Sustained effects of attentional re-training on chocolate consumption.

PubMed

Kemps, Eva; Tiggemann, Marika; Elford, Joanna

2015-12-01

Accumulating evidence shows that cognitive bias modification produces immediate changes in attentional bias for, and consumption of, rewarding substances including food. This study examined the longevity of these attentional bias modification effects. A modified dot probe paradigm was used to determine whether alterations in biased attentional processing of food cues, and subsequent effects on consumption, were maintained at 24-h and one-week follow-up. One hundred and forty-nine undergraduate women were trained to direct their attention toward ('attend') or away from ('avoid') food cues (i.e., pictures of chocolate). Within each group, half received a single training session, the other half completed 5 weekly training sessions. Attentional bias for chocolate cues increased in the 'attend' group, and decreased in the 'avoid' group immediately post training. Participants in the 'avoid' group also ate disproportionately less of a chocolate food product in a so-called taste test than did those in the 'attend' group. Importantly, the observed re-training effects were maintained 24 h later and also one week later, but only following multiple training sessions. There are a number of limitations that could be addressed in future research: (a) the inclusion of a no-training control group, (b) the inclusion of a suspicion probe to detect awareness of the purpose of the taste test, and (c) the use of different tasks to assess and re-train attentional bias. The results showed sustained effects of attentional re-training on attentional bias and consumption. They further demonstrate the importance of administering multiple re-training sessions in attentional bias modification protocols. Copyright © 2014 Elsevier Ltd. All rights reserved.

Personality in general and clinical samples: Measurement invariance of the Multidimensional Personality Questionnaire.

PubMed

Eigenhuis, Annemarie; Kamphuis, Jan H; Noordhof, Arjen

2017-09-01

A growing body of research suggests that the same general dimensions can describe normal and pathological personality, but most of the supporting evidence is exploratory. We aim to determine in a confirmatory framework the extent to which responses on the Multidimensional Personality Questionnaire (MPQ) are identical across general and clinical samples. We tested the Dutch brief form of the MPQ (MPQ-BF-NL) for measurement invariance across a general population subsample (N = 365) and a clinical sample (N = 365), using Multiple Group Confirmatory Factor Analysis (MGCFA) and Multiple Group Exploratory Structural Equation Modeling (MGESEM). As an omnibus personality test, the MPQ-BF-NL revealed strict invariance, indicating absence of bias. Unidimensional per scale tests for measurement invariance revealed that 10% of items appeared to contain bias across samples. Item bias only affected the scale interpretation of Achievement, with individuals from the clinical sample more readily admitting to put high demands on themselves than individuals from the general sