical alternative for glaucomatous patients. To analyze the change in intraocular pressure (IOP) and glaucoma medications using different MIGS devices (Trabectome, iStent, Excimer Laser Trabeculotomy (ELT), iStent Supra, CyPass, XEN, Hydrus, Fugo Blade, Ab interno canaloplasty, Goniscopy-assisted transluminal trabeculotomy) as a solo procedure or in association with phacoemulsification. Randomized control trials (RCT) and non-RCT (non randomized comparative studies, NRS, and before-after studies) were included. Studies with at least one year of follow-up in patients affected by primary open angle glaucoma, pseudoexfoliative glaucoma or pigmentary glaucoma were considered. Risk of Bias assessment was performed using the Cochrane Risk of Bias and the ROBINS-I tools. The main outcome was the effect of MIGS devices compared to medical therapy, cataract surgery, other glaucoma surgeries and other MIGS on both IOP and use of glaucoma medications 12 months after surgery. Outcomes measures were the mean difference in the change of IOP and glaucoma medication compared to baseline at one and two years and all ocular adverse events. The current meta-analysis is registered on PROSPERO (reference n° CRD42016037280). Over a total of 3,069 studies, nine RCT and 21 case series with a total of 2.928 eyes were included. Main concerns about risk of bias in RCTs were lack of blinding, allocation concealment and attrition bias while in non-RCTs they were represented by patients' selection, masking of participants and co-intervention management. Limited evidence was found based on both RCTs and non RCTs that compared MIGS surgery with medical therapy or other MIGS. In before-after series, MIGS surgery seemed effective in lowering both IOP and glaucoma drug use. MIGS showed a good safety profile: IOP spikes were the most frequent complications and no cases of infection or BCVA loss due to glaucoma were reported. Although MIGS seem efficient in the reduction of the IOP and glaucoma medication and show good safety profile, this evidence is mainly derived from non-comparative studies and further, good quality RCTs are warranted.

An alternative empirical likelihood method in missing response problems and causal inference.

PubMed

Ren, Kaili; Drummond, Christopher A; Brewster, Pamela S; Haller, Steven T; Tian, Jiang; Cooper, Christopher J; Zhang, Biao

2016-11-30

Missing responses are common problems in medical, social, and economic studies. When responses are missing at random, a complete case data analysis may result in biases. A popular debias method is inverse probability weighting proposed by Horvitz and Thompson. To improve efficiency, Robins et al. proposed an augmented inverse probability weighting method. The augmented inverse probability weighting estimator has a double-robustness property and achieves the semiparametric efficiency lower bound when the regression model and propensity score model are both correctly specified. In this paper, we introduce an empirical likelihood-based estimator as an alternative to Qin and Zhang (2007). Our proposed estimator is also doubly robust and locally efficient. Simulation results show that the proposed estimator has better performance when the propensity score is correctly modeled. Moreover, the proposed method can be applied in the estimation of average treatment effect in observational causal inferences. Finally, we apply our method to an observational study of smoking, using data from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions clinical trial. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Efficient global biopolymer sampling with end-transfer configurational bias Monte Carlo

NASA Astrophysics Data System (ADS)

Arya, Gaurav; Schlick, Tamar

2007-01-01

We develop an "end-transfer configurational bias Monte Carlo" method for efficient thermodynamic sampling of complex biopolymers and assess its performance on a mesoscale model of chromatin (oligonucleosome) at different salt conditions compared to other Monte Carlo moves. Our method extends traditional configurational bias by deleting a repeating motif (monomer) from one end of the biopolymer and regrowing it at the opposite end using the standard Rosenbluth scheme. The method's sampling efficiency compared to local moves, pivot rotations, and standard configurational bias is assessed by parameters relating to translational, rotational, and internal degrees of freedom of the oligonucleosome. Our results show that the end-transfer method is superior in sampling every degree of freedom of the oligonucleosomes over other methods at high salt concentrations (weak electrostatics) but worse than the pivot rotations in terms of sampling internal and rotational sampling at low-to-moderate salt concentrations (strong electrostatics). Under all conditions investigated, however, the end-transfer method is several orders of magnitude more efficient than the standard configurational bias approach. This is because the characteristic sampling time of the innermost oligonucleosome motif scales quadratically with the length of the oligonucleosomes for the end-transfer method while it scales exponentially for the traditional configurational-bias method. Thus, the method we propose can significantly improve performance for global biomolecular applications, especially in condensed systems with weak nonbonded interactions and may be combined with local enhancements to improve local sampling.

Optical and Electrical Performance of MOS-Structure Silicon Solar Cells with Antireflective Transparent ITO and Plasmonic Indium Nanoparticles under Applied Bias Voltage.

PubMed

Ho, Wen-Jeng; Sue, Ruei-Siang; Lin, Jian-Cheng; Syu, Hong-Jang; Lin, Ching-Fuh

2016-08-10

This paper reports impressive improvements in the optical and electrical performance of metal-oxide-semiconductor (MOS)-structure silicon solar cells through the incorporation of plasmonic indium nanoparticles (In-NPs) and an indium-tin-oxide (ITO) electrode with periodic holes (perforations) under applied bias voltage. Samples were prepared using a plain ITO electrode or perforated ITO electrode with and without In-NPs. The samples were characterized according to optical reflectance, dark current voltage, induced capacitance voltage, external quantum efficiency, and photovoltaic current voltage. Our results indicate that induced capacitance voltage and photovoltaic current voltage both depend on bias voltage, regardless of the type of ITO electrode. Under a bias voltage of 4.0 V, MOS cells with perforated ITO and plain ITO, respectively, presented conversion efficiencies of 17.53% and 15.80%. Under a bias voltage of 4.0 V, the inclusion of In-NPs increased the efficiency of cells with perforated ITO and plain ITO to 17.80% and 16.87%, respectively.

Optical and Electrical Performance of MOS-Structure Silicon Solar Cells with Antireflective Transparent ITO and Plasmonic Indium Nanoparticles under Applied Bias Voltage

PubMed Central

Ho, Wen-Jeng; Sue, Ruei-Siang; Lin, Jian-Cheng; Syu, Hong-Jang; Lin, Ching-Fuh

2016-01-01

This paper reports impressive improvements in the optical and electrical performance of metal-oxide-semiconductor (MOS)-structure silicon solar cells through the incorporation of plasmonic indium nanoparticles (In-NPs) and an indium-tin-oxide (ITO) electrode with periodic holes (perforations) under applied bias voltage. Samples were prepared using a plain ITO electrode or perforated ITO electrode with and without In-NPs. The samples were characterized according to optical reflectance, dark current voltage, induced capacitance voltage, external quantum efficiency, and photovoltaic current voltage. Our results indicate that induced capacitance voltage and photovoltaic current voltage both depend on bias voltage, regardless of the type of ITO electrode. Under a bias voltage of 4.0 V, MOS cells with perforated ITO and plain ITO, respectively, presented conversion efficiencies of 17.53% and 15.80%. Under a bias voltage of 4.0 V, the inclusion of In-NPs increased the efficiency of cells with perforated ITO and plain ITO to 17.80% and 16.87%, respectively. PMID:28773801

Factors influencing foraging search efficiency: why do scarce lappet-faced vultures outperform ubiquitous white-backed vultures?

PubMed

Spiegel, Orr; Getz, Wayne M; Nathan, Ran

2013-05-01

The search phase is a critical component of foraging behavior, affecting interspecific competition and community dynamics. Nevertheless, factors determining interspecific variation in search efficiency are still poorly understood. We studied differences in search efficiency between the lappet-faced vulture (Torgos tracheliotus; LFV) and the white-backed vulture (Gyps africanus; WBV) foraging on spatiotemporally unpredictable carcasses in Etosha National Park, Namibia. We used experimental food supply and high-resolution GPS tracking of free-ranging vultures to quantify search efficiency and elucidate the factors underlying the observed interspecific differences using a biased correlated random walk simulation model bootstrapped with the GPS tracking data. We found that LFV's search efficiency was higher than WBV's in both first-to-find, first-to-land, and per-individual-finding rate measures. Modifying species-specific traits in the simulation model allows us to assess the relative role of each factor in LFV's higher efficiency. Interspecific differences in morphology (through the effect on perceptual range and motion ability) and searchers' spatial dispersion (due to different roost arrangements) are in correspondence with the empirically observed advantage of LFV over WBV searchers, whereas differences in other aspects of the movement patterns appear to play a minor role. Our results provide mechanistic explanations for interspecific variation in search efficiency for species using similar resources and foraging modes.

Random Assignment: Practical Considerations from Field Experiments.

ERIC Educational Resources Information Center

Dunford, Franklyn W.

1990-01-01

Seven qualitative issues associated with randomization that have the potential to weaken or destroy otherwise sound experimental designs are reviewed and illustrated via actual field experiments. Issue areas include ethics and legality, liability risks, manipulation of randomized outcomes, hidden bias, design intrusiveness, case flow, and…

Sequential causal inference: Application to randomized trials of adaptive treatment strategies

PubMed Central

Dawson, Ree; Lavori, Philip W.

2009-01-01

SUMMARY Clinical trials that randomize subjects to decision algorithms, which adapt treatments over time according to individual response, have gained considerable interest as investigators seek designs that directly inform clinical decision making. We consider designs in which subjects are randomized sequentially at decision points, among adaptive treatment options under evaluation. We present a sequential method to estimate the comparative effects of the randomized adaptive treatments, which are formalized as adaptive treatment strategies. Our causal estimators are derived using Bayesian predictive inference. We use analytical and empirical calculations to compare the predictive estimators to (i) the ‘standard’ approach that allocates the sequentially obtained data to separate strategy-specific groups as would arise from randomizing subjects at baseline; (ii) the semi-parametric approach of marginal mean models that, under appropriate experimental conditions, provides the same sequential estimator of causal differences as the proposed approach. Simulation studies demonstrate that sequential causal inference offers substantial efficiency gains over the standard approach to comparing treatments, because the predictive estimators can take advantage of the monotone structure of shared data among adaptive strategies. We further demonstrate that the semi-parametric asymptotic variances, which are marginal ‘one-step’ estimators, may exhibit significant bias, in contrast to the predictive variances. We show that the conditions under which the sequential method is attractive relative to the other two approaches are those most likely to occur in real studies. PMID:17914714

Phage display peptide libraries: deviations from randomness and correctives

PubMed Central

Ryvkin, Arie; Ashkenazy, Haim; Weiss-Ottolenghi, Yael; Piller, Chen; Pupko, Tal; Gershoni, Jonathan M

2018-01-01

Abstract Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications. PMID:29420788

Explicating the Conditions Under Which Multilevel Multiple Imputation Mitigates Bias Resulting from Random Coefficient-Dependent Missing Longitudinal Data.

PubMed

Gottfredson, Nisha C; Sterba, Sonya K; Jackson, Kristina M

2017-01-01

Random coefficient-dependent (RCD) missingness is a non-ignorable mechanism through which missing data can arise in longitudinal designs. RCD, for which we cannot test, is a problematic form of missingness that occurs if subject-specific random effects correlate with propensity for missingness or dropout. Particularly when covariate missingness is a problem, investigators typically handle missing longitudinal data by using single-level multiple imputation procedures implemented with long-format data, which ignores within-person dependency entirely, or implemented with wide-format (i.e., multivariate) data, which ignores some aspects of within-person dependency. When either of these standard approaches to handling missing longitudinal data is used, RCD missingness leads to parameter bias and incorrect inference. We explain why multilevel multiple imputation (MMI) should alleviate bias induced by a RCD missing data mechanism under conditions that contribute to stronger determinacy of random coefficients. We evaluate our hypothesis with a simulation study. Three design factors are considered: intraclass correlation (ICC; ranging from .25 to .75), number of waves (ranging from 4 to 8), and percent of missing data (ranging from 20 to 50%). We find that MMI greatly outperforms the single-level wide-format (multivariate) method for imputation under a RCD mechanism. For the MMI analyses, bias was most alleviated when the ICC is high, there were more waves of data, and when there was less missing data. Practical recommendations for handling longitudinal missing data are suggested.

Highly Efficient Amplifier for Ka-Band Communications

NASA Technical Reports Server (NTRS)

1996-01-01

An amplifier developed under a Small Business Innovation Research (SBIR) contract will have applications for both satellite and terrestrial communications. This power amplifier uses an innovative series bias arrangement of active devices to achieve over 40-percent efficiency at Ka-band frequencies with an output power of 0.66 W. The amplifier is fabricated on a 2.0- by 3.8-square millimeter chip through the use of Monolithic Microwave Integrated Circuit (MMIC) technology, and it uses state-of-the-art, Pseudomorphic High-Electron-Mobility Transistor (PHEMT) devices. Although the performance of the MMIC chip depends on these high-performance devices, the real innovations here are a unique series bias scheme, which results in a high-voltage chip supply, and careful design of the on-chip planar output stage combiner. This design concept has ramifications beyond the chip itself because it opens up the possibility of operation directly from a satellite power bus (usually 28 V) without a dc-dc converter. This will dramatically increase the overall system efficiency. Conventional microwave power amplifier designs utilize many devices all connected in parallel from the bias supply. This results in a low-bias voltage, typically 5 V, and a high bias current. With this configuration, substantial I(sup 2) R losses (current squared times resistance) may arise in the system bias-distribution network. By placing the devices in a series bias configuration, the total current is reduced, leading to reduced distribution losses. Careful design of the on-chip planar output stage power combiner is also important in minimizing losses. Using these concepts, a two-stage amplifier was designed for operation at 33 GHz and fabricated in a standard MMIC foundry process with 0.20-m PHEMT devices. Using a 20-V bias supply, the amplifier achieved efficiencies of over 40 percent with an output power of 0.66 W and a 16-dB gain over a 2-GHz bandwidth centered at 33 GHz. With a 28-V bias, a power level of 1.1 W was achieved with a 12-dB gain and a 36-percent efficiency. This represents the best reported combination of power and efficiency at this frequency. In addition to delivering excellent power and gain, this Ka-band MMIC power amplifier has an efficiency that is 10 percent greater than existing designs. The unique design offers an excellent match for spacecraft applications since the amplifier supply voltage is closely matched to the typical value of spacecraft bus voltage. These amplifiers may be used alone in applications of 1 W or less, or several may be combined or used in an array to produce moderate power, Ka-band transmitters with minimal power combining and less thermal stress owing to the combination of excellent efficiency and power output. The higher voltage operation of this design may also save mass and power because the dc-dc power converter is replaced with a simpler voltage regulator.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Non-Hermitian localization in biological networks.

PubMed

Amir, Ariel; Hatano, Naomichi; Nelson, David R

2016-04-01

We explore the spectra and localization properties of the N-site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N, the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90^{∘} rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

The effects of recall errors and of selection bias in epidemiologic studies of mobile phone use and cancer risk.

PubMed

Vrijheid, Martine; Deltour, Isabelle; Krewski, Daniel; Sanchez, Marie; Cardis, Elisabeth

2006-07-01

This paper examines the effects of systematic and random errors in recall and of selection bias in case-control studies of mobile phone use and cancer. These sensitivity analyses are based on Monte-Carlo computer simulations and were carried out within the INTERPHONE Study, an international collaborative case-control study in 13 countries. Recall error scenarios simulated plausible values of random and systematic, non-differential and differential recall errors in amount of mobile phone use reported by study subjects. Plausible values for the recall error were obtained from validation studies. Selection bias scenarios assumed varying selection probabilities for cases and controls, mobile phone users, and non-users. Where possible these selection probabilities were based on existing information from non-respondents in INTERPHONE. Simulations used exposure distributions based on existing INTERPHONE data and assumed varying levels of the true risk of brain cancer related to mobile phone use. Results suggest that random recall errors of plausible levels can lead to a large underestimation in the risk of brain cancer associated with mobile phone use. Random errors were found to have larger impact than plausible systematic errors. Differential errors in recall had very little additional impact in the presence of large random errors. Selection bias resulting from underselection of unexposed controls led to J-shaped exposure-response patterns, with risk apparently decreasing at low to moderate exposure levels. The present results, in conjunction with those of the validation studies conducted within the INTERPHONE study, will play an important role in the interpretation of existing and future case-control studies of mobile phone use and cancer risk, including the INTERPHONE study.

Non-Hermitian localization in biological networks

NASA Astrophysics Data System (ADS)

Amir, Ariel; Hatano, Naomichi; Nelson, David R.

2016-04-01

We explore the spectra and localization properties of the N -site banded one-dimensional non-Hermitian random matrices that arise naturally in sparse neural networks. Approximately equal numbers of random excitatory and inhibitory connections lead to spatially localized eigenfunctions and an intricate eigenvalue spectrum in the complex plane that controls the spontaneous activity and induced response. A finite fraction of the eigenvalues condense onto the real or imaginary axes. For large N , the spectrum has remarkable symmetries not only with respect to reflections across the real and imaginary axes but also with respect to 90∘ rotations, with an unusual anisotropic divergence in the localization length near the origin. When chains with periodic boundary conditions become directed, with a systematic directional bias superimposed on the randomness, a hole centered on the origin opens up in the density-of-states in the complex plane. All states are extended on the rim of this hole, while the localized eigenvalues outside the hole are unchanged. The bias-dependent shape of this hole tracks the bias-independent contours of constant localization length. We treat the large-N limit by a combination of direct numerical diagonalization and using transfer matrices, an approach that allows us to exploit an electrostatic analogy connecting the "charges" embodied in the eigenvalue distribution with the contours of constant localization length. We show that similar results are obtained for more realistic neural networks that obey "Dale's law" (each site is purely excitatory or inhibitory) and conclude with perturbation theory results that describe the limit of large directional bias, when all states are extended. Related problems arise in random ecological networks and in chains of artificial cells with randomly coupled gene expression patterns.

A 60 GOPS/W, -1.8 V to 0.9 V body bias ULP cluster in 28 nm UTBB FD-SOI technology

NASA Astrophysics Data System (ADS)

Rossi, Davide; Pullini, Antonio; Loi, Igor; Gautschi, Michael; Gürkaynak, Frank K.; Bartolini, Andrea; Flatresse, Philippe; Benini, Luca

2016-03-01

Ultra-low power operation and extreme energy efficiency are strong requirements for a number of high-growth application areas, such as E-health, Internet of Things, and wearable Human-Computer Interfaces. A promising approach to achieve up to one order of magnitude of improvement in energy efficiency over current generation of integrated circuits is near-threshold computing. However, frequency degradation due to aggressive voltage scaling may not be acceptable across all performance-constrained applications. Thread-level parallelism over multiple cores can be used to overcome the performance degradation at low voltage. Moreover, enabling the processors to operate on-demand and over a wide supply voltage and body bias ranges allows to achieve the best possible energy efficiency while satisfying a large spectrum of computational demands. In this work we present the first ever implementation of a 4-core cluster fabricated using conventional-well 28 nm UTBB FD-SOI technology. The multi-core architecture we present in this work is able to operate on a wide range of supply voltages starting from 0.44 V to 1.2 V. In addition, the architecture allows a wide range of body bias to be applied from -1.8 V to 0.9 V. The peak energy efficiency 60 GOPS/W is achieved at 0.5 V supply voltage and 0.5 V forward body bias. Thanks to the extended body bias range of conventional-well FD-SOI technology, high energy efficiency can be guaranteed for a wide range of process and environmental conditions. We demonstrate the ability to compensate for up to 99.7% of chips for process variation with only ±0.2 V of body biasing, and compensate temperature variation in the range -40 °C to 120 °C exploiting -1.1 V to 0.8 V body biasing. When compared to leading-edge near-threshold RISC processors optimized for extremely low power applications, the multi-core architecture we propose has 144× more performance at comparable energy efficiency levels. Even when compared to other low-power processors with comparable performance, including those implemented in 28 nm technology, our platform provides 1.4× to 3.7× better energy efficiency.

Science faculty’s subtle gender biases favor male students

PubMed Central

Moss-Racusin, Corinne A.; Dovidio, John F.; Brescoll, Victoria L.; Graham, Mark J.; Handelsman, Jo

2012-01-01

Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. Abundant research has demonstrated gender bias in many demographic groups, but has yet to experimentally investigate whether science faculty exhibit a bias against female students that could contribute to the gender disparity in academic science. In a randomized double-blind study (n = 127), science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. We also assessed faculty participants’ preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student. These results suggest that interventions addressing faculty gender bias might advance the goal of increasing the participation of women in science. PMID:22988126

State-dependent biasing method for importance sampling in the weighted stochastic simulation algorithm.

PubMed

Roh, Min K; Gillespie, Dan T; Petzold, Linda R

2010-11-07

The weighted stochastic simulation algorithm (wSSA) was developed by Kuwahara and Mura [J. Chem. Phys. 129, 165101 (2008)] to efficiently estimate the probabilities of rare events in discrete stochastic systems. The wSSA uses importance sampling to enhance the statistical accuracy in the estimation of the probability of the rare event. The original algorithm biases the reaction selection step with a fixed importance sampling parameter. In this paper, we introduce a novel method where the biasing parameter is state-dependent. The new method features improved accuracy, efficiency, and robustness.

Data quality assurance: an analysis of patient non-response.

PubMed

Derby, Dustin C; Haan, Andrea; Wood, Kurt

2011-01-01

Patient satisfaction is paramount to maintaining high clinical quality assurance. This study seeks to compare response rates, response bias, and the completeness of data between paper and electronic collection modes of a chiropractic patient satisfaction survey. A convenience sample of 206 patients presenting to a chiropractic college clinic were surveyed concerning satisfaction with their chiropractic care. Paper (in-clinic and postal) and electronic modes of survey administration were compared for response rates and non-response bias. The online data collection mode resulted in fewer non-responses and a higher response rate, and did not evince response bias when compared to paper modes. The postal paper mode predicted non-response rates over the in-clinic paper and online modalities and exhibited a gender bias. This current study was a single clinic study; future studies should consider multi-clinic data collections. Busy clinic operations and available staff resources restricted the ability to conduct a random sampling of patients or to invite all eligible patients, therefore limiting the generalizability of collected survey data. Results of this study will provide data to aid development of survey protocols that efficiently, account for available human resources, and are convenient for patients while allowing for the most complete and accurate data collection possible in an educational clinic setting. Understanding patient responses across survey modes is critical for the cultivation of quality business intelligence within college teaching clinic settings. This study bridges measurement evidence from three popular data collection modalities and offers support for higher levels of quality for web-based data collection.

Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

PubMed

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

The need for randomization in animal trials: an overview of systematic reviews.

PubMed

Hirst, Jennifer A; Howick, Jeremy; Aronson, Jeffrey K; Roberts, Nia; Perera, Rafael; Koshiaris, Constantinos; Heneghan, Carl

2014-01-01

Randomization, allocation concealment, and blind outcome assessment have been shown to reduce bias in human studies. Authors from the Collaborative Approach to Meta Analysis and Review of Animal Data from Experimental Studies (CAMARADES) collaboration recently found that these features protect against bias in animal stroke studies. We extended the scope the work from CAMARADES to include investigations of treatments for any condition. We conducted an overview of systematic reviews. We searched Medline and Embase for systematic reviews of animal studies testing any intervention (against any control) and we included any disease area and outcome. We included reviews comparing randomized versus not randomized (but otherwise controlled), concealed versus unconcealed treatment allocation, or blinded versus unblinded outcome assessment. Thirty-one systematic reviews met our inclusion criteria: 20 investigated treatments for experimental stroke, 4 reviews investigated treatments for spinal cord diseases, while 1 review each investigated treatments for bone cancer, intracerebral hemorrhage, glioma, multiple sclerosis, Parkinson's disease, and treatments used in emergency medicine. In our sample 29% of studies reported randomization, 15% of studies reported allocation concealment, and 35% of studies reported blinded outcome assessment. We pooled the results in a meta-analysis, and in our primary analysis found that failure to randomize significantly increased effect sizes, whereas allocation concealment and blinding did not. In our secondary analyses we found that randomization, allocation concealment, and blinding reduced effect sizes, especially where outcomes were subjective. Our study demonstrates the need for randomization, allocation concealment, and blind outcome assessment in animal research across a wide range of outcomes and disease areas. Since human studies are often justified based on results from animal studies, our results suggest that unduly biased animal studies should not be allowed to constitute part of the rationale for human trials.

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

PubMed

Biro, Peter A

2013-02-01

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

Quantitative comparison of randomization designs in sequential clinical trials based on treatment balance and allocation randomness.

PubMed

Zhao, Wenle; Weng, Yanqiu; Wu, Qi; Palesch, Yuko

2012-01-01

To evaluate the performance of randomization designs under various parameter settings and trial sample sizes, and identify optimal designs with respect to both treatment imbalance and allocation randomness, we evaluate 260 design scenarios from 14 randomization designs under 15 sample sizes range from 10 to 300, using three measures for imbalance and three measures for randomness. The maximum absolute imbalance and the correct guess (CG) probability are selected to assess the trade-off performance of each randomization design. As measured by the maximum absolute imbalance and the CG probability, we found that performances of the 14 randomization designs are located in a closed region with the upper boundary (worst case) given by Efron's biased coin design (BCD) and the lower boundary (best case) from the Soares and Wu's big stick design (BSD). Designs close to the lower boundary provide a smaller imbalance and a higher randomness than designs close to the upper boundary. Our research suggested that optimization of randomization design is possible based on quantified evaluation of imbalance and randomness. Based on the maximum imbalance and CG probability, the BSD, Chen's biased coin design with imbalance tolerance method, and Chen's Ehrenfest urn design perform better than popularly used permuted block design, EBCD, and Wei's urn design. Copyright © 2011 John Wiley & Sons, Ltd.

Network sampling coverage II: The effect of non-random missing data on network measurement

PubMed Central

Smith, Jeffrey A.; Moody, James; Morgan, Jonathan

2016-01-01

Missing data is an important, but often ignored, aspect of a network study. Measurement validity is affected by missing data, but the level of bias can be difficult to gauge. Here, we describe the effect of missing data on network measurement across widely different circumstances. In Part I of this study (Smith and Moody, 2013), we explored the effect of measurement bias due to randomly missing nodes. Here, we drop the assumption that data are missing at random: what happens to estimates of key network statistics when central nodes are more/less likely to be missing? We answer this question using a wide range of empirical networks and network measures. We find that bias is worse when more central nodes are missing. With respect to network measures, Bonacich centrality is highly sensitive to the loss of central nodes, while closeness centrality is not; distance and bicomponent size are more affected than triad summary measures and behavioral homophily is more robust than degree-homophily. With respect to types of networks, larger, directed networks tend to be more robust, but the relation is weak. We end the paper with a practical application, showing how researchers can use our results (translated into a publically available java application) to gauge the bias in their own data. PMID:27867254

Network sampling coverage II: The effect of non-random missing data on network measurement.

PubMed

Smith, Jeffrey A; Moody, James; Morgan, Jonathan

2017-01-01

Missing data is an important, but often ignored, aspect of a network study. Measurement validity is affected by missing data, but the level of bias can be difficult to gauge. Here, we describe the effect of missing data on network measurement across widely different circumstances. In Part I of this study (Smith and Moody, 2013), we explored the effect of measurement bias due to randomly missing nodes. Here, we drop the assumption that data are missing at random: what happens to estimates of key network statistics when central nodes are more/less likely to be missing? We answer this question using a wide range of empirical networks and network measures. We find that bias is worse when more central nodes are missing. With respect to network measures, Bonacich centrality is highly sensitive to the loss of central nodes, while closeness centrality is not; distance and bicomponent size are more affected than triad summary measures and behavioral homophily is more robust than degree-homophily. With respect to types of networks, larger, directed networks tend to be more robust, but the relation is weak. We end the paper with a practical application, showing how researchers can use our results (translated into a publically available java application) to gauge the bias in their own data.

Probability theory plus noise: Replies to Crupi and Tentori (2016) and to Nilsson, Juslin, and Winman (2016).

PubMed

Costello, Fintan; Watts, Paul

2016-01-01

A standard assumption in much of current psychology is that people do not reason about probability using the rules of probability theory but instead use various heuristics or "rules of thumb," which can produce systematic reasoning biases. In Costello and Watts (2014), we showed that a number of these biases can be explained by a model where people reason according to probability theory but are subject to random noise. More importantly, that model also predicted agreement with probability theory for certain expressions that cancel the effects of random noise: Experimental results strongly confirmed this prediction, showing that probabilistic reasoning is simultaneously systematically biased and "surprisingly rational." In their commentaries on that paper, both Crupi and Tentori (2016) and Nilsson, Juslin, and Winman (2016) point to various experimental results that, they suggest, our model cannot explain. In this reply, we show that our probability theory plus noise model can in fact explain every one of the results identified by these authors. This gives a degree of additional support to the view that people's probability judgments embody the rational rules of probability theory and that biases in those judgments can be explained as simply effects of random noise. (c) 2015 APA, all rights reserved).

Accurate reconstruction of the jV-characteristic of organic solar cells from measurements of the external quantum efficiency

NASA Astrophysics Data System (ADS)

Meyer, Toni; Körner, Christian; Vandewal, Koen; Leo, Karl

2018-04-01

In two terminal tandem solar cells, the current density - voltage (jV) characteristic of the individual subcells is typically not directly measurable, but often required for a rigorous device characterization. In this work, we reconstruct the jV-characteristic of organic solar cells from measurements of the external quantum efficiency under applied bias voltages and illumination. We show that it is necessary to perform a bias irradiance variation at each voltage and subsequently conduct a mathematical correction of the differential to the absolute external quantum efficiency to obtain an accurate jV-characteristic. Furthermore, we show that measuring the external quantum efficiency as a function of voltage for a single bias irradiance of 0.36 AM1.5g equivalent sun provides a good approximation of the photocurrent density over voltage curve. The method is tested on a selection of efficient, common single-junctions. The obtained conclusions can easily be transferred to multi-junction devices with serially connected subcells.

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

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

Soundarajan, Sucheta; Wendt, Jeremy D.

2016-06-01

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to bemore » found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.« less

Immediate movement history influences reach-to-grasp action selection in children and adults.

PubMed

Kent, Samuel W; Wilson, Andrew D; Plumb, Mandy S; Williams, Justin H G; Mon-Williams, Mark

2009-01-01

Action selection is subject to many biases. Immediate movement history is one such bias seen in young infants. Is this bias strong enough to affect adult behavior? Adult participants reached and grasped a cylinder positioned to require either pronation or supination of the hand. Successive cylinder positions changed either randomly or systematically between trials. Random positioning led to optimized economy of movement. In contrast, systematic changes in position biased action selection toward previously selected actions at the expense of movement economy. Thus, one switches to a new movement only when the savings outweigh the costs of the switch. Immediate movement history had an even larger influence on children aged 7-15 years. This suggests that switching costs are greater in children, which is consistent with their reduced grasping experience. The presence of this effect in adults suggests that immediate movement history exerts a more widespread and pervasive influence on patterns of action selection than researchers had previously recognized.

[Periodontal treatment for cardiovascular risk factors: a systematic review].

PubMed

Deng, Linkai; Li, Chunjie; Li, Qian; Zhang, Yukui; Zhao, Hongwei

2013-10-01

To evaluate the efficacy of periodontal treatment for the management of cardiovascular risk factors. Eligible studies in Cochrane Controlled Trials Register/CENTRAL, PubMed, EMBASE, and China Biology Medicine disc (CBMdisc) were searched until October 13, 2011. References of the included studies were hand searched. Two reviewers assessed the risk of bias and extracted the data of the included studies in duplicate. Meta-analysis was conducted with Revman 5.1. Six randomized controlled trials involving 682 participants were included. One case had low risk of bias, another one had moderate risk of bias, and the remaining four had high risk of bias. Meta-analysis showed that periodontal treatment has no significant effect on C-reactive protein, total cholesterol, low-density lipoprotein cholesterol, and triglycerides (P > 0.05). However, the treatment had a significant effect on high-density lipoprotein cholesterol [MD = 0.05, 95% CI (0.00, 0.09), P = 0.04]. Periodontal treatment has good effects on controlling high-density lipoprotein cholesterol although more randomized controlled trials must be conducted to verify its effectiveness.

Wide brick tunnel randomization - an unequal allocation procedure that limits the imbalance in treatment totals.

PubMed

Kuznetsova, Olga M; Tymofyeyev, Yevgen

2014-04-30

In open-label studies, partial predictability of permuted block randomization provides potential for selection bias. To lessen the selection bias in two-arm studies with equal allocation, a number of allocation procedures that limit the imbalance in treatment totals at a pre-specified level but do not require the exact balance at the ends of the blocks were developed. In studies with unequal allocation, however, the task of designing a randomization procedure that sets a pre-specified limit on imbalance in group totals is not resolved. Existing allocation procedures either do not preserve the allocation ratio at every allocation or do not include all allocation sequences that comply with the pre-specified imbalance threshold. Kuznetsova and Tymofyeyev described the brick tunnel randomization for studies with unequal allocation that preserves the allocation ratio at every step and, in the two-arm case, includes all sequences that satisfy the smallest possible imbalance threshold. This article introduces wide brick tunnel randomization for studies with unequal allocation that allows all allocation sequences with imbalance not exceeding any pre-specified threshold while preserving the allocation ratio at every step. In open-label studies, allowing a larger imbalance in treatment totals lowers selection bias because of the predictability of treatment assignments. The applications of the technique in two-arm and multi-arm open-label studies with unequal allocation are described. Copyright © 2013 John Wiley & Sons, Ltd.

Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

PubMed

Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

2017-04-01

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. PMID:24786942

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. © 2014 American Physical Therapy Association.

Reliability and Validity Assessment of a Linear Position Transducer

PubMed Central

Garnacho-Castaño, Manuel V.; López-Lastra, Silvia; Maté-Muñoz, José L.

2015-01-01

The objectives of the study were to determine the validity and reliability of peak velocity (PV), average velocity (AV), peak power (PP) and average power (AP) measurements were made using a linear position transducer. Validity was assessed by comparing measurements simultaneously obtained using the Tendo Weightlifting Analyzer Systemi and T-Force Dynamic Measurement Systemr (Ergotech, Murcia, Spain) during two resistance exercises, bench press (BP) and full back squat (BS), performed by 71 trained male subjects. For the reliability study, a further 32 men completed both lifts using the Tendo Weightlifting Analyzer Systemz in two identical testing sessions one week apart (session 1 vs. session 2). Intraclass correlation coefficients (ICCs) indicating the validity of the Tendo Weightlifting Analyzer Systemi were high, with values ranging from 0.853 to 0.989. Systematic biases and random errors were low to moderate for almost all variables, being higher in the case of PP (bias ±157.56 W; error ±131.84 W). Proportional biases were identified for almost all variables. Test-retest reliability was strong with ICCs ranging from 0.922 to 0.988. Reliability results also showed minimal systematic biases and random errors, which were only significant for PP (bias -19.19 W; error ±67.57 W). Only PV recorded in the BS showed no significant proportional bias. The Tendo Weightlifting Analyzer Systemi emerged as a reliable system for measuring movement velocity and estimating power in resistance exercises. The low biases and random errors observed here (mainly AV, AP) make this device a useful tool for monitoring resistance training. Key points This study determined the validity and reliability of peak velocity, average velocity, peak power and average power measurements made using a linear position transducer The Tendo Weight-lifting Analyzer Systemi emerged as a reliable system for measuring movement velocity and power. PMID:25729300

The effects of Cognitive Bias Modification training and oxytocin administration on trust in maternal support: study protocol for a randomized controlled trial.

PubMed

Verhees, Martine W F T; Ceulemans, Eva; Bakermans-Kranenburg, Marian J; van IJzendoorn, Marinus H; de Winter, Simon; Bosmans, Guy

2017-07-14

Lack of trust in parental support is a transdiagnostic risk factor for the development of psychological problems throughout the lifespan. Research suggests that children's cognitive attachment representations and related information processing biases could be an important target for interventions aiming to build trust in the parent-child relationship. A paradigm that can alter these biases and increase trust is that of Cognitive Bias Modification (CBM), during which a target processing bias is systematically trained. Trust-related CBM training effects could possibly be enhanced by oxytocin, a neuropeptide that has been proposed to play an important role in social information processing and social relationships. The present article describes the study protocol for a double-blind randomized controlled trial (RCT) aimed at testing the individual and combined effects of CBM training and oxytocin administration on trust in maternal support. One hundred children (aged 8-12 years) are randomly assigned to one of four intervention conditions. Participants inhale a nasal spray that either contains oxytocin (OT) or a placebo. Additionally, they receive either a CBM training aimed at positively modifying trust-related information processing bias or a neutral placebo training aimed to have no trust-related effects. Main and interaction effects of the interventions are assessed on three levels of trust-related outcome measures: trust-related interpretation bias; self-reported trust; and mother-child interactional behavior. Importantly, side-effects of a single administration of OT in middle childhood are monitored closely to provide further information on the safety of OT administration in this age group. The present RCT is the first study to combine CBM training with oxytocin to test for individual and combined effects on trust in mother. If effective, CBM training and oxytocin could be easily applicable and nonintrusive additions to interventions that target trust in the context of the parent-child relationship. ClinicalTrials.gov, ID: NCT02737254 . Registered on 23 March 2016.

Laboratory instrumentation and techniques for characterizing multi-junction solar cells for space applications

NASA Technical Reports Server (NTRS)

Woodyard, James R.

1995-01-01

Multi-junction solar cells are attractive for space applications because they can be designed to convert a larger fraction of AMO into electrical power at a lower cost than single-junction cells. The performance of multi-junction cells is much more sensitive to the spectral irradiance of the illuminating source than single-junction cells. The design of high efficiency multi-junction cells for space applications requires matching the optoelectronic properties of the junctions to AMO spectral irradiance. Unlike single-junction cells, it is not possible to carry out quantum efficiency measurements using only a monochromatic probe beam and determining the cell short-circuit current assuming linearity of the quantum efficiency. Additionally, current-voltage characteristics can not be calculated from measurements under non-AMO light sources using spectral-correction methods. There are reports in the literature on characterizing the performance of multi junction cells by measuring and convoluting the quantum efficiency of each junction with the spectral irradiance; the technique is of limited value for the characterization of cell performance under AMO power-generating conditions. We report the results of research to develop instrumentation and techniques for characterizing multi junction solar cells for space . An integrated system is described which consists of a standard lamp, spectral radiometer, dual-source solar simulator, and personal computer based current-voltage and quantum efficiency equipment. The spectral radiometer is calibrated regularly using the tungsten-halogen standard lamp which has a calibration based on NIST scales. The solar simulator produces the light bias beam for current-voltage and cell quantum efficiency measurements. The calibrated spectral radiometer is used to 'fit' the spectral irradiance of the dual-source solar simulator to WRL AMO data. The quantum efficiency apparatus includes a monochromatic probe beam for measuring the absolute cell quantum efficiency at various voltage biases, including the voltage bias corresponding to the maximum-power point under AMO light bias. The details of the procedures to 'fit' the spectral irradiance to AMO will be discussed. An assessment of the role of the accuracy of the 'fit' of the spectral irradiance and probe beam intensity on measured cell characteristics will be presented. quantum efficiencies were measured with both spectral light bias and AMO light bias; the measurements show striking differences. Spectral irradiances were convoluted with cell quantum efficiencies to calculate cell currents as function of voltage. The calculated currents compare with measured currents at the 1% level. Measurements on a variety of multi-junction cells will be presented. The dependence of defects in junctions on cell quantum efficiencies measured under light and voltage bias conditions will be presented. Comments will be made on issues related to standards for calibration, and limitations of the instrumentation and techniques. Expeditious development of multi-junction solar cell technology for space presents challenges for cell characterization in the laboratory.

Clearing out a maze: A model of chemotactic motion in porous media

NASA Astrophysics Data System (ADS)

Schilling, Tanja; Voigtmann, Thomas

2017-12-01

We study the anomalous dynamics of a biased "hungry" (or "greedy") random walk on a percolating cluster. The model mimics chemotaxis in a porous medium: In close resemblance to the 1980s arcade game PAC-MA N ®, the hungry random walker consumes food, which is initially distributed in the maze, and biases its movement towards food-filled sites. We observe that the mean-squared displacement of the process follows a power law with an exponent that is different from previously known exponents describing passive or active microswimmer dynamics. The change in dynamics is well described by a dynamical exponent that depends continuously on the propensity to move towards food. It results in slower differential growth when compared to the unbiased random walk.

Different hunting strategies select for different weights in red deer.

PubMed

Martínez, María; Rodríguez-Vigal, Carlos; Jones, Owen R; Coulson, Tim; San Miguel, Alfonso

2005-09-22

Much insight can be derived from records of shot animals. Most researchers using such data assume that their data represents a random sample of a particular demographic class. However, hunters typically select a non-random subset of the population and hunting is, therefore, not a random process. Here, with red deer (Cervus elaphus) hunting data from a ranch in Toledo, Spain, we demonstrate that data collection methods have a significant influence upon the apparent relationship between age and weight. We argue that a failure to correct for such methodological bias may have significant consequences for the interpretation of analyses involving weight or correlated traits such as breeding success, and urge researchers to explore methods to identify and correct for such bias in their data.

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

2018-04-01

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

Effects of social approval bias on self-reported fruit and vegetable consumption: a randomized controlled trial.

PubMed

Miller, Tracy M; Abdel-Maksoud, Madiha F; Crane, Lori A; Marcus, Al C; Byers, Tim E

2008-06-27

Self-reports of dietary intake in the context of nutrition intervention research can be biased by the tendency of respondents to answer consistent with expected norms (social approval bias). The objective of this study was to assess the potential influence of social approval bias on self-reports of fruit and vegetable intake obtained using both food frequency questionnaire (FFQ) and 24-hour recall methods. A randomized blinded trial compared reported fruit and vegetable intake among subjects exposed to a potentially biasing prompt to that from control subjects. Subjects included 163 women residing in Colorado between 35 and 65 years of age who were randomly selected and recruited by telephone to complete what they were told would be a future telephone survey about health. Randomly half of the subjects then received a letter prior to the interview describing this as a study of fruit and vegetable intake. The letter included a brief statement of the benefits of fruits and vegetables, a 5-A-Day sticker, and a 5-a-Day refrigerator magnet. The remainder received the same letter, but describing the study purpose only as a more general nutrition survey, with neither the fruit and vegetable message nor the 5-A-Day materials. Subjects were then interviewed on the telephone within 10 days following the letters using an eight-item FFQ and a limited 24-hour recall to estimate fruit and vegetable intake. All interviewers were blinded to the treatment condition. By the FFQ method, subjects who viewed the potentially biasing prompts reported consuming more fruits and vegetables than did control subjects (5.2 vs. 3.7 servings per day, p < 0.001). By the 24-hour recall method, 61% of the intervention group but only 32% of the control reported eating fruits and vegetables on 3 or more occasions the prior day (p = 0.002). These associations were independent of age, race/ethnicity, education level, self-perceived health status, and time since last medical check-up. Self-reports of fruit and vegetable intake using either a food frequency questionnaire or a limited 24-hour recall are both susceptible to substantial social approval bias. Valid assessments of intervention effects in nutritional intervention trials may require objective measures of dietary change.

Forward-biased nanophotonic detector for ultralow-energy dissipation receiver

NASA Astrophysics Data System (ADS)

Nozaki, Kengo; Matsuo, Shinji; Fujii, Takuro; Takeda, Koji; Shinya, Akihiko; Kuramochi, Eiichi; Notomi, Masaya

2018-04-01

Generally, reverse-biased photodetectors (PDs) are used for high-speed optical receivers. The forward voltage region is only utilized in solar-cells, and this photovoltaic operation would not be concurrently obtained with high efficiency and high speed operation. Here we report that photonic-crystal waveguide PDs enable forward-biased high-speed operation at 40 Gbit/s with keeping high responsivity (0.88 A/W). Within our knowledge, this is the first demonstration of the forward-biased PDs with high responsivity. This achievement is attributed to the ultracompactness of our PD and the strong light confinement within the absorber and depleted regions, thereby enabling efficient photo-carrier generation and fast extraction. This result indicates that it is possible to construct a high-speed and ultracompact photo-receiver without an electrical amplifier nor an external bias circuit. Since there is no electrical energy required, our estimation shows that the consumption energy is just the optical energy of the injected signal pulse which is about 1 fJ/bit. Hence, it will lead to an ultimately efficient and highly integrable optical-to-electrical converter in a chip, which will be a key ingredient for dense nanophotonic communication and processors.

Behavioral Intervention Materials Compendium. OPRE Report 2018-08

ERIC Educational Resources Information Center

Anzelone, Caitlin, Ed.; Dechausay, Nadine, Ed.; Alemany, Xavier, Ed.

2018-01-01

The Behavioral Interventions to Advance Self-Sufficiency (BIAS) project conducted 15 randomized controlled trials of behavioral interventions across eight states, in the domains of work support, child support, and child care. BIAS used a systematic approach called "behavioral diagnosis and design" to develop the interventions and their…

Statistical inference for the additive hazards model under outcome-dependent sampling.

PubMed

Yu, Jichang; Liu, Yanyan; Sandler, Dale P; Zhou, Haibo

2015-09-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer.

Statistical inference for the additive hazards model under outcome-dependent sampling

PubMed Central

Yu, Jichang; Liu, Yanyan; Sandler, Dale P.; Zhou, Haibo

2015-01-01

Cost-effective study design and proper inference procedures for data from such designs are always of particular interests to study investigators. In this article, we propose a biased sampling scheme, an outcome-dependent sampling (ODS) design for survival data with right censoring under the additive hazards model. We develop a weighted pseudo-score estimator for the regression parameters for the proposed design and derive the asymptotic properties of the proposed estimator. We also provide some suggestions for using the proposed method by evaluating the relative efficiency of the proposed method against simple random sampling design and derive the optimal allocation of the subsamples for the proposed design. Simulation studies show that the proposed ODS design is more powerful than other existing designs and the proposed estimator is more efficient than other estimators. We apply our method to analyze a cancer study conducted at NIEHS, the Cancer Incidence and Mortality of Uranium Miners Study, to study the risk of radon exposure to cancer. PMID:26379363

A focus group study to understand biases and confounders in a cluster randomized controlled trial on low back pain in primary care in Norway.

PubMed

Werner, Erik L; Løchting, Ida; Storheim, Kjersti; Grotle, Margreth

2018-05-22

Cluster randomized controlled trials are often used in research in primary care but creates challenges regarding biases and confounders. We recently presented a study on low back pain from primary care in Norway with equal effects in the intervention and the control group. In order to understand the specific mechanisms that may produce biases in a cluster randomized trial we conducted a focus group study among the participating health care providers. The aim of this study was to understand how the participating providers themselves influenced on the study and thereby possibly on the results of the cluster randomized controlled trial. The providers were invited to share their experiences from their participation in the COPE study, from recruitment of patients to accomplishment of either the intervention or control consultations. Six clinicians from the intervention group and four from the control group took part in the focus group interviews. The group discussions focused on feasibility of the study in primary care and particularly on identifying potential biases and confounders in the study. The audio-recorded interviews were transcribed verbatim and analyzed according to a systematic text condensation. The themes for the analysis emerged from the group discussions. A personal interest for back pain, logistic factors at the clinics and an assessment of the patients' capacity to accomplish the study prior to their recruitment was reported. The providers were allowed to provide additional therapy to the intervention and it turned out that some of these could be regarded as opposed to the messages of the intervention. The providers seemed to select different items from the educational package according to personal beliefs and their perception of the patients' acceptance. The study disclosed several potential biases to the COPE study which may have impacted on the study results. Awareness of these is highly important when planning and conducting a cluster randomized controlled trial. Procedures in the recruitment of both providers and patients seem to be key factors and the providers should be aware of their role in a scientific study in order to standardize the provision of the intervention.

A comparison of the test-negative and the traditional case-control study designs for estimation of influenza vaccine effectiveness under nonrandom vaccination.

PubMed

Shi, Meng; An, Qian; Ainslie, Kylie E C; Haber, Michael; Orenstein, Walter A

2017-12-08

As annual influenza vaccination is recommended for all U.S. persons aged 6 months or older, it is unethical to conduct randomized clinical trials to estimate influenza vaccine effectiveness (VE). Observational studies are being increasingly used to estimate VE. We developed a probability model for comparing the bias and the precision of VE estimates from two case-control designs: the traditional case-control (TCC) design and the test-negative (TN) design. In both study designs, acute respiratory illness (ARI) patients seeking medical care testing positive for influenza infection are considered cases. In the TN design, ARI patients seeking medical care who test negative serve as controls, while in the TCC design, controls are randomly selected individuals from the community who did not contract an ARI. Our model assigns each study participant a covariate corresponding to the person's health status. The probabilities of vaccination and of contracting influenza and non-influenza ARI depend on health status. Hence, our model allows non-random vaccination and confounding. In addition, the probability of seeking care for ARI may depend on vaccination and health status. We consider two outcomes of interest: symptomatic influenza (SI) and medically-attended influenza (MAI). If vaccination does not affect the probability of non-influenza ARI, then VE estimates from TN studies usually have smaller bias than estimates from TCC studies. We also found that if vaccinated influenza ARI patients are less likely to seek medical care than unvaccinated patients because the vaccine reduces symptoms' severity, then estimates of VE from both types of studies may be severely biased when the outcome of interest is SI. The bias is not present when the outcome of interest is MAI. The TN design produces valid estimates of VE if (a) vaccination does not affect the probabilities of non-influenza ARI and of seeking care against influenza ARI, and (b) the confounding effects resulting from non-random vaccination are similar for influenza and non-influenza ARI. Since the bias of VE estimates depends on the outcome against which the vaccine is supposed to protect, it is important to specify the outcome of interest when evaluating the bias.

Surprisingly rational: probability theory plus noise explains biases in judgment.

PubMed

Costello, Fintan; Watts, Paul

2014-07-01

The systematic biases seen in people's probability judgments are typically taken as evidence that people do not use the rules of probability theory when reasoning about probability but instead use heuristics, which sometimes yield reasonable judgments and sometimes yield systematic biases. This view has had a major impact in economics, law, medicine, and other fields; indeed, the idea that people cannot reason with probabilities has become a truism. We present a simple alternative to this view, where people reason about probability according to probability theory but are subject to random variation or noise in the reasoning process. In this account the effect of noise is canceled for some probabilistic expressions. Analyzing data from 2 experiments, we find that, for these expressions, people's probability judgments are strikingly close to those required by probability theory. For other expressions, this account produces systematic deviations in probability estimates. These deviations explain 4 reliable biases in human probabilistic reasoning (conservatism, subadditivity, conjunction, and disjunction fallacies). These results suggest that people's probability judgments embody the rules of probability theory and that biases in those judgments are due to the effects of random noise. (c) 2014 APA, all rights reserved.

Growing cell-phone population and noncoverage bias in traditional random digit dial telephone health surveys.

PubMed

Lee, Sunghee; Brick, J Michael; Brown, E Richard; Grant, David

2010-08-01

Examine the effect of including cell-phone numbers in a traditional landline random digit dial (RDD) telephone survey. The 2007 California Health Interview Survey (CHIS). CHIS 2007 is an RDD telephone survey supplementing a landline sample in California with a sample of cell-only (CO) adults. We examined the degree of bias due to exclusion of CO populations and compared a series of demographic and health-related characteristics by telephone usage. When adjusted for noncoverage in the landline sample through weighting, the potential noncoverage bias due to excluding CO adults in landline telephone surveys is diminished. Both CO adults and adults who have both landline and cell phones but mostly use cell phones appear different from other telephone usage groups. Controlling for demographic differences did not attenuate the significant distinctiveness of cell-mostly adults. While careful weighting can mitigate noncoverage bias in landline telephone surveys, the rapid growth of cell-phone population and their distinctive characteristics suggest it is important to include a cell-phone sample. Moreover, the threat of noncoverage bias in telephone health survey estimates could mislead policy makers with possibly serious consequences for their ability to address important health policy issues.

The response of covered silicon detectors to monoenergetic gamma rays

NASA Technical Reports Server (NTRS)

Reier, M.

1972-01-01

Measurements were made of the efficiency in detecting gamma rays of a 0.3-mm, a 3-mm, and a 5-mm silicon detector covered with different absorbers. Calibrated sources covering the range from 279 KeV to 2.75 MeV were used. The need for the absorbers in order to obtain meaningful results, and their contribution to detector response at electron biases from 50 to 200 KeV, are discussed in detail. It is shown that the results are independent of the atomic number of the absorber. In addition, the role of the absorber in increasing the efficiency with increasing photon energy for low bias setting is demonstrated for the 0.3-mm crystal. Qualitative explanations are given for the shapes of all curves of efficiency versus energy at each bias.

The effect of an intervention to break the gender bias habit for faculty at one institution: a cluster randomized, controlled trial.

PubMed

Carnes, Molly; Devine, Patricia G; Baier Manwell, Linda; Byars-Winston, Angela; Fine, Eve; Ford, Cecilia E; Forscher, Patrick; Isaac, Carol; Kaatz, Anna; Magua, Wairimu; Palta, Mari; Sheridan, Jennifer

2015-02-01

Despite sincere commitment to egalitarian, meritocratic principles, subtle gender bias persists, constraining women's opportunities for academic advancement. The authors implemented a pair-matched, single-blind, cluster randomized, controlled study of a gender-bias-habit-changing intervention at a large public university. Participants were faculty in 92 departments or divisions at the University of Wisconsin-Madison. Between September 2010 and March 2012, experimental departments were offered a gender-bias-habit-changing intervention as a 2.5-hour workshop. Surveys measured gender bias awareness; motivation, self-efficacy, and outcome expectations to reduce bias; and gender equity action. A timed word categorization task measured implicit gender/leadership bias. Faculty completed a work-life survey before and after all experimental departments received the intervention. Control departments were offered workshops after data were collected. Linear mixed-effects models showed significantly greater changes post intervention for faculty in experimental versus control departments on several outcome measures, including self-efficacy to engage in gender-equity-promoting behaviors (P = .013). When ≥ 25% of a department's faculty attended the workshop (26 of 46 departments), significant increases in self-reported action to promote gender equity occurred at three months (P = .007). Post intervention, faculty in experimental departments expressed greater perceptions of fit (P = .024), valuing of their research (P = .019), and comfort in raising personal and professional conflicts (P = .025). An intervention that facilitates intentional behavioral change can help faculty break the gender bias habit and change department climate in ways that should support the career advancement of women in academic medicine, science, and engineering.

Gender bias affects forests worldwide

Treesearch

Marlène Elias; Susan S Hummel; Bimbika S Basnett; Carol J.P. Colfer

2017-01-01

Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure,...

Toward a Better Understanding of the Relationship between Belief in the Paranormal and Statistical Bias: The Potential Role of Schizotypy

PubMed Central

Dagnall, Neil; Denovan, Andrew; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2016-01-01

The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief), belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS) and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy). Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience (UnExp) subscale of O-LIFE and paranormal belief measures [RPBS full scale, traditional paranormal beliefs (TPB) and new age philosophy]. Performance on standard problems correlated negatively with UnExp and belief in the paranormal (particularly the TPB dimension of the RPBS). Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to UnExp. Structural equation modeling specified that belief in the paranormal mediated the indirect relationship between UnExp and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst UnExp correlated positively with conjunction proneness (controlling for perception of randomness), there was no association between UnExp and perception of randomness (controlling for conjunction). PMID:27471481

Toward a Better Understanding of the Relationship between Belief in the Paranormal and Statistical Bias: The Potential Role of Schizotypy.

PubMed

Dagnall, Neil; Denovan, Andrew; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2016-01-01

The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief), belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS) and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy). Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience (UnExp) subscale of O-LIFE and paranormal belief measures [RPBS full scale, traditional paranormal beliefs (TPB) and new age philosophy]. Performance on standard problems correlated negatively with UnExp and belief in the paranormal (particularly the TPB dimension of the RPBS). Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to UnExp. Structural equation modeling specified that belief in the paranormal mediated the indirect relationship between UnExp and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst UnExp correlated positively with conjunction proneness (controlling for perception of randomness), there was no association between UnExp and perception of randomness (controlling for conjunction).

Randomized controlled trials of simulation-based interventions in Emergency Medicine: a methodological review.

PubMed

Chauvin, Anthony; Truchot, Jennifer; Bafeta, Aida; Pateron, Dominique; Plaisance, Patrick; Yordanov, Youri

2018-04-01

The number of trials assessing Simulation-Based Medical Education (SBME) interventions has rapidly expanded. Many studies show that potential flaws in design, conduct and reporting of randomized controlled trials (RCTs) can bias their results. We conducted a methodological review of RCTs assessing a SBME in Emergency Medicine (EM) and examined their methodological characteristics. We searched MEDLINE via PubMed for RCT that assessed a simulation intervention in EM, published in 6 general and internal medicine and in the top 10 EM journals. The Cochrane Collaboration risk of Bias tool was used to assess risk of bias, intervention reporting was evaluated based on the "template for intervention description and replication" checklist, and methodological quality was evaluated by the Medical Education Research Study Quality Instrument. Reports selection and data extraction was done by 2 independents researchers. From 1394 RCTs screened, 68 trials assessed a SBME intervention. They represent one quarter of our sample. Cardiopulmonary resuscitation (CPR) is the most frequent topic (81%). Random sequence generation and allocation concealment were performed correctly in 66 and 49% of trials. Blinding of participants and assessors was performed correctly in 19 and 68%. Risk of attrition bias was low in three-quarters of the studies (n = 51). Risk of selective reporting bias was unclear in nearly all studies. The mean MERQSI score was of 13.4/18.4% of the reports provided a description allowing the intervention replication. Trials assessing simulation represent one quarter of RCTs in EM. Their quality remains unclear, and reproducing the interventions appears challenging due to reporting issues.

Evolutionary Trends and the Salience Bias (with Apologies to Oil Tankers, Karl Marx, and Others).

ERIC Educational Resources Information Center

McShea, Daniel W.

1994-01-01

Examines evolutionary trends, specifically trends in size, complexity, and fitness. Notes that documentation of these trends consists of either long lists of cases, or descriptions of a small number of salient cases. Proposes the use of random samples to avoid this "saliency bias." (SR)

What Constitutes Commercial Bias Compared with the Personal Opinion of Experts?

ERIC Educational Resources Information Center

Cornish, Jean K.; Leist, James C.

2006-01-01

Introduction: The presence of commercial messages in continuing medical education (CME) is an ongoing cause of concern. This study identifies actions perceived by CME participants to convey commercial bias from CME faculty. Methods: A questionnaire listing actions associated with CME activities was distributed to 230 randomly selected participants…

Anti-Fat Bias by Professors Teaching Physical Education Majors

ERIC Educational Resources Information Center

Fontana, Fabio; Furtado, Ovande, Jr.; Mazzardo, Oldemar, Jr.; Hong, Deockki; de Campos, Wagner

2017-01-01

Anti-fat bias by professors in physical education departments may interfere with the training provided to pre-service teachers. The purpose of this study was to evaluate the attitudes of professors in physical education departments toward obese individuals. Professors from randomly selected institutions across all four US regions participated in…

Examinations of Home Economics Textbooks for Sex Bias.

ERIC Educational Resources Information Center

Weis, Susan F.

1979-01-01

Four analyses were conducted on a sample of 100 randomly selected, secondary home economics textbooks published between 1964 and 1974. Results indicated that the contents presented sex bias in language usage, in pictures portraying male and female role environments, and in role behaviors and expectations emphasized. (Author/JH)

Stoppage in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Grønborg, Therese K.; Hansen, Stefan N.; Nielsen, Svend V.; Skytthe, Axel; Parner, Erik T.

2015-01-01

Stoppage refers to changes in reproductive behavior following the birth of a child with a severe disease. The presence of stoppage can bias estimates of sibling recurrence risk if not properly addressed. If stoppage occurs non-randomly (differential stoppage), it is possibly an additional source of bias in sibling recurrence risk estimation. This…

[Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

PubMed

Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

2015-05-01

The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

Effects of Bias Modification Training in Binge Eating Disorder.

PubMed

Schmitz, Florian; Svaldi, Jennifer

2017-09-01

Food-related attentional biases have been identified as maintaining factors in binge eating disorder (BED) as they can trigger a binge episode. Bias modification training may reduce symptoms, as it has been shown to be successful in other appetitive disorders. The aim of this study was to assess and modify food-related biases in BED. It was tested whether biases could be increased and decreased by means of a modified dot-probe paradigm, how long such bias modification persisted, and whether this affected subjective food craving. Participants were randomly assigned to a bias enhancement (attend to food stimulus) group or to a bias reduction (avoid food stimulus) group. Food-related attentional bias was found to be successfully reduced in the bias-reduction group, and effects persisted briefly. Additionally, subjective craving for food was influenced by the intervention, and possible mechanisms are discussed. Given these promising initial results, future research should investigate boundary conditions of the experimental intervention to understand how it could complement treatment of BED. Copyright © 2017. Published by Elsevier Ltd.

Evidence-based medicine, the research-practice gap, and biases in medical and surgical decision making in dermatology.

PubMed

Eaglstein, William H

2010-10-01

The objectives of this article are to promote a better understanding of a group of biases that influence therapeutic decision making by physicians/dermatologists and to raise the awareness that these biases contribute to a research-practice gap that has an impact on physicians and treatment solutions. The literature included a wide range of peer-reviewed articles dealing with biases in decision making, evidence-based medicine, randomized controlled clinical trials, and the research-practice gap. Bias against new therapies, bias in favor of indirect harm or omission, and bias against change when multiple new choices are offered may unconsciously affect therapeutic decision making. Although there is no comprehensive understanding or theory as to how choices are made by physicians, recognition of certain cognition patterns and their associated biases will help narrow the research-practice gap and optimize decision making regarding therapeutic choices.

Simplified biased random walk model for RecA-protein-mediated homology recognition offers rapid and accurate self-assembly of long linear arrays of binding sites

NASA Astrophysics Data System (ADS)

Kates-Harbeck, Julian; Tilloy, Antoine; Prentiss, Mara

2013-07-01

Inspired by RecA-protein-based homology recognition, we consider the pairing of two long linear arrays of binding sites. We propose a fully reversible, physically realizable biased random walk model for rapid and accurate self-assembly due to the spontaneous pairing of matching binding sites, where the statistics of the searched sample are included. In the model, there are two bound conformations, and the free energy for each conformation is a weakly nonlinear function of the number of contiguous matched bound sites.

Electrolytes as Cathode Interlayers in Inverted Organic Solar Cells: Influence of the Cations on Bias-Dependent Performance.

PubMed

Li, Yaru; Liu, Xiaohui; Li, Xiaodong; Zhang, Wenjun; Xing, Feifei; Fang, Junfeng

2017-03-08

The performance of organic solar cells (OSCs) with edetate electrolytes depends on external bias, and ions are speculated to be responsible for this phenomenon. To clarify the detailed relationship between the ions of electrolytes and the bias-dependent behaviors of devices, this work introduces four edetate cathode interlayers (EDTA-X, X = nH(4-n)Na, n = 0, 1, 2, and 4) containing different kinds and number of cations into inverted OSCs. The results show that the devices initial and saturated (after external bias treatment) power conversion efficiencies (PCEs) both decrease with the increase in the number of H + . Moreover, the bias-dependent degrees increase with the increase in H + number; with that, the PCE increment of EDTA-4H device is 53.4%, while that of the EDTA-4Na device is almost unchanged. The electrical impedance spectroscopy and capacitance-voltage tests reveal that the interfacial recombination is greatly suppressed by external bias treatment, which is not a result of the decreased density of defect states. The results indicate that the ion's motion, specifically the H + motion, under external electrical field is responsible for the bias-dependent behavior, which is conducive to the design of new efficient electrolytic interlayers without bias-dependent performance.

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.

Efficiency enhancement using voltage biasing for ferroelectric polarization in dye-sensitized solar cells

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Song, Myoung Geun; Bark, Chung Wung

2018-01-01

Dye-sensitized solar cells (DSSCs) are one of the most promising third generation solar cells that have been extensively researched over the past decade as alternative to silicon-based solar cells, due to their low production cost and high energy-conversion efficiency. In general, a DSSC consists of a transparent electrode, a counter electrode, and an electrolyte such as dye. To achieve high power-conversion efficiency in cells, many research groups have focused their efforts on developing efficient dyes for liquid electrolytes. In this work, we report on the photovoltaic properties of DSSCs fabricated using a mixture of TiO2 with nanosized Fe-doped bismuth lanthanum titanate (nFe-BLT) powder). Firstly, nFe-BLT powders were prepared using a high-energy ball milling process and then, TiO2 and nFe-BLT powders were stoichiometrically blended. Direct current (DC) bias of 20 MV/m was applied to lab-made DSSCs. With the optimal concentration of nFe-BLT doped in the electrode, their light-to-electricity conversion efficiency could be improved by ∼64% compared with DSSCs where no DC bias was applied.

Effect of standardized training on the reliability of the Cochrane risk of bias assessment tool: a prospective study.

PubMed

da Costa, Bruno R; Beckett, Brooke; Diaz, Alison; Resta, Nina M; Johnston, Bradley C; Egger, Matthias; Jüni, Peter; Armijo-Olivo, Susan

2017-03-03

The Cochrane risk of bias tool is commonly criticized for having a low reliability. We aimed to investigate whether training of raters, with objective and standardized instructions on how to assess risk of bias, can improve the reliability of the Cochrane risk of bias tool. In this pilot study, four raters inexperienced in risk of bias assessment were randomly allocated to minimal or intensive standardized training for risk of bias assessment of randomized trials of physical therapy treatments for patients with knee osteoarthritis pain. Two raters were experienced risk of bias assessors who served as reference. The primary outcome of our study was between-group reliability, defined as the agreement of the risk of bias assessments of inexperienced raters with the reference assessments of experienced raters. Consensus-based assessments were used for this purpose. The secondary outcome was within-group reliability, defined as the agreement of assessments within pairs of inexperienced raters. We calculated the chance-corrected weighted Kappa to quantify agreement within and between groups of raters for each of the domains of the risk of bias tool. A total of 56 trials were included in our analysis. The Kappa for the agreement of inexperienced raters with reference across items of the risk of bias tool ranged from 0.10 to 0.81 for the minimal training group and from 0.41 to 0.90 for the standardized training group. The Kappa values for the agreement within pairs of inexperienced raters across the items of the risk of bias tool ranged from 0 to 0.38 for the minimal training group and from 0.93 to 1 for the standardized training group. Between-group differences in Kappa for the agreement of inexperienced raters with reference always favored the standardized training group and was most pronounced for incomplete outcome data (difference in Kappa 0.52, p < 0.001) and allocation concealment (difference in Kappa 0.30, p = 0.004). Intensive, standardized training on risk of bias assessment may significantly improve the reliability of the Cochrane risk of bias tool.

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.

Different hunting strategies select for different weights in red deer

PubMed Central

Martínez, María; Rodríguez-Vigal, Carlos; Jones, Owen R; Coulson, Tim; Miguel, Alfonso San

2005-01-01

Much insight can be derived from records of shot animals. Most researchers using such data assume that their data represents a random sample of a particular demographic class. However, hunters typically select a non-random subset of the population and hunting is, therefore, not a random process. Here, with red deer (Cervus elaphus) hunting data from a ranch in Toledo, Spain, we demonstrate that data collection methods have a significant influence upon the apparent relationship between age and weight. We argue that a failure to correct for such methodological bias may have significant consequences for the interpretation of analyses involving weight or correlated traits such as breeding success, and urge researchers to explore methods to identify and correct for such bias in their data. PMID:17148205

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

Why Are People Bad at Detecting Randomness? A Statistical Argument

ERIC Educational Resources Information Center

Williams, Joseph J.; Griffiths, Thomas L.

2013-01-01

Errors in detecting randomness are often explained in terms of biases and misconceptions. We propose and provide evidence for an account that characterizes the contribution of the inherent statistical difficulty of the task. Our account is based on a Bayesian statistical analysis, focusing on the fact that a random process is a special case of…

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

PubMed

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

2015-06-01

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

The response of covered silicon detectors to monoenergetic gamma rays.

NASA Technical Reports Server (NTRS)

Reier, M.

1972-01-01

Measurements have been made of the efficiency in detecting gamma rays of a 0.3-mm-, 3-mm-, and 5-mm-thick silicon detector covered with different absorbers. Calibrated sources over the range from 279 keV to 2.75 MeV were used. The need for the absorbers to obtain meaningful results and their contribution to the response of the detectors at electron biases from 50 to 200 keV are discussed in detail. It is shown that the results are virtually independent of the atomic number of the absorber. In addition, the role of the absorber in increasing the efficiency with increasing photon energy for low bias settings is demonstrated for the 0.3-mm crystal. Qualitative explanations are given for the shapes of all curves of efficiency versus energy at each bias.

Bias modification training can alter approach bias and chocolate consumption.

PubMed

Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika

2016-01-01

Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

Safety and Efficacy of Catheter Direct Thrombolysis in Management of Acute Iliofemoral Deep Vein Thrombosis: A Systematic Review.

PubMed

Elbasty, Ahmed; Metcalf, James

2017-12-01

Catheter direct thrombolysis (CDT) has been shown to be an effective treatment for deep venous thrombosis. The objective of the review is to improve safety and efficacy of the CDT by using ward based protocol, better able to predict complications and treatment outcome through monitoring of haemostatic parameters and clinical observation during thrombolysis procedure. MEDLINE, EMBASE, CENTRAL and Web of Science were searched for all articles on deep venous thrombosis, thrombolysis and correlations of clinical events (bleeding, successful thrombolysis) during thrombolysis with hemostatic parameters to March 2016. The risk of bias in included studies was assessed by Cochrane Collaboration's tool and Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions. Twenty-four studies were included in the review and we found that improving safety and efficacy of CDT by using ward based protocol depending on eight factors; strict patient selection criteria, types of fibrinolytic drugs, mode of fibrinolytic drug injection, biochemical markers monitoring (fibrinogen, D-dimer, activated partial thromboplastin time, plasminogen activator inhibitor-1), timing of intervention, usage of intermittent pneumatic calf, ward monitoring and thrombolysis imaging assessment (intravascular ultrasound). These factors may help to improve safety and efficacy by reducing total thrombolytic drug dosage and at the same time ensure successful lysis. There is a marked lack of randomized controlled trials discussing the safety and efficacy of catheter direct thrombolysis. CDT can be performed safely and efficiently in clinical ward, providing that careful nursing, biochemical monitoring, proper selection and mode of infusion of fibrinolytic drugs, usage of Intermittent pneumatic calf and adequate thrombolysis imaging assessment are ensured.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Making Heads or Tails of Probability: An Experiment with Random Generators

ERIC Educational Resources Information Center

Morsanyi, Kinga; Handley, Simon J.; Serpell, Sylvie

2013-01-01

Background: The equiprobability bias is a tendency for individuals to think of probabilistic events as "equiprobable" by nature, and to judge outcomes that occur with different probabilities as equally likely. The equiprobability bias has been repeatedly found to be related to formal education in statistics, and it is claimed to be based…

Educational Research with Real-World Data: Reducing Selection Bias with Propensity Scores

ERIC Educational Resources Information Center

Adelson, Jill L.

2013-01-01

Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations…

Bias from Wireless Substitution in Surveys of Hispanics

ERIC Educational Resources Information Center

Dutwin, David; Keeter, Scott; Kennedy, Courtney

2010-01-01

Increasingly, American households are choosing to forgo ownership of landline telephones in favor of cell phones. Presently, more than 25% of Hispanics now only own a cell phone. Concern about potential bias from noncoverage of this "cell-only" population in traditional general population RDD (random digit dial) telephone interviewing has been a…

Biases and Standard Errors of Standardized Regression Coefficients

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Chan, Wai

2011-01-01

The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…

Real time radiation dosimeters based on vertically aligned multiwall carbon nanotubes and graphene.

PubMed

Funaro, Maria; Sarno, Maria; Ciambelli, Paolo; Altavilla, Claudia; Proto, Antonio

2013-02-22

Measurements of the absorbed dose and quality assurance programs play an important role in radiotherapy. Ionization chambers (CIs) are considered the most important dosimeters for their high accuracy, practicality and reliability, allowing absolute dose measurements. However, they have a relative large physical size, which limits their spatial resolution, and require a high bias voltage to achieve an acceptable collection of charges, excluding their use for in vivo dosimetry. In this paper, we propose new real time radiation detectors with electrodes based on graphene or vertically aligned multiwall carbon nanotubes (MWCNTs). We have investigated their charge collection efficiency and compared their performance with electrodes made of a conventional material. Moreover, in order to highlight the effect of nanocarbons, reference radiation detectors were also tested. The proposed dosimeters display an excellent linear response to dose and collect more charge than reference ones at a standard bias voltage, permitting the construction of miniaturized CIs. Moreover, an MWCNT based CI gives the best charge collection efficiency and it enables working also to lower bias voltages and zero volts, allowing in vivo applications. Graphene based CIs show better performance with respect to reference dosimeters at a standard bias voltage. However, at decreasing bias voltage the charge collection efficiency becomes worse if compared to a reference detector, likely due to graphene's semiconducting behavior.

Estimating disease prevalence in two-phase studies.

PubMed

Alonzo, Todd A; Pepe, Margaret Sullivan; Lumley, Thomas

2003-04-01

Disease prevalence is ideally estimated using a 'gold standard' to ascertain true disease status on all subjects in a population of interest. In practice, however, the gold standard may be too costly or invasive to be applied to all subjects, in which case a two-phase design is often employed. Phase 1 data consisting of inexpensive and non-invasive screening tests on all study subjects are used to determine the subjects that receive the gold standard in the second phase. Naive estimates of prevalence in two-phase studies can be biased (verification bias). Imputation and re-weighting estimators are often used to avoid this bias. We contrast the forms and attributes of the various prevalence estimators. Distribution theory and simulation studies are used to investigate their bias and efficiency. We conclude that the semiparametric efficient approach is the preferred method for prevalence estimation in two-phase studies. It is more robust and comparable in its efficiency to imputation and other re-weighting estimators. It is also easy to implement. We use this approach to examine the prevalence of depression in adolescents with data from the Great Smoky Mountain Study.

Beauty is in the efficient coding of the beholder.

PubMed

Renoult, Julien P; Bovet, Jeanne; Raymond, Michel

2016-03-01

Sexual ornaments are often assumed to be indicators of mate quality. Yet it remains poorly known how certain ornaments are chosen before any coevolutionary race makes them indicative. Perceptual biases have been proposed to play this role, but known biases are mostly restricted to a specific taxon, which precludes evaluating their general importance in sexual selection. Here we identify a potentially universal perceptual bias in mate choice. We used an algorithm that models the sparseness of the activity of simple cells in the primary visual cortex (or V1) of humans when coding images of female faces. Sparseness was found positively correlated with attractiveness as rated by men and explained up to 17% of variance in attractiveness. Because V1 is adapted to process signals from natural scenes, in general, not faces specifically, our results indicate that attractiveness for female faces is influenced by a visual bias. Sparseness and more generally efficient neural coding are ubiquitous, occurring in various animals and sensory modalities, suggesting that the influence of efficient coding on mate choice can be widespread in animals.

Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients.

PubMed

Green, Alexander R; Carney, Dana R; Pallin, Daniel J; Ngo, Long H; Raymond, Kristal L; Iezzoni, Lisa I; Banaji, Mahzarin R

2007-09-01

Studies documenting racial/ethnic disparities in health care frequently implicate physicians' unconscious biases. No study to date has measured physicians' unconscious racial bias to test whether this predicts physicians' clinical decisions. To test whether physicians show implicit race bias and whether the magnitude of such bias predicts thrombolysis recommendations for black and white patients with acute coronary syndromes. An internet-based tool comprising a clinical vignette of a patient presenting to the emergency department with an acute coronary syndrome, followed by a questionnaire and three Implicit Association Tests (IATs). Study invitations were e-mailed to all internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston; 287 completed the study, met inclusion criteria, and were randomized to either a black or white vignette patient. IAT scores (normal continuous variable) measuring physicians' implicit race preference and perceptions of cooperativeness. Physicians' attribution of symptoms to coronary artery disease for vignette patients with randomly assigned race, and their decisions about thrombolysis. Assessment of physicians' explicit racial biases by questionnaire. Physicians reported no explicit preference for white versus black patients or differences in perceived cooperativeness. In contrast, IATs revealed implicit preference favoring white Americans (mean IAT score = 0.36, P < .001, one-sample t test) and implicit stereotypes of black Americans as less cooperative with medical procedures (mean IAT score 0.22, P < .001), and less cooperative generally (mean IAT score 0.30, P < .001). As physicians' prowhite implicit bias increased, so did their likelihood of treating white patients and not treating black patients with thrombolysis (P = .009). This study represents the first evidence of unconscious (implicit) race bias among physicians, its dissociation from conscious (explicit) bias, and its predictive validity. Results suggest that physicians' unconscious biases may contribute to racial/ethnic disparities in use of medical procedures such as thrombolysis for myocardial infarction.

Biased and greedy random walks on two-dimensional lattices with quenched randomness: The greedy ant within a disordered environment

NASA Astrophysics Data System (ADS)

Mitran, T. L.; Melchert, O.; Hartmann, A. K.

2013-12-01

The main characteristics of biased greedy random walks (BGRWs) on two-dimensional lattices with real-valued quenched disorder on the lattice edges are studied. Here the disorder allows for negative edge weights. In previous studies, considering the negative-weight percolation (NWP) problem, this was shown to change the universality class of the existing, static percolation transition. In the presented study, four different types of BGRWs and an algorithm based on the ant colony optimization heuristic were considered. Regarding the BGRWs, the precise configurations of the lattice walks constructed during the numerical simulations were influenced by two parameters: a disorder parameter ρ that controls the amount of negative edge weights on the lattice and a bias strength B that governs the drift of the walkers along a certain lattice direction. The random walks are “greedy” in the sense that the local optimal choice of the walker is to preferentially traverse edges with a negative weight (associated with a net gain of “energy” for the walker). Here, the pivotal observable is the probability that, after termination, a lattice walk exhibits a total negative weight, which is here considered as percolating. The behavior of this observable as function of ρ for different bias strengths B is put under scrutiny. Upon tuning ρ, the probability to find such a feasible lattice walk increases from zero to 1. This is the key feature of the percolation transition in the NWP model. Here, we address the question how well the transition point ρc, resulting from numerically exact and “static” simulations in terms of the NWP model, can be resolved using simple dynamic algorithms that have only local information available, one of the basic questions in the physics of glassy systems.

Randomized controlled trials in children's heart surgery in the 21st century: a systematic review.

PubMed

Drury, Nigel E; Patel, Akshay J; Oswald, Nicola K; Chong, Cher-Rin; Stickley, John; Barron, David J; Jones, Timothy J

2018-04-01

Randomized controlled trials are the gold standard for evaluating health care interventions, yet are uncommon in children's heart surgery. We conducted a systematic review of clinical trials in paediatric cardiac surgery to evaluate the scope and quality of the current international literature. We searched MEDLINE, CENTRAL and LILACS, and manually screened retrieved references and systematic reviews to identify all randomized controlled trials reporting the effect of any intervention on the conduct or outcomes of heart surgery in children published in any language since January 2000; secondary publications and those reporting inseparable adult data were excluded. Two reviewers independently screened studies for eligibility and extracted data; the Cochrane Risk of Bias tool was used to assess for potential biases. We identified 333 trials from 34 countries randomizing 23 902 children. Most were early phase (313, 94.0%), recruiting few patients (median 45, interquartile range 28-82), and only 11 (3.3%) directly evaluated a surgical intervention. One hundred and nine (32.7%) trials calculated a sample size, 52 (15.6%) reported a CONSORT diagram, 51 (15.3%) were publicly registered and 25 (7.5%) had a Data Monitoring Committee. The overall risk of bias was low in 22 (6.6%), high in 69 (20.7%) and unclear in 242 (72.7%). The recent literature in children's heart surgery contains few late-phase clinical trials. Most trials did not conform to the accepted standards of reporting, and the overall risk of bias was low in few studies. There is a need for high-quality, multicentre clinical trials to provide a robust evidence base for contemporary paediatric cardiac surgical practice.

Randomized controlled trials in children’s heart surgery in the 21st century: a systematic review

PubMed Central

Drury, Nigel E; Patel, Akshay J; Oswald, Nicola K; Chong, Cher-Rin; Stickley, John; Barron, David J; Jones, Timothy J

2018-01-01

Abstract OBJECTIVES Randomized controlled trials are the gold standard for evaluating health care interventions, yet are uncommon in children’s heart surgery. We conducted a systematic review of clinical trials in paediatric cardiac surgery to evaluate the scope and quality of the current international literature. METHODS We searched MEDLINE, CENTRAL and LILACS, and manually screened retrieved references and systematic reviews to identify all randomized controlled trials reporting the effect of any intervention on the conduct or outcomes of heart surgery in children published in any language since January 2000; secondary publications and those reporting inseparable adult data were excluded. Two reviewers independently screened studies for eligibility and extracted data; the Cochrane Risk of Bias tool was used to assess for potential biases. RESULTS We identified 333 trials from 34 countries randomizing 23 902 children. Most were early phase (313, 94.0%), recruiting few patients (median 45, interquartile range 28–82), and only 11 (3.3%) directly evaluated a surgical intervention. One hundred and nine (32.7%) trials calculated a sample size, 52 (15.6%) reported a CONSORT diagram, 51 (15.3%) were publicly registered and 25 (7.5%) had a Data Monitoring Committee. The overall risk of bias was low in 22 (6.6%), high in 69 (20.7%) and unclear in 242 (72.7%). CONCLUSIONS The recent literature in children’s heart surgery contains few late-phase clinical trials. Most trials did not conform to the accepted standards of reporting, and the overall risk of bias was low in few studies. There is a need for high-quality, multicentre clinical trials to provide a robust evidence base for contemporary paediatric cardiac surgical practice. PMID:29186478

Bayesian methods including nonrandomized study data increased the efficiency of postlaunch RCTs.

PubMed

Schmidt, Amand F; Klugkist, Irene; Klungel, Olaf H; Nielen, Mirjam; de Boer, Anthonius; Hoes, Arno W; Groenwold, Rolf H H

2015-04-01

Findings from nonrandomized studies on safety or efficacy of treatment in patient subgroups may trigger postlaunch randomized clinical trials (RCTs). In the analysis of such RCTs, results from nonrandomized studies are typically ignored. This study explores the trade-off between bias and power of Bayesian RCT analysis incorporating information from nonrandomized studies. A simulation study was conducted to compare frequentist with Bayesian analyses using noninformative and informative priors in their ability to detect interaction effects. In simulated subgroups, the effect of a hypothetical treatment differed between subgroups (odds ratio 1.00 vs. 2.33). Simulations varied in sample size, proportions of the subgroups, and specification of the priors. As expected, the results for the informative Bayesian analyses were more biased than those from the noninformative Bayesian analysis or frequentist analysis. However, because of a reduction in posterior variance, informative Bayesian analyses were generally more powerful to detect an effect. In scenarios where the informative priors were in the opposite direction of the RCT data, type 1 error rates could be 100% and power 0%. Bayesian methods incorporating data from nonrandomized studies can meaningfully increase power of interaction tests in postlaunch RCTs. Copyright © 2015 Elsevier Inc. All rights reserved.

MIXED MODEL AND ESTIMATING EQUATION APPROACHES FOR ZERO INFLATION IN CLUSTERED BINARY RESPONSE DATA WITH APPLICATION TO A DATING VIOLENCE STUDY1

PubMed Central

Fulton, Kara A.; Liu, Danping; Haynie, Denise L.; Albert, Paul S.

2016-01-01

The NEXT Generation Health study investigates the dating violence of adolescents using a survey questionnaire. Each student is asked to affirm or deny multiple instances of violence in his/her dating relationship. There is, however, evidence suggesting that students not in a relationship responded to the survey, resulting in excessive zeros in the responses. This paper proposes likelihood-based and estimating equation approaches to analyze the zero-inflated clustered binary response data. We adopt a mixed model method to account for the cluster effect, and the model parameters are estimated using a maximum-likelihood (ML) approach that requires a Gaussian–Hermite quadrature (GHQ) approximation for implementation. Since an incorrect assumption on the random effects distribution may bias the results, we construct generalized estimating equations (GEE) that do not require the correct specification of within-cluster correlation. In a series of simulation studies, we examine the performance of ML and GEE methods in terms of their bias, efficiency and robustness. We illustrate the importance of properly accounting for this zero inflation by reanalyzing the NEXT data where this issue has previously been ignored. PMID:26937263

Efficacy of attention bias modification using threat and appetitive stimuli: a meta-analytic review.

PubMed

Beard, Courtney; Sawyer, Alice T; Hofmann, Stefan G

2012-12-01

Attention bias modification (ABM) protocols aim to modify attentional biases underlying many forms of pathology. Our objective was to conduct an effect size analysis of ABM across a wide range of samples and psychological problems. We conducted a literature search using PubMed, PsycInfo, and author searches to identify randomized studies that examined the effects of ABM on attention and subjective experiences. We identified 37 studies (41 experiments) totaling 2,135 participants who were randomized to training toward neutral, positive, threat, or appetitive stimuli or to a control condition. The effect size estimate for changes in attentional bias was large for the neutral versus threat comparisons (g=1.06), neutral versus appetitive (g=1.41), and neutral versus control comparisons (g=0.80), and small for positive versus control (g=0.24). The effects of ABM on attention bias were moderated by stimulus type (words vs. pictures) and sample characteristics (healthy vs. high symptomatology). Effect sizes of ABM on subjective experiences ranged from 0.03 to 0.60 for postchallenge outcomes, -0.31 to 0.51 for posttreatment, and were moderated by number of training sessions, stimulus type, and stimulus orientation (top/bottom vs. left/right). Fail-safe N calculations suggested that the effect size estimates were robust for the training effects on attentional biases, but not for the effect on subjective experiences. ABM studies using threat stimuli produced significant effects on attention bias across comparison conditions, whereas appetitive stimuli produced changes in attention only when comparing appetitive versus neutral conditions. ABM has a moderate and robust effect on attention bias when using threat stimuli. Further studies are needed to determine whether these effects are also robust when using appetitive stimuli and for affecting subjective experiences. Copyright © 2012. Published by Elsevier Ltd.

Effect of an Intervention to Break the Gender Bias Habit for Faculty at One Institution: A Cluster Randomized, Controlled Trial

PubMed Central

Carnes, Molly; Devine, Patricia G.; Manwell, Linda Baier; Byars-Winston, Angela; Fine, Eve; Ford, Cecilia E.; Forscher, Patrick; Isaac, Carol; Kaatz, Anna; Magua, Wairimu; Palta, Mari; Sheridan, Jennifer

2014-01-01

Purpose Despite sincere commitment to egalitarian, meritocratic principles, subtle gender bias persists, constraining women’s opportunities for academic advancement. The authors implemented a pair-matched, single-blind, cluster-randomized, controlled study of a gender bias habit-changing intervention at a large public university. Method Participants were faculty in 92 departments or divisions at the University of Wisconsin-Madison. Between September 2010 and March 2012, experimental departments were offered a gender bias habit-changing intervention as a 2.5 hour workshop. Surveys measured gender bias awareness; motivation, self-efficacy, and outcome expectations to reduce bias; and gender equity action. A timed word categorization task measured implicit gender/leadership bias. Faculty completed a worklife survey before and after all experimental departments received the intervention. Control departments were offered workshops after data were collected. Results Linear mixed-effects models showed significantly greater changes post-intervention for faculty in experimental vs. control departments on several outcome measures, including self-efficacy to engage in gender equity promoting behaviors (P = .013). When ≥ 25% of a department’s faculty attended the workshop (26 of 46 departments), significant increases in self-reported action to promote gender equity occurred at 3 months (P = .007). Post-intervention, faculty in experimental departments expressed greater perceptions of fit (P = .024), valuing of their research (P = .019), and comfort in raising personal and professional conflicts (P = .025). Conclusions An intervention that facilitates intentional behavioral change can help faculty break the gender bias habit and change department climate in ways that should support the career advancement of women in academic medicine, science, and engineering. PMID:25374039

Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples.

PubMed

Elloumi, Fathi; Hu, Zhiyuan; Li, Yan; Parker, Joel S; Gulley, Margaret L; Amos, Keith D; Troester, Melissa A

2011-06-30

Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

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.

Variable-bias coin tossing

NASA Astrophysics Data System (ADS)

Colbeck, Roger; Kent, Adrian

2006-03-01

Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT.

Experimental modification of interpretation bias about animal fear in young children: effects on cognition, avoidance behavior, anxiety vulnerability, and physiological responding.

PubMed

Lester, Kathryn J; Field, Andy P; Muris, Peter

2011-01-01

This study investigated the effects of experimentally modifying interpretation biases for children's cognitions, avoidance behavior, anxiety vulnerability, and physiological responding. Sixty-seven children (6-11 years) were randomly assigned to receive a positive or negative interpretation bias modification procedure to induce interpretation biases toward or away from threat about ambiguous situations involving Australian marsupials. Children rapidly learned to select outcomes of ambiguous situations, which were congruent with their assigned condition. Furthermore, following positive modification, children's threat biases about novel ambiguous situations significantly decreased, whereas threat biases significantly increased after negative modification. In response to a stress-evoking behavioral avoidance test, positive modification attenuated behavioral avoidance compared to negative modification. However, no significant effects of bias modification on anxiety vulnerability or physiological responses to this stress-evoking Behavioral Avoidance Task were observed.

GRADE guidelines: 5. Rating the quality of evidence--publication bias.

PubMed

Guyatt, Gordon H; Oxman, Andrew D; Montori, Victor; Vist, Gunn; Kunz, Regina; Brozek, Jan; Alonso-Coello, Pablo; Djulbegovic, Ben; Atkins, David; Falck-Ytter, Yngve; Williams, John W; Meerpohl, Joerg; Norris, Susan L; Akl, Elie A; Schünemann, Holger J

2011-12-01

In the GRADE approach, randomized trials start as high-quality evidence and observational studies as low-quality evidence, but both can be rated down if a body of evidence is associated with a high risk of publication bias. Even when individual studies included in best-evidence summaries have a low risk of bias, publication bias can result in substantial overestimates of effect. Authors should suspect publication bias when available evidence comes from a number of small studies, most of which have been commercially funded. A number of approaches based on examination of the pattern of data are available to help assess publication bias. The most popular of these is the funnel plot; all, however, have substantial limitations. Publication bias is likely frequent, and caution in the face of early results, particularly with small sample size and number of events, is warranted. Copyright © 2011 Elsevier Inc. All rights reserved.

Artificial bias typically neglected in comparisons of uncertain atmospheric data

NASA Astrophysics Data System (ADS)

Pitkänen, Mikko R. A.; Mikkonen, Santtu; Lehtinen, Kari E. J.; Lipponen, Antti; Arola, Antti

2016-09-01

Publications in atmospheric sciences typically neglect biases caused by regression dilution (bias of the ordinary least squares line fitting) and regression to the mean (RTM) in comparisons of uncertain data. We use synthetic observations mimicking real atmospheric data to demonstrate how the biases arise from random data uncertainties of measurements, model output, or satellite retrieval products. Further, we provide examples of typical methods of data comparisons that have a tendency to pronounce the biases. The results show, that data uncertainties can significantly bias data comparisons due to regression dilution and RTM, a fact that is known in statistics but disregarded in atmospheric sciences. Thus, we argue that often these biases are widely regarded as measurement or modeling errors, for instance, while they in fact are artificial. It is essential that atmospheric and geoscience communities become aware of and consider these features in research.

Effects of varenicline and cognitive bias modification on neural response to smoking-related cues: study protocol for a randomized controlled study.

PubMed

Attwood, Angela S; Williams, Tim; Adams, Sally; McClernon, Francis J; Munafò, Marcus R

2014-10-07

Smoking-related cues can trigger drug-seeking behaviors, and computer-based interventions that reduce cognitive biases towards such cues may be efficacious and cost-effective cessation aids. In order to optimize such interventions, there needs to be better understanding of the mechanisms underlying the effects of cognitive bias modification (CBM). Here we present a protocol for an investigation of the neural effects of CBM and varenicline in non-quitting daily smokers. We will recruit 72 daily smokers who report smoking at least 10 manufactured cigarettes or 15 roll-ups per day and who smoke within one hour of waking. Participants will attend two sessions approximately one week apart. At the first session participants will be screened for eligibility and randomized to receive either varenicline or a placebo over a seven-day period. On the final drug-taking day (day seven) participants will attend a second session and be further randomized to one of three CBM conditions (training towards smoking cues, training away from smoking cues, or control training). Participants will then undergo a functional magnetic resonance imaging scan during which they will view smoking-related pictorial cues. Primary outcome measures are changes in cognitive bias as measured by the visual dot-probe task, and neural responses to smoking-related cues. Secondary outcome measures will be cognitive bias as measured by a transfer task (modified Stroop test of smoking-related cognitive bias) and subjective mood and cigarette craving. This study will add to the relatively small literature examining the effects of CBM in addictions. It will address novel questions regarding the neural effects of CBM. It will also investigate whether varenicline treatment alters neural response to smoking-related cues. These findings will inform future research that can develop behavioral treatments that target relapse prevention. Registered with Current Controlled Trials: ISRCTN65690030. Registered on 30 January 2014.

Are Anti-Stigma Films a Useful Strategy for Reducing Weight Bias Among Trainee Healthcare Professionals? Results of a Pilot Randomized Control Trial

PubMed Central

Swift, Judy Anne; Tischler, Victoria; Markham, Sophie; Gunning, Ingrid; Glazebrook, Cris; Beer, Charlotte; Puhl, Rebecca

2013-01-01

Background Weight bias is an important clinical issue that the educators of tomorrow's healthcare professionals cannot afford to ignore. This study, therefore, aimed to pilot a randomized controlled trial of the effects of educational films designed to reduce weight stigmatization toward obese patients on trainee dietitians’ and doctors’ attitudes. Methods A pre-post experimental design with a 6-week follow-up, which consisted of an intervention group (n = 22) and a control group (n = 21), was conducted to assess the efficacy of brief anti-stigma films in reducing weight bias, and to test whether future, larger-scale studies among trainee healthcare professionals are feasible. Results Participants at baseline demonstrated weight bias, on both implicit and explicit attitude measures, as well as strong beliefs that obesity is under a person's control. The intervention films significantly improved explicit attitudes and beliefs toward obese people, and participant evaluation was very positive. The intervention did not significantly improve implicit anti-fat bias. Conclusion The current study suggests both that it is possible to conduct a substantive trial of the effects of educational films designed to reduce weight stigma on a larger cohort of trainee healthcare professionals, and that brief educational interventions may be effective in reducing stigmatizing attitudes in this population. PMID:23466551

Are anti-stigma films a useful strategy for reducing weight bias among trainee healthcare professionals? Results of a pilot randomized control trial.

PubMed

Swift, Judy Anne; Tischler, Victoria; Markham, Sophie; Gunning, Ingrid; Glazebrook, Cris; Beer, Charlotte; Puhl, Rebecca

2013-01-01

Weight bias is an important clinical issue that the educators of tomorrow's healthcare professionals cannot afford to ignore. This study, therefore, aimed to pilot a randomized controlled trial of the effects of educational films designed to reduce weight stigmatization toward obese patients on trainee dietitians' and doctors' attitudes. A pre-post experimental design with a 6-week follow-up, which consisted of an intervention group (n = 22) and a control group (n = 21), was conducted to assess the efficacy of brief anti-stigma films in reducing weight bias, and to test whether future, larger-scale studies among trainee healthcare professionals are feasible. Participants at baseline demonstrated weight bias, on both implicit and explicit attitude measures, as well as strong beliefs that obesity is under a person's control. The intervention films significantly improved explicit attitudes and beliefs toward obese people, and participant evaluation was very positive. The intervention did not significantly improve implicit anti-fat bias. The current study suggests both that it is possible to conduct a substantive trial of the effects of educational films designed to reduce weight stigma on a larger cohort of trainee healthcare professionals, and that brief educational interventions may be effective in reducing stigmatizing attitudes in this population.

Characterization of superconducting nanowire single-photon detector with artificial constrictions

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

Zhang, Ling; Liu, Dengkuan; Wu, Junjie

2014-06-15

Statistical studies on the performance of different superconducting nanowire single-photon detectors (SNSPDs) on one chip suggested that random constrictions existed in the nanowire that were barely registered by scanning electron microscopy. With the aid of advanced e-beam lithography, artificial geometric constrictions were fabricated on SNSPDs as well as single nanowires. In this way, we studied the influence of artificial constrictions on SNSPDs in a straight forward manner. By introducing artificial constrictions with different wire widths in single nanowires, we concluded that the dark counts of SNSPDs originate from a single constriction. Further introducing artificial constrictions in SNSPDs, we studied themore » relationship between detection efficiency and kinetic inductance and the bias current, confirming the hypothesis that constrictions exist in SNSPDs.« less

Attention training through gaze-contingent feedback: Effects on reappraisal and negative emotions.

PubMed

Sanchez, Alvaro; Everaert, Jonas; Koster, Ernst H W

2016-10-01

Reappraisal is central to emotion regulation but its mechanisms are unclear. This study tested the theoretical prediction that emotional attention bias is linked to reappraisal of negative emotion-eliciting stimuli and subsequent emotional responding using a novel attentional control training. Thirty-six undergraduates were randomly assigned to either the control or the attention training condition and were provided with different task instructions while they performed an interpretation task. Whereas control participants freely created interpretations, participants in the training condition were instructed to allocate attention toward positive words to efficiently create positive interpretations (i.e., recruiting attentional control) while they were provided with gaze-contingent feedback on their viewing behavior. Transfer to attention bias and reappraisal success was evaluated using a dot-probe task and an emotion regulation task which were administered before and after the training. The training condition was effective at increasing attentional control and resulted in beneficial effects on the transfer tasks. Analyses supported a serial indirect effect with larger attentional control acquisition in the training condition leading to negative attention bias reduction, in turn predicting greater reappraisal success which reduced negative emotions. Our results indicate that attentional mechanisms influence the use of reappraisal strategies and its impact on negative emotions. The novel attention training highlights the importance of tailored feedback to train attentional control. The findings provide an important step toward personalized delivery of attention training. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Attention training to pleasant stimuli in anxiety.

PubMed

Sass, Sarah M; Evans, Travis C; Xiong, Kue; Mirghassemi, Felicia; Tran, Huy

2017-01-01

Attentional bias for threatening stimuli in anxiety is a common finding in the literature. The present study addressed whether attention training toward pleasant stimuli can reduce anxiety symptoms and induce a processing bias in favor of pleasant information in nonpatients who were selected to score similarly to individuals with generalized anxiety or panic disorder on a measure of worry or physiological arousal, respectively. Participants were randomly assigned to attention training to pleasant (ATP) stimuli or to a placebo control (PC) condition. All participants completed baseline and post-test dot-probe measures of attentional bias while event-related brain potentials were recorded. As expected, worry symptoms decreased in the ATP and not PC condition. ATP was also associated with early evidence (P100 amplitude) of greater attentional prioritization of probes replacing neutral stimuli within threat-neutral word pairs from pre-to-post intervention and later RT evidence of facilitated processing of probes replacing pleasant stimuli within pleasant-threat word pairs at post compared to PC. PC was associated with later evidence (P300 latency) of less efficient evaluation of probes following pleasant stimuli within pleasant-threat word pairs from pre-to-post and later RT evidence of facilitated processing of probes following threat stimuli within pleasant-threat word pairs at post compared to ATP. Results highlight early and later mechanisms of attention processing changes and underscore the potential of pleasant stimuli in optimizing attention-training interventions for anxiety. Published by Elsevier B.V.

Monodisperse Picoliter Droplets for Low-Bias and Contamination-Free Reactions in Single-Cell Whole Genome Amplification

PubMed Central

Maruyama, Toru; Yamagishi, Keisuke; Mori, Tetsushi; Takeyama, Haruko

2015-01-01

Whole genome amplification (WGA) is essential for obtaining genome sequences from single bacterial cells because the quantity of template DNA contained in a single cell is very low. Multiple displacement amplification (MDA), using Phi29 DNA polymerase and random primers, is the most widely used method for single-cell WGA. However, single-cell MDA usually results in uneven genome coverage because of amplification bias, background amplification of contaminating DNA, and formation of chimeras by linking of non-contiguous chromosomal regions. Here, we present a novel MDA method, termed droplet MDA, that minimizes amplification bias and amplification of contaminants by using picoliter-sized droplets for compartmentalized WGA reactions. Extracted DNA fragments from a lysed cell in MDA mixture are divided into 105 droplets (67 pL) within minutes via flow through simple microfluidic channels. Compartmentalized genome fragments can be individually amplified in these droplets without the risk of encounter with reagent-borne or environmental contaminants. Following quality assessment of WGA products from single Escherichia coli cells, we showed that droplet MDA minimized unexpected amplification and improved the percentage of genome recovery from 59% to 89%. Our results demonstrate that microfluidic-generated droplets show potential as an efficient tool for effective amplification of low-input DNA for single-cell genomics and greatly reduce the cost and labor investment required for determination of nearly complete genome sequences of uncultured bacteria from environmental samples. PMID:26389587

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.

Attention and interpretation bias modification treatment for social anxiety disorder: A randomized clinical trial of efficacy and synergy.

PubMed

Naim, Reut; Kivity, Yogev; Bar-Haim, Yair; Huppert, Jonathan D

2018-06-01

Attention bias modification treatment (ABMT) and cognitive bias modification of interpretation (CBM-I) both have demonstrated efficacy in alleviating social anxiety, but how they compare with each other, their combination, and with a combined control condition has not been studied. We examined their relative and combined efficacy compared to control conditions in a randomized controlled trial (RCT). Ninety-five adults diagnosed with social anxiety disorder (SAD), were randomly allocated to 4 groups: ABMT + CBM-I control (hereafter ABMT; n = 23), CBM-I + ABMT control (hereafter CBM-I; n = 24), combined ABMT + CBM-I (n = 23), and combined control (n = 25). Treatment included eight sessions over four weeks. Clinician-rated and self-reported measures of social anxiety symptoms, functional impairment, and threat-related attention and interpretive biases were evaluated at baseline, post-treatment, and 3-month follow-up. ABMT yielded greater symptom reduction as measured by both clinician-ratings (Cohen's ds = 0.57-0.70) and self-reports (ds = 0.70-0.85) compared with the CBM-I, the combined ABMT + CBM-I, and the combined control conditions. Neither of the other conditions demonstrated superior symptom change compared to the control condition. No group differences were found for functioning or cognitive biases measures. Limitations mainly include the mix of active and control treatments applied across the different groups. Therefore, the net effect of each of the treatments by itself could not be clearly tested. Results suggest superiority of ABMT compared to CBM-I and their combination in terms of symptom reduction. Possible interpretations and methodological issues underlying the observed findings are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Top-Down-Driven Grouping Overrules the Central Attentional Bias

ERIC Educational Resources Information Center

Linnell, Karina J.; Humphreys, Glyn W.

2007-01-01

A central bias in spatial selection has been proposed to explain the decreasing search efficiency with increasing target eccentricity that results when distractors can occur closer to fixation than the target (J. M. Wolfe, P. O'Neill, & S. C. Bennett, 1998). The authors found evidence for such a bias using an odd-man-out variant of conjunction…

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.

PubMed

Egbewale, Bolaji E; Lewis, Martyn; Sim, Julius

2014-04-09

Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126,000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.

Assessing the risk of bias in randomized controlled trials in the field of dentistry indexed in the Lilacs (Literatura Latino-Americana e do Caribe em Ciências da Saúde) database.

PubMed

Ferreira, Christiane Alves; Loureiro, Carlos Alfredo Salles; Saconato, Humberto; Atallah, Alvaro Nagib

2011-03-01

Well-conducted randomized controlled trials (RCTs) represent the highest level of evidence when the research question relates to the effect of therapeutic or preventive interventions. However, the degree of control over bias between RCTs presents great variability between studies. For this reason, with the increasing interest in and production of systematic reviews and meta-analyses, it has been necessary to develop methodology supported by empirical evidence, so as to encourage and enhance the production of valid RCTs with low risk of bias. The aim here was to conduct a methodological analysis within the field of dentistry, regarding the risk of bias in open-access RCTs available in the Lilacs (Literatura Latino-Americana e do Caribe em Ciências da Saúde) database. This was a methodology study conducted at Universidade Federal de São Paulo (Unifesp) that assessed the risk of bias in RCTs, using the following dimensions: allocation sequence generation, allocation concealment, blinding, and data on incomplete outcomes. Out of the 4,503 articles classified, only 10 studies (0.22%) were considered to be true RCTs and, of these, only a single study was classified as presenting low risk of bias. The items that the authors of these RCTs most frequently controlled for were blinding and data on incomplete outcomes. The effective presence of bias seriously weakened the reliability of the results from the dental studies evaluated, such that they would be of little use for clinicians and administrators as support for decision-making processes.

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.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

PubMed Central

2014-01-01

Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

A randomized evaluation of a computer-based physician's workstation: design considerations and baseline results.

PubMed Central

Rotman, B. L.; Sullivan, A. N.; McDonald, T.; DeSmedt, P.; Goodnature, D.; Higgins, M.; Suermondt, H. J.; Young, C. Y.; Owens, D. K.

1995-01-01

We are performing a randomized, controlled trial of a Physician's Workstation (PWS), an ambulatory care information system, developed for use in the General Medical Clinic (GMC) of the Palo Alto VA. Goals for the project include selecting appropriate outcome variables and developing a statistically powerful experimental design with a limited number of subjects. As PWS provides real-time drug-ordering advice, we retrospectively examined drug costs and drug-drug interactions in order to select outcome variables sensitive to our short-term intervention as well as to estimate the statistical efficiency of alternative design possibilities. Drug cost data revealed the mean daily cost per physician per patient was 99.3 cents +/- 13.4 cents, with a range from 0.77 cent to 1.37 cents. The rate of major interactions per prescription for each physician was 2.9% +/- 1%, with a range from 1.5% to 4.8%. Based on these baseline analyses, we selected a two-period parallel design for the evaluation, which maximized statistical power while minimizing sources of bias. PMID:8563376

Layers: A molecular surface peeling algorithm and its applications to analyze protein structures

PubMed Central

Karampudi, Naga Bhushana Rao; Bahadur, Ranjit Prasad

2015-01-01

We present an algorithm ‘Layers’ to peel the atoms of proteins as layers. Using Layers we show an efficient way to transform protein structures into 2D pattern, named residue transition pattern (RTP), which is independent of molecular orientations. RTP explains the folding patterns of proteins and hence identification of similarity between proteins is simple and reliable using RTP than with the standard sequence or structure based methods. Moreover, Layers generates a fine-tunable coarse model for the molecular surface by using non-random sampling. The coarse model can be used for shape comparison, protein recognition and ligand design. Additionally, Layers can be used to develop biased initial configuration of molecules for protein folding simulations. We have developed a random forest classifier to predict the RTP of a given polypeptide sequence. Layers is a standalone application; however, it can be merged with other applications to reduce the computational load when working with large datasets of protein structures. Layers is available freely at http://www.csb.iitkgp.ernet.in/applications/mol_layers/main. PMID:26553411

Correcting power and p-value calculations for bias in diffusion tensor imaging.

PubMed

Lauzon, Carolyn B; Landman, Bennett A

2013-07-01

Diffusion tensor imaging (DTI) provides quantitative parametric maps sensitive to tissue microarchitecture (e.g., fractional anisotropy, FA). These maps are estimated through computational processes and subject to random distortions including variance and bias. Traditional statistical procedures commonly used for study planning (including power analyses and p-value/alpha-rate thresholds) specifically model variability, but neglect potential impacts of bias. Herein, we quantitatively investigate the impacts of bias in DTI on hypothesis test properties (power and alpha-rate) using a two-sided hypothesis testing framework. We present theoretical evaluation of bias on hypothesis test properties, evaluate the bias estimation technique SIMEX for DTI hypothesis testing using simulated data, and evaluate the impacts of bias on spatially varying power and alpha rates in an empirical study of 21 subjects. Bias is shown to inflame alpha rates, distort the power curve, and cause significant power loss even in empirical settings where the expected difference in bias between groups is zero. These adverse effects can be attenuated by properly accounting for bias in the calculation of power and p-values. Copyright © 2013 Elsevier Inc. All rights reserved.

Non-random temporary emigration and the robust design: Conditions for bias at the end of a time series: Section VIII

USGS Publications Warehouse

Langtimm, Catherine A.

2008-01-01

Knowing the extent and magnitude of the potential bias can help in making decisions as to what time frame provides the best estimates or the most reliable opportunity to model and test hypotheses about factors affecting survival probability. To assess bias, truncating the capture histories to shorter time frames and reanalyzing the data to compare time-specific estimates may help identify spurious effects. Running simulations that mimic the parameter values and movement conditions in the real situation can provide estimates of standardized bias that can be used to identify those annual estimates that are biased to the point where the 95% confidence intervals are inadequate in describing the uncertainty of the estimates.

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.

Continuous representation of tumor microvessel density and detection of angiogenic hotspots in histological whole-slide images.

PubMed

Kather, Jakob Nikolas; Marx, Alexander; Reyes-Aldasoro, Constantino Carlos; Schad, Lothar R; Zöllner, Frank Gerrit; Weis, Cleo-Aron

2015-08-07

Blood vessels in solid tumors are not randomly distributed, but are clustered in angiogenic hotspots. Tumor microvessel density (MVD) within these hotspots correlates with patient survival and is widely used both in diagnostic routine and in clinical trials. Still, these hotspots are usually subjectively defined. There is no unbiased, continuous and explicit representation of tumor vessel distribution in histological whole slide images. This shortcoming distorts angiogenesis measurements and may account for ambiguous results in the literature. In the present study, we describe and evaluate a new method that eliminates this bias and makes angiogenesis quantification more objective and more efficient. Our approach involves automatic slide scanning, automatic image analysis and spatial statistical analysis. By comparing a continuous MVD function of the actual sample to random point patterns, we introduce an objective criterion for hotspot detection: An angiogenic hotspot is defined as a clustering of blood vessels that is very unlikely to occur randomly. We evaluate the proposed method in N=11 images of human colorectal carcinoma samples and compare the results to a blinded human observer. For the first time, we demonstrate the existence of statistically significant hotspots in tumor images and provide a tool to accurately detect these hotspots.

A comparison of two experimental design approaches in applying conjoint analysis in patient-centered outcomes research: a randomized trial.

PubMed

Kinter, Elizabeth T; Prior, Thomas J; Carswell, Christopher I; Bridges, John F P

2012-01-01

While the application of conjoint analysis and discrete-choice experiments in health are now widely accepted, a healthy debate exists around competing approaches to experimental design. There remains, however, a paucity of experimental evidence comparing competing design approaches and their impact on the application of these methods in patient-centered outcomes research. Our objectives were to directly compare the choice-model parameters and predictions of an orthogonal and a D-efficient experimental design using a randomized trial (i.e., an experiment on experiments) within an application of conjoint analysis studying patient-centered outcomes among outpatients diagnosed with schizophrenia in Germany. Outpatients diagnosed with schizophrenia were surveyed and randomized to receive choice tasks developed using either an orthogonal or a D-efficient experimental design. The choice tasks elicited judgments from the respondents as to which of two patient profiles (varying across seven outcomes and process attributes) was preferable from their own perspective. The results from the two survey designs were analyzed using the multinomial logit model, and the resulting parameter estimates and their robust standard errors were compared across the two arms of the study (i.e., the orthogonal and D-efficient designs). The predictive performances of the two resulting models were also compared by computing their percentage of survey responses classified correctly, and the potential for variation in scale between the two designs of the experiments was tested statistically and explored graphically. The results of the two models were statistically identical. No difference was found using an overall chi-squared test of equality for the seven parameters (p = 0.69) or via uncorrected pairwise comparisons of the parameter estimates (p-values ranged from 0.30 to 0.98). The D-efficient design resulted in directionally smaller standard errors for six of the seven parameters, of which only two were statistically significant, and no differences were found in the observed D-efficiencies of their standard errors (p = 0.62). The D-efficient design resulted in poorer predictive performance, but this was not significant (p = 0.73); there was some evidence that the parameters of the D-efficient design were biased marginally towards the null. While no statistical difference in scale was detected between the two designs (p = 0.74), the D-efficient design had a higher relative scale (1.06). This could be observed when the parameters were explored graphically, as the D-efficient parameters were lower. Our results indicate that orthogonal and D-efficient experimental designs have produced results that are statistically equivalent. This said, we have identified several qualitative findings that speak to the potential differences in these results that may have been statistically identified in a larger sample. While more comparative studies focused on the statistical efficiency of competing design strategies are needed, a more pressing research problem is to document the impact the experimental design has on respondent efficiency.

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

Effect of standardized training on the reliability of the Cochrane risk of bias assessment tool: a study protocol.

PubMed

da Costa, Bruno R; Resta, Nina M; Beckett, Brooke; Israel-Stahre, Nicholas; Diaz, Alison; Johnston, Bradley C; Egger, Matthias; Jüni, Peter; Armijo-Olivo, Susan

2014-12-13

The Cochrane risk of bias (RoB) tool has been widely embraced by the systematic review community, but several studies have reported that its reliability is low. We aim to investigate whether training of raters, including objective and standardized instructions on how to assess risk of bias, can improve the reliability of this tool. We describe the methods that will be used in this investigation and present an intensive standardized training package for risk of bias assessment that could be used by contributors to the Cochrane Collaboration and other reviewers. This is a pilot study. We will first perform a systematic literature review to identify randomized clinical trials (RCTs) that will be used for risk of bias assessment. Using the identified RCTs, we will then do a randomized experiment, where raters will be allocated to two different training schemes: minimal training and intensive standardized training. We will calculate the chance-corrected weighted Kappa with 95% confidence intervals to quantify within- and between-group Kappa agreement for each of the domains of the risk of bias tool. To calculate between-group Kappa agreement, we will use risk of bias assessments from pairs of raters after resolution of disagreements. Between-group Kappa agreement will quantify the agreement between the risk of bias assessment of raters in the training groups and the risk of bias assessment of experienced raters. To compare agreement of raters under different training conditions, we will calculate differences between Kappa values with 95% confidence intervals. This study will investigate whether the reliability of the risk of bias tool can be improved by training raters using standardized instructions for risk of bias assessment. One group of inexperienced raters will receive intensive training on risk of bias assessment and the other will receive minimal training. By including a control group with minimal training, we will attempt to mimic what many review authors commonly have to do, that is-conduct risk of bias assessment in RCTs without much formal training or standardized instructions. If our results indicate that an intense standardized training does improve the reliability of the RoB tool, our study is likely to help improve the quality of risk of bias assessments, which is a central component of evidence synthesis.

The Consequences of Teenage Childbearing: Consistent Estimates When Abortion Makes Miscarriage Nonrandom*

PubMed Central

Ashcraft, Adam; Fernández-Val, Iván; Lang, Kevin

2012-01-01

Miscarriage, even if biologically random, is not socially random. Willingness to abort reduces miscarriage risk. Because abortions are favorably selected among pregnant teens, those miscarrying are less favorably selected than those giving birth or aborting but more favorably selected than those giving birth. Therefore, using miscarriage as an instrument is biased towards a benign view of teen motherhood while OLS on just those giving birth or miscarrying has the opposite bias. We derive a consistent estimator that reduces to a weighted average of OLS and IV when outcomes are independent of abortion timing. Estimated effects are generally adverse but modest. PMID:24443589

Estimating the encounter rate variance in distance sampling

USGS Publications Warehouse

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

Acute effects of intoxication and arousal on approach / avoidance biases toward sexual risk stimuli in heterosexual men

PubMed Central

Simons, Jeffrey S.; Maisto, Stephen A.; Wray, Tyler B.; Emery, Noah N.

2015-01-01

This study tested the effects of alcohol intoxication and physiological arousal on cognitive biases toward erotic stimuli and condoms. Ninety-seven heterosexual men were randomized to 1 of 6 independent conditions in a 2 (high arousal or control) × 3 (alcohol target BAC = 0.08), placebo, or juice control) design and then completed a variant of the Approach Avoidance Task (AAT). The AAT assessed reaction times toward approaching and avoiding erotic stimuli and condoms with a joystick. Consistent with hypotheses, the alcohol condition exhibited an approach bias toward erotic stimuli, whereas the control and placebo groups exhibited an approach bias toward condom stimuli. Similarly, the participants in the high arousal condition exhibited an approach bias toward erotic stimuli and the low arousal control condition exhibited an approach bias toward condoms. The results suggest that acute changes in intoxication and physiological arousal independently foster biased responding towards sexual stimuli and these biases are associated with sexual risk intentions. PMID:25808719

Waveguide-integrated single- and multi-photon detection at telecom wavelengths using superconducting nanowires

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

Ferrari, Simone; Kahl, Oliver; Kovalyuk, Vadim

We investigate single- and multi-photon detection regimes of superconducting nanowire detectors embedded in silicon nitride nanophotonic circuits. At near-infrared wavelengths, simultaneous detection of up to three photons is observed for 120 nm wide nanowires biased far from the critical current, while narrow nanowires below 100 nm provide efficient single photon detection. A theoretical model is proposed to determine the different detection regimes and to calculate the corresponding internal quantum efficiency. The predicted saturation of the internal quantum efficiency in the single photon regime agrees well with plateau behavior observed at high bias currents.

Time-Lag Bias in Trials of Pediatric Antidepressants: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Reyes, Magdalena M.; Panza, Kaitlyn E.; Martin, Andres; Bloch, Michael H.

2011-01-01

Objective: To determine whether there is evidence of a time-lag bias in the publication of pediatric antidepressant trials. Method: We conducted a meta-analysis of published and unpublished randomized placebo-controlled trials of serotonin reuptake inhibitors (SRIs) in subjects less than 18 years of age with major depressive disorder. Our main…

Researching Sex Bias in the Classroom.

ERIC Educational Resources Information Center

Donlan, Dan

This paper outlines five methods of research on sex bias in the classroom: one-time survey, one class/one treatment, two class/two treatment, one class/random assignment to treatment, and analysis of differentiated effect. It shows how each method could be used in attempting to measure the effect of a unit on Norma Klein's "Mom, the Wolfman and…

Where You Come from or Where You Go? Distinguishing between School Quality and the Effectiveness of Teacher Preparation Program Graduates

ERIC Educational Resources Information Center

Mihaly, Kata; McCaffrey, Daniel; Sass, Tim R.; Lockwood, J. R.

2013-01-01

We consider the challenges and implications of controlling for school contextual bias when modeling teacher preparation program effects. Because teachers are not randomly distributed across schools, failing to account for contextual factors in achievement models could bias preparation program estimates. Including school fixed effects controls for…

Effects of a Community Toxic Release on the Psychological Status of Children

ERIC Educational Resources Information Center

Greve, Kevin W.; Bianchini, Kevin J.; Stickle, Timothy R.; Love, Jeffrey M.; Doane, Bridget M.; Thompson, Matthew D.

2007-01-01

This study sought to determine the emotional effects of a major community toxic release on children in the exposed community while controlling for the potential effects of response bias. Controlling for the response bias inherent in litigated contexts is an advance over previous studies of toxic exposure in children. A randomly selected…

Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction.

PubMed

Malkyarenko, Dariya I; Chenevert, Thomas L

2014-12-01

To describe an efficient procedure to empirically characterize gradient nonlinearity and correct for the corresponding apparent diffusion coefficient (ADC) bias on a clinical magnetic resonance imaging (MRI) scanner. Spatial nonlinearity scalars for individual gradient coils along superior and right directions were estimated via diffusion measurements of an isotropicic e-water phantom. Digital nonlinearity model from an independent scanner, described in the literature, was rescaled by system-specific scalars to approximate 3D bias correction maps. Correction efficacy was assessed by comparison to unbiased ADC values measured at isocenter. Empirically estimated nonlinearity scalars were confirmed by geometric distortion measurements of a regular grid phantom. The applied nonlinearity correction for arbitrarily oriented diffusion gradients reduced ADC bias from 20% down to 2% at clinically relevant offsets both for isotropic and anisotropic media. Identical performance was achieved using either corrected diffusion-weighted imaging (DWI) intensities or corrected b-values for each direction in brain and ice-water. Direction-average trace image correction was adequate only for isotropic medium. Empiric scalar adjustment of an independent gradient nonlinearity model adequately described DWI bias for a clinical scanner. Observed efficiency of implemented ADC bias correction quantitatively agreed with previous theoretical predictions and numerical simulations. The described procedure provides an independent benchmark for nonlinearity bias correction of clinical MRI scanners.

Efficient randomization of biological networks while preserving functional characterization of individual nodes.

PubMed

Iorio, Francesco; Bernardo-Faura, Marti; Gobbi, Andrea; Cokelaer, Thomas; Jurman, Giuseppe; Saez-Rodriguez, Julio

2016-12-20

Networks are popular and powerful tools to describe and model biological processes. Many computational methods have been developed to infer biological networks from literature, high-throughput experiments, and combinations of both. Additionally, a wide range of tools has been developed to map experimental data onto reference biological networks, in order to extract meaningful modules. Many of these methods assess results' significance against null distributions of randomized networks. However, these standard unconstrained randomizations do not preserve the functional characterization of the nodes in the reference networks (i.e. their degrees and connection signs), hence including potential biases in the assessment. Building on our previous work about rewiring bipartite networks, we propose a method for rewiring any type of unweighted networks. In particular we formally demonstrate that the problem of rewiring a signed and directed network preserving its functional connectivity (F-rewiring) reduces to the problem of rewiring two induced bipartite networks. Additionally, we reformulate the lower bound to the iterations' number of the switching-algorithm to make it suitable for the F-rewiring of networks of any size. Finally, we present BiRewire3, an open-source Bioconductor package enabling the F-rewiring of any type of unweighted network. We illustrate its application to a case study about the identification of modules from gene expression data mapped on protein interaction networks, and a second one focused on building logic models from more complex signed-directed reference signaling networks and phosphoproteomic data. BiRewire3 it is freely available at https://www.bioconductor.org/packages/BiRewire/ , and it should have a broad application as it allows an efficient and analytically derived statistical assessment of results from any network biology tool.

Reducing obesity prejudice in medical education.

PubMed

Matharu, Kabir; Shapiro, Johanna F; Hammer, Rachel R; Kravitz, R L; Wilson, Machelle D; Fitzgerald, Faith T

2014-01-01

Healthcare worker attitudes toward obese individuals facilitate discrimination and contribute to poor health outcomes. Previous studies have demonstrated medical student bias toward obese individuals, but few have examined effects of the educational environment on these prejudicial beliefs. We sought to determine whether an innovative educational intervention (reading a play about obesity) could diminish obesity prejudice relative to a standard medical lecture. We conducted a randomized, controlled trial enrolling medical students (n = 129) from three universities. Students were assigned to play-reading or a standard lecture. Explicit attitudes and implicit bias toward obese individuals were assessed prior to intervention and after four months. At baseline, students demonstrated moderate explicit and implicit bias toward obese people despite high scores on empathy. Students randomized to the play-reading group had significantly decreased explicit fat bias (P = 0.01) at follow-up, while students in the lecture group showed increased endorsement of a prescriptive model of care at the expense of a patient-centered approach (P = 0.03). There was a significant increase in empathy for those in both the theater (P = 0.007) and lecture group (P = 0.02). The intervention had no significant effect on implicit bias or regard for obesity as a civil rights issue. Dramatic reading may be superior to traditional medical lectures for showcasing patient rights and preferences. The present study demonstrates for the first time that play-reading diminishes conscious obesity bias. Further research should determine whether nontraditional methods of instruction promote improved understanding of and care for obese patients.

Intra-amniotic inflammation and child neurodevelopment: a systematic review protocol.

PubMed

Soucy-Giguère, Laurence; Gasse, Cédric; Giguère, Yves; Demers, Suzanne; Bujold, Emmanuel; Boutin, Amélie

2018-01-22

Intra-amniotic inflammation is associated with adverse pregnancy and neonatal outcomes. However, the impact on child neurodevelopment remains unclear. We aim to assess the effect of intra-amniotic inflammation on neurodevelopmental outcomes in children. The databases MEDLINE, Embase, CINAHL, and Cochrane will be searched from their inception until November 2017. Randomized trials and cohort studies in which inflammatory markers were measured in amniotic fluid collected by amniocentesis and in which infant's neurodevelopment was assessed will be eligible. Two reviewers will independently select eligible studies, assess their risk of bias, and extract data. Results will be compared and a third party will be consulted in case of disagreement. Our primary outcome of interest is child neurodevelopment, assessed with either a validated tool or by revision of medical records for specific diagnosis. Secondary outcomes will include abnormal brain imaging. Relative risks will be pooled and sensitivity analyses will be performed for the indication of amniocentesis, gestational age at amniocentesis, gestational age at delivery, and fetal sex. Risk of bias will be assessed using the Cochrane Collaboration's tool for assessing the risk of bias in randomized trials or an adapted version of the ROBINS-1 for the risk of bias in non-randomized studies. This systematic review will report the current evidence regarding the association between amniotic inflammation and child neurodevelopment, and the modifiers of this association. The review will generate new hypotheses on pathological pathways and will guide future research. PROSPERO 2017 65065.

Antiviral treatment of Bell's palsy based on baseline severity: a systematic review and meta-analysis.

PubMed

Turgeon, Ricky D; Wilby, Kyle J; Ensom, Mary H H

2015-06-01

We conducted a systematic review with meta-analysis to evaluate the efficacy of antiviral agents on complete recovery of Bell's palsy. We searched CENTRAL, Embase, MEDLINE, International Pharmaceutical Abstracts, and sources of unpublished literature to November 1, 2014. Primary and secondary outcomes were complete and satisfactory recovery, respectively. To evaluate statistical heterogeneity, we performed subgroup analysis of baseline severity of Bell's palsy and between-study sensitivity analyses based on risk of allocation and detection bias. The 10 included randomized controlled trials (2419 patients; 807 with severe Bell's palsy at onset) had variable risk of bias, with 9 trials having a high risk of bias in at least 1 domain. Complete recovery was not statistically significantly greater with antiviral use versus no antiviral use in the random-effects meta-analysis of 6 trials (relative risk, 1.06; 95% confidence interval, 0.97-1.16; I(2) = 65%). Conversely, random-effects meta-analysis of 9 trials showed a statistically significant difference in satisfactory recovery (relative risk, 1.10; 95% confidence interval, 1.02-1.18; I(2) = 63%). Response to antiviral agents did not differ visually or statistically between patients with severe symptoms at baseline and those with milder disease (test for interaction, P = .11). Sensitivity analyses did not show a clear effect of bias on outcomes. Antiviral agents are not efficacious in increasing the proportion of patients with Bell's palsy who achieved complete recovery, regardless of baseline symptom severity. Copyright © 2015 Elsevier Inc. All rights reserved.

The role of metformin on vitamin B12 deficiency: a meta-analysis review.

PubMed

Niafar, Mitra; Hai, Faizi; Porhomayon, Jahan; Nader, Nader Djalal

2015-02-01

Metformin is the only biguanide oral hypoglycemic drug, that is used to treat patients with type-2 diabetes mellitus. There are some reports of metformin being associated with decreased serum levels of vitamin B12 (VB12). The objective of this study is to systematically analyze the impact of metformin on the frequency of VB12 deficiency and serum levels of VB12. A search of various databases provided 18 retrospective cohort studies and 11 randomized controlled trials. Pooled estimates of odds ratio with 95% confidence interval using random effect model were conducted. Studies were examined for heterogeneity, publication bias and sensitivity analysis. Separate analysis of randomized control trials (RCTs) including both low-risk and high-risk bias was also conducted. 29 studies were selected with a total of 8,089 patients. 19 studies were rated intermediate or high quality. Primary outcome suggested increased incidence of VB12 deficiency in metformin group (OR = 2.45, 95% CI 1.74-3.44, P < 0.0001.) Heterogeneity was relatively high (I(2) = 53%), with minor publication bias. Secondary outcome suggested lower serum VB12 concentrations in metformin group (Mean difference = -65.8, 95% CI -78.1 to -53.6 pmol/L, P < 0.00001) with high heterogeneity (I(2) = 98%,) and low publication bias. RCTs analysis of low-and high-risk group revealed similar trends. We conclude that metformin treatment is significantly associated with an increase in incidence of VB12 deficiency and reduced serum VB12 levels.

Albumin in Burn Shock Resuscitation: A Meta-Analysis of Controlled Clinical Studies.

PubMed

Navickis, Roberta J; Greenhalgh, David G; Wilkes, Mahlon M

2016-01-01

Critical appraisal of outcomes after burn shock resuscitation with albumin has previously been restricted to small relatively old randomized trials, some with high risk of bias. Extensive recent data from nonrandomized studies assessing the use of albumin can potentially reduce bias and add precision. The objective of this meta-analysis was to determine the effect of burn shock resuscitation with albumin on mortality and morbidity in adult patients. Randomized and nonrandomized controlled clinical studies evaluating mortality and morbidity in adult patients receiving albumin for burn shock resuscitation were identified by multiple methods, including computer database searches and examination of journal contents and reference lists. Extracted data were quantitatively combined by random-effects meta-analysis. Four randomized and four nonrandomized studies with 688 total adult patients were included. Treatment effects did not differ significantly between the included randomized and nonrandomized studies. Albumin infusion during the first 24 hours showed no significant overall effect on mortality. However, significant statistical heterogeneity was present, which could be abolished by excluding two studies at high risk of bias. After those exclusions, albumin infusion was associated with reduced mortality. The pooled odds ratio was 0.34 with a 95% confidence interval of 0.19 to 0.58 (P < .001). Albumin administration was also accompanied by decreased occurrence of compartment syndrome (pooled odds ratio, 0.19; 95% confidence interval, 0.07-0.50; P < .001). This meta-analysis suggests that albumin can improve outcomes of burn shock resuscitation. However, the scope and quality of current evidence are limited, and additional trials are needed.

Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China

PubMed Central

Li, Hao; Dong, Siping

2015-01-01

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making. PMID:26396090

Rethinking the assessment of risk of bias due to selective reporting: a cross-sectional study.

PubMed

Page, Matthew J; Higgins, Julian P T

2016-07-08

Selective reporting is included as a core domain of Cochrane's tool for assessing risk of bias in randomised trials. There has been no evaluation of review authors' use of this domain. We aimed to evaluate assessments of selective reporting in a cross-section of Cochrane reviews and to outline areas for improvement. We obtained data on selective reporting judgements for 8434 studies included in 586 Cochrane reviews published from issue 1-8, 2015. One author classified the reasons for judgements of high risk of selective reporting bias. We randomly selected 100 reviews with at least one trial rated at high risk of outcome non-reporting bias (non-/partial reporting of an outcome on the basis of its results). One author recorded whether the authors of these reviews incorporated the selective reporting assessment when interpreting results. Of the 8434 studies, 1055 (13 %) were rated at high risk of bias on the selective reporting domain. The most common reason was concern about outcome non-reporting bias. Few studies were rated at high risk because of concerns about bias in selection of the reported result (e.g. reporting of only a subset of measurements, analysis methods or subsets of the data that were pre-specified). Review authors often specified in the risk of bias tables the study outcomes that were not reported (84 % of studies) but less frequently specified the outcomes that were partially reported (61 % of studies). At least one study was rated at high risk of outcome non-reporting bias in 31 % of reviews. In the random sample of these reviews, only 30 % incorporated this information when interpreting results, by acknowledging that the synthesis of an outcome was missing data that were not/partially reported. Our audit of user practice in Cochrane reviews suggests that the assessment of selective reporting in the current risk of bias tool does not work well. It is not always clear which outcomes were selectively reported or what the corresponding risk of bias is in the synthesis with missing outcome data. New tools that will make it easier for reviewers to convey this information are being developed.

An investigation of associations between clinicians' ethnic or racial bias and hypertension treatment, medication adherence and blood pressure control.

PubMed

Blair, Irene V; Steiner, John F; Hanratty, Rebecca; Price, David W; Fairclough, Diane L; Daugherty, Stacie L; Bronsert, Michael; Magid, David J; Havranek, Edward P

2014-07-01

Few studies have directly investigated the association of clinicians' implicit (unconscious) bias with health care disparities in clinical settings. To determine if clinicians' implicit ethnic or racial bias is associated with processes and outcomes of treatment for hypertension among black and Latino patients, relative to white patients. Primary care clinicians completed Implicit Association Tests of ethnic and racial bias. Electronic medical records were queried for a stratified, random sample of the clinicians' black, Latino and white patients to assess treatment intensification, adherence and control of hypertension. Multilevel random coefficient models assessed the associations between clinicians' implicit biases and ethnic or racial differences in hypertension care and outcomes. Standard measures of treatment intensification and medication adherence were calculated from pharmacy refills. Hypertension control was assessed by the percentage of time that patients met blood pressure goals recorded during primary care visits. One hundred and thirty-eight primary care clinicians and 4,794 patients with hypertension participated. Black patients received equivalent treatment intensification, but had lower medication adherence and worse hypertension control than white patients; Latino patients received equivalent treatment intensification and had similar hypertension control, but lower medication adherence than white patients. Differences in treatment intensification, medication adherence and hypertension control were unrelated to clinician implicit bias for black patients (P = 0.85, P = 0.06 and P = 0.31, respectively) and for Latino patients (P = 0.55, P = 0.40 and P = 0.79, respectively). An increase in clinician bias from average to strong was associated with a relative change of less than 5 % in all outcomes for black and Latino patients. Implicit bias did not affect clinicians' provision of care to their minority patients, nor did it affect the patients' outcomes. The identification of health care contexts in which bias does not impact outcomes can assist both patients and clinicians in their efforts to build trust and partnership.

Improved variance estimation of classification performance via reduction of bias caused by small sample size.

PubMed

Wickenberg-Bolin, Ulrika; Göransson, Hanna; Fryknäs, Mårten; Gustafsson, Mats G; Isaksson, Anders

2006-03-13

Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm that the classifier is robust with good generalization performance to new examples, or at least that it performs better than random guessing. A suggested alternative is to obtain a confidence interval of the error rate using repeated design and test sets selected from available examples. However, it is known that even in the ideal situation of repeated designs and tests with completely novel samples in each cycle, a small test set size leads to a large bias in the estimate of the true variance between design sets. Therefore different methods for small sample performance estimation such as a recently proposed procedure called Repeated Random Sampling (RSS) is also expected to result in heavily biased estimates, which in turn translates into biased confidence intervals. Here we explore such biases and develop a refined algorithm called Repeated Independent Design and Test (RIDT). Our simulations reveal that repeated designs and tests based on resampling in a fixed bag of samples yield a biased variance estimate. We also demonstrate that it is possible to obtain an improved variance estimate by means of a procedure that explicitly models how this bias depends on the number of samples used for testing. For the special case of repeated designs and tests using new samples for each design and test, we present an exact analytical expression for how the expected value of the bias decreases with the size of the test set. We show that via modeling and subsequent reduction of the small sample bias, it is possible to obtain an improved estimate of the variance of classifier performance between design sets. However, the uncertainty of the variance estimate is large in the simulations performed indicating that the method in its present form cannot be directly applied to small data sets.

Bias field tailored plasmonic nano-electrode for high-power terahertz photonic devices

PubMed Central

Moon, Kiwon; Lee, Il-Min; Shin, Jun-Hwan; Lee, Eui Su; Kim, Namje; Lee, Won-Hui; Ko, Hyunsung; Han, Sang-Pil; Park, Kyung Hyun

2015-01-01

Photoconductive antennas with nano-structured electrodes and which show significantly improved performances have been proposed to satisfy the demand for compact and efficient terahertz (THz) sources. Plasmonic field enhancement was previously considered the dominant mechanism accounting for the improvements in the underlying physics. However, we discovered that the role of plasmonic field enhancement is limited and near-field distribution of bias field should be considered as well. In this paper, we clearly show that the locally enhanced bias field due to the size effect is much more important than the plasmonic enhanced absorption in the nano-structured electrodes for the THz emitters. Consequently, an improved nano-electrode design is presented by tailoring bias field distribution and plasmonic enhancement. Our findings will pave the way for new perspectives in the design and analysis of plasmonic nano-structures for more efficient THz photonic devices. PMID:26347288

Bias field tailored plasmonic nano-electrode for high-power terahertz photonic devices.

PubMed

Moon, Kiwon; Lee, Il-Min; Shin, Jun-Hwan; Lee, Eui Su; Kim, Namje; Lee, Won-Hui; Ko, Hyunsung; Han, Sang-Pil; Park, Kyung Hyun

2015-09-08

Photoconductive antennas with nano-structured electrodes and which show significantly improved performances have been proposed to satisfy the demand for compact and efficient terahertz (THz) sources. Plasmonic field enhancement was previously considered the dominant mechanism accounting for the improvements in the underlying physics. However, we discovered that the role of plasmonic field enhancement is limited and near-field distribution of bias field should be considered as well. In this paper, we clearly show that the locally enhanced bias field due to the size effect is much more important than the plasmonic enhanced absorption in the nano-structured electrodes for the THz emitters. Consequently, an improved nano-electrode design is presented by tailoring bias field distribution and plasmonic enhancement. Our findings will pave the way for new perspectives in the design and analysis of plasmonic nano-structures for more efficient THz photonic devices.

Are attentional bias and memory bias for negative words causally related?

PubMed

Blaut, Agata; Paulewicz, Borysław; Szastok, Marta; Prochwicz, Katarzyna; Koster, Ernst

2013-09-01

In cognitive theories of depression, processing biases are assumed to be partly responsible for the onset and maintenance of mood disorders. Despite a wealth of studies examining the relation between depression and individual biases (at the level of attention, interpretation, and memory), little is known about relationships between different biases. The purpose of the present study was to assess if attentional bias is causally related to memory bias. 71 participants were randomly assigned to a control (n = 37) or attentional training group (n = 34). The attentional manipulation was followed by an explicit, intentional memory task during which novel neutral, negative, and positive words were presented. It was found that individuals with elevated depression score trained to orient away from negative words did not display a memory bias for negative words (adjectives) whereas similar individuals displayed this memory bias in the control condition. Generalization of the findings is limited because of the short study time frame and specific nature of the memory task. These results indicate that altering attentional bias can influence elaborative processing of emotional material and that this bias could be one of the causes of mood congruent memory in depression. Copyright © 2013 Elsevier Ltd. All rights reserved.

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

Test-treatment RCTs are susceptible to bias: a review of the methodological quality of randomized trials that evaluate diagnostic tests.

PubMed

Ferrante di Ruffano, Lavinia; Dinnes, Jacqueline; Sitch, Alice J; Hyde, Chris; Deeks, Jonathan J

2017-02-24

There is a growing recognition for the need to expand our evidence base for the clinical effectiveness of diagnostic tests. Many international bodies are calling for diagnostic randomized controlled trials to provide the most rigorous evidence of impact to patient health. Although these so-called test-treatment RCTs are very challenging to undertake due to their methodological complexity, they have not been subjected to a systematic appraisal of their methodological quality. The extent to which these trials may be producing biased results therefore remains unknown. We set out to address this issue by conducting a methodological review of published test-treatment trials to determine how often they implement adequate methods to limit bias and safeguard the validity of results. We ascertained all test-treatment RCTs published 2004-2007, indexed in CENTRAL, including RCTs which randomized patients to diagnostic tests and measured patient outcomes after treatment. Tests used for screening, monitoring or prognosis were excluded. We assessed adequacy of sequence generation, allocation concealment and intention-to-treat, appropriateness of primary analyses, blinding and reporting of power calculations, and extracted study characteristics including the primary outcome. One hundred three trials compared 105 control with 119 experimental interventions, and reported 150 primary outcomes. Randomization and allocation concealment were adequate in 57 and 37% of trials. Blinding was uncommon (patients 5%, clinicians 4%, outcome assessors 21%), as was an adequate intention-to-treat analysis (29%). Overall 101 of 103 trials (98%) were at risk of bias, as judged using standard Cochrane criteria. Test-treatment trials are particularly susceptible to attrition and inadequate primary analyses, lack of blinding and under-powering. These weaknesses pose much greater methodological and practical challenges to conducting reliable RCT evaluations of test-treatment strategies than standard treatment interventions. We suggest a cautious approach that first examines whether a test-treatment intervention can accommodate the methodological safeguards necessary to minimize bias, and highlight that test-treatment RCTs require different methods to ensure reliability than standard treatment trials. Please see the companion paper to this article: http://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0286-0 .

Establishing Long-Term Efficacy in Chronic Disease: Use of Recursive Partitioning and Propensity Score Adjustment to Estimate Outcome in MS

PubMed Central

Goodin, Douglas S.; Jones, Jason; Li, David; Traboulsee, Anthony; Reder, Anthony T.; Beckmann, Karola; Konieczny, Andreas; Knappertz, Volker

2011-01-01

Context Establishing the long-term benefit of therapy in chronic diseases has been challenging. Long-term studies require non-randomized designs and, thus, are often confounded by biases. For example, although disease-modifying therapy in MS has a convincing benefit on several short-term outcome-measures in randomized trials, its impact on long-term function remains uncertain. Objective Data from the 16-year Long-Term Follow-up study of interferon-beta-1b is used to assess the relationship between drug-exposure and long-term disability in MS patients. Design/Setting To mitigate the bias of outcome-dependent exposure variation in non-randomized long-term studies, drug-exposure was measured as the medication-possession-ratio, adjusted up or down according to multiple different weighting-schemes based on MS severity and MS duration at treatment initiation. A recursive-partitioning algorithm assessed whether exposure (using any weighing scheme) affected long-term outcome. The optimal cut-point that was used to define “high” or “low” exposure-groups was chosen by the algorithm. Subsequent to verification of an exposure-impact that included all predictor variables, the two groups were compared using a weighted propensity-stratified analysis in order to mitigate any treatment-selection bias that may have been present. Finally, multiple sensitivity-analyses were undertaken using different definitions of long-term outcome and different assumptions about the data. Main Outcome Measure Long-Term Disability. Results In these analyses, the same weighting-scheme was consistently selected by the recursive-partitioning algorithm. This scheme reduced (down-weighted) the effectiveness of drug exposure as either disease duration or disability at treatment-onset increased. Applying this scheme and using propensity-stratification to further mitigate bias, high-exposure had a consistently better clinical outcome compared to low-exposure (Cox proportional hazard ratio = 0.30–0.42; p<0.0001). Conclusions Early initiation and sustained use of interferon-beta-1b has a beneficial impact on long-term outcome in MS. Our analysis strategy provides a methodological framework for bias-mitigation in the analysis of non-randomized clinical data. Trial Registration Clinicaltrials.gov NCT00206635 PMID:22140424

Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses

PubMed Central

Hernán, Miguel A.; Sauer, Brian C.; Hernández-Díaz, Sonia; Platt, Robert; Shrier, Ian

2016-01-01

Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research. PMID:27237061

Training the removal of negative information from working memory: A preliminary investigation of a working memory bias modification task.

PubMed

Robinaugh, Donald J; Crane, Margaret E; Enock, Philip M; McNally, Richard J

2016-01-01

Rumination in depressed adults is associated with a bias toward retaining negative information in working memory. We developed a task designed to modify this cognitive bias by having subjects repeatedly practice removing negative words from working memory, thereby enabling them to retain positive and neutral words. To assess the efficacy of this task, we recruited 60 adults who reported elevated repetitive negative thought (RNT) and randomly assigned them to receive a single administration of either the working memory bias modification (WMBM) task or a control task. Subjects in the WMBM condition exhibited greater reduction in proactive interference for negative information than did those in the control condition. These results suggest that the WMBM task reduces biased retention of negative information in working memory and, thus, may be useful in investigating the possible causal role of this cognitive bias in RNT or depression.

Internet-based cognitive bias modification for obsessive compulsive disorder: study protocol for a randomized controlled trial.

PubMed

Williams, Alishia D; Pajak, Rosanna; O'Moore, Kathleen; Andrews, Gavin; Grisham, Jessica R

2014-05-29

Cognitive bias modification (CBM) interventions have demonstrated efficacy in augmenting core biases implicated in psychopathology. The current randomized controlled trial (RCT) will evaluate the efficacy of an internet-delivered positive imagery cognitive bias modification intervention for obsessive compulsive disorder (OCD) when compared to a control condition. Patients meeting diagnostic criteria for a current or lifetime diagnosis of OCD will be recruited via the research arm of a not-for-profit clinical and research unit in Australia. The minimum sample size for each group (alpha set at 0.05, power at .80) was identified as 29, but increased to 35 to allow for 20% attrition. We will measure the impact of CBM on interpretations bias using the OC Bias Measure (The Ambiguous Scenarios Test for OCD ;AST-OCD) and OC-beliefs (The Obsessive Beliefs Questionnaire-TRIP; OBQ-TRIP). Secondary outcome measures include the Dimensional Obsessive-Compulsive Scale (DOCS), the Patient Health Questionnaire (PHQ-9), The Kessler Psychological Distress Scale (K10), and the Word Sentence Association Test for OCD (WSAO). Change in diagnostic status will be indexed using the OCD Mini International Neuropsychiatric Interview (M.I.N.I) Module at baseline and follow-up. Intent-to-treat (ITT) marginal and mixed-effect models using restricted maximum likelihood (REML) estimation will be used to evaluate the primary hypotheses. Stability of bias change will be assessed at 1-month follow-up. A limitation of the online nature of the study is the inability to include a behavioral outcome measure. The trial was registered on 10 October 2013 with the Australian New Zealand Clinical Trials Registry (ACTRN12613001130752).

Systematic overview and critical appraisal of meta-analyses of interventions in intensive care medicine.

PubMed

Koster, T M; Wetterslev, J; Gluud, C; Keus, F; van der Horst, I C C

2018-05-24

Meta-analysed intervention effect estimates are perceived to represent the highest level of evidence. However, such effects and the randomized clinical trials which are included in them need critical appraisal before the effects can be trusted. Critical appraisal of a predefined set of all meta-analyses on interventions in intensive care medicine to assess their quality and assessed the risks of bias in those meta-analyses having the best quality. We conducted a systematic search to select all meta-analyses of randomized clinical trials on interventions used in intensive care medicine. Selected meta-analyses were critically appraised for basic scientific criteria, (1) presence of an available protocol, (2) report of a full search strategy, and (3) use of any bias risk assessment of included trials. All meta-analyses which qualified these criteria were scrutinized by full "Risk of Bias in Systematic Reviews" ROBIS evaluation of 4 domains of risks of bias, and a "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" PRISMA evaluation. We identified 467 meta-analyses. A total of 56 meta-analyses complied with these basic scientific criteria. We scrutinized the risks of bias in the 56 meta-analyses by full ROBIS evaluation and a PRISMA evaluation. Only 4 meta-analyses scored low risk of bias in all the 4 ROBIS domains and 41 meta-analyses reported all 27 items of the PRISMA checklist. In contrast with what might be perceived as the highest level of evidence only 0.9% of all meta-analyses were judged to have overall low risk of bias. © 2018 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

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…

On the Upward Bias of the Dissimilarity Index and Its Corrections

ERIC Educational Resources Information Center

Mazza, Angelo; Punzo, Antonio

2015-01-01

The dissimilarity index of Duncan and Duncan is widely used in a broad range of contexts to assess the overall extent of segregation in the allocation of two groups in two or more units. Its sensitivity to random allocation implies an upward bias with respect to the unknown amount of systematic segregation. In this article, following a multinomial…

Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

2013-01-01

We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…

Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects

ERIC Educational Resources Information Center

Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.

2014-01-01

We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…

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…

Construction and characterization of a normalized cDNA library of Nannochloropsis oculata (Eustigmatophyceae)

NASA Astrophysics Data System (ADS)

Yu, Jianzhong; Ma, Xiaolei; Pan, Kehou; Yang, Guanpin; Yu, Wengong

2010-07-01

We constructed and characterized a normalized cDNA library of Nannochloropsis oculata CS-179, and obtained 905 nonredundant sequences (NRSs) ranging from 431-1 756 bp in length. Among them, 496 were very similar to nonredundant ones in the GenBank ( E ≤1.0e-05), and 349 ESTs had significant hits with the clusters of eukaryotic orthologous groups (KOG). Bases G and/or C at the third position of codons of 14 amino acid residues suggested a strong bias in the conserved domain of 362 NRSs (>60%). We also identified the unigenes encoding phosphorus and nitrogen transporters, suggesting that N. oculata could efficiently transport and metabolize phosphorus and nitrogen, and recognized the unigenes that involved in biosynthesis and storage of both fatty acids and polyunsaturated fatty acids (PUFAs), which will facilitate the demonstration of eicosapentaenoic acid (EPA) biosynthesis pathway of N. oculata. In comparison with the original cDNA library, the normalized library significantly increased the efficiencies of random sequencing and rarely expressed genes discovering, and decreased the frequency of abundant gene sequences.

Consequences of "Minimal" Group Affiliations in Children

ERIC Educational Resources Information Center

Dunham, Yarrow; Baron, Andrew Scott; Carey, Susan

2011-01-01

Three experiments (total N = 140) tested the hypothesis that 5-year-old children's membership in randomly assigned "minimal" groups would be sufficient to induce intergroup bias. Children were randomly assigned to groups and engaged in tasks involving judgments of unfamiliar in-group or out-group children. Despite an absence of information…

Application of Crossover Design for Conducting Rigorous Extension Evaluations

ERIC Educational Resources Information Center

Jayaratne, K. S. U.; Bird, Carolyn L.; McClelland, Jacquelyn W.

2013-01-01

With the increasing demand for accountability of Extension programming, Extension professionals need to apply rigorous evaluation designs. Randomized designs are useful to eliminate selection biases of program participants and to improve the accuracy of evaluation. However, randomized control designs are not practical to apply in Extension program…

Compliance-Effect Correlation Bias in Instrumental Variables Estimators

ERIC Educational Resources Information Center

Reardon, Sean F.

2010-01-01

Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…

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.

Worksite Environmental Interventions for Obesity Prevention and Control: Evidence from Group Randomized Trials.

PubMed

Fernandez, Isabel Diana; Becerra, Adan; Chin, Nancy P

2014-06-01

Worksites provide multiple advantages to prevent and treat obesity and to test environmental interventions to tackle its multiple causal factors. We present a literature review of group-randomized and non-randomized trials that tested worksite environmental, multiple component interventions for obesity prevention and control paying particular attention to the conduct of formative research prior to intervention development. The evidence on environmental interventions on measures of obesity appears to be strong since most of the studies have a low (4/8) and unclear (2/8) risk of bias. Among the studies reviewed whose potential risk of bias was low, the magnitude of the effect was modest and sometimes in the unexpected direction. None of the four studies describing an explicit formative research stage with clear integration of findings into the intervention was able to demonstrate an effect on the main outcome of interest. We present alternative explanation for the findings and recommendations for future research.

Rational group decision making: A random field Ising model at T = 0

NASA Astrophysics Data System (ADS)

Galam, Serge

1997-02-01

A modified version of a finite random field Ising ferromagnetic model in an external magnetic field at zero temperature is presented to describe group decision making. Fields may have a non-zero average. A postulate of minimum inter-individual conflicts is assumed. Interactions then produce a group polarization along one very choice which is however randomly selected. A small external social pressure is shown to have a drastic effect on the polarization. Individual bias related to personal backgrounds, cultural values and past experiences are introduced via quenched local competing fields. They are shown to be instrumental in generating a larger spectrum of collective new choices beyond initial ones. In particular, compromise is found to results from the existence of individual competing bias. Conflict is shown to weaken group polarization. The model yields new psychosociological insights about consensus and compromise in groups.

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 .

Non-equilibrium Green's functions study of discrete dopants variability on an ultra-scaled FinFET

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

Valin, R., E-mail: r.valinferreiro@swansea.ac.uk; Martinez, A., E-mail: a.e.Martinez@swansea.ac.uk; Barker, J. R., E-mail: john.barker@glasgow.ac.uk

In this paper, we study the effect of random discrete dopants on the performance of a 6.6 nm channel length silicon FinFET. The discrete dopants have been distributed randomly in the source/drain region of the device. Due to the small dimensions of the FinFET, a quantum transport formalism based on the non-equilibrium Green's functions has been deployed. The transfer characteristics for several devices that differ in location and number of dopants have been calculated. Our results demonstrate that discrete dopants modify the effective channel length and the height of the source/drain barrier, consequently changing the channel control of the charge. Thismore » effect becomes more significant at high drain bias. As a consequence, there is a strong effect on the variability of the on-current, off-current, sub-threshold slope, and threshold voltage. Finally, we have also calculated the mean and standard deviation of these parameters to quantify their variability. The obtained results show that the variability at high drain bias is 1.75 larger than at low drain bias. However, the variability of the on-current, off-current, and sub-threshold slope remains independent of the drain bias. In addition, we have found that a large source to drain current by tunnelling current occurs at low gate bias.« less

Scanning method as an unbiased simulation technique and its application to the study of self-attracting random walks

NASA Astrophysics Data System (ADS)

Meirovitch, Hagai

1985-12-01

The scanning method proposed by us [J. Phys. A 15, L735 (1982); Macromolecules 18, 563 (1985)] for simulation of polymer chains is further developed and applied, for the first time, to a model with finite interactions. In addition to ``importance sampling,'' we remove the bias introduced by the scanning method with a procedure suggested recently by Schmidt [Phys. Rev. Lett. 51, 2175 (1983)]; this procedure has the advantage of enabling one to estimate the statistical error. We find these two procedures to be equally efficient. The model studied is an N-step random walk on a lattice, in which a random walk i has a statistical weight &, where p<1 is an attractive energy parameter and Mi is the number of distinct sites visited by walk i. This model, which corresponds to a model of random walks moving in a medium with randomly distributed static traps, has been solved analytically for N-->∞ for any dimension d by Donsker and Varadhan (DV) and by others. and lnφ, where φ is the survival probability in the trapping problem, diverge like Nα with α=d/(d+2). Most numerical studies, however, have failed to reach the DV regime in which d/(d+2) becomes a good approximation for α. On the other hand, our results for α (obtained for N<=150) are close to the DV values for p<=0.7 and p<=0.6 for d=2 and 3, respectively. This suggests that the scanning method is more efficient than both the commonly used direct Monte Carlo technique, and the Rosenbluth and Rosenbluth method [J. Chem. Phys. 23, 356 (1954)]. Our results support the conclusion of Havlin et al. [Phys. Rev. Lett. 53, 407 (1984)] that the DV regime exists already for φ<=10-13 for both d=2 and 3. We also find that at the percolation threshold pc the exponents for the end-to-end distance are small, but larger than zero, and that the probability of a walk returning to the origin behaves approximately as N-1/3 for both d=2 and 3.

A procedure for removing the effect of response bias errors from waterfowl hunter questionnaire responses

USGS Publications Warehouse

Atwood, E.L.

1958-01-01

Response bias errors are studied by comparing questionnaire responses from waterfowl hunters using four large public hunting areas with actual hunting data from these areas during two hunting seasons. To the extent that the data permit, the sources of the error in the responses were studied and the contribution of each type to the total error was measured. Response bias errors, including both prestige and memory bias, were found to be very large as compared to non-response and sampling errors. Good fits were obtained with the seasonal kill distribution of the actual hunting data and the negative binomial distribution and a good fit was obtained with the distribution of total season hunting activity and the semi-logarithmic curve. A comparison of the actual seasonal distributions with the questionnaire response distributions revealed that the prestige and memory bias errors are both positive. The comparisons also revealed the tendency for memory bias errors to occur at digit frequencies divisible by five and for prestige bias errors to occur at frequencies which are multiples of the legal daily bag limit. A graphical adjustment of the response distributions was carried out by developing a smooth curve from those frequency classes not included in the predictable biased frequency classes referred to above. Group averages were used in constructing the curve, as suggested by Ezekiel [1950]. The efficiency of the technique described for reducing response bias errors in hunter questionnaire responses on seasonal waterfowl kill is high in large samples. The graphical method is not as efficient in removing response bias errors in hunter questionnaire responses on seasonal hunting activity where an average of 60 percent was removed.

Generalized Redistribute-to-the-Right Algorithm: Application to the Analysis of Censored Cost Data

PubMed Central

CHEN, SHUAI; ZHAO, HONGWEI

2013-01-01

Medical cost estimation is a challenging task when censoring of data is present. Although researchers have proposed methods for estimating mean costs, these are often derived from theory and are not always easy to understand. We provide an alternative method, based on a replace-from-the-right algorithm, for estimating mean costs more efficiently. We show that our estimator is equivalent to an existing one that is based on the inverse probability weighting principle and semiparametric efficiency theory. We also propose an alternative method for estimating the survival function of costs, based on the redistribute-to-the-right algorithm, that was originally used for explaining the Kaplan–Meier estimator. We show that this second proposed estimator is equivalent to a simple weighted survival estimator of costs. Finally, we develop a more efficient survival estimator of costs, using the same redistribute-to-the-right principle. This estimator is naturally monotone, more efficient than some existing survival estimators, and has a quite small bias in many realistic settings. We conduct numerical studies to examine the finite sample property of the survival estimators for costs, and show that our new estimator has small mean squared errors when the sample size is not too large. We apply both existing and new estimators to a data example from a randomized cardiovascular clinical trial. PMID:24403869

Measuring and analyzing the causes of problematic Internet use.

PubMed

Chiang, I-Ping; Su, Yung-Hsiang

2012-11-01

Since Internet surfing became a daily activity, people have changed their behavior. This research analyzes the causes of problematic Internet use through an online survey, where 1,094 samples were collected. Based on the results of structural equation modeling analysis, the following conclusions are reached: First, novelty, security, and efficiency increase users' online trust. Second, information and efficiency enhance users' sharing and anonymity online. Third, greater trust in Internet environments leads to an increase in a user's cognitive bias toward online behavioral responsibility and Internet addiction. Fourth, a user's attitude toward online sharing further increases the cognitive bias toward online copyright. Fifth, a user's attitude toward anonymity increases cognitive bias toward online copyright, online behavioral responsibility, and deepens Internet addiction.

Extreme events and event size fluctuations in biased random walks on networks.

PubMed

Kishore, Vimal; Santhanam, M S; Amritkar, R E

2012-05-01

Random walk on discrete lattice models is important to understand various types of transport processes. The extreme events, defined as exceedences of the flux of walkers above a prescribed threshold, have been studied recently in the context of complex networks. This was motivated by the occurrence of rare events such as traffic jams, floods, and power blackouts which take place on networks. In this work, we study extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology. The walkers preferentially choose to hop toward the hubs or small degree nodes. In this setting, we show that extremely large fluctuations in event sizes are possible on small degree nodes when the walkers are biased toward the hubs. In particular, we obtain the distribution of event sizes on the network. Further, the probability for the occurrence of extreme events on any node in the network depends on its "generalized strength," a measure of the ability of a node to attract walkers. The generalized strength is a function of the degree of the node and that of its nearest neighbors. We obtain analytical and simulation results for the probability of occurrence of extreme events on the nodes of a network using a generalized random walk model. The result reveals that the nodes with a larger value of generalized strength, on average, display lower probability for the occurrence of extreme events compared to the nodes with lower values of generalized strength.

[Methodological controversies in chronic obstructive pulmonary disease therapeutic trials].

PubMed

Suissa, Samy

2009-03-01

Pharmacological treatment of chronic obstructive pulmonary disease (COPD) relies principally on long-acting bronchodilators. Inhaled corticosteroids (ICS) were introduced for COPD two decades ago, despite the fact that no randomized trial had yet assessed their efficacy for this indication. Since then, the numerous randomized trials and meta-analyses performed to justify their use in COPD have been contradictory and controversial. Moreover, observational studies have reported efficacy rates so exceptional that they are almost too good to be true. These studies contain important methodological flaws that produce the appearance of efficacy. The randomized trials infringe the fundamental principle of intention-to-treat analysis, an analysis necessary to prevent important biases. Two other complications are the interruption of treatment at the moment of randomization and the use of a run-in period; in both cases, the withdrawal of treatment can introduce bias. The observational studies reporting phenomenal reductions in mortality with ICS were distorted by "immortal time" bias. Finally, recent data suggest that the effect of ICS/bronchodilator combinations is due mainly to the effect of the long-acting bronchodilator. Given the absence of proof of the efficacy of inhaled corticosteroids in COPD and their associated risks, especially of ocular damage and pneumonia, and particularly among the elderly, as well as the high doses currently prescribed in COPD, it is difficult to recommend their use in this indication. They should be prescribed in COPD for at most a limited population of patients.

The PEDro scale had acceptably high convergent validity, construct validity, and interrater reliability in evaluating methodological quality of pharmaceutical trials.

PubMed

Yamato, Tie Parma; Maher, Chris; Koes, Bart; Moseley, Anne

2017-06-01

The Physiotherapy Evidence Database (PEDro) scale has been widely used to investigate methodological quality in physiotherapy randomized controlled trials; however, its validity has not been tested for pharmaceutical trials. The aim of this study was to investigate the validity and interrater reliability of the PEDro scale for pharmaceutical trials. The reliability was also examined for the Cochrane Back and Neck (CBN) Group risk of bias tool. This is a secondary analysis of data from a previous study. We considered randomized placebo controlled trials evaluating any pain medication for chronic spinal pain or osteoarthritis. Convergent validity was evaluated by correlating the PEDro score with the summary score of the CBN risk of bias tool. The construct validity was tested using a linear regression analysis to determine the degree to which the total PEDro score is associated with treatment effect sizes, journal impact factor, and the summary score for the CBN risk of bias tool. The interrater reliability was estimated using the Prevalence and Bias Adjusted Kappa coefficient and 95% confidence interval (CI) for the PEDro scale and CBN risk of bias tool. Fifty-three trials were included, with 91 treatment effect sizes included in the analyses. The correlation between PEDro scale and CBN risk of bias tool was 0.83 (95% CI 0.76-0.88) after adjusting for reliability, indicating strong convergence. The PEDro score was inversely associated with effect sizes, significantly associated with the summary score for the CBN risk of bias tool, and not associated with the journal impact factor. The interrater reliability for each item of the PEDro scale and CBN risk of bias tool was at least substantial for most items (>0.60). The intraclass correlation coefficient for the PEDro score was 0.80 (95% CI 0.68-0.88), and for the CBN, risk of bias tool was 0.81 (95% CI 0.69-0.88). There was evidence for the convergent and construct validity for the PEDro scale when used to evaluate methodological quality of pharmacological trials. Both risk of bias tools have acceptably high interrater reliability. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of pharmacological and nonpharmacological treatments on brain functional magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment: a critical review.

PubMed

Canu, Elisa; Sarasso, Elisabetta; Filippi, Massimo; Agosta, Federica

2018-02-20

A growing number of pharmacological and nonpharmacological trials have been performed to test the efficacy of approved or experimental treatments in Alzheimer disease (AD) and mild cognitive impairment (MCI). In this context, functional magnetic resonance imaging (fMRI) may be a good candidate to detect brain changes after a short period of treatment. This critical review aimed to identify and discuss the available studies that have tested the efficacy of pharmacological and nonpharmacological treatments in AD and MCI cases using task-based or resting-state fMRI measures as primary outcomes. A PubMed-based literature search was performed with the use of the three macro-areas: 'disease', 'type of MRI', and 'type of treatment'. Each contribution was individually reviewed according to the Cochrane Collaboration's tool for assessing risk of bias. Study limitations were systematically detected and critically discussed. We selected 34 pharmacological and 13 nonpharmacological articles. According to the Cochrane Collaboration's tool for assessing risk of bias, 40% of these studies were randomized but only a few described clearly the randomization procedure, 36% declared the blindness of participants and personnel, and only 21% reported the blindness of outcome assessment. In addition, 28% of the studies presented more than 20% drop-outs at short- and/or long-term assessments. Additional common shortcomings of the reviewed works were related to study design, patient selection, sample size, choice of outcome measures, management of drop-out cases, and fMRI methods. There is an urgent need to obtain efficient treatments for AD and MCI. fMRI is powerful enough to detect even subtle changes over a short period of treatment; however, the soundness of methods should be improved to enable meaningful data interpretation.

Safety and Efficacy of Catheter Direct Thrombolysis in Management of Acute Iliofemoral Deep Vein Thrombosis: A Systematic Review

PubMed Central

Elbasty, Ahmed; Metcalf, James

2017-01-01

Purpose Catheter direct thrombolysis (CDT) has been shown to be an effective treatment for deep venous thrombosis. The objective of the review is to improve safety and efficacy of the CDT by using ward based protocol, better able to predict complications and treatment outcome through monitoring of haemostatic parameters and clinical observation during thrombolysis procedure. Materials and Methods MEDLINE, EMBASE, CENTRAL and Web of Science were searched for all articles on deep venous thrombosis, thrombolysis and correlations of clinical events (bleeding, successful thrombolysis) during thrombolysis with hemostatic parameters to March 2016. The risk of bias in included studies was assessed by Cochrane Collaboration’s tool and Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions. Results Twenty-four studies were included in the review and we found that improving safety and efficacy of CDT by using ward based protocol depending on eight factors; strict patient selection criteria, types of fibrinolytic drugs, mode of fibrinolytic drug injection, biochemical markers monitoring (fibrinogen, D-dimer, activated partial thromboplastin time, plasminogen activator inhibitor-1), timing of intervention, usage of intermittent pneumatic calf, ward monitoring and thrombolysis imaging assessment (intravascular ultrasound). These factors may help to improve safety and efficacy by reducing total thrombolytic drug dosage and at the same time ensure successful lysis. There is a marked lack of randomized controlled trials discussing the safety and efficacy of catheter direct thrombolysis. Conclusion CDT can be performed safely and efficiently in clinical ward, providing that careful nursing, biochemical monitoring, proper selection and mode of infusion of fibrinolytic drugs, usage of Intermittent pneumatic calf and adequate thrombolysis imaging assessment are ensured. PMID:29354622

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Efficacy and Safety of SGLT2 Inhibitors in Patients with Type 1 Diabetes: A Meta-analysis of Randomized Controlled Trials.

PubMed

Yang, Yingying; Pan, Hui; Wang, Bo; Chen, Shi; Zhu, Huijuan

2017-04-10

Objective To assess the efficiency and safety of a novel sodium-glucose co-transporter 2 (SGLT2) inhibitor-SGLT2 inhibitors, in combination with insulin for type 1 diabetes mellitus (T1DM). Methods We searched Medline, Embase, and the Cochrane Collaboration Library to identify the eligible studies published between January 2010 and July 2016 without restriction of language. The Food and Drug Administration (FDA) data and ClinicalTrials (http://www.clinicaltrials.gov) were also searched. The included studies met the following criteria: randomized controlled trials; T1DM patients aged between 18 and 65 years old; patients were treated with insulin plus SGLT2 inhibitors for more than 2 weeks; patients' glycosylated hemoglobin (HbA1c) levels were between 7% and 12%. The SGLT2 inhibitors group was treated with SGLT2 inhibitors plus insulin, and the placebo group received placebo plus insulin treatment. The outcomes should include one of the following items: fasting blood glucose, HbA1c, glycosuria, or adverse effects. Data were analyzed by two physicians independently. The risk of bias was evaluated by using the Cochrane Collaboration's Risk of Bias tool and heterogeneity among studies was assessed using Chi-square test. Random effect model was used to analyze the treatment effects with Revman 5.3.Results Three trials including 178 patients were enrolled. As compared to the placebo group, SGLT2 inhibitor absolutely decreased fasting blood glucose [mean differences (MD) -2.47 mmol/L, 95% confidence interval (CI) -3.65 to -1.28, P<0.001] and insulin dosage (standardized MD -0.75 U, 95%CI -1.17 to -0.33, P<0.001). SGLT2 inhibitors could also increase the excretion of urine glucose (MD 131.09 g/24 h, 95%CI 91.79 to 170.39, P<0.001). There were no significant differences in the incidences of hyperglycemia [odds ratio (OR) 1.82, 95%CI 0.63 to 5.29, P=0.27], urinary tract infection (OR 0.95, 95%CI 0.19 to 4.85, P=0.95), genital tract infection (OR 0.27, 95%CI 0.01 to 7.19, P=0.43), and diabetic ketoacidosis (OR 6.03, 95%CI 0.27 to 135.99, P=0.26) between the two groups.Conclusion SGLT2 inhibitors combined with insulin might be an efficient and safe treatment modality for T1DM patients.

Cancerous tumor: the high frequency of a rare event.

PubMed

Galam, S; Radomski, J P

2001-05-01

A simple model for cancer growth is presented using cellular automata. Cells diffuse randomly on a two-dimensional square lattice. Individual cells can turn cancerous at a very low rate. During each diffusive step, local fights may occur between healthy and cancerous cells. Associated outcomes depend on some biased local rules, which are independent of the overall cancerous cell density. The models unique ingredients are the frequency of local fights and the bias amplitude. While each isolated cancerous cell is eventually destroyed, an initial two-cell tumor cluster is found to have a nonzero probabilty to spread over the whole system. The associated phase diagram for survival or death is obtained as a function of both the rate of fight and the bias distribution. Within the model, although the occurrence of a killing cluster is a very rare event, it turns out to happen almost systematically over long periods of time, e.g., on the order of an adults life span. Thus, after some age, survival from tumorous cancer becomes random.

A Multiphase Design Strategy for Dealing with Participation Bias

PubMed Central

Haneuse, S.; Chen, J.

2012-01-01

Summary A recently funded study of the impact of oral contraceptive use on the risk of bone fracture employed the randomized recruitment scheme of Weinberg and Wacholder (1990, Biometrics 46, 963–975). One potential complication in the bone fracture study is the potential for differential response rates between cases and controls; participation rates in previous, related studies have been around 70%. Although data from randomized recruitment schemes may be analyzed within the two-phase study framework, ignoring potential differential participation may lead to biased estimates of association. To overcome this, we build on the two-phase framework and propose an extension by introducing an additional stage of data collection aimed specifically at addressing potential differential participation. Four estimators that correct for both sampling and participation bias are proposed; two are general purpose and two are for the special case where covariates underlying the participation mechanism are discrete. Because the fracture study is ongoing, we illustrate the methods using infant mortality data from North Carolina. PMID:20377576

Exploring the repetition bias in voluntary task switching.

PubMed

Mittelstädt, Victor; Dignath, David; Schmidt-Ott, Magdalena; Kiesel, Andrea

2018-01-01

In the voluntary task-switching paradigm, participants are required to randomly select tasks. We reasoned that the consistent finding of a repetition bias (i.e., participants repeat tasks more often than expected by chance) reflects reasonable adaptive task selection behavior to balance the goal of random task selection with the goals to minimize the time and effort for task performance. We conducted two experiments in which participants were provided with variable amount of preview for the non-chosen task stimuli (i.e., potential switch stimuli). We assumed that switch stimuli would initiate some pre-processing resulting in improved performance in switch trials. Results showed that reduced switch costs due to extra-preview in advance of each trial were accompanied by more task switches. This finding is in line with the characteristics of rational adaptive behavior. However, participants were not biased to switch tasks more often than chance despite large switch benefits. We suggest that participants might avoid effortful additional control processes that modulate the effects of preview on task performance and task choice.

Do health care institutions value research? A mixed methods study of barriers and facilitators to methodological rigor in pediatric randomized trials.

PubMed

Hamm, Michele P; Scott, Shannon D; Klassen, Terry P; Moher, David; Hartling, Lisa

2012-10-18

Pediatric randomized controlled trials (RCTs) are susceptible to a high risk of bias. We examined the barriers and facilitators that pediatric trialists face in the design and conduct of unbiased trials. We used a mixed methods design, with semi-structured interviews building upon the results of a quantitative survey. We surveyed Canadian (n=253) and international (n=600) pediatric trialists regarding their knowledge and awareness of bias and their perceived barriers and facilitators in conducting clinical trials. We then interviewed 13 participants from different subspecialties and geographic locations to gain a more detailed description of how their experiences and attitudes towards research interacted with trial design and conduct. The survey response rate was 23.0% (186/807). 68.1% of respondents agreed that bias is a problem in pediatric RCTs and 72.0% felt that there is sufficient evidence to support changing some aspects of how trials are conducted. Knowledge related to bias was variable, with inconsistent awareness of study design features that may introduce bias into a study. Interview participants highlighted a lack of formal training in research methods, a negative research culture, and the pragmatics of trial conduct as barriers. Facilitators included contact with knowledgeable and supportive colleagues and infrastructure for research. A lack of awareness of bias and negative attitudes towards research present significant barriers in terms of conducting methodologically rigorous pediatric RCTs. Knowledge translation efforts must focus on these issues to ensure the relevance and validity of trial results.

An adaptive multi-level simulation algorithm for stochastic biological systems

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

Lester, C., E-mail: lesterc@maths.ox.ac.uk; Giles, M. B.; Baker, R. E.

2015-01-14

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Montemore » Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the efficiency of our method using a number of examples.« less

Environmental risk factors and Parkinson's disease: An umbrella review of meta-analyses.

PubMed

Bellou, Vanesa; Belbasis, Lazaros; Tzoulaki, Ioanna; Evangelou, Evangelos; Ioannidis, John P A

2016-02-01

Parkinson's disease is a neurological disorder with complex pathogenesis implicating both environmental and genetic factors. We aimed to summarise the environmental risk factors that have been studied for potential association with Parkinson's disease, assess the presence of diverse biases, and identify the risk factors with the strongest support. We searched PubMed from inception to September 18, 2015, to identify systematic reviews and meta-analyses of observational studies that examined associations between environmental factors and Parkinson's disease. For each meta-analysis we estimated the summary effect size by random-effects and fixed-effects models, the 95% confidence interval and the 95% prediction interval. We estimated the between-study heterogeneity expressed by I(2), evidence of small-study effects and evidence of excess significance bias. Overall, 75 unique meta-analyses on different risk factors for Parkinson's disease were examined, covering diverse biomarkers, dietary factors, drugs, medical history or comorbid diseases, exposure to toxic environmental agents and habits. 21 of 75 meta-analyses had results that were significant at p < 0.001 by random-effects. Evidence for an association was convincing (more than 1000 cases, p < 10(-6) by random-effects, not large heterogeneity, 95% prediction interval excluding the null value and absence of hints for small-study effects and excess significance bias) for constipation, and physical activity. Many environmental factors have substantial evidence of association with Parkinson's disease, but several, perhaps most, of them may reflect reverse causation, residual confounding, information bias, sponsor conflicts or other caveats. Copyright © 2016. Published by Elsevier Ltd.

The comprehensive summary of surgical versus non-surgical treatment for obesity: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Cheng, Ji; Gao, Jinbo; Shuai, Xiaoming; Wang, Guobin; Tao, Kaixiong

2016-06-28

Bariatric surgery has emerged as a competitive strategy for obese patients. However, its comparative efficacy against non-surgical treatments remains ill-defined, especially among nonseverely obese crowds. Therefore, we implemented a systematic review and meta-analysis in order for an academic addition to current literatures. Literatures were retrieved from databases of PubMed, Web of Science, EMBASE and Cochrane Library. Randomized trials comparing surgical with non-surgical therapies for obesity were included. A Revised Jadad's Scale and Risk of Bias Summary were employed for methodological assessment. Subgroups analysis, sensitivity analysis and publication bias assessment were respectively performed in order to find out the source of heterogeneity, detect the outcome stability and potential publication bias. 25 randomized trials were eligibly included, totally comprising of 1194 participants. Both groups displayed well comparability concerning baseline parameters (P > 0.05). The pooled results of primary endpoints (weight loss and diabetic remission) revealed a significant advantage among surgical patients rather than those receiving non-surgical treatments (P < 0.05). Furthermore, except for certain cardiovascular indicators, bariatric surgery was superior to conventional arms in terms of metabolic secondary parameters (P < 0.05). Additionally, the pooled outcomes were confirmed to be stable by sensitivity analysis. Although Egger's test (P < 0.01) and Begg's test (P<0.05) had reported the presence of publication bias among included studies, "Trim-and-Fill" method verified that the pooled outcomes remained stable. Bariatric surgery is a better therapeutic option for weight loss, irrespective of follow-up duration, surgical techniques and obesity levels.

Simulation-Based Abdominal Ultrasound Training - A Systematic Review.

PubMed

Østergaard, M L; Ewertsen, C; Konge, L; Albrecht-Beste, E; Bachmann Nielsen, M

2016-06-01

The aim is to provide a complete overview of the different simulation-based training options for abdominal ultrasound and to explore the evidence of their effect. This systematic review was performed according to the PRISMA guidelines and Medline, Embase, Web of Science, and the Cochrane Library was searched. Articles were divided into three categories based on study design (randomized controlled trials, before-and-after studies and descriptive studies) and assessed for level of evidence using the Oxford Centre for Evidence Based Medicine (OCEBM) system and for bias using the Cochrane Collaboration risk of bias assessment tool. Seventeen studies were included in the analysis: four randomized controlled trials, eight before-and-after studies with pre- and post-test evaluations, and five descriptive studies. No studies scored the highest level of evidence, and 14 had the lowest level. Bias was high for 11 studies, low for four, and unclear for two. No studies used a test with established evidence of validity or examined the correlation between obtained skills on the simulators and real-life clinical skills. Only one study used blinded assessors. The included studies were heterogeneous in the choice of simulator, study design, participants, and outcome measures, and the level of evidence for effect was inadequate. In all studies simulation training was equally or more beneficial than other instructions or no instructions. Study designs had significant built-in bias and confounding issues; therefore, further research should be based on randomized controlled trials using tests with validity evidence and blinded assessors. © Georg Thieme Verlag KG Stuttgart · New York.

Detection of mastitis in dairy cattle by use of mixture models for repeated somatic cell scores: a Bayesian approach via Gibbs sampling.

PubMed

Odegård, J; Jensen, J; Madsen, P; Gianola, D; Klemetsdal, G; Heringstad, B

2003-11-01

The distribution of somatic cell scores could be regarded as a mixture of at least two components depending on a cow's udder health status. A heteroscedastic two-component Bayesian normal mixture model with random effects was developed and implemented via Gibbs sampling. The model was evaluated using datasets consisting of simulated somatic cell score records. Somatic cell score was simulated as a mixture representing two alternative udder health statuses ("healthy" or "diseased"). Animals were assigned randomly to the two components according to the probability of group membership (Pm). Random effects (additive genetic and permanent environment), when included, had identical distributions across mixture components. Posterior probabilities of putative mastitis were estimated for all observations, and model adequacy was evaluated using measures of sensitivity, specificity, and posterior probability of misclassification. Fitting different residual variances in the two mixture components caused some bias in estimation of parameters. When the components were difficult to disentangle, so were their residual variances, causing bias in estimation of Pm and of location parameters of the two underlying distributions. When all variance components were identical across mixture components, the mixture model analyses returned parameter estimates essentially without bias and with a high degree of precision. Including random effects in the model increased the probability of correct classification substantially. No sizable differences in probability of correct classification were found between models in which a single cow effect (ignoring relationships) was fitted and models where this effect was split into genetic and permanent environmental components, utilizing relationship information. When genetic and permanent environmental effects were fitted, the between-replicate variance of estimates of posterior means was smaller because the model accounted for random genetic drift.

Theory-based self-management educational interventions on patients with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials.

PubMed

Zhao, Fang-Fang; Suhonen, Riitta; Koskinen, Sanna; Leino-Kilpi, Helena

2017-04-01

To synthesize the effects of theory-based self-management educational interventions on patients with type 2 diabetes (T2DM) in randomized controlled trials. Type 2 diabetes is a common chronic disease causing complications that put a heavy burden on society and reduce the quality of life of patients. Good self-management of diabetes can prevent complications and improve the quality of life of T2DM patients. Systematic review with meta-analysis of randomized controlled trials following Cochrane methods. A literature search was carried out in the MEDLINE, EMBASE, CINAHL, PSYCINFO, and Web of Science databases (1980-April 2015). The risk of bias of these eligible studies was assessed independently by two authors using the Cochrane Collaboration's tool. The Publication bias of the main outcomes was examined. Statistical heterogeneity and random-effects model were used for meta-analysis. Twenty studies with 5802 participants met the inclusion criteria. The interventions in the studies were based on one or more theories which mostly belong to mid-range theories. The pooled main outcomes by random-effects model showed significant improvements in HbA1c, self-efficacy, and diabetes knowledge, but not in BMI. As for quality of life, no conclusions can be drawn as the pooled outcome became the opposite with reduced heterogeneity after one study was excluded. No significant publication bias was found in the main outcomes. To get theory-based interventions to produce more effects, the role of patients should be more involved and stronger and the education team should be trained beyond the primary preparation for the self-management education program. © 2016 John Wiley & Sons Ltd.

Language of publication restrictions in systematic reviews gave different results depending on whether the intervention was conventional or complementary.

PubMed

Pham, Ba'; Klassen, Terry P; Lawson, Margaret L; Moher, David

2005-08-01

To assess whether language of publication restrictions impact the estimates of an intervention's effectiveness, whether such impact is similar for conventional medicine and complementary medicine interventions, and whether the results are influenced by publication bias and statistical heterogeneity. We set out to examine the extent to which including reports of randomized controlled trials (RCTs) in languages other than English (LOE) influences the results of systematic reviews, using a broad dataset of 42 language-inclusive systematic reviews, involving 662 RCTs, including both conventional medicine (CM) and complementary and alternative medicine (CAM) interventions. For CM interventions, language-restricted systematic reviews, compared with language-inclusive ones, did not introduce biased results, in terms of estimates of intervention effectiveness (random effects ration of odds rations ROR=1.02; 95% CI=0.83-1.26). For CAM interventions, however, language-restricted systematic reviews resulted in a 63% smaller protective effect estimate than language-inclusive reviews (random effects ROR=1.63; 95% CI=1.03-2.60). Language restrictions do not change the results of CM systematic reviews but do substantially alter the results of CAM systematic reviews. These findings are robust even after sensitivity analyses, and do not appear to be influenced by statistical heterogeneity and publication bias.

Composition bias and the origin of ORFan genes

PubMed Central

Yomtovian, Inbal; Teerakulkittipong, Nuttinee; Lee, Byungkook; Moult, John; Unger, Ron

2010-01-01

Motivation: Intriguingly, sequence analysis of genomes reveals that a large number of genes are unique to each organism. The origin of these genes, termed ORFans, is not known. Here, we explore the origin of ORFan genes by defining a simple measure called ‘composition bias’, based on the deviation of the amino acid composition of a given sequence from the average composition of all proteins of a given genome. Results: For a set of 47 prokaryotic genomes, we show that the amino acid composition bias of real proteins, random ‘proteins’ (created by using the nucleotide frequencies of each genome) and ‘proteins’ translated from intergenic regions are distinct. For ORFans, we observed a correlation between their composition bias and their relative evolutionary age. Recent ORFan proteins have compositions more similar to those of random ‘proteins’, while the compositions of more ancient ORFan proteins are more similar to those of the set of all proteins of the organism. This observation is consistent with an evolutionary scenario wherein ORFan genes emerged and underwent a large number of random mutations and selection, eventually adapting to the composition preference of their organism over time. Contact: ron@biocoml.ls.biu.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20231229

Inferring animal densities from tracking data using Markov chains.

PubMed

Whitehead, Hal; Jonsen, Ian D

2013-01-01

The distributions and relative densities of species are keys to ecology. Large amounts of tracking data are being collected on a wide variety of animal species using several methods, especially electronic tags that record location. These tracking data are effectively used for many purposes, but generally provide biased measures of distribution, because the starts of the tracks are not randomly distributed among the locations used by the animals. We introduce a simple Markov-chain method that produces unbiased measures of relative density from tracking data. The density estimates can be over a geographical grid, and/or relative to environmental measures. The method assumes that the tracked animals are a random subset of the population in respect to how they move through the habitat cells, and that the movements of the animals among the habitat cells form a time-homogenous Markov chain. We illustrate the method using simulated data as well as real data on the movements of sperm whales. The simulations illustrate the bias introduced when the initial tracking locations are not randomly distributed, as well as the lack of bias when the Markov method is used. We believe that this method will be important in giving unbiased estimates of density from the growing corpus of animal tracking data.

Dual function conducting polymer diodes

DOEpatents

Heeger, Alan J.; Yu, Gang

1996-01-01

Dual function diodes based on conjugated organic polymer active layers are disclosed. When positively biased the diodes function as light emitters. When negatively biased they are highly efficient photodiodes. Methods of preparation and use of these diodes in displays and input/output devices are also disclosed.

Assessing the quality of humidity measurements from global operational radiosonde sensors

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Soden, Brian; Ferraro, Ralph; Arkin, Phillip; Vömel, Holger

2013-07-01

The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.

Researchers' Perceptions of Statistical Significance Contribute to Bias in Health and Exercise Science

ERIC Educational Resources Information Center

Buchanan, Taylor L.; Lohse, Keith R.

2016-01-01

We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…

Regression Artifacts in Nonequivalent Control Group Designs: An Empirical Investigation of Bias in ANCOVA and Matching Designs.

ERIC Educational Resources Information Center

Vermillion, James E.

The presence of artifactual bias in analysis of covariance (ANCOVA) and in matching nonequivalent control group (NECG) designs was empirically investigated. The data set was obtained from a study of the effects of a television program on children from three day care centers in Mexico in which the subjects had been randomly selected within centers.…

Use of Bayes theorem to correct size-specific sampling bias in growth data.

PubMed

Troynikov, V S

1999-03-01

The bayesian decomposition of posterior distribution was used to develop a likelihood function to correct bias in the estimates of population parameters from data collected randomly with size-specific selectivity. Positive distributions with time as a parameter were used for parametrization of growth data. Numerical illustrations are provided. The alternative applications of the likelihood to estimate selectivity parameters are discussed.

Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

PubMed Central

Bocedi, Greta; Reid, Jane M

2015-01-01

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy-son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual-based models describing the SSS and “sexy-son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry. PMID:25330405

Estimating scaled treatment effects with multiple outcomes.

PubMed

Kennedy, Edward H; Kangovi, Shreya; Mitra, Nandita

2017-01-01

In classical study designs, the aim is often to learn about the effects of a treatment or intervention on a single outcome; in many modern studies, however, data on multiple outcomes are collected and it is of interest to explore effects on multiple outcomes simultaneously. Such designs can be particularly useful in patient-centered research, where different outcomes might be more or less important to different patients. In this paper, we propose scaled effect measures (via potential outcomes) that translate effects on multiple outcomes to a common scale, using mean-variance and median-interquartile range based standardizations. We present efficient, nonparametric, doubly robust methods for estimating these scaled effects (and weighted average summary measures), and for testing the null hypothesis that treatment affects all outcomes equally. We also discuss methods for exploring how treatment effects depend on covariates (i.e., effect modification). In addition to describing efficiency theory for our estimands and the asymptotic behavior of our estimators, we illustrate the methods in a simulation study and a data analysis. Importantly, and in contrast to much of the literature concerning effects on multiple outcomes, our methods are nonparametric and can be used not only in randomized trials to yield increased efficiency, but also in observational studies with high-dimensional covariates to reduce confounding bias.

Increased attention but more efficient disengagement: neuroscientific evidence for defensive processing of threatening health information.

PubMed

Kessels, Loes T E; Ruiter, Robert A C; Jansma, Bernadette M

2010-07-01

Previous studies indicate that people respond defensively to threatening health information, especially when the information challenges self-relevant goals. The authors investigated whether reduced acceptance of self-relevant health risk information is already visible in early attention processes, that is, attention disengagement processes. In a randomized, controlled trial with 29 smoking and nonsmoking students, a variant of Posner's cueing task was used in combination with the high-temporal resolution method of event-related brain potentials (ERPs). Reaction times and P300 ERP. Smokers showed lower P300 amplitudes in response to high- as opposed to low-threat invalid trials when moving their attention to a target in the opposite visual field, indicating more efficient attention disengagement processes. Furthermore, both smokers and nonsmokers showed increased P300 amplitudes in response to the presentation of high- as opposed to low-threat valid trials, indicating threat-induced attention-capturing processes. Reaction time measures did not support the ERP data, indicating that the ERP measure can be extremely informative to measure low-level attention biases in health communication. The findings provide the first neuroscientific support for the hypothesis that threatening health information causes more efficient disengagement among those for whom the health threat is self-relevant. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression.

PubMed

Meng, Yilin; Roux, Benoît

2015-08-11

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression

PubMed Central

2015-01-01

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost. PMID:26574437

Measuring and Benchmarking Technical Efficiency of Public Hospitals in Tianjin, China: A Bootstrap-Data Envelopment Analysis Approach.

PubMed

Li, Hao; Dong, Siping

2015-01-01

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application of this method for benchmarking and inter-organizational learning. It is found that the bias corrected efficiency scores of Bootstrap-DEA differ significantly from those of the traditional Banker, Charnes, and Cooper (BCC) model, which means that Chinese researchers need to update their DEA models for more scientific calculation of hospital efficiency scores. Our research has helped shorten the gap between China and the international world in relative efficiency measurement and improvement of hospitals. It is suggested that Bootstrap-DEA be widely applied into afterward research to measure relative efficiency and productivity of Chinese hospitals so as to better serve for efficiency improvement and related decision making. © The Author(s) 2015.

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.

Effect of study design on the reported effect of cardiac resynchronization therapy (CRT) on quantitative physiological measures: stratified meta-analysis in narrow-QRS heart failure and implications for planning future studies.

PubMed

Jabbour, Richard J; Shun-Shin, Matthew J; Finegold, Judith A; Afzal Sohaib, S M; Cook, Christopher; Nijjer, Sukhjinder S; Whinnett, Zachary I; Manisty, Charlotte H; Brugada, Josep; Francis, Darrel P

2015-01-06

Biventricular pacing (CRT) shows clear benefits in heart failure with wide QRS, but results in narrow QRS have appeared conflicting. We tested the hypothesis that study design might have influenced findings. We identified all reports of CRT-P/D therapy in subjects with narrow QRS reporting effects on continuous physiological variables. Twelve studies (2074 patients) met these criteria. Studies were stratified by presence of bias-resistance steps: the presence of a randomized control arm over a single arm, and blinded outcome measurement. Change in each endpoint was quantified using a standardized effect size (Cohen's d). We conducted separate meta-analyses for each variable in turn, stratified by trial quality. In non-randomized, non-blinded studies, the majority of variables (10 of 12, 83%) showed significant improvement, ranging from a standardized mean effect size of +1.57 (95%CI +0.43 to +2.7) for ejection fraction to +2.87 (+1.78 to +3.95) for NYHA class. In the randomized, non-blinded study, only 3 out of 6 variables (50%) showed improvement. For the randomized blinded studies, 0 out of 9 variables (0%) showed benefit, ranging from -0.04 (-0.31 to +0.22) for ejection fraction to -0.1 (-0.73 to +0.53) for 6-minute walk test. Differences in degrees of resistance to bias, rather than choice of endpoint, explain the variation between studies of CRT in narrow-QRS heart failure addressing physiological variables. When bias-resistance features are implemented, it becomes clear that these patients do not improve in any tested physiological variable. Guidance from studies without careful planning to resist bias may be far less useful than commonly perceived. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Stable room-temperature thallium bromide semiconductor radiation detectors

NASA Astrophysics Data System (ADS)

Datta, A.; Fiala, J.; Becla, P.; Motakef, Shariar

2017-10-01

Thallium bromide (TlBr) is a highly efficient ionic semiconductor with excellent radiation detection properties. However, at room temperature, TlBr devices polarize under an applied electric field. This phenomenon not only degrades the charge collection efficiency of the detectors but also promotes chemical reaction of the metal electrodes with bromine, resulting in an unstable electric field and premature failure of the device. This drawback has been crippling the TlBr semiconductor radiation detector technology over the past few decades. In this exhaustive study, this polarization phenomenon has been counteracted using innovative bias polarity switching schemes. Here the highly mobile Br- species, with an estimated electro-diffusion velocity of 10-8 cm/s, face opposing electro-migration forces during every polarity switch. This minimizes the device polarization and availability of Br- ions near the metal electrode. Our results indicate that it is possible to achieve longer device lifetimes spanning more than 17 000 h (five years of 8 × 7 operation) for planar and pixelated radiation detectors using this technique. On the other hand, at constant bias, 2500 h is the longest reported lifetime with most devices less than 1000 h. After testing several biasing switching schemes, it is concluded that the critical bias switching frequency at an applied bias of 1000 V/cm is about 17 μHz. Using this groundbreaking result, it will now be possible to deploy this highly efficient room temperature semiconductor material for field applications in homeland security, medical imaging, and physics research.

Using Propensity Scores in Quasi-Experimental Designs to Equate Groups

ERIC Educational Resources Information Center

Lane, Forrest C.; Henson, Robin K.

2010-01-01

Education research rarely lends itself to large scale experimental research and true randomization, leaving the researcher to quasi-experimental designs. The problem with quasi-experimental research is that underlying factors may impact group selection and lead to potentially biased results. One way to minimize the impact of non-randomization is…

Randomized Item Response Theory Models

ERIC Educational Resources Information Center

Fox, Jean-Paul

2005-01-01

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…

Performance of Random Effects Model Estimators under Complex Sampling Designs

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

In this article, we consider estimation of parameters of random effects models from samples collected via complex multistage designs. Incorporation of sampling weights is one way to reduce estimation bias due to unequal probabilities of selection. Several weighting methods have been proposed in the literature for estimating the parameters of…

Health indicators: eliminating bias from convenience sampling estimators.

PubMed

Hedt, Bethany L; Pagano, Marcello

2011-02-28

Public health practitioners are often called upon to make inference about a health indicator for a population at large when the sole available information are data gathered from a convenience sample, such as data gathered on visitors to a clinic. These data may be of the highest quality and quite extensive, but the biases inherent in a convenience sample preclude the legitimate use of powerful inferential tools that are usually associated with a random sample. In general, we know nothing about those who do not visit the clinic beyond the fact that they do not visit the clinic. An alternative is to take a random sample of the population. However, we show that this solution would be wasteful if it excluded the use of available information. Hence, we present a simple annealing methodology that combines a relatively small, and presumably far less expensive, random sample with the convenience sample. This allows us to not only take advantage of powerful inferential tools, but also provides more accurate information than that available from just using data from the random sample alone. Copyright © 2011 John Wiley & Sons, Ltd.

Antipersistent dynamics in kinetic models of wealth exchange

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Chatterjee, Arnab; Sen, Parongama

2011-11-01

We investigate the detailed dynamics of gains and losses made by agents in some kinetic models of wealth exchange. An earlier work suggested that a walk in an abstract gain-loss space can be conceived for the agents. For models in which agents do not save, or save with uniform saving propensity, the walk has diffusive behavior. For the case in which the saving propensity λ is distributed randomly (0≤λ<1), the resultant walk showed a ballistic nature (except at a particular value of λ*≈0.47). Here we consider several other features of the walk with random λ. While some macroscopic properties of this walk are comparable to a biased random walk, at microscopic level, there are gross differences. The difference turns out to be due to an antipersistent tendency toward making a gain (loss) immediately after making a loss (gain). This correlation is in fact present in kinetic models without saving or with uniform saving as well, such that the corresponding walks are not identical to ordinary random walks. In the distributed saving case, antipersistence occurs with a simultaneous overall bias.

Beliefs about expectations moderate the influence of expectations on pain perception.

PubMed

Handley, Ian M; Fowler, Stephanie L; Rasinski, Heather M; Helfer, Suzanne G; Geers, Andrew L

2013-03-01

Expectations congruently influence, or bias, pain perception. Recent social psychological research reveals that individuals differ in the extent to which they believe in expectation biases and that individuals who believe in expectation biases may adjust for this bias in their perceptions and reactions. That is, idiosyncratic beliefs about expectations can moderate the influence of expectations on experience. Prior research has not examined whether idiosyncratic beliefs about expectations can alter the degree to which one's expectations influence pain perception. Using a laboratory pain stimulus, we examined the possibility that beliefs about expectation biases alter pain responses following both pain- and placebo-analgesic expectations. Participants' beliefs about expectation biases were measured. Next, participants were randomly assigned to receive either a pain expectation or a placebo-analgesia expectation prior to a cold-pressor task. After the task, participants rated their pain. Beliefs about expectation biases significantly influenced pain reports. Specifically, pain reports were more influenced by provided expectations the less participants believed in expectation biases (i.e., pain expectations resulted in more pain than analgesia expectations). Beliefs about the expectation bias are an important and under-examined predictor of pain and placebo analgesia.

Effect of physician disclosure of specialty bias on patient trust and treatment choice.

PubMed

Sah, Sunita; Fagerlin, Angela; Ubel, Peter

2016-07-05

This paper explores the impact of disclosures of bias on advisees. Disclosure-informing advisees of a potential bias-is a popular solution for managing conflicts of interest. Prior research has focused almost exclusively on disclosures of financial conflicts of interest but little is known about how disclosures of other types of biases could impact advisees. In medicine, for example, physicians often recommend the treatment they specialize in; e.g., surgeons are more likely to recommend surgery than nonsurgeons. In recognition of this bias, some physicians inform patients about their specialty bias when other similarly effective treatment options exist. Using field data (recorded transcripts of surgeon-patient consultations) from Veteran Affairs hospitals and a randomized controlled laboratory experiment, we examine and find that disclosures of specialty bias increase patients' trust and their likelihood of choosing a treatment in accordance with the physicians' specialty. Physicians in the field also increased the strength of their recommendation to have the specialty treatment when they disclosed their bias or discussed the opportunity for the patient to seek a consultation with a physician from another specialty. These findings have important implications for handling advisor bias, shared advisor-advisee decision-making, and disclosure policies.

Internet-based attentional bias modification training as add-on to regular treatment in alcohol and cannabis dependent outpatients: a study protocol of a randomized control trial.

PubMed

Heitmann, Janika; van Hemel-Ruiter, Madelon E; Vermeulen, Karin M; Ostafin, Brian D; MacLeod, Colin; Wiers, Reinout W; DeFuentes-Merillas, Laura; Fledderus, Martine; Markus, Wiebren; de Jong, Peter J

2017-05-23

The automatic tendency to attend to and focus on substance-related cues in the environment (attentional bias), has been found to contribute to the persistence of addiction. Attentional bias modification (ABM) interventions might, therefore, contribute to treatment outcome and the reduction of relapse rates. Based on some promising research findings, we designed a study to test the clinical relevance of ABM as an add-on component of regular intervention for alcohol and cannabis patients. The current protocol describes a study which will investigate the effectiveness and cost-effectiveness of a newly developed home-delivered, multi-session, internet-based ABM (iABM) intervention as an add-on to treatment as usual (TAU). TAU consists of cognitive behavioural therapy-based treatment according to the Dutch guidelines for the treatment of addiction. Participants (N = 213) will be outpatients from specialized addiction care institutions diagnosed with alcohol or cannabis dependency who will be randomly assigned to one of three conditions: TAU + iABM; TAU + placebo condition; TAU-only. Primary outcome measures are substance use, craving, and rates of relapse. Changes in attentional bias will be measured to investigate whether changes in primary outcome measures can be attributed to the modification of attentional bias. Indices of cost-effectiveness and secondary physical and psychological complaints (depression, anxiety, and stress) are assessed as secondary outcome measures. This randomized control trial will be the first to investigate whether a home-delivered, multi-session iABM intervention is (cost-) effective in reducing relapse rates in alcohol and cannabis dependency as an add-on to TAU, compared with an active and a waiting list control group. If proven effective, this ABM intervention could be easily implemented as a home-delivered component of current TAU. Netherlands Trial Register, NTR5497 , registered on 18th September 2015.

Ribavirin for treating Crimean Congo haemorrhagic fever.

PubMed

Johnson, Samuel; Henschke, Nicholas; Maayan, Nicola; Mills, Inga; Buckley, Brian S; Kakourou, Artemisia; Marshall, Rachel

2018-06-05

Crimean Congo haemorrhagic fever (CCHF) is a tick-borne disease that occurs in parts of Asia, Europe and Africa. Since 2000 the infection has caused epidemics in Turkey, Iran, Russia, Uganda and Pakistan. Good-quality general supportive medical care helps reduce mortality. There is uncertainty and controversy about treating CCHF with the antiviral drug ribavirin. To assess the effects of ribavirin for treating people with Crimean Congo haemorrhagic fever. We searched the Cochrane Infectious Diseases Group Specialized Register; the Central Register of Controlled Trials (CENTRAL); MEDLINE (PubMed); Embase (OVID); Science Citation Index-Expanded, Social Sciences Citation index, conference proceedings (Web of Science); and CINAHL (EBSCOHost). We also searched the WHO International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov for trials in progress. We conducted all searches up to 16 October 2017. We also contacted experts in the field and obtained further studies from these sources. We evaluated studies assessing the use of ribavirin in people with suspected or confirmed Crimean Congo haemorrhagic fever. We included randomised control trials (RCTs); non-randomised studies (NRSs) that included more than 10 participants designed as cohort studies with comparators; and case-control studies. Two review authors assessed eligibility, risk of bias, and extracted data. For non-randomized studies we used the ROBINS-I tool to assess risk of bias. The main effects analysis included all studies where we judged the risk of bias to be low, moderate or high. We summarized dichotomous outcomes using risk ratios (RRs) and continuous outcomes using mean differences (MDs), and used meta-analyses where appropriate. We carried out a subsidiary appraisal and analysis of studies with critical risk of bias for the primary outcome, as these are often cited to support using ribavirin. For the main effects analysis, five studies met our inclusion criteria: one RCT with 136 participants and four non-randomized studies with 612 participants. We excluded 18 non-randomized studies with critical risk of bias, where none had attempted to control for confounding.We do not know if ribavirin reduces mortality (1 RCT; RR 1.13, 95% confidence interval (CI) 0.29 to 4.32; 136 participants; very low-certainty evidence; 3 non-randomized studies; RR 0.72, 95% CI 0.41 to 1.28; 549 participants; very low-certainty evidence). We do not know if ribavirin reduces the length of stay in hospital (1 RCT: mean difference (MD) 0.70 days, 95% CI -0.39 to 1.79; 136 participants; and 1 non-randomized study: MD -0.80, 95% CI -2.70 to 1.10; 50 participants; very low-certainty evidence). We do not know if it reduces the risk of patients needing platelet transfusions (1 RCT: RR 1.23, 95% CI 0.77 to 1.96; 136 participants; very low-certainty evidence). For adverse effects (including haemolytic anaemia and a need to discontinue treatment), we do not know whether there is an increased risk with ribavirin in people with CCHF as data are insufficient.We do not know if adding ribavirin to early supportive care improves outcomes. One non-randomized study assessed mortality in people receiving ribavirin and supportive care within four days or less from symptom onset compared to after four days since symptom onset: mortality was lower in the group receiving early supportive care and ribavirin, but it is not possible to distinguish between the effects of ribavirin and early supportive medical care alone.In the subsidiary analysis, 18 studies compared people receiving ribavirin with those not receiving ribavirin. All had a critical risk of bias due to confounding, reflected in the mortality point estimates favouring ribavirin. We do not know if ribavirin is effective for treating Crimean Congo haemorrhagic fever. Non-randomized studies are often cited as evidence of an effect, but the risk of bias in these studies is high.

Fully correcting the meteor speed distribution for radar observing biases

NASA Astrophysics Data System (ADS)

Moorhead, Althea V.; Brown, Peter G.; Campbell-Brown, Margaret D.; Heynen, Denis; Cooke, William J.

2017-09-01

Meteor radars such as the Canadian Meteor Orbit Radar (CMOR) have the ability to detect millions of meteors, making it possible to study the meteoroid environment in great detail. However, meteor radars also suffer from a number of detection biases; these biases must be fully corrected for in order to derive an accurate description of the meteoroid population. We present a bias correction method for patrol radars that accounts for the full form of ionization efficiency and mass distribution. This is an improvement over previous methods such as that of Taylor (1995), which requires power-law distributions for ionization efficiency and a single mass index. We apply this method to the meteor speed distribution observed by CMOR and find a significant enhancement of slow meteors compared to earlier treatments. However, when the data set is severely restricted to include only meteors with very small uncertainties in speed, the fraction of slow meteors is substantially reduced, indicating that speed uncertainties must be carefully handled.

Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.

PubMed

Hernán, Miguel A; Sauer, Brian C; Hernández-Díaz, Sonia; Platt, Robert; Shrier, Ian

2016-11-01

Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research. Copyright © 2016 Elsevier Inc. All rights reserved.

Revisited: A Systematic Review of Therapeutic Hypothermia for Adult Patients Following Traumatic Brain Injury.

PubMed

Watson, Hannah I; Shepherd, Andrew A; Rhodes, Jonathan K J; Andrews, Peter J D

2018-06-01

Therapeutic hypothermia has been of topical interest for many years and with the publication of two international, multicenter randomized controlled trials, the evidence base now needs updating. The aim of this systematic review of randomized controlled trials is to assess the efficacy of therapeutic hypothermia in adult traumatic brain injury focusing on mortality, poor outcomes, and new pneumonia. The following databases were searched from January 1, 2011, to January 26, 2018: Cochrane Central Register of Controlled Trial, MEDLINE, PubMed, and EMBASE. Only foreign articles published in the English language were included. Only articles that were randomized controlled trials investigating adult traumatic brain injury sustained following an acute, closed head injury were included. Two authors independently assessed at each stage. Quality was assessed using the Cochrane Collaboration's tool for assessing the risk of bias. All extracted data were combined using the Mantel-Haenszel estimator for pooled risk ratio with 95% CIs. p value of less than 0.05 was considered statistically significant. All statistical analyses were conducted using RevMan 5 (Cochrane Collaboration, Version 5.3, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). Twenty-two studies with 2,346 patients are included. Randomized controlled trials with a low risk of bias show significantly more mortality in the therapeutic hypothermia group (risk ratio, 1.37; 95% CI, 1.04-1.79; p = 0.02), whereas randomized controlled trials with a high risk of bias show the opposite with a higher mortality in the control group (risk ratio, 0.70; 95% CI, 0.60-0.82; p < 0.00001). Overall, this review is in-keeping with the conclusions published by the most recent randomized controlled trials. High-quality studies show no significant difference in mortality, poor outcomes, or new pneumonia. In addition, this review shows a place for fever control in the management of traumatic brain injury.

Comparative Effectiveness Research in Oncology

PubMed Central

2013-01-01

Although randomized controlled trials represent the gold standard for comparative effective research (CER), a number of additional methods are available when randomized controlled trials are lacking or inconclusive because of the limitations of such trials. In addition to more relevant, efficient, and generalizable trials, there is a need for additional approaches utilizing rigorous methodology while fully recognizing their inherent limitations. CER is an important construct for defining and summarizing evidence on effectiveness and safety and comparing the value of competing strategies so that patients, providers, and policymakers can be offered appropriate recommendations for optimal patient care. Nevertheless, methodological as well as political and social challenges for CER remain. CER requires constant and sophisticated methodological oversight of study design and analysis similar to that required for randomized trials to reduce the potential for bias. At the same time, if appropriately conducted, CER offers an opportunity to identify the most effective and safe approach to patient care. Despite rising and unsustainable increases in health care costs, an even greater challenge to the implementation of CER arises from the social and political environment questioning the very motives and goals of CER. Oncologists and oncology professional societies are uniquely positioned to provide informed clinical and methodological expertise to steer the appropriate application of CER toward critical discussions related to health care costs, cost-effectiveness, and the comparative value of the available options for appropriate care of patients with cancer. PMID:23697601

Perspectives of voltage control for magnetic exchange bias in multiferroic heterostructures

NASA Astrophysics Data System (ADS)

Yang, Q.; Zhou, Z.; Sun, N. X.; Liu, M.

2017-04-01

Exchange bias, as an internal magnetic bias induced by a ferromagnetic-antiferromagnetic exchange coupling, is extremely important in many magnetic applications such as memories, sensors and other devices. Voltage control of exchange bias in multiferroics provides an energy-efficient way to achieve a rapidly 180° deterministic switching of magnetization, which has been considered as a key challenge in realizing next generation of fast, compact and ultra-low power magnetoelectric memories and sensors. Additionally, exchange bias can enhance dynamic magnetoelectric coupling strength in an external-field-free manner. In this paper, we provide a perspective on voltage control of exchange bias in different multiferroic heterostructures. Brief mechanization and related experiments are discussed as well as future trend and challenges that can be overcome by electrically tuning of exchange bias in state-of-the-art magnetoelectric devices.

Free Energy Computations by Minimization of Kullback-Leibler Divergence: An Efficient Adaptive Biasing Potential Method for Sparse Representations

DTIC Science & Technology

2011-10-14

landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and...statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy...experimentally, to characterize global changes as well as investigate relative stabilities. In most applications, a brute- force computation based on

Information filtering via biased random walk on coupled social network.

PubMed

Nie, Da-Cheng; Zhang, Zi-Ke; Dong, Qiang; Sun, Chongjing; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.

Information Filtering via Biased Random Walk on Coupled Social Network

PubMed Central

Dong, Qiang; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods. PMID:25147867

Estimation of reliable range of electron temperature measurements with sets of given optical bandpass filters for KSTAR Thomson scattering system based on synthetic Thomson data

NASA Astrophysics Data System (ADS)

Kim, K.-h.; Oh, T.-s.; Park, K.-r.; Lee, J. H.; Ghim, Y.-c.

2017-11-01

One factor determining the reliability of measurements of electron temperature using a Thomson scattering (TS) system is transmittance of the optical bandpass filters in polychromators. We investigate the system performance as a function of electron temperature to determine reliable range of measurements for a given set of the optical bandpass filters. We show that such a reliability, i.e., both bias and random errors, can be obtained by building a forward model of the KSTAR TS system to generate synthetic TS data with the prescribed electron temperature and density profiles. The prescribed profiles are compared with the estimated ones to quantify both bias and random errors.

Integrating cognitive bias modification into a standard cognitive behavioural treatment package for social phobia: a randomized controlled trial.

PubMed

Rapee, Ronald M; MacLeod, Colin; Carpenter, Leigh; Gaston, Jonathan E; Frei, Jacqueline; Peters, Lorna; Baillie, Andrew J

2013-05-01

The aim of the current study was to integrate recent developments in the retraining of attentional biases towards threat into a standard cognitive behavioural treatment package for social phobia. 134 participants (M age-32.4: 53% female) meeting DSM-IV criteria for social phobia received a 12-week cognitive behavioural treatment program. They were randomly allocated to receive on a daily basis using home practice, either an additional computerised probe procedure designed to train attentional resource allocation away from threat, or a placebo variant of this procedure. Measures included diagnostic severity, social anxiety symptoms, life interference, and depression as well as state anxiety in response to a laboratory social threat. At the end of treatment there were no significant differences between groups in attentional bias towards threat or in treatment response (all p's>0.05). Both groups showed similar and highly significant reductions in diagnostic severity, social anxiety symptoms, depression symptoms, and life interference at post-treatment that was maintained and in most cases increased at 6 month follow-up (uncontrolled effect sizes ranged from d=0.34 to d=1.90). The current results do not indicate that integration of information processing-derived attentional bias modification procedures into standard treatment packages as conducted in this study augments attentional change or enhances treatment efficacy. Further refinement of bias modification techniques, and better methods of integrating them with conventional approaches, may be needed to produce better effects. Copyright © 2013 Elsevier Ltd. All rights reserved.

Measurement of Effective Drift Velocities of Electrons and Holes in Shallow Multiple Quantum Well P-I Modulators

NASA Astrophysics Data System (ADS)

Yang, Ching-Mei

1995-01-01

P-i-n diodes containing multiple quantum wells (MQWs) in the i-region are the building blocks for photonic devices. When we apply electric field across these devices and illuminate it with light, photo-carriers are created in the i-region. These carriers escape from the wells and drift toward the electrodes; thus photo-voltage is created. The rise- and decay-times of photo-voltages are related to the transport of carriers. In this dissertation, we present theoretical and experimental studies on carrier transport mechanisms of three shallow MQW GaAs/Al _{x}Ga_{1-x}As p-i-n diodes (x = 0.02, 0.04, 0.08) at various bias voltages. We start with the description of the sample structures and their package. We then present the characteristics of these samples including their transmission spectra and responsivity. We will demonstrate that the over-all high quality of these samples, including a strong exciton resonant absorption, ~100% internal quantum efficiencies and completely depleted i-region at bias between +0.75 V to -5 V bias. In our theoretical studies, we first discuss the possible carrier sweep-out mechanisms and estimate the response times associated with these mechanisms. Based on our theoretical model, we conclude that only the drift times of carriers and enhanced diffusion times are important for shallow MQW p-i-n diodes: at high bias, the fast drift times of electrons and holes control the rise-times; at low bias, the slow drift times of holes and the enhanced diffusion times control the decay-times. We have performed picosecond time-resolved pump/probe electro-absorption measurements on these samples. We then obtained the drift times, effective drift velocities and effective mobilities of electrons and holes for these devices. We find that the carrier effective drift velocities (especially for holes) seemed insensitive to the Al concentration in the barriers (in the range of x = 2% to 8%), even though the x = 2% sample does show an overall faster response time. We think the slight difference of the rise- and decay-times of these devices may also be affected by random differences between the samples.

Understanding health economic analysis in critical care: insights from recent randomized controlled trials.

PubMed

Sud, Sachin; Cuthbertson, Brian H

2011-10-01

The article reviews the methods of health economic analysis (HEA) in clinical trials of critically ill patients. Emphasis is placed on the usefulness of HEA in the context of positive and 'no effect' studies, with recent examples. The need to control costs and promote effective spending in caring for the critically ill has garnered considerable attention due to the high cost of critical illness. Many clinical trials focus on short-term mortality, ignoring costs and quality of life, and fail to change clinical practice or promote efficient use of resources. Incorporating HEA into clinical trials is a possible solution. Such studies have shown some interventions, although expensive, provide good value, whereas others should be withdrawn from clinical practice. Incorporating HEA into randomized controlled trials (RCTs) requires careful attention to collect all relevant costs. Decision trees, modeling assumptions and methods for collecting costs and measuring outcomes should be planned and published beforehand to minimize bias. Costs and cost-effectiveness are potentially useful outcomes in RCTs of critically ill patients. Future RCTs should incorporate parallel HEA to provide both economic outcomes, which are important to the community, alongside patient-centered outcomes, which are important to individuals.

A New Continuous Rotation IMU Alignment Algorithm Based on Stochastic Modeling for Cost Effective North-Finding Applications

PubMed Central

Li, Yun; Wu, Wenqi; Jiang, Qingan; Wang, Jinling

2016-01-01

Based on stochastic modeling of Coriolis vibration gyros by the Allan variance technique, this paper discusses Angle Random Walk (ARW), Rate Random Walk (RRW) and Markov process gyroscope noises which have significant impacts on the North-finding accuracy. A new continuous rotation alignment algorithm for a Coriolis vibration gyroscope Inertial Measurement Unit (IMU) is proposed in this paper, in which the extended observation equations are used for the Kalman filter to enhance the estimation of gyro drift errors, thus improving the north-finding accuracy. Theoretical and numerical comparisons between the proposed algorithm and the traditional ones are presented. The experimental results show that the new continuous rotation alignment algorithm using the extended observation equations in the Kalman filter is more efficient than the traditional two-position alignment method. Using Coriolis vibration gyros with bias instability of 0.1°/h, a north-finding accuracy of 0.1° (1σ) is achieved by the new continuous rotation alignment algorithm, compared with 0.6° (1σ) north-finding accuracy for the two-position alignment and 1° (1σ) for the fixed-position alignment. PMID:27983585

Estimating the occupancy of spotted owl habitat areas by sampling and adjusting for bias

Treesearch

David L. Azuma; James A. Baldwin; Barry R. Noon

1990-01-01

A basic sampling scheme is proposed to estimate the proportion of sampled units (Spotted Owl Habitat Areas (SOHAs) or randomly sampled 1000-acre polygon areas (RSAs)) occupied by spotted owl pairs. A bias adjustment for the possibility of missing a pair given its presence on a SOHA or RSA is suggested. The sampling scheme is based on a fixed number of visits to a...

Lifestyle interventions targeting body weight changes during the menopause transition: a systematic review.

PubMed

Jull, Janet; Stacey, Dawn; Beach, Sarah; Dumas, Alex; Strychar, Irene; Ufholz, Lee-Anne; Prince, Stephanie; Abdulnour, Joseph; Prud'homme, Denis

2014-01-01

To determine the effectiveness of exercise and/or nutrition interventions and to address body weight changes during the menopause transition. A systematic review of the literature was conducted using electronic databases, grey literature, and hand searching. Two independent researchers screened for studies using experimental designs to evaluate the impact of exercise and/or nutrition interventions on body weight and/or central weight gain performed during the menopausal transition. Studies were quality appraised using Cochrane risk of bias. Included studies were analyzed descriptively. Of 3,564 unique citations screened, 3 studies were eligible (2 randomized controlled trials, and 1 pre/post study). Study quality ranged from low to high risk of bias. One randomized controlled trial with lower risk of bias concluded that participation in an exercise program combined with dietary interventions might mitigate body adiposity increases, which is normally observed during the menopause transition. The other two studies with higher risk of bias suggested that exercise might attenuate weight loss or weight gain and change abdominal adiposity patterns. High quality studies evaluating the effectiveness of interventions targeting body weight changes in women during their menopause transition are needed. Evidence from one higher quality study indicates an effective multifaceted intervention for women to minimize changes in body adiposity.

Is reiki or prayer effective in relieving pain during hospitalization for cesarean? A systematic review and meta-analysis of randomized controlled trials.

PubMed

Ferraz, Guilherme Augusto Rago; Rodrigues, Meline Rosseto Kron; Lima, Silvana Andrea Molina; Lima, Marcelo Aparecido Ferraz; Maia, Gabriela Lopes; Pilan, Carlos Alberto; Omodei, Michelle Sako; Molina, Ana Cláudia; El Dib, Regina; Rudge, Marilza Vieira Cunha

2017-01-01

This systematic review compared reiki and prayer with drug use for relieving pain during hospitalization for cesarean, given that the popularity of integrative medicine and spiritual healing has been increasing. It had the aim of evaluating whether reiki or prayer is effective in relieving pain during cesarean section. Systematic review with meta-analysis conducted at Botucatu Medical School, UNESP, São Paulo, Brazil. The following databases were searched up to March 2016: MEDLINE, Embase, LILACS and CENTRAL. Randomized controlled trials published in English or Portuguese were included in the review. Two reviewers independently screened eligible articles, extracted data and assessed the risk of bias. A GRADE table was produced to evaluate the risk of bias. There was evidence with a high risk of bias showing a statistically significant decrease in pain score through use of reiki and prayer, in relation to the protocol group: mean difference = -1.68; 95% confidence interval: -1.92 to -1.43; P < 0.00001; I2 = 92%. Furthermore, there was no statistically significant difference in heart rate or systolic or diastolic blood pressure. Evidence with a high risk of bias suggested that reiki and prayer meditation might be associated with pain reduction.

Lifestyle Interventions Targeting Body Weight Changes during the Menopause Transition: A Systematic Review

PubMed Central

Jull, Janet; Stacey, Dawn; Beach, Sarah; Dumas, Alex; Strychar, Irene; Ufholz, Lee-Anne; Prince, Stephanie; Abdulnour, Joseph; Prud'homme, Denis

2014-01-01

Objective. To determine the effectiveness of exercise and/or nutrition interventions and to address body weight changes during the menopause transition. Methods. A systematic review of the literature was conducted using electronic databases, grey literature, and hand searching. Two independent researchers screened for studies using experimental designs to evaluate the impact of exercise and/or nutrition interventions on body weight and/or central weight gain performed during the menopausal transition. Studies were quality appraised using Cochrane risk of bias. Included studies were analyzed descriptively. Results. Of 3,564 unique citations screened, 3 studies were eligible (2 randomized controlled trials, and 1 pre/post study). Study quality ranged from low to high risk of bias. One randomized controlled trial with lower risk of bias concluded that participation in an exercise program combined with dietary interventions might mitigate body adiposity increases, which is normally observed during the menopause transition. The other two studies with higher risk of bias suggested that exercise might attenuate weight loss or weight gain and change abdominal adiposity patterns. Conclusions. High quality studies evaluating the effectiveness of interventions targeting body weight changes in women during their menopause transition are needed. Evidence from one higher quality study indicates an effective multifaceted intervention for women to minimize changes in body adiposity. PMID:24971172

Gain degradation and efficiencies of spiral electron multipliers

NASA Technical Reports Server (NTRS)

Judge, R. J. R.; Palmer, D. A.

1973-01-01

The characteristics of spiral electron multipliers as functions of accumulated counts were investigated. The mean gain of the multipliers showed a steady decline from about 100 million when new, to about one million after 100 billion events when biased in a saturation mode. For prolonged use in a space environment, improved life expectancy might be obtained with a varying bias voltage adjusted to maintain the gain comfortably above a given discrimination level. Pulse-height distributions at various stages of the lifetime and variations of efficiency with energy of detected electrons are presented.

Determinants of translation speed are randomly distributed across transcripts resulting in a universal scaling of protein synthesis times

NASA Astrophysics Data System (ADS)

Sharma, Ajeet K.; Ahmed, Nabeel; O'Brien, Edward P.

2018-02-01

Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10 % of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.

Assessing health system interventions: key points when considering the value of randomization

PubMed Central

Schellenberg, Joanna; Todd, Jim

2011-01-01

Abstract Research is needed to help identify interventions that will improve the capacity or functioning of health systems and thereby contribute to achieving global health goals. Well conducted, randomized controlled trials (RCTs), insofar as they reduce bias and confounding, provide the strongest evidence for identifying which interventions delivered directly to individuals are safe and effective. When ethically feasible, they can also help reduce bias and confounding when assessing interventions targeting entire health systems. However, additional challenges emerge when research focuses on interventions that target the multiple units of organization found within health systems. Hence, one cannot complacently assume that randomization can reduce or eliminate bias and confounding to the same degree in every instance. While others have articulated arguments in favour of alternative designs, this paper is intended to help people understand why the potential value afforded by RCTs may be threatened. Specifically, it suggests six points to be borne in mind when exploring the challenges entailed in designing or evaluating RCTs on health system interventions: (i) the number of units available for randomization; (ii) the complexity of the organizational unit under study; (iii) the complexity of the intervention; (iv) the complexity of the cause–effect pathway, (v) contamination; and (vi) outcome heterogeneity. The authors suggest that the latter may be informative and that the reasons behind it should be explored and not ignored. Based on improved understanding of the value and possible limitations of RCTs on health system interventions, the authors show why we need broader platforms of research to complement RCTs. PMID:22271948

A dual-docking microfluidic cell migration assay (D2-Chip) for testing neutrophil chemotaxis and the memory effect.

PubMed

Yang, Ke; Wu, Jiandong; Xu, Guoqing; Xie, Dongxue; Peretz-Soroka, Hagit; Santos, Susy; Alexander, Murray; Zhu, Ling; Zhang, Michael; Liu, Yong; Lin, Francis

2017-04-18

Chemotaxis is a classic mechanism for guiding cell migration and an important topic in both fundamental cell biology and health sciences. Neutrophils are a widely used model to study eukaryotic cell migration and neutrophil chemotaxis itself can lead to protective or harmful immune actions to the body. While much has been learnt from past research about how neutrophils effectively navigate through a chemoattractant gradient, many interesting questions remain unclear. For example, while it is tempting to model neutrophil chemotaxis using the well-established biased random walk theory, the experimental proof was challenged by the cell's highly persistent migrating nature. A special experimental design is required to test the key predictions from the random walk model. Another question that has interested the cell migration community for decades concerns the existence of chemotactic memory and its underlying mechanism. Although chemotactic memory has been suggested in various studies, a clear quantitative experimental demonstration will improve our understanding of the migratory memory effect. Motivated by these questions, we developed a microfluidic cell migration assay (so-called dual-docking chip or D 2 -Chip) that can test both the biased random walk model and the memory effect for neutrophil chemotaxis on a single chip enabled by multi-region gradient generation and dual-region cell alignment. Our results provide experimental support for the biased random walk model and chemotactic memory for neutrophil chemotaxis. Quantitative data analyses provide new insights into neutrophil chemotaxis and memory by making connections to entropic disorder, cell morphology and oscillating migratory response.

Cognitive enhancement treatments for bipolar disorder: A systematic review and methodological recommendations.

PubMed

Miskowiak, Kamilla W; Carvalho, André F; Vieta, Eduard; Kessing, Lars V

2016-10-01

Cognitive dysfunction is an emerging treatment target in bipolar disorder (BD). Several trials have assessed the efficacy of novel pharmacological and psychological treatments on cognition in BD but the findings are contradictory and unclear. A systematic search following the PRISMA guidelines was conducted on PubMed and PsychInfo. Eligible articles reported randomized, controlled or open-label trials investigating pharmacological or psychological treatments targeting cognitive dysfunction in BD. The quality of the identified randomized controlled trials (RCTs) was evaluated with the Cochrane Collaboration's Risk of Bias tool. We identified 19 eligible studies of which 13 were RCTs and six were open-label or non-randomized studies. The findings regarding efficacy on cognition were overall disappointing or preliminary, possibly due to several methodological challenges. For the RCTs, the risk of bias was high in nine cases, unclear in one case and low in three cases. Key reasons for the high risk of bias were lack of details on the randomization process, suboptimal handling of missing data and lack of a priori priority between cognition outcomes. Other challenges were the lack of consensus on whether and how to screen for cognitive impairment and on how to assess efficacy on cognition. In conclusion, methodological problems are likely to impede the success rates of cognition trials in BD. We recommend adherence to the CONSORT guidelines for RCTs, screening for cognitive impairment before inclusion of trial participants and selection of one primary cognition outcome. Future implementation of a 'neurocircuitry-based' biomarker model to evaluate neural target engagement is warranted. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images

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

Reiser, I; Lu, Z

2014-06-01

Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions includedmore » two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.« less

Continual training of attentional bias in social anxiety.

PubMed

Li, Songwei; Tan, Jieqing; Qian, Mingyi; Liu, Xinghua

2008-08-01

Using the dot-probe paradigm, it has been shown that high social anxiety is associated with an attentional bias toward negative information. In the present study, individuals with high social anxiety were divided into two groups randomly. One group was the attentional bias training group (Group T), and the other was the control group (Group C). For Group T, 7 days' continuous training of attentional bias was conducted using the dot-probe paradigm to make socially anxious individuals focus more on positive face pictures. The results showed that the training was effective in changing attentional bias in Group T. Scores of the Social Interaction Anxiety Scale (SIAS) in Group T were reduced compared to Group C, while the scores of Social Phobia Scale (SPS) and scores of Negative Evaluation Scale (FNE) showed no difference between the two groups, which suggested a limited reduction of social anxiety.

Terror mismanagement: evidence that mortality salience exacerbates attentional bias in social anxiety.

PubMed

Finch, Emma C; Iverach, Lisa; Menzies, Ross G; Jones, Mark

2016-11-01

Death anxiety is a basic fear underlying a range of psychological conditions, and has been found to increase avoidance in social anxiety. Given that attentional bias is a core feature of social anxiety, the aim of the present study was to examine the impact of mortality salience (MS) on attentional bias in social anxiety. Participants were 36 socially anxious and 37 non-socially anxious individuals, randomly allocated to a MS or control condition. An eye-tracking procedure assessed initial bias towards, and late-stage avoidance of, socially threatening facial expressions. As predicted, socially anxious participants in the MS condition demonstrated significantly more initial bias to social threat than non-socially anxious participants in the MS condition and socially anxious participants in the control condition. However, this effect was not found for late-stage avoidance of social threat. These findings suggest that reminders of death may heighten initial vigilance towards social threat.

Terror mismanagement: evidence that mortality salience exacerbates attentional bias in social anxiety

PubMed Central

Finch, Emma C.; Iverach, Lisa; Menzies, Ross G.; Jones, Mark

2016-01-01

ABSTRACT Death anxiety is a basic fear underlying a range of psychological conditions, and has been found to increase avoidance in social anxiety. Given that attentional bias is a core feature of social anxiety, the aim of the present study was to examine the impact of mortality salience (MS) on attentional bias in social anxiety. Participants were 36 socially anxious and 37 non-socially anxious individuals, randomly allocated to a MS or control condition. An eye-tracking procedure assessed initial bias towards, and late-stage avoidance of, socially threatening facial expressions. As predicted, socially anxious participants in the MS condition demonstrated significantly more initial bias to social threat than non-socially anxious participants in the MS condition and socially anxious participants in the control condition. However, this effect was not found for late-stage avoidance of social threat. These findings suggest that reminders of death may heighten initial vigilance towards social threat. PMID:26211552

The self-attribution bias and paranormal beliefs.

PubMed

van Elk, Michiel

2017-03-01

The present study investigated the relation between paranormal beliefs, illusory control and the self-attribution bias, i.e., the motivated tendency to attribute positive outcomes to oneself while negative outcomes are externalized. Visitors of a psychic fair played a card guessing game and indicated their perceived control over randomly selected cards as a function of the congruency and valence of the card. A stronger self-attribution bias was observed for paranormal believers compared to skeptics and this bias was specifically related to traditional religious beliefs and belief in superstition. No relation between paranormal beliefs and illusory control was found. Self-report measures indicated that paranormal beliefs were associated to being raised in a spiritual family and to anomalous experiences during childhood. Thereby this study suggests that paranormal beliefs are related to specific cognitive biases that in turn are shaped by socio-cultural factors. Copyright © 2017 Elsevier Inc. All rights reserved.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

PubMed

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

Investigating the efficacy of attention bias modification in reducing high spider fear: The role of individual differences in initial bias

PubMed Central

Fox, Elaine; Zougkou, Konstantina; Ashwin, Chris; Cahill, Shanna

2015-01-01

Background and objectives Attention Bias Modification (ABM) targets attention bias (AB) towards threat and is a potential therapeutic intervention for anxiety. The current study investigated whether initial AB (towards or away from spider images) influenced the effectiveness of ABM in spider fear. Methods AB was assessed with an attentional probe task consisting of spider and neutral images presented simultaneously followed by a probe in spider congruent or spider incongruent locations. Response time (RT) differences between spider and neutral trials > 25 ms was considered ‘Bias Toward’ threat. RT difference < - 25 ms was considered ‘Bias Away’ from threat, and a difference between −25 ms and +25 ms was considered ‘No Bias’. Participants were categorized into Initial Bias groups using pre-ABM AB scores calculated at the end of the study. 66 participants' (Bias Toward n = 27, Bias Away n = 18, No Bias n = 21) were randomly assigned to ABM-active training designed to reduce or eliminate a bias toward threat and 61 (Bias Toward n = 17, Bias Away n = 18, No Bias n = 26) to ABM-control. Results ABM-active had the largest impact on those demonstrating an initial Bias Towards spider images in terms of changing AB and reducing Spider Fear Vulnerability, with the Bias Away group experiencing least benefit from ABM. However, all Initial Bias groups benefited equally from active ABM in a Stress Task. Limitations Participants were high spider fearful but not formally diagnosed with a specific phobia. Therefore, results should be confirmed within a clinical population. Conclusions Individual differences in Initial Bias may be an important determinant of ABM efficacy. PMID:26060177

Assessing Sensitive Attributes Using the Randomized Response Technique: Evidence for the Importance of Response Symmetry

ERIC Educational Resources Information Center

Ostapczuk, Martin; Moshagen, Morten; Zhao, Zengmei; Musch, Jochen

2009-01-01

Randomized response techniques (RRTs) aim to reduce social desirability bias in the assessment of sensitive attributes but differ regarding privacy protection. The less protection a design offers, the more likely respondents cheat by disobeying the instructions. In asymmetric RRT designs, respondents can play safe by giving a response that is…

Missing Not at Random Models for Latent Growth Curve Analyses

ERIC Educational Resources Information Center

Enders, Craig K.

2011-01-01

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

Day Hospital and Residential Addiction Treatment: Randomized and Nonrandomized Managed Care Clients

ERIC Educational Resources Information Center

Witbrodt, Jane; Bond, Jason; Kaskutas, Lee Ann; Weisner, Constance; Jaeger, Gary; Pating, David; Moore, Charles

2007-01-01

Male and female managed care clients randomized to day hospital (n=154) or community residential treatment (n=139) were compared on substance use outcomes at 6 and 12 months. To address possible bias in naturalistic studies, outcomes were also examined for clients who self-selected day hospital (n=321) and for clients excluded from randomization…

Effects of nicotine and nicotine expectancy on attentional bias for emotional stimuli.

PubMed

Adams, Sally; Attwood, Angela S; Munafò, Marcus R

2015-06-01

Nicotine's effects on mood are thought to enhance its addictive potential. However, the mechanisms underlying the effects of nicotine on affect regulation have not been reliably demonstrated in human laboratory studies. We investigated the effects of nicotine abstinence (Experiment 1), and nicotine challenge and expectancy (Experiment 2) on attentional bias towards facial emotional stimuli differing in emotional valence. In Experiment 1, 46 nicotine-deprived smokers were randomized to either continue to abstain from smoking or to smoke immediately before testing. In Experiment 2, 96 nicotine-deprived smokers were randomized to smoke a nicotinized or denicotinized cigarette and to be told that the cigarette did or did not contain nicotine. In both experiments participants completed a visual probe task, where positively valenced (happy) and negatively valenced (sad) facial expressions were presented, together with neutral facial expressions. In Experiment 1, there was evidence of an interaction between probe location and abstinence on reaction time, indicating that abstinent smokers showed an attentional bias for neutral stimuli. In Experiment 2, there was evidence of an interaction between probe location, nicotine challenge and expectation on reaction time, indicating that smokers receiving nicotine, but told that they did not receive nicotine, showed an attentional bias for emotional stimuli. Our data suggest that nicotine abstinence appears to disrupt attentional bias towards emotional facial stimuli. These data provide support for nicotine's modulation of attentional bias as a central mechanism for maintaining affect regulation in cigarette smoking. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quality of Reporting Randomized Controlled Trials in Five Leading Neurology Journals in 2008 and 2013 Using the Modified "Risk of Bias" Tool.

PubMed

Zhai, Xiao; Cui, Jin; Wang, Yiran; Qu, Zhiquan; Mu, Qingchun; Li, Peiwen; Zhang, Chaochao; Yang, Mingyuan; Chen, Xiao; Chen, Ziqiang; Li, Ming

2017-03-01

To examine the risk of bias of methodological quality of reporting randomized clinical trials (RCTs) in major neurology journals before and after the update (2011) of Cochrane risk of bias tool. RCTs in 5 leading neurology journals in 2008 and 2013 were searched systematically. Characteristics were extracted based on the list of the modified Cochrane Collaboration's tool. Country, number of patients, type of intervention, and funding source also were examined for further analysis. A total of 138 RCTs were enrolled in this study. The rates of following a trial plan were 61.6% for the allocation generation, 52.9% for the allocation concealment, 84.8% for the blinding of the participants or the personnel, 34.8% for the blinding of outcome assessment, 78.3% for the incomplete outcome data, and 67.4% for the selective reporting. A significant setback was found in "the selective reporting" in 2013 than that in 2008. Trials performed by multi-centers and on a large scale had significantly more "low risk of bias" trials. Not only the number of surgical trials (5.8%) was much less than that of trials using drugs (73.9%), but also the reporting quality of surgical trials were worse (P = 0.008). Finally, only 17.4% trials met the criterion of "low risk of bias." The modified "risk of bias" tool is an improved version for assessment. Methodological quality of reporting RCTs in the 5neurology journals is unsatisfactory, especially that for surgical RCTs, and it could be further improved. Copyright © 2017 Elsevier Inc. All rights reserved.

Application of Biased Metropolis Algorithms: From protons to proteins

PubMed Central

Bazavov, Alexei; Berg, Bernd A.; Zhou, Huan-Xiang

2015-01-01

We show that sampling with a biased Metropolis scheme is essentially equivalent to using the heatbath algorithm. However, the biased Metropolis method can also be applied when an efficient heatbath algorithm does not exist. This is first illustrated with an example from high energy physics (lattice gauge theory simulations). We then illustrate the Rugged Metropolis method, which is based on a similar biased updating scheme, but aims at very different applications. The goal of such applications is to locate the most likely configurations in a rugged free energy landscape, which is most relevant for simulations of biomolecules. PMID:26612967

Quality of reporting of randomized clinical trials in implant dentistry. A systematic review on critical aspects in design, outcome assessment and clinical relevance.

PubMed

Cairo, Francesco; Sanz, Ignacio; Matesanz, Paula; Nieri, Michele; Pagliaro, Umberto

2012-02-01

The aim of this systematic review (SR) was to assess the quality of reporting randomized clinical trials (RCTs) in the field of implant dentistry, its evolution over time and the possible relations between quality items and reported outcomes. RCTs in implant dentistry were retrieved through electronic and hand searches. Risk of bias in individual studies was assessed focusing on study design, outcome assessment and clinical relevance. Associations between quality items and year of publication of RCTs or reporting of statistically significant outcomes were tested. Among the 495 originally screened manuscripts published from 1989 to April 2011, 276 RCTs were assessed in this SR; 59% of them were published between 2006 and 2011. RCTs were mainly parallel (65%), with a single centre (83%) and a superiority design (88%). Trials in implant dentistry showed several methodological flaws: only 37% showed a random sequence generation at low risk of bias, 75% did not provide information on allocation concealment, only 12% performed a correct sample size calculation, the examiner was blind solely in 42% of studies where blinding was feasible. In addition, only 21% of RCTs declared operator experience and 31% reported patient-related outcomes. Many quality items improved over time. Allocation concealment at high risk of bias (p = 0.0125), no information on drop-out (p = 0.0318) and lack of CONSORT adherence (p = 0.0333) were associated with statistically significant reported outcomes. The overall quality of reporting of RCTs in implant dentistry is poor and only partially improved in the last years. Caution is suggested when interpreting these RCTs since risk of bias was associated with higher chance of reporting of statistically significant results. © 2012 John Wiley & Sons A/S.

The effect of antenatal education in small classes on obstetric and psycho-social outcomes - a systematic review.

PubMed

Brixval, Carina Sjöberg; Axelsen, Solveig Forberg; Lauemøller, Stine Glenstrup; Andersen, Stig Krøger; Due, Pernille; Koushede, Vibeke

2015-02-28

The aims of antenatal education are broad and encompass outcomes related to pregnancy, birth, and parenthood. Both form and content of antenatal education have changed over time without evidence of effects on relevant outcomes. The effect of antenatal education in groups, with participation of a small number of participants, may differ from the effect of other forms of antenatal education due to, for example, group dynamic. The objective of this systematic review is to assess the effects of antenatal education in small groups on obstetric as well as psycho-social outcomes. Bibliographic databases (Medline, EMBASE, CENTRAL, CINAHL, Web of Science, and PsycINFO) were searched. We included randomized and quasi-randomized trials irrespective of language, publication year, publication type, and publication status. Only trials carried out in the Western world were considered in this review. Studies were assessed for bias using the Cochrane risk of bias tool. Results are presented as structured summaries of the included trials and as forest plots. We identified 5,708 records. Of these, 17 studies met inclusion criteria. Studies varied greatly in content of the experimental and control condition. All outcomes were only reported in a single or a few trials, leading to limited or uncertain confidence in effect estimates. Given the heterogeneity in interventions and outcomes and also the high risk of bias of studies, we are unable to draw definitive conclusions as to the impact of small group antenatal education on obstetric and psycho-social outcomes. Insufficient evidence exists as to whether antenatal education in small classes is effective in regard to obstetric and psycho-social outcomes. We recommend updating this review following the emergence of well-conducted randomized controlled trials with a low risk of bias. PROSPERO CRD42013004319.

On the sea-state bias of the Geosat altimeter

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Koblinsky, Chester J.

1991-01-01

The sea-state bias in a satellite altimeter's range measurement is caused by the influence of ocean waves on the radar return pulse; it results in an estimate of sea level that is too low according to some function of the wave height. This bias is here estimated for Geosat by correlating collinear differences of altimetric sea-surface heights with collinear differences of significant wave heights (H1/3). Corrections for satellite orbit error are estimated simultaneously with the sea-state bias. Based on twenty 17-day repeat cycles of the Geosat Exact Repeat Mission, the solution for the sea-state bias is 2.6 + or - 0.2 percent of H1/3. The least-squares residuals, however, show a correlation with wind speed U, so the traditional model of the bias has been supplemented with a second term: H1/3 + alpha-2H1/3U. This second term produces a small, but statistically significant, reduction in variance of the residuals. Both systematic and random errors in H1/3 and U tend to bias the estimates of alpha-1 and alpha-2, which complicates comparisons of the results with ground-based measurements of the sea-state bias.

On the sea-state bias of the Geosat altimeter

NASA Astrophysics Data System (ADS)

Ray, Richard D.; Koblinsky, Chester J.

1991-06-01

The sea-state bias in a satellite altimeter's range measurement is caused by the influence of ocean waves on the radar return pulse; it results in an estimate of sea level that is too low according to some function of the wave height. This bias is here estimated for Geosat by correlating collinear differences of altimetric sea-surface heights with collinear differences of significant wave heights (H1/3). Corrections for satellite orbit error are estimated simultaneously with the sea-state bias. Based on twenty 17-day repeat cycles of the Geosat Exact Repeat Mission, the solution for the sea-state bias is 2.6 + or - 0.2 percent of H1/3. The least-squares residuals, however, show a correlation with wind speed U, so the traditional model of the bias has been supplemented with a second term: H1/3 + alpha-2H1/3U. This second term produces a small, but statistically significant, reduction in variance of the residuals. Both systematic and random errors in H1/3 and U tend to bias the estimates of alpha-1 and alpha-2, which complicates comparisons of the results with ground-based measurements of the sea-state bias.

Clinical Knowledge from Observational Studies: Everything You Wanted to Know but Were Afraid to Ask.

PubMed

Gershon, Andrea S; Jafarzadeh, S Reza; Wilson, Kevin C; Walkey, Allan J

2018-05-07

Well-done randomized trials provide accurate estimates of treatment effect by producing groups that are similar on all measures except for the intervention of interest. However, inferences of efficacy in tightly-controlled experimental settings may not translate into similar effectiveness in real-world settings. Observational studies generally enable inferences over a wider range of patient characteristics and evaluation of a broader range of outcomes over a longer period than randomized trials. However, clinicians are often reluctant to incorporate the findings of observational studies into clinical practice. Reason for uncertainty regarding observational studies include a lack of familiarity with observational research methods, occasional disagreements between results of observational studies and randomized trials, the perceived risk of spurious results from systematic bias, and prior teaching that randomized trials are the most reliable source of medical evidence. We propose that a better understanding of observational research will enhance clinicians' ability to distinguish reliable observational studies from those that are subjected to biases and, therefore, provide more confidence to apply observational research results into clinical practice when appropriate. Herein, we explain why observational studies may be perceived as less conclusive than randomized trials, address situations in which observational research and randomized trials produced different findings, and provide information on observational study design so that quality can be evaluated. We conclude that observational research is a valuable source of medical evidence and that clinical action is strongest when supported by both high quality observational studies and randomized trials.

Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

PubMed

Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L

2014-03-01

Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.

Analysis and correction of gradient nonlinearity bias in ADC measurements

PubMed Central

Malyarenko, Dariya I.; Ross, Brian D.; Chenevert, Thomas L.

2013-01-01

Purpose Gradient nonlinearity of MRI systems leads to spatially-dependent b-values and consequently high non-uniformity errors (10–20%) in ADC measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. PMID:23794533

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.

Directed intermittent search for a hidden target on a dendritic tree

NASA Astrophysics Data System (ADS)

Newby, Jay M.; Bressloff, Paul C.

2009-08-01

Motivated by experimental observations of active (motor-driven) intracellular transport in neuronal dendrites, we analyze a stochastic model of directed intermittent search on a tree network. A particle injected from the cell body or soma into the primary branch of the dendritic tree randomly switches between a stationary search phase and a mobile nonsearch phase that is biased in the forward direction. A (synaptic) target is presented somewhere within the tree, which the particle can locate if it is within a certain range and in the searching phase. We approximate the moment generating function using Green’s function methods. The moment generating function is then used to compute the hitting probability and conditional mean first passage time to the target. We show that in contrast to a previously explored finite interval case, there is a range of parameters for which a bidirectional search strategy is more efficient than a unidirectional one in finding the target.

Multiple Imputation For Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys

PubMed Central

Rendall, Michael S.; Ghosh-Dastidar, Bonnie; Weden, Margaret M.; Baker, Elizabeth H.; Nazarov, Zafar

2013-01-01

Within-survey multiple imputation (MI) methods are adapted to pooled-survey regression estimation where one survey has more regressors, but typically fewer observations, than the other. This adaptation is achieved through: (1) larger numbers of imputations to compensate for the higher fraction of missing values; (2) model-fit statistics to check the assumption that the two surveys sample from a common universe; and (3) specificying the analysis model completely from variables present in the survey with the larger set of regressors, thereby excluding variables never jointly observed. In contrast to the typical within-survey MI context, cross-survey missingness is monotonic and easily satisfies the Missing At Random (MAR) assumption needed for unbiased MI. Large efficiency gains and substantial reduction in omitted variable bias are demonstrated in an application to sociodemographic differences in the risk of child obesity estimated from two nationally-representative cohort surveys. PMID:24223447

Enhanced Wang Landau sampling of adsorbed protein conformations.

PubMed

Radhakrishna, Mithun; Sharma, Sumit; Kumar, Sanat K

2012-03-21

Using computer simulations to model the folding of proteins into their native states is computationally expensive due to the extraordinarily low degeneracy of the ground state. In this paper, we develop an efficient way to sample these folded conformations using Wang Landau sampling coupled with the configurational bias method (which uses an unphysical "temperature" that lies between the collapse and folding transition temperatures of the protein). This method speeds up the folding process by roughly an order of magnitude over existing algorithms for the sequences studied. We apply this method to study the adsorption of intrinsically disordered hydrophobic polar protein fragments on a hydrophobic surface. We find that these fragments, which are unstructured in the bulk, acquire secondary structure upon adsorption onto a strong hydrophobic surface. Apparently, the presence of a hydrophobic surface allows these random coil fragments to fold by providing hydrophobic contacts that were lost in protein fragmentation. © 2012 American Institute of Physics

Ultrastructural and functional fate of recycled vesicles in hippocampal synapses

PubMed Central

Rey, Stephanie A.; Smith, Catherine A.; Fowler, Milena W.; Crawford, Freya; Burden, Jemima J.; Staras, Kevin

2015-01-01

Efficient recycling of synaptic vesicles is thought to be critical for sustained information transfer at central terminals. However, the specific contribution that retrieved vesicles make to future transmission events remains unclear. Here we exploit fluorescence and time-stamped electron microscopy to track the functional and positional fate of vesicles endocytosed after readily releasable pool (RRP) stimulation in rat hippocampal synapses. We show that most vesicles are recovered near the active zone but subsequently take up random positions in the cluster, without preferential bias for future use. These vesicles non-selectively queue, advancing towards the release site with further stimulation in an actin-dependent manner. Nonetheless, the small subset of vesicles retrieved recently in the stimulus train persist nearer the active zone and exhibit more privileged use in the next RRP. Our findings reveal heterogeneity in vesicle fate based on nanoscale position and timing rules, providing new insights into the origins of future pool constitution. PMID:26292808

Effects of date palm pollen on fertility: research proposal for a systematic review.

PubMed

Abdi, Fatemeh; Roozbeh, Nasibeh; Mortazavian, Amir Mohammad

2017-08-01

Over 10-15% of couples in different countries are infertile. Male infertility is a contributing factor and the only cause of infertility in respectively 50% and 20-30% of all cases of infertility. According to previous research, micro-elements isolated from date palm pollen (DPP), e.g. estrogen and sterols, may enhance male and female fertility. DPP has also been reported to improve sperm parameters including sperm motility and viability, acrosome reaction, and lipid peroxidation. This article may justify the need for a future systematic review and meta-analysis about the effects of DPP on the reproductive system and DPP's ability to enhance fertility. It will then describe the methodology of such a study. A comprehensive search of relevant randomized and quasi-randomized controlled trials will be performed in MEDLINE, EMBASE, Web of Science, Cochrane Central, ProQuest, and Google Scholar databases. Two authors will independently assess the eligibility of the studies and consult the third author in cases of disagreement. The risk of bias of the randomized controlled trials and animal studies will be evaluated using the Cochrane risk of bias tool and the Systematic Review Centre for Laboratory animal Experimentation (SYRCLE) risk of bias tool, respectively. This study will raise no ethical issues as it will review the findings of previous research. The results are intended to be published in a peer-reviewed medical journal.

Helicobacter pylori Eradication for Prevention of Metachronous Recurrence after Endoscopic Resection of Early Gastric Cancer.

PubMed

Bang, Chang Seok; Baik, Gwang Ho; Shin, In Soo; Kim, Jin Bong; Suk, Ki Tae; Yoon, Jai Hoon; Kim, Yeon Soo; Kim, Dong Joon

2015-06-01

Controversies persist regarding the effect of Helicobacter pylori eradication on the development of metachronous gastric cancer after endoscopic resection of early gastric cancer (EGC). The aim of this study was to assess the efficacy of Helicobacter pylori eradication after endoscopic resection of EGC for the prevention of metachronous gastric cancer. A systematic literature review and meta-analysis were conducted using the core databases PubMed, EMBASE, and the Cochrane Library. The rates of development of metachronous gastric cancer between the Helicobacter pylori eradication group vs. the non-eradication group were extracted and analyzed using risk ratios (RRs). A random effect model was applied. The methodological quality of the enrolled studies was assessed by the Risk of Bias table and by the Newcastle-Ottawa Scale. Publication bias was evaluated through the funnel plot with trim and fill method, Egger's test, and by the rank correlation test. Ten studies (2 randomized and 8 non-randomized/5,914 patients with EGC or dysplasia) were identified and analyzed. Overall, the Helicobacter pylori eradication group showed a RR of 0.467 (95% CI: 0.362-0.602, P < 0.001) for the development of metachronous gastric cancer after endoscopic resection of EGC. Subgroup analyses showed consistent results. Publication bias was not detected. Helicobacter pylori eradication after endoscopic resection of EGC reduces the occurrence of metachronous gastric cancer.

Medical School Experiences Associated with Change in Implicit Racial Bias Among 3547 Students: A Medical Student CHANGES Study Report.

PubMed

van Ryn, Michelle; Hardeman, Rachel; Phelan, Sean M; Burgess, Diana J; Dovidio, John F; Herrin, Jeph; Burke, Sara E; Nelson, David B; Perry, Sylvia; Yeazel, Mark; Przedworski, Julia M

2015-12-01

Physician implicit (unconscious, automatic) bias has been shown to contribute to racial disparities in medical care. The impact of medical education on implicit racial bias is unknown. To examine the association between change in student implicit racial bias towards African Americans and student reports on their experiences with 1) formal curricula related to disparities in health and health care, cultural competence, and/or minority health; 2) informal curricula including racial climate and role model behavior; and 3) the amount and favorability of interracial contact during school. Prospective observational study involving Web-based questionnaires administered during first (2010) and last (2014) semesters of medical school. A total of 3547 students from a stratified random sample of 49 U.S. medical schools. Change in implicit racial attitudes as assessed by the Black-White Implicit Association Test administered during the first semester and again during the last semester of medical school. In multivariable modeling, having completed the Black-White Implicit Association Test during medical school remained a statistically significant predictor of decreased implicit racial bias (-5.34, p ≤ 0.001: mixed effects regression with random intercept across schools). Students' self-assessed skills regarding providing care to African American patients had a borderline association with decreased implicit racial bias (-2.18, p = 0.056). Having heard negative comments from attending physicians or residents about African American patients (3.17, p = 0.026) and having had unfavorable vs. very favorable contact with African American physicians (18.79, p = 0.003) were statistically significant predictors of increased implicit racial bias. Medical school experiences in all three domains were independently associated with change in student implicit racial attitudes. These findings are notable given that even small differences in implicit racial attitudes have been shown to affect behavior and that implicit attitudes are developed over a long period of repeated exposure and are difficult to change.

Unicompartmental Knee Arthroplasty: Does a Selection Bias Exist?

PubMed

Howell, Robert E; Lombardi, Adolph V; Crilly, Ryan; Opolot, Shem; Berend, Keith R

2015-10-01

Unicompartmental knee arthroplasty (UKA) is a minimally invasive option reported to allow a more rapid recovery and better patient outcomes. However, whether these outcomes are related to selection bias has not been fully investigated. This study examines whether a bias existed in selection of UKA candidates. We compared outcomes of patients who were scheduled for UKA but had the plan changed intraoperatively to total knee arthroplasty (TKA) to two randomly selected contemporaneous control groups: 1) patients planned as UKA who received UKA and 2) patients planned as TKA who received TKA. Our results not only showed a selection bias existed, but also showed patients converted to TKA intraoperatively had similar clinical results to patients receiving UKAs and better results than patients originally scheduled for TKA. Copyright © 2015 Elsevier Inc. All rights reserved.

InGaN working electrodes with assisted bias generated from GaAs solar cells for efficient water splitting.

PubMed

Liu, Shu-Yen; Sheu, J K; Lin, Yu-Chuan; Chen, Yu-Tong; Tu, S J; Lee, M L; Lai, W C

2013-11-04

Hydrogen generation through water splitting by n-InGaN working electrodes with bias generated from GaAs solar cell was studied. Instead of using an external bias provided by power supply, a GaAs-based solar cell was used as the driving force to increase the rate of hydrogen production. The water-splitting system was tuned using different approaches to set the operating points to the maximum power point of the GaAs solar cell. The approaches included changing the electrolytes, varying the light intensity, and introducing the immersed ITO ohmic contacts on the working electrodes. As a result, the hybrid system comprising both InGaN-based working electrodes and GaAs solar cells operating under concentrated illumination could possibly facilitate efficient water splitting.

A fully integrated, wide-load-range, high-power-conversion-efficiency switched capacitor DC-DC converter with adaptive bias comparator for ultra-low-power power management integrated circuit

NASA Astrophysics Data System (ADS)

Asano, Hiroki; Hirose, Tetsuya; Kojima, Yuta; Kuroki, Nobutaka; Numa, Masahiro

2018-04-01

In this paper, we present a wide-load-range switched-capacitor DC-DC buck converter with an adaptive bias comparator for ultra-low-power power management integrated circuit. The proposed converter is based on a conventional one and modified to operate in a wide load range by developing a load current monitor used in an adaptive bias comparator. Measurement results demonstrated that our proposed converter generates a 1.0 V output voltage from a 3.0 V input voltage at a load of up to 100 µA, which is 20 times higher than that of the conventional one. The power conversion efficiency was higher than 60% in the load range from 0.8 to 100 µA.

Competing risk bias was common in Kaplan-Meier risk estimates published in prominent medical journals.

PubMed

van Walraven, Carl; McAlister, Finlay A

2016-01-01

Risk estimates from Kaplan-Meier curves are well known to medical researchers, reviewers, and editors. In this study, we determined the proportion of Kaplan-Meier analyses published in prominent medical journals that are potentially biased because of competing events ("competing risk bias"). We randomly selected 100 studies that had at least one Kaplan-Meier analysis and were recently published in prominent medical journals. Susceptibility to competing risk bias was determined by examining the outcome and potential competing events. In susceptible studies, bias was quantified using a previously validated prediction model when the number of outcomes and competing events were given. Forty-six studies (46%) contained Kaplan-Meier analyses susceptible to competing risk bias. Sixteen studies (34.8%) susceptible to competing risk cited the number of outcomes and competing events; in six of these studies (6/16, 37.5%), the outcome risk from the Kaplan-Meier estimate (relative to the true risk) was biased upward by 10% or more. Almost half of Kaplan-Meier analyses published in medical journals are susceptible to competing risk bias and may overestimate event risk. This bias was found to be quantitatively important in a third of such studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Music for insomnia in adults.

PubMed

Jespersen, Kira V; Koenig, Julian; Jennum, Poul; Vuust, Peter

2015-08-13

Insomnia is a common sleep disorder in modern society. It causes reduced quality of life and is associated with impairments in physical and mental health. Listening to music is widely used as a sleep aid, but it remains unclear if it can actually improve insomnia in adults. To assess the effects of listening to music on insomnia in adults and to assess the influence of specific variables that may moderate the effect. We searched CENTRAL, PubMed, Embase, nine other databases and two trials registers in May 2015. In addition, we handsearched specific music therapy journals, reference lists of included studies, and contacted authors of published studies to identify additional studies eligible for inclusion, including any unpublished or ongoing trials. Randomised controlled trials and quasi-randomised controlled trials that compared the effects of listening to music with no treatment or treatment-as-usual on sleep improvement in adults with insomnia. Two authors independently screened abstracts, selected studies, assessed risk of bias, and extracted data from all studies eligible for inclusion. Data on pre-defined outcome measures were subjected to meta-analyses when consistently reported by at least two studies. We undertook meta-analyses using both fixed-effect and random-effects models. Heterogeneity across included studies was assessed using the I² statistic. We included six studies comprising a total of 314 participants. The studies examined the effect of listening to pre-recorded music daily, for 25 to 60 minutes, for a period of three days to five weeks.Based on the Grades of Recommendations, Assessment, Development and Evaluation (GRADE) approach, we judged the evidence from five studies that measured the effect of music listening on sleep quality to be of moderate quality. We judged the evidence from one study that examined other aspects of sleep (see below) to be of low quality. We downgraded the quality of the evidence mainly because of limitations in design or being the only published study. As regards risk of bias, most studies were at high risk of bias on at least one domain: one study was at high risk of selection bias and one was judged to be at unclear risk; six studies were at high risk of performance bias; three studies were at high risk of detection bias; one study was at high risk of attrition bias and was study was judged to be at unclear risk; two studies were judged to be at unclear risk of reporting bias; and four studies were at high risk of other bias.Five studies (N = 264) reporting on sleep quality as assessed by the Pittsburgh Sleep Quality Index (PSQI) were included in the meta-analysis. The results of a random-effects meta-analysis revealed an effect in favour of music listening (mean difference (MD) -2.80; 95% confidence interval (CI) -3.42 to -2.17; Z = 8.77, P < 0.00001; moderate-quality evidence). The size of the effect indicates an increase in sleep quality of the size of about one standard deviation in favour of the intervention compared to no treatment or treatment-as-usual.Only one study (N = 50; low-quality evidence) reported data on sleep onset latency, total sleep time, sleep interruption, and sleep efficiency. However, It found no evidence to suggest that the intervention benefited these outcomes. None of the included studies reported any adverse events. The findings of this review provide evidence that music may be effective for improving subjective sleep quality in adults with insomnia symptoms. The intervention is safe and easy to administer. More research is needed to establish the effect of listening to music on other aspects of sleep as well as the daytime consequences of insomnia.

Evidence synthesis for medical decision making and the appropriate use of quality scores.

PubMed

Doi, Suhail A R

2014-09-01

Meta-analyses today continue to be run using conventional random-effects models that ignore tangible information from studies such as the quality of the studies involved, despite the expectation that results of better quality studies reflect more valid results. Previous research has suggested that quality scores derived from such quality appraisals are unlikely to be useful in meta-analysis, because they would produce biased estimates of effects that are unlikely to be offset by a variance reduction within the studied models. However, previous discussions took place in the context of such scores viewed in terms of their ability to maximize their association with both the magnitude and direction of bias. In this review, another look is taken at this concept, this time asserting that probabilistic bias quantification is not possible or even required of quality scores when used in meta-analysis for redistribution of weights. The use of such a model is contrasted with the conventional random effects model of meta-analysis to demonstrate why the latter is inadequate in the face of a properly specified quality score weighting method. © 2014 Marshfield Clinic.

Do nonexercisers also share the positive exerciser stereotype?: An elicitation and comparison of beliefs about exercisers.

PubMed

Rodgers, Wendy M; Hall, Craig R; Wilson, Philip M; Berry, Tanya R

2009-02-01

The purpose of this research was to examine whether exercisers and nonexercisers are rated similarly on a variety of characteristics by a sample of randomly selected regular exercisers, nonexercisers who intend to exercise, and nonexercisers with no intention to exercise. Previous research by Martin Ginis et al. (2003) has demonstrated an exerciser stereotype that advantages exercisers. It is unknown, however, the extent to which an exerciser stereotype is shared by nonexercisers, particularly nonintenders. Following an item-generation procedure, a sample of 470 (n=218 men; n=252 women) people selected using random digit dialing responded to a questionnaire assessing the extent to which they agreed that exercisers and nonexercisers possessed 24 characteristics, such as "happy," "fit," "fat," and "lazy." The results strongly support a positive exerciser bias, with exercisers rated more favorably on 22 of the 24 items. The degree of bias was equivalent in all groups of respondents. Examination of the demographic characteristics revealed no differences among the three groups on age, work status, or child-care responsibilities, suggesting that there is a pervasive positive exerciser bias.

Do humans and nonhuman animals share the grouping principles of the Iambic - Trochaic Law?

PubMed Central

de la Mora, Daniela M.; Nespor, Marina; Toro, Juan M.

2014-01-01

The Iambic-Trochaic Law describes humans’ tendency to form trochaic groups over sequences varying in pitch or intensity (i.e., the loudest or highest sound marks group beginnings), and iambic groups over sequences varying in duration (i.e., the longest sound marks group endings). The extent to which these perceptual biases are shared by humans and nonhuman animals is yet unclear. In Experiment 1, we trained rats to discriminate pitch-alternating sequences of tones from sequences randomly varying in pitch. In Experiment 2, rats were trained to discriminate duration-alternating sequences of tones from sequences randomly varying in duration. We found that nonhuman animals group as trochees sequences based on pitch variations, but they do not group as iambs sequences varying in duration. Importantly, humans grouped the same stimuli following the principles of the Iambic-Trochaic Law (Experiment 3). These results suggest an early emergence of the trochaic rhythmic grouping bias based on pitch, possibly relying on perceptual abilities shared by humans and other mammals as well, whereas the iambic rhythmic grouping bias based on duration might depend on language experience. PMID:22956287

Do humans and nonhuman animals share the grouping principles of the iambic-trochaic law?

PubMed

de la Mora, Daniela M; Nespor, Marina; Toro, Juan M

2013-01-01

The iambic-trochaic law describes humans' tendency to form trochaic groups over sequences varying in pitch or intensity (i.e., the loudest or highest sounds mark group beginnings), and iambic groups over sequences varying in duration (i.e., the longest sounds mark group endings). The extent to which these perceptual biases are shared by humans and nonhuman animals is yet unclear. In Experiment 1, we trained rats to discriminate pitch-alternating sequences of tones from sequences randomly varying in pitch. In Experiment 2, rats were trained to discriminate duration-alternating sequences of tones from sequences randomly varying in duration. We found that nonhuman animals group sequences based on pitch variations as trochees, but they do not group sequences varying in duration as iambs. Importantly, humans grouped the same stimuli following the principles of the iambic-trochaic law (Exp. 3). These results suggest the early emergence of the trochaic rhythmic grouping bias based on pitch, possibly relying on perceptual abilities shared by humans and other mammals, whereas the iambic rhythmic grouping bias based on duration might depend on language experience.

The effect of berberine on insulin resistance in women with polycystic ovary syndrome: detailed statistical analysis plan (SAP) for a multicenter randomized controlled trial.

PubMed

Zhang, Ying; Sun, Jin; Zhang, Yun-Jiao; Chai, Qian-Yun; Zhang, Kang; Ma, Hong-Li; Wu, Xiao-Ke; Liu, Jian-Ping

2016-10-21

Although Traditional Chinese Medicine (TCM) has been widely used in clinical settings, a major challenge that remains in TCM is to evaluate its efficacy scientifically. This randomized controlled trial aims to evaluate the efficacy and safety of berberine in the treatment of patients with polycystic ovary syndrome. In order to improve the transparency and research quality of this clinical trial, we prepared this statistical analysis plan (SAP). The trial design, primary and secondary outcomes, and safety outcomes were declared to reduce selection biases in data analysis and result reporting. We specified detailed methods for data management and statistical analyses. Statistics in corresponding tables, listings, and graphs were outlined. The SAP provided more detailed information than trial protocol on data management and statistical analysis methods. Any post hoc analyses could be identified via referring to this SAP, and the possible selection bias and performance bias will be reduced in the trial. This study is registered at ClinicalTrials.gov, NCT01138930 , registered on 7 June 2010.

Empathy Intervention to Reduce Implicit Bias in Pre-Service Teachers.

PubMed

Whitford, Denise K; Emerson, Andrea M

2018-01-01

There have been long-term concerns regarding discriminatory discipline practices used with culturally and linguistically diverse students, with little research on the impact teacher-centered empathy interventions may have on this population. This randomized pretest-posttest control group design investigates the ability of a brief empathy-inducing intervention to improve the implicit bias of pre-service teachers, as measured by the Implicit Association Test. We found the empathy intervention statistically significant at decreasing the implicit bias of White female pre-service teachers toward Black individuals ( F = 7.55, η 2  = 0.22, p = 0.01). Implications and future research are discussed, including extended intervention periods.

Driven Metadynamics: Reconstructing Equilibrium Free Energies from Driven Adaptive-Bias Simulations

PubMed Central

2013-01-01

We present a novel free-energy calculation method that constructively integrates two distinct classes of nonequilibrium sampling techniques, namely, driven (e.g., steered molecular dynamics) and adaptive-bias (e.g., metadynamics) methods. By employing nonequilibrium work relations, we design a biasing protocol with an explicitly time- and history-dependent bias that uses on-the-fly work measurements to gradually flatten the free-energy surface. The asymptotic convergence of the method is discussed, and several relations are derived for free-energy reconstruction and error estimation. Isomerization reaction of an atomistic polyproline peptide model is used to numerically illustrate the superior efficiency and faster convergence of the method compared with its adaptive-bias and driven components in isolation. PMID:23795244

Distinctions between fraud, bias, errors, misunderstanding, and incompetence.

PubMed

DeMets, D L

1997-12-01

Randomized clinical trials are challenging not only in their design and analysis, but in their conduct as well. Despite the best intentions and efforts, problems often arise in the conduct of trials, including errors, misunderstandings, and bias. In some instances, key players in a trial may discover that they are not able or competent to meet requirements of the study. In a few cases, fraudulent activity occurs. While none of these problems is desirable, randomized clinical trials are usually found sufficiently robust by many key individuals to produce valid results. Other problems are not tolerable. Confusion may arise among scientists, scientific and lay press, and the public about the distinctions between these areas and their implications. We shall try to define these problems and illustrate their impact through a series of examples.

Using partial site aggregation to reduce bias in random utility travel cost models

NASA Astrophysics Data System (ADS)

Lupi, Frank; Feather, Peter M.

1998-12-01

We propose a "partial aggregation" strategy for defining the recreation sites that enter choice sets in random utility models. Under the proposal, the most popular sites and sites that will be the subject of policy analysis enter choice sets as individual sites while remaining sites are aggregated into groups of similar sites. The scheme balances the desire to include all potential substitute sites in the choice sets with practical data and modeling constraints. Unlike fully aggregate models, our analysis and empirical applications suggest that the partial aggregation approach reasonably approximates the results of a disaggregate model. The partial aggregation approach offers all of the data and computational advantages of models with aggregate sites but does not suffer from the same degree of bias as fully aggregate models.

Old models explain new observations of butterfly movement at patch edges.

PubMed

Crone, Elizabeth E; Schultz, Cheryl B

2008-07-01

Understanding movement in heterogeneous environments is central to predicting how landscape changes affect animal populations. Several recent studies point out an intriguing and distinctive looping behavior by butterflies at habitat patch edges and hypothesize that this behavior requires a new framework for analyzing animal movement. We show that this looping behavior could be caused by a longstanding movement model, biased correlated random walk, with bias toward habitat patches. The ability of this longstanding model to explain recent observations reinforces the point that butterflies respond to habitat heterogeneity and do not move randomly through heterogeneous environments. We discuss the implications of different movement models for predicting butterfly responses to landscape change, and our rationale for retaining longstanding movement models, rather than developing new modeling frameworks for looping behavior at patch edges.

Evaluation of Model Specification, Variable Selection, and Adjustment Methods in Relation to Propensity Scores and Prognostic Scores in Multilevel Data

ERIC Educational Resources Information Center

Yu, Bing; Hong, Guanglei

2012-01-01

This study uses simulation examples representing three types of treatment assignment mechanisms in data generation (the random intercept and slopes setting, the random intercept setting, and a third setting with a cluster-level treatment and an individual-level outcome) in order to determine optimal procedures for reducing bias and improving…

Can Broad Inferences Be Drawn from Lottery Analyses of School Choice Programs? An Exploration of Appropriate Sensitivity Analyses

ERIC Educational Resources Information Center

Zimmer, Ron; Engberg, John

2016-01-01

School choice programs continue to be controversial, spurring a number of researchers into evaluating them. When possible, researchers evaluate the effect of attending a school of choice using randomized designs to eliminate possible selection bias. Randomized designs are often thought of as the gold standard for research, but many circumstances…

Massage Therapy for Pain and Function in Patients With Arthritis: A Systematic Review of Randomized Controlled Trials.

PubMed

Nelson, Nicole L; Churilla, James R

2017-09-01

Massage therapy is gaining interest as a therapeutic approach to managing osteoarthritis and rheumatoid arthritis symptoms. To date, there have been no systematic reviews investigating the effects of massage therapy on these conditions. Systematic review was used. The primary aim of this review was to critically appraise and synthesize the current evidence regarding the effects of massage therapy as a stand-alone treatment on pain and functional outcomes among those with osteoarthritis or rheumatoid arthritis. Relevant randomized controlled trials were searched using the electronic databases Google Scholar, MEDLINE, and PEDro. The PEDro scale was used to assess risk of bias, and the quality of evidence was assessed with the GRADE approach. This review found seven randomized controlled trials representing 352 participants who satisfied the inclusion criteria. Risk of bias ranged from four to seven. Our results found low- to moderate-quality evidence that massage therapy is superior to nonactive therapies in reducing pain and improving certain functional outcomes. It is unclear whether massage therapy is more effective than other forms of treatment. There is a need for large, methodologically rigorous randomized controlled trials investigating the effectiveness of massage therapy as an intervention for individuals with arthritis.

A maximum pseudo-profile likelihood estimator for the Cox model under length-biased sampling

PubMed Central

Huang, Chiung-Yu; Qin, Jing; Follmann, Dean A.

2012-01-01

This paper considers semiparametric estimation of the Cox proportional hazards model for right-censored and length-biased data arising from prevalent sampling. To exploit the special structure of length-biased sampling, we propose a maximum pseudo-profile likelihood estimator, which can handle time-dependent covariates and is consistent under covariate-dependent censoring. Simulation studies show that the proposed estimator is more efficient than its competitors. A data analysis illustrates the methods and theory. PMID:23843659

Chemotaxis of C. elegans in 3D media: a model for navigation of undulatory microswimmers

NASA Astrophysics Data System (ADS)

Patel, Amar; Bilbao, Alejandro; Rahman, Mizanur; Vanapalli, Siva; Blawzdziewicz, Jerzy

2017-11-01

While the natural environment of C. elegans consists of complex 3D media (e.g., decomposing organic matter and water), most studies of chemotactic behavior of this nematode are limited to 2D. We present a 3D chemotaxis model that combines a realistic geometrical representation of body movements associated with 3D maneuvers, an analysis of mechanical interactions of the nematode body with the surrounding medium to determine nematode trajectories, and a simple memory-function description of chemosensory apparatus that controls the frequency, magnitude, and timing of turning maneuvers. We show that two main chemotaxis strategies of C. elegans moving in 2D, i.e., the biased random walk and gradual turn, are effective also in 3D, provided that 2D turns are supplemented by the roll maneuvers that enable 3D reorientation. Optimal choices of chemosensing and gait-control parameters are discussed; we show that the nematode can maintain efficient chemotaxis in burrowing and swimming by adjusting the undulation frequency alone, without changing the chemotactic component of the body control. Understanding how C. elegans efficiently navigates in 3D media may help in developing self-navigating artificial microswimmers. Supported by NSF Grant No. CBET 1603627.

Beluga whale, Delphinapterus leucas, vocalizations from the Churchill River, Manitoba, Canada.

PubMed

Chmelnitsky, Elly G; Ferguson, Steven H

2012-06-01

Classification of animal vocalizations is often done by a human observer using aural and visual analysis but more efficient, automated methods have also been utilized to reduce bias and increase reproducibility. Beluga whale, Delphinapterus leucas, calls were described from recordings collected in the summers of 2006-2008, in the Churchill River, Manitoba. Calls (n=706) were classified based on aural and visual analysis, and call characteristics were measured; calls were separated into 453 whistles (64.2%; 22 types), 183 pulsed∕noisy calls (25.9%; 15 types), and 70 combined calls (9.9%; seven types). Measured parameters varied within each call type but less variation existed in pulsed and noisy call types and some combined call types than in whistles. A more efficient and repeatable hierarchical clustering method was applied to 200 randomly chosen whistles using six call characteristics as variables; twelve groups were identified. Call characteristics varied less in cluster analysis groups than in whistle types described by visual and aural analysis and results were similar to the whistle contours described. This study provided the first description of beluga calls in Hudson Bay and using two methods provides more robust interpretations and an assessment of appropriate methods for future studies.

Publication bias in animal research presented at the 2008 Society of Critical Care Medicine Conference.

PubMed

Conradi, Una; Joffe, Ari R

2017-07-07

To determine a direct measure of publication bias by determining subsequent full-paper publication (P) of studies reported in animal research abstracts presented at an international conference (A). We selected 100 random (using a random-number generator) A from the 2008 Society of Critical Care Medicine Conference. Using a data collection form and study manual, we recorded methodology and result variables from A. We searched PubMed and EMBASE to June 2015, and DOAJ and Google Scholar to May 2017 to screen for subsequent P. Methodology and result variables were recorded from P to determine changes in reporting from A. Predictors of P were examined using Fisher's Exact Test. 62% (95% CI 52-71%) of studies described in A were subsequently P after a median 19 [IQR 9-33.3] months from conference presentation. Reporting of studies in A was of low quality: randomized 27% (the method of randomization and allocation concealment not described), blinded 0%, sample-size calculation stated 0%, specifying the primary outcome 26%, numbers given with denominators 6%, and stating number of animals used 47%. Only being an orally presented (vs. poster presented) A (14/16 vs. 48/84, p = 0.025) predicted P. Reporting of studies in P was of poor quality: randomized 39% (the method of randomization and allocation concealment not described), likely blinded 6%, primary outcome specified 5%, sample size calculation stated 0%, numbers given with denominators 34%, and number of animals used stated 56%. Changes in reporting from A to P occurred: from non-randomized to randomized 19%, from non-blinded to blinded 6%, from negative to positive outcomes 8%, from having to not having a stated primary outcome 16%, and from non-statistically to statistically significant findings 37%. Post-hoc, using publication data, P was predicted by having positive outcomes (published 62/62, unpublished 33/38; p = 0.003), or statistically significant results (published 58/62, unpublished 20/38; p < 0.001). Only 62% (95% CI 52-71%) of animal research A are subsequently P; this was predicted by oral presentation of the A, finally having positive outcomes, and finally having statistically significant results. Publication bias is prevalent in critical care animal research.

Current limiting cathodes for non transit-time limited operation of InP TED's in the 100 GHz window

NASA Astrophysics Data System (ADS)

Friscouri, Marie-Renée; Rolland, Paul-Alain

1985-03-01

Reverse-biased low-barrier Schottky contact and reverse-biased isotype GaInAsP/InP heterojunction, used as current limiting cathodes for InP TED's, are investigated on the basis of output power and efficiency improvement as compared to N +NN + devices.

Gate-Tunable WSe2/SnSe2 Backward Diode with Ultrahigh-Reverse Rectification Ratio.

PubMed

Murali, Krishna; Dandu, Medha; Das, Sarthak; Majumdar, Kausik

2018-02-14

Backward diodes conduct more efficiently in the reverse bias than in the forward bias, providing superior high-frequency response, temperature stability, radiation hardness, and 1/f noise performance than a conventional diode conducting in the forward direction. Here, we demonstrate a van der Waals material-based backward diode by exploiting the giant staggered band offsets of WSe 2 /SnSe 2 vertical heterojunction. The diode exhibits an ultrahigh-reverse rectification ratio (R) of ∼2.1 × 10 4 , and the same is maintained up to an unusually large bias of 1.5 V-outperforming existing backward diode reports using conventional bulk semiconductors as well as one- and two-dimensional materials by more than an order of magnitude while maintaining an impressive curvature coefficient (γ) of ∼37 V -1 . The transport mechanism in the diode is shown to be efficiently tunable by external gate and drain bias, as well as by the thickness of the WSe 2 layer and the type of metal contacts used. These results pave the way for practical electronic circuit applications using two-dimensional materials and their heterojunctions.

Efficient Optical Logic, Interconnections and Processing Using Quantum Confined Structures

DTIC Science & Technology

1991-05-01

No bis I With bias Ra ( b ’ OotI o lNo bias Use Il) felectro-refraicc n to phase-s’:t A- X I 3 Wavelength 3 Figure II-1. Efficient modulation in a...operation. The top (bottom) mirror of an AFP structure has an amplitude reflection coefficient of rt( b ) and power reflectivity of RT( B )=Ir0)12, viewed...and ( b ) for the case of a=O and a=ln(rb/rt), respectively. Adding (1) and (2), we obtain the total amplitude reflection rto as: -13- I Ii/V aoabl

Development of reverse biased p-n junction electron emission

NASA Technical Reports Server (NTRS)

Fowler, P.; Muly, E. C.

1971-01-01

A cold cathode emitter of hot electrons for use as a source of electrons in vacuum gauges and mass spectrometers was developed using standard Norton electroluminescent silicon carbide p-n diodes operated under reverse bias conditions. Continued development including variations in the geometry of these emitters was carried out such that emitters with an emission efficiency (emitted current/junction current) as high as 3 x 10-0.00001 were obtained. Pulse measurements of the diode characteristics were made and showed that higher efficiency can be attained under pulse conditions probably due to the resulting lower temperatures resulting from such operation.

The mixed impact of medical school on medical students' implicit and explicit weight bias.

PubMed

Phelan, Sean M; Puhl, Rebecca M; Burke, Sara E; Hardeman, Rachel; Dovidio, John F; Nelson, David B; Przedworski, Julia; Burgess, Diana J; Perry, Sylvia; Yeazel, Mark W; van Ryn, Michelle

2015-10-01

Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web-based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Medical schools may reduce students' weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients. © 2015 John Wiley & Sons Ltd.

Estimation of treatment effects in all-comers randomized clinical trials with a predictive marker.

PubMed

Choai, Yuki; Matsui, Shigeyuki

2015-03-01

Recent advances in genomics and biotechnologies have accelerated the development of molecularly targeted treatments and accompanying markers to predict treatment responsiveness. However, it is common at the initiation of a definitive phase III clinical trial that there is no compelling biological basis or early trial data for a candidate marker regarding its capability in predicting treatment effects. In this case, it is reasonable to include all patients as eligible for randomization, but to plan for prospective subgroup analysis based on the marker. One analysis plan in such all-comers designs is the so-called fallback approach that first tests for overall treatment efficacy and then proceeds to testing in a biomarker-positive subgroup if the first test is not significant. In this approach, owing to the adaptive nature of the analysis and a correlation between the two tests, a bias will arise in estimating the treatment effect in the biomarker-positive subgroup after a non-significant first overall test. In this article, we formulate the bias function and show a difficulty in obtaining unbiased estimators for a whole range of an associated parameter. To address this issue, we propose bias-corrected estimation methods, including those based on an approximation of the bias function under a bounded range of the parameter using polynomials. We also provide an interval estimation method based on a bivariate doubly truncated normal distribution. Simulation experiments demonstrated a success in bias reduction. Application to a phase III trial for lung cancer is provided. © 2014, The International Biometric Society.

A multi-site proof-of-concept investigation of computerized approach-avoidance training in adolescent cannabis users.

PubMed

Jacobus, Joanna; Taylor, Charles T; Gray, Kevin M; Meredith, Lindsay R; Porter, Anna M; Li, Irene; Castro, Norma; Squeglia, Lindsay M

2018-06-01

Few effective treatment options exist for cannabis-using youth. This pilot study aimed to test Approach-Avoidance Training to reduce cannabis use with non-treatment-seeking adolescents. Eighty cannabis-using non-treatment-seeking adolescents (average age 19) were recruited from San Diego, California and Charleston, South Carolina, and randomized to complete either six sessions of Cannabis Approach-Avoidance Task Training (CAAT-training) designed to reduce automatic approach biases for cannabis cues or CAAT-sham training. Change in two primary outcome variables was examined: 1) cannabis approach bias and 2) percent cannabis use days over study enrollment. Change in percent alcohol use days over study enrollment was explored as a secondary outcome. A mixed models repeated measures analysis confirmed the group by time interaction effect for approach bias failed to reach statistical significance (p = .06). Significant group by time interaction effects (ps < 0.05) predicted percent days of cannabis and alcohol use over study enrollment. Participants randomized to the avoid cannabis condition (CAAT-training) reported 7% fewer days of cannabis use compared to 0% change for sham; unexpectedly, those in the avoid cannabis condition reported 10% percent more alcohol use days compared to 3% more for sham. Computerized cognitive bias modification paradigms may have utility in reducing adolescent cannabis use. Future work should consider developing a paradigm that addresses both cannabis and alcohol, as well as alternative computerized approaches for coping with addictive behavior in conjunction with bias modification. Copyright © 2018 Elsevier B.V. All rights reserved.

Investigating the (cost-) effectiveness of attention bias modification (ABM) for outpatients with major depressive disorder (MDD): a randomized controlled trial protocol.

PubMed

Ferrari, Gina R A; Becker, Eni S; Smit, Filip; Rinck, Mike; Spijker, Jan

2016-11-03

Despite the range of available, evidence-based treatment options for Major Depressive Disorder (MDD), the rather low response and remission rates suggest that treatment is not optimal, yet. Computerized attention bias modification (ABM) trainings may have the potential to be provided as cost-effective intervention as adjunct to usual care (UC), by speeding up recovery and bringing more patients into remission. Research suggests, that a selective attention for negative information contributes to development and maintenance of depression and that reducing this negative bias might be of therapeutic value. Previous ABM studies in depression, however, have been limited by small sample sizes, lack of long-term follow-up measures or focus on sub-clinical samples. This study aims at evaluating the long-term (cost-) effectiveness of internet-based ABM, as add-on treatment to UC in adult outpatients with MDD, in a specialized mental health care setting. This study presents a double-blind randomized controlled trial in two parallel groups with follow-ups at 1, 6, and 12 months, combined with an economic evaluation. One hundred twenty six patients, diagnosed with MDD, who are registered for specialized outpatient services at a mental health care organization in the Netherlands, are randomized into either a positive training (towards positive and away from negative stimuli) or a sham training, as control condition (continuous attentional bias assessment). Patients complete eight training sessions (seven at home) during a period of two weeks (four weekly sessions). Primary outcome measures are change in attentional bias (pre- to post-test), mood response to stress (at post-test) and long-term effects on depressive symptoms (up to 1-year follow-up). Secondary outcome measures include rumination, resilience, positive and negative affect, and transfer to other cognitive measures (i.e., attentional bias for verbal stimuli, cognitive control, positive mental imagery), as well as quality of life and costs. This is the first study investigating the long-term effects of ABM in adult outpatients with MDD, alongside an economic evaluation. Next to exploring the mechanism underlying ABM effects, this study provides first insight into the effects of combining ABM and UC and the potential implementation of ABM in clinical practice. Trialregister.nl, NTR5285 . Registered 20 July 2015.

The Good, the Bad, and the Irrelevant: Neural Mechanisms of Learning Real and Hypothetical Rewards and Effort

PubMed Central

Kolling, Nils; Nelissen, Natalie; Wittmann, Marco K.; Harmer, Catherine J.; Rushworth, Matthew F. S.

2015-01-01

Natural environments are complex, and a single choice can lead to multiple outcomes. Agents should learn which outcomes are due to their choices and therefore relevant for future decisions and which are stochastic in ways common to all choices and therefore irrelevant for future decisions between options. We designed an experiment in which human participants learned the varying reward and effort magnitudes of two options and repeatedly chose between them. The reward associated with a choice was randomly real or hypothetical (i.e., participants only sometimes received the reward magnitude associated with the chosen option). The real/hypothetical nature of the reward on any one trial was, however, irrelevant for learning the longer-term values of the choices, and participants ought to have only focused on the informational content of the outcome and disregarded whether it was a real or hypothetical reward. However, we found that participants showed an irrational choice bias, preferring choices that had previously led, by chance, to a real reward in the last trial. Amygdala and ventromedial prefrontal activity was related to the way in which participants' choices were biased by real reward receipt. By contrast, activity in dorsal anterior cingulate cortex, frontal operculum/anterior insula, and especially lateral anterior prefrontal cortex was related to the degree to which participants resisted this bias and chose effectively in a manner guided by aspects of outcomes that had real and more sustained relationships with particular choices, suppressing irrelevant reward information for more optimal learning and decision making. SIGNIFICANCE STATEMENT In complex natural environments, a single choice can lead to multiple outcomes. Human agents should only learn from outcomes that are due to their choices, not from outcomes without such a relationship. We designed an experiment to measure learning about reward and effort magnitudes in an environment in which other features of the outcome were random and had no relationship with choice. We found that, although people could learn about reward magnitudes, they nevertheless were irrationally biased toward repeating certain choices as a function of the presence or absence of random reward features. Activity in different brain regions in the prefrontal cortex either reflected the bias or reflected resistance to the bias. PMID:26269633

Non-Uniform Bias Enhancement of a Varactor-Tuned FSS used with a Low Profile 2.4 GHz Dipole Antenna

NASA Technical Reports Server (NTRS)

Cure, David; Weller, Thomas M.; Miranda, Felix A.

2012-01-01

In this paper a low profile antenna using a nonuniformly biased varactor-tuned frequency selective surface (FSS) is presented. The tunable FSS avoids the use of vias and has a simplified DC bias network. The voltages to the DC bias ports can be varied independently allowing adjustment in the frequency response and enhanced radiation properties. The measured data demonstrate tunability from 2.15 GHz to 2.63 GHz with peak efficiencies that range from 50% to 90% and instantaneous bandwidths of 50 MHz to 280 MHz within the tuning range. The total antenna thickness is approximately lambda/45.

Bias-selectable dual-band mid-/long-wavelength infrared photodetectors based on InAs/InAs{sub 1−x}Sb{sub x} type-II superlattices

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

Haddadi, A.; Chevallier, R.; Chen, G.

2015-01-05

A high performance bias-selectable mid-/long-wavelength infrared photodetector based on InAs/InAs{sub 1−x}Sb{sub x} type-II superlattices on GaSb substrate has been demonstrated. The mid- and long-wavelength channels' 50% cut-off wavelengths were ∼5.1 and ∼9.5 μm at 77 K. The mid-wavelength channel exhibited a quantum efficiency of 45% at 100 mV bias voltage under front-side illumination and without any anti-reflection coating. With a dark current density of 1 × 10{sup −7} A/cm{sup 2} under 100 mV applied bias, the mid-wavelength channel exhibited a specific detectivity of 8.2 × 10{sup 12 }cm·√(Hz)/W at 77 K. The long-wavelength channel exhibited a quantum efficiency of 40%, a dark current density of 5.7 × 10{sup −4} A/cm{sup 2} undermore » −150 mV applied bias at 77 K, providing a specific detectivity value of 1.64 × 10{sup 11 }cm·√(Hz)/W.« less

A randomized approach to speed up the analysis of large-scale read-count data in the application of CNV detection.

PubMed

Wang, WeiBo; Sun, Wei; Wang, Wei; Szatkiewicz, Jin

2018-03-01

The application of high-throughput sequencing in a broad range of quantitative genomic assays (e.g., DNA-seq, ChIP-seq) has created a high demand for the analysis of large-scale read-count data. Typically, the genome is divided into tiling windows and windowed read-count data is generated for the entire genome from which genomic signals are detected (e.g. copy number changes in DNA-seq, enrichment peaks in ChIP-seq). For accurate analysis of read-count data, many state-of-the-art statistical methods use generalized linear models (GLM) coupled with the negative-binomial (NB) distribution by leveraging its ability for simultaneous bias correction and signal detection. However, although statistically powerful, the GLM+NB method has a quadratic computational complexity and therefore suffers from slow running time when applied to large-scale windowed read-count data. In this study, we aimed to speed up substantially the GLM+NB method by using a randomized algorithm and we demonstrate here the utility of our approach in the application of detecting copy number variants (CNVs) using a real example. We propose an efficient estimator, the randomized GLM+NB coefficients estimator (RGE), for speeding up the GLM+NB method. RGE samples the read-count data and solves the estimation problem on a smaller scale. We first theoretically validated the consistency and the variance properties of RGE. We then applied RGE to GENSENG, a GLM+NB based method for detecting CNVs. We named the resulting method as "R-GENSENG". Based on extensive evaluation using both simulated and empirical data, we concluded that R-GENSENG is ten times faster than the original GENSENG while maintaining GENSENG's accuracy in CNV detection. Our results suggest that RGE strategy developed here could be applied to other GLM+NB based read-count analyses, i.e. ChIP-seq data analysis, to substantially improve their computational efficiency while preserving the analytic power.

Clinicians' implicit ethnic/racial bias and perceptions of care among Black and Latino patients.

PubMed

Blair, Irene V; Steiner, John F; Fairclough, Diane L; Hanratty, Rebecca; Price, David W; Hirsh, Holen K; Wright, Leslie A; Bronsert, Michael; Karimkhani, Elhum; Magid, David J; Havranek, Edward P

2013-01-01

We investigated whether clinicians' explicit and implicit ethnic/racial bias is related to black and Latino patients' perceptions of their care in established clinical relationships. We administered a telephone survey to 2,908 patients, stratified by ethnicity/race, and randomly selected from the patient panels of 134 clinicians who had previously completed tests of explicit and implicit ethnic/racial bias. Patients completed the Primary Care Assessment Survey, which addressed their clinicians' interpersonal treatment, communication, trust, and contextual knowledge. We created a composite measure of patient-centered care from the 4 subscales. Levels of explicit bias were low among clinicians and unrelated to patients' perceptions. Levels of implicit bias varied among clinicians, and those with greater implicit bias were rated lower in patient-centered care by their black patients as compared with a reference group of white patients (P = .04). Latino patients gave the clinicians lower ratings than did other groups (P <.0001), and this did not depend on the clinicians' implicit bias (P = .98). This is among the first studies to investigate clinicians' implicit bias and communication processes in ongoing clinical relationships. Our findings suggest that clinicians' implicit bias may jeopardize their clinical relationships with black patients, which could have negative effects on other care processes. As such, this finding supports the Institute of Medicine's suggestion that clinician bias may contribute to health disparities. Latinos' overall greater concerns about their clinicians appear to be based on aspects of care other than clinician bias.

Quality of evidence revealing subtle gender biases in science is in the eye of the beholder.

PubMed

Handley, Ian M; Brown, Elizabeth R; Moss-Racusin, Corinne A; Smith, Jessi L

2015-10-27

Scientists are trained to evaluate and interpret evidence without bias or subjectivity. Thus, growing evidence revealing a gender bias against women-or favoring men-within science, technology, engineering, and mathematics (STEM) settings is provocative and raises questions about the extent to which gender bias may contribute to women's underrepresentation within STEM fields. To the extent that research illustrating gender bias in STEM is viewed as convincing, the culture of science can begin to address the bias. However, are men and women equally receptive to this type of experimental evidence? This question was tested with three randomized, double-blind experiments-two involving samples from the general public (n = 205 and 303, respectively) and one involving a sample of university STEM and non-STEM faculty (n = 205). In all experiments, participants read an actual journal abstract reporting gender bias in a STEM context (or an altered abstract reporting no gender bias in experiment 3) and evaluated the overall quality of the research. Results across experiments showed that men evaluate the gender-bias research less favorably than women, and, of concern, this gender difference was especially prominent among STEM faculty (experiment 2). These results suggest a relative reluctance among men, especially faculty men within STEM, to accept evidence of gender biases in STEM. This finding is problematic because broadening the participation of underrepresented people in STEM, including women, necessarily requires a widespread willingness (particularly by those in the majority) to acknowledge that bias exists before transformation is possible.

Remote sensing leaf water stress in coffee (Coffea arabica) using secondary effects of water absorption and random forests

NASA Astrophysics Data System (ADS)

Chemura, Abel; Mutanga, Onisimo; Dube, Timothy

2017-08-01

Water management is an important component in agriculture, particularly for perennial tree crops such as coffee. Proper detection and monitoring of water stress therefore plays an important role not only in mitigating the associated adverse impacts on crop growth and productivity but also in reducing expensive and environmentally unsustainable irrigation practices. Current methods for water stress detection in coffee production mainly involve monitoring plant physiological characteristics and soil conditions. In this study, we tested the ability of selected wavebands in the VIS/NIR range to predict plant water content (PWC) in coffee using the random forest algorithm. An experiment was set up such that coffee plants were exposed to different levels of water stress and reflectance and plant water content measured. In selecting appropriate parameters, cross-correlation identified 11 wavebands, reflectance difference identified 16 and reflectance sensitivity identified 22 variables related to PWC. Only three wavebands (485 nm, 670 nm and 885 nm) were identified by at least two methods as significant. The selected wavebands were trained (n = 36) and tested on independent data (n = 24) after being integrated into the random forest algorithm to predict coffee PWC. The results showed that the reflectance sensitivity selected bands performed the best in water stress detection (r = 0.87, RMSE = 4.91% and pBias = 0.9%), when compared to reflectance difference (r = 0.79, RMSE = 6.19 and pBias = 2.5%) and cross-correlation selected wavebands (r = 0.75, RMSE = 6.52 and pBias = 1.6). These results indicate that it is possible to reliably predict PWC using wavebands in the VIS/NIR range that correspond with many of the available multispectral scanners using random forests and further research at field and landscape scale is required to operationalize these findings.

Randomized Trials Built on Sand: Examples from COPD, Hormone Therapy, and Cancer

PubMed Central

Suissa, Samy

2012-01-01

The randomized controlled trial is the fundamental study design to evaluate the effectiveness of medications and receive regulatory approval. Observational studies, on the other hand, are essential to address post-marketing drug safety issues but have also been used to uncover new indications or new benefits for already marketed drugs. Hormone replacement therapy (HRT) for instance, effective for menopausal symptoms, was reported in several observational studies during the 1980s and 1990s to also significantly reduce the incidence of coronary heart disease. This claim was refuted in 2002 by the large-scale Women’s Health Initiative randomized trial. An example of a new indication for an old drug is that of metformin, an anti-diabetic medication, which is being hailed as a potential anti-cancer agent, primarily on the basis of several recent observational studies that reported impressive reductions in cancer incidence and mortality with its use. These observational studies have now sparked the conduct of large-scale randomized controlled trials currently ongoing in cancer. We show in this paper that the spectacular effects on new indications or new outcomes reported in many observational studies in chronic obstructive pulmonary disease (COPD), HRT, and cancer are the result of time-related biases, such as immortal time bias, that tend to seriously exaggerate the benefits of a drug and that eventually disappear with the proper statistical analysis. In all, while observational studies are central to assess the effects of drugs, their proper design and analysis are essential to avoid bias. The scientific evidence on the potential beneficial effects in new indications of existing drugs will need to be more carefully assessed before embarking on long and expensive unsubstantiated trials. PMID:23908838

Correlation of anomalous write error rates and ferromagnetic resonance spectrum in spin-transfer-torque-magnetic-random-access-memory devices containing in-plane free layers

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

Evarts, Eric R.; Rippard, William H.; Pufall, Matthew R.

In a small fraction of magnetic-tunnel-junction-based magnetic random-access memory devices with in-plane free layers, the write-error rates (WERs) are higher than expected on the basis of the macrospin or quasi-uniform magnetization reversal models. In devices with increased WERs, the product of effective resistance and area, tunneling magnetoresistance, and coercivity do not deviate from typical device properties. However, the field-swept, spin-torque, ferromagnetic resonance (FS-ST-FMR) spectra with an applied DC bias current deviate significantly for such devices. With a DC bias of 300 mV (producing 9.9 × 10{sup 6} A/cm{sup 2}) or greater, these anomalous devices show an increase in the fraction of the power presentmore » in FS-ST-FMR modes corresponding to higher-order excitations of the free-layer magnetization. As much as 70% of the power is contained in higher-order modes compared to ≈20% in typical devices. Additionally, a shift in the uniform-mode resonant field that is correlated with the magnitude of the WER anomaly is detected at DC biases greater than 300 mV. These differences in the anomalous devices indicate a change in the micromagnetic resonant mode structure at high applied bias.« less

Does attention bias modification improve attentional control? A double-blind randomized experiment with individuals with social anxiety disorder.

PubMed

Heeren, Alexandre; Mogoaşe, Cristina; McNally, Richard J; Schmitz, Anne; Philippot, Pierre

2015-01-01

People with anxiety disorders often exhibit an attentional bias for threat. Attention bias modification (ABM) procedure may reduce this bias, thereby diminishing anxiety symptoms. In ABM, participants respond to probes that reliably follow non-threatening stimuli (e.g., neutral faces) such that their attention is directed away from concurrently presented threatening stimuli (e.g., disgust faces). Early studies showed that ABM reduced anxiety more than control procedures lacking any contingency between valenced stimuli and probes. However, recent work suggests that no-contingency training and training toward threat cues can be as effective as ABM in reducing anxiety, implying that any training may increase executive control over attention, thereby helping people inhibit their anxious thoughts. Extending this work, we randomly assigned participants with DSM-IV diagnosed social anxiety disorder to either training toward non-threat (ABM), training toward threat, or no-contingency condition, and we used the attention network task (ANT) to assess all three components of attention. After two training sessions, subjects in all three conditions exhibited indistinguishably significant declines from baseline to post-training in self-report and behavioral measures of anxiety on an impromptu speech task. Moreover, all groups exhibited similarly significant improvements on the alerting and executive (but not orienting) components of attention. Implications for ABM research are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Challenges of Guarantee-Time Bias

PubMed Central

Giobbie-Hurder, Anita; Gelber, Richard D.; Regan, Meredith M.

2013-01-01

The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy. PMID:23835712

A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias.

PubMed

Ma, Xiaoye; Chen, Yong; Cole, Stephen R; Chu, Haitao

2016-12-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities, and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. © The Author(s) 2014.

A Hybrid Bayesian Hierarchical Model Combining Cohort and Case-control Studies for Meta-analysis of Diagnostic Tests: Accounting for Partial Verification Bias

PubMed Central

Ma, Xiaoye; Chen, Yong; Cole, Stephen R.; Chu, Haitao

2014-01-01

To account for between-study heterogeneity in meta-analysis of diagnostic accuracy studies, bivariate random effects models have been recommended to jointly model the sensitivities and specificities. As study design and population vary, the definition of disease status or severity could differ across studies. Consequently, sensitivity and specificity may be correlated with disease prevalence. To account for this dependence, a trivariate random effects model had been proposed. However, the proposed approach can only include cohort studies with information estimating study-specific disease prevalence. In addition, some diagnostic accuracy studies only select a subset of samples to be verified by the reference test. It is known that ignoring unverified subjects may lead to partial verification bias in the estimation of prevalence, sensitivities and specificities in a single study. However, the impact of this bias on a meta-analysis has not been investigated. In this paper, we propose a novel hybrid Bayesian hierarchical model combining cohort and case-control studies and correcting partial verification bias at the same time. We investigate the performance of the proposed methods through a set of simulation studies. Two case studies on assessing the diagnostic accuracy of gadolinium-enhanced magnetic resonance imaging in detecting lymph node metastases and of adrenal fluorine-18 fluorodeoxyglucose positron emission tomography in characterizing adrenal masses are presented. PMID:24862512

[Correlation of codon biases and potential secondary structures with mRNA translation efficiency in unicellular organisms].

PubMed

Vladimirov, N V; Likhoshvaĭ, V A; Matushkin, Iu G

2007-01-01

Gene expression is known to correlate with degree of codon bias in many unicellular organisms. However, such correlation is absent in some organisms. Recently we demonstrated that inverted complementary repeats within coding DNA sequence must be considered for proper estimation of translation efficiency, since they may form secondary structures that obstruct ribosome movement. We have developed a program for estimation of potential coding DNA sequence expression in defined unicellular organism using its genome sequence. The program computes elongation efficiency index. Computation is based on estimation of coding DNA sequence elongation efficiency, taking into account three key factors: codon bias, average number of inverted complementary repeats, and free energy of potential stem-loop structures formed by the repeats. The influence of these factors on translation is numerically estimated. An optimal proportion of these factors is computed for each organism individually. Quantitative translational characteristics of 384 unicellular organisms (351 bacteria, 28 archaea, 5 eukaryota) have been computed using their annotated genomes from NCBI GenBank. Five potential evolutionary strategies of translational optimization have been determined among studied organisms. A considerable difference of preferred translational strategies between Bacteria and Archaea has been revealed. Significant correlations between elongation efficiency index and gene expression levels have been shown for two organisms (S. cerevisiae and H. pylori) using available microarray data. The proposed method allows to estimate numerically the coding DNA sequence translation efficiency and to optimize nucleotide composition of heterologous genes in unicellular organisms. http://www.mgs.bionet.nsc.ru/mgs/programs/eei-calculator/.

A trigger-based design for evaluating the safety of in utero antiretroviral exposure in uninfected children of human immunodeficiency virus-infected mothers.

PubMed

Williams, Paige L; Seage, George R; Van Dyke, Russell B; Siberry, George K; Griner, Raymond; Tassiopoulos, Katherine; Yildirim, Cenk; Read, Jennifer S; Huo, Yanling; Hazra, Rohan; Jacobson, Denise L; Mofenson, Lynne M; Rich, Kenneth

2012-05-01

The Pediatric HIV/AIDS Cohort Study's Surveillance Monitoring of ART Toxicities Study is a prospective cohort study conducted at 22 US sites between 2007 and 2011 that was designed to evaluate the safety of in utero antiretroviral drug exposure in children not infected with human immunodeficiency virus who were born to mothers who were infected. This ongoing study uses a "trigger-based" design; that is, initial assessments are conducted on all children, and only those meeting certain thresholds or "triggers" undergo more intensive evaluations to determine whether they have had an adverse event (AE). The authors present the estimated rates of AEs for each domain of interest in the Surveillance Monitoring of ART Toxicities Study. They also evaluated the efficiency of this trigger-based design for estimating AE rates and for testing associations between in utero exposures to antiretroviral drugs and AEs. The authors demonstrate that estimated AE rates from the trigger-based design are unbiased after correction for the sensitivity of the trigger for identifying AEs. Even without correcting for bias based on trigger sensitivity, the trigger approach is generally more efficient for estimating AE rates than is evaluating a random sample of the same size. Minor losses in efficiency when comparing AE rates between persons exposed and unexposed in utero to particular antiretroviral drugs or drug classes were observed under most scenarios.

Attention Training and the Threat Bias: An ERP Study

PubMed Central

O’Toole, Laura; Dennis, Tracy A.

2011-01-01

Anxiety is characterized by exaggerated attention to threat. Several studies suggest that this threat bias plays a causal role in the development and maintenance of anxiety disorders. Furthermore, although the threat bias can be reduced in anxious individuals and induced in non-anxious individual, the attentional mechanisms underlying these changes remain unclear. To address this issue, 49 non-anxious adults were randomly assigned to either attentional training toward or training away from threat using a modified version of the dot probe task. Behavioral measures of attentional biases were also generated pre- and post-training using the dot probe task. Event-related potentials (ERPs) were generated to threat and non-threat face pairs and probes during pre- and post-training assessments. Effects of training on behavioral measures of the threat bias were significant, but only for those participants showing pre-training biases. Attention training also influenced early spatial attention, as measured by post-training P1 amplitudes to cues. Results illustrate the importance of taking pre-training attention biases in non-anxious individuals into account when evaluating the effects of attention training and tracking physiological changes in attention following training. PMID:22083026

Testing whether decision aids introduce cognitive biases: results of a randomized trial.

PubMed

Ubel, Peter A; Smith, Dylan M; Zikmund-Fisher, Brian J; Derry, Holly A; McClure, Jennifer; Stark, Azadeh; Wiese, Cheryl; Greene, Sarah; Jankovic, Aleksandra; Fagerlin, Angela

2010-08-01

Women at high risk of breast cancer face a difficult decision whether to take medications like tamoxifen to prevent a first breast cancer diagnosis. Decision aids (DAs) offer a promising method of helping them make this decision. But concern lingers that DAs might introduce cognitive biases. We recruited 663 women at high risk of breast cancer and presented them with a DA designed to experimentally test potential methods of identifying and reducing cognitive biases that could influence this decision, by varying specific aspects of the DA across participants in a factorial design. Participants were susceptible to a cognitive bias - an order effect - such that those who learned first about the risks of tamoxifen thought more favorably of the drug than women who learned first about the benefits. This order effect was eliminated among women who received additional information about competing health risks. We discovered that the order of risk/benefit information influenced women's perceptions of tamoxifen. This bias was eliminated by providing contextual information about competing health risks. We have demonstrated the feasibility of using factorial experimental designs to test whether DAs introduce cognitive biases, and whether specific elements of DAs can reduce such biases. Published by Elsevier Ireland Ltd.

A reconfigurable waveguide for energy-efficient transmission and local manipulation of information in a nanomagnetic device

NASA Astrophysics Data System (ADS)

Haldar, Arabinda; Kumar, Dheeraj; Adeyeye, Adekunle Olusola

2016-05-01

Spin-wave-based devices promise to usher in an era of low-power computing where information is carried by the precession of the electrons' spin instead of dissipative translation of their charge. This potential is, however, undermined by the need for a bias magnetic field, which must remain powered on to maintain an anisotropic device characteristic. Here, we propose a reconfigurable waveguide design that can transmit and locally manipulate spin waves without the need for any external bias field once initialized. We experimentally demonstrate the transmission of spin waves in straight as well as curved waveguides without a bias field, which has been elusive so far. Furthermore, we experimentally show a binary gating of the spin-wave signal by controlled switching of the magnetization, locally, in the waveguide. The results have potential implications in high-density integration and energy-efficient operation of nanomagnetic devices at room temperature.

Sol-gel synthesis of Cu-doped p-CdS nanoparticles and their analysis as p-CdS/n-ZnO thin film photodiode

NASA Astrophysics Data System (ADS)

Arya, Sandeep; Sharma, Asha; Singh, Bikram; Riyas, Mohammad; Bandhoria, Pankaj; Aatif, Mohammad; Gupta, Vinay

2018-05-01

Copper (Cu) doped p-CdS nanoparticles have been synthesized via sol-gel method. The as-synthesized nanoparticles were successfully characterized and implemented for fabrication of Glass/ITO/n-ZnO/p-CdS/Al thin film photodiode. The fabricated device is tested for small (-1 V to +1 V) bias voltage. Results verified that the junction leakage current within the dark is very small. During reverse bias condition, the maximum amount of photocurrent is obtained under illumination of 100 μW/cm2. Electrical characterizations confirmed that the external quantum efficiency (EQE), gain and responsivity of n-ZnO/p-CdS photodiode show improved photo response than conventional p-type materials for such a small bias voltage. It is therefore revealed that the Cu-doped CdS nanoparticles is an efficient p-type material for fabrication of thin film photo-devices.

Efficacy of Psychotherapies for Borderline Personality Disorder: A Systematic Review and Meta-analysis.

PubMed

Cristea, Ioana A; Gentili, Claudio; Cotet, Carmen D; Palomba, Daniela; Barbui, Corrado; Cuijpers, Pim

2017-04-01

Borderline personality disorder (BPD) is a debilitating condition, but several psychotherapies are considered effective. To conduct an updated systematic review and meta-analysis of randomized clinical trials to assess the efficacy of psychotherapies for BPD populations. Search terms were combined for borderline personality and randomized trials in PubMed, PsycINFO, EMBASE, and the Cochrane Central Register of Controlled Trials (from database inception to November 2015), as well as the reference lists of earlier meta-analyses. Included were randomized clinical trials of adults with diagnosed BPD randomized to psychotherapy exclusively or to a control intervention. Study selection differentiated stand-alone designs (in which an independent psychotherapy was compared with control interventions) from add-on designs (in which an experimental intervention added to usual treatment was compared with usual treatment alone). Data extraction coded characteristics of trials, participants, and interventions and assessed risk of bias using 4 domains of the Cochrane Collaboration Risk of Bias tool (independent extraction by 2 assessors). Outcomes were pooled using a random-effects model. Subgroup and meta-regression analyses were conducted. Standardized mean differences (Hedges g) were calculated using all outcomes reported in the trials for borderline symptoms, self-harm, suicide, health service use, and general psychopathology at posttest and follow-up. Differential treatment retention at posttest was analyzed, reporting odds ratios. Thirty-three trials (2256 participants) were included. For borderline-relevant outcomes combined (symptoms, self-harm, and suicide) at posttest, the investigated psychotherapies were moderately more effective than control interventions in stand-alone designs (g = 0.32; 95% CI, 0.14-0.51) and add-on designs (g = 0.40; 95% CI, 0.15-0.65). Results were similar for other outcomes, including stand-alone designs: self-harm (g = 0.32; 95% CI, 0.09-0.54), suicide (g = 0.44; 95% CI, 0.15-0.74), health service use (g = 0.40; 95% CI, 0.22-0.58), and general psychopathology (g = 0.32; 95% CI, 0.09-0.55), with no differences between design types. There were no significant differences in the odds ratios for treatment retention (1.32; 95% CI, 0.87-2.00 for stand-alone designs and 1.01; 95% CI, 0.55-1.87 for add-on designs). Thirteen trials reported borderline-relevant outcomes at follow-up (g = 0.45; 95% CI, 0.15-0.75). Dialectical behavior therapy (g = 0.34; 95% CI, 0.15-0.53) and psychodynamic approaches (g = 0.41; 95% CI, 0.12-0.69) were the only types of psychotherapies more effective than control interventions. Risk of bias was a significant moderator in subgroup and meta-regression analyses (slope β = -0.16; 95% CI, -0.29 to -0.03; P = .02). Publication bias was persistent, particularly for follow-up. Psychotherapies, most notably dialectical behavior therapy and psychodynamic approaches, are effective for borderline symptoms and related problems. Nonetheless, effects are small, inflated by risk of bias and publication bias, and particularly unstable at follow-up.

Biases in comparative analyses of extinction risk: mind the gap.

PubMed

González-Suárez, Manuela; Lucas, Pablo M; Revilla, Eloy

2012-11-01

1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species' traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species' traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14-99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Correction of confounding bias in non-randomized studies by appropriate weighting.

PubMed

Schmoor, Claudia; Gall, Christine; Stampf, Susanne; Graf, Erika

2011-03-01

In non-randomized studies, the assessment of a causal effect of treatment or exposure on outcome is hampered by possible confounding. Applying multiple regression models including the effects of treatment and covariates on outcome is the well-known classical approach to adjust for confounding. In recent years other approaches have been promoted. One of them is based on the propensity score and considers the effect of possible confounders on treatment as a relevant criterion for adjustment. Another proposal is based on using an instrumental variable. Here inference relies on a factor, the instrument, which affects treatment but is thought to be otherwise unrelated to outcome, so that it mimics randomization. Each of these approaches can basically be interpreted as a simple reweighting scheme, designed to address confounding. The procedures will be compared with respect to their fundamental properties, namely, which bias they aim to eliminate, which effect they aim to estimate, and which parameter is modelled. We will expand our overview of methods for analysis of non-randomized studies to methods for analysis of randomized controlled trials and show that analyses of both study types may target different effects and different parameters. The considerations will be illustrated using a breast cancer study with a so-called Comprehensive Cohort Study design, including a randomized controlled trial and a non-randomized study in the same patient population as sub-cohorts. This design offers ideal opportunities to discuss and illustrate the properties of the different approaches. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Avoidable waste related to inadequate methods and incomplete reporting of interventions: a systematic review of randomized trials performed in Sub-Saharan Africa.

PubMed

Ndounga Diakou, Lee Aymar; Ntoumi, Francine; Ravaud, Philippe; Boutron, Isabelle

2017-07-05

Randomized controlled trials (RCTs) are needed to improve health care in Sub-Saharan Africa (SSA). However, inadequate methods and incomplete reporting of interventions can prevent the transposition of research in practice which leads waste of research. The aim of this systematic review was to assess the avoidable waste in research related to inadequate methods and incomplete reporting of interventions in RCTs performed in SSA. We performed a methodological systematic review of RCTs performed in SSA and published between 1 January 2014 and 31 March 2015. We searched PubMed, the Cochrane library and the African Index Medicus to identify reports. We assessed the risk of bias using the Cochrane Risk of Bias tool, and for each risk of bias item, determined whether easy adjustments with no or minor cost could change the domain to low risk of bias. The reporting of interventions was assessed by using standardized checklists based on the Consolidated Standards for Reporting Trials, and core items of the Template for Intervention Description and Replication. Corresponding authors of reports with incomplete reporting of interventions were contacted to obtain additional information. Data were descriptively analyzed. Among 121 RCTs selected, 74 (61%) evaluated pharmacological treatments (PTs), including drugs and nutritional supplements; and 47 (39%) nonpharmacological treatments (NPTs) (40 participative interventions, 1 surgical procedure, 3 medical devices and 3 therapeutic strategies). Overall, the randomization sequence was adequately generated in 76 reports (62%) and the intervention allocation concealed in 48 (39%). The primary outcome was described as blinded in 46 reports (38%), and incomplete outcome data were adequately addressed in 78 (64%). Applying easy methodological adjustments with no or minor additional cost to trials with at least one domain at high risk of bias could have reduced the number of domains at high risk for 24 RCTs (19%). Interventions were completely reported for 73/121 (60%) RCTs: 51/74 (68%) of PTs and 22/47 (46%) of NPTs. Additional information was obtained from corresponding authors for 11/48 reports (22%). Inadequate methods and incomplete reporting of published SSA RCTs could be improved by easy and inexpensive methodological adjustments and adherence to reporting guidelines.

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

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

Sharma, D; Badano, A; Sempau, J

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. Themore » weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.« less

Nonlinear vs. linear biasing in Trp-cage folding simulations

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-01

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Nonlinear vs. linear biasing in Trp-cage folding simulations.

PubMed

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

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…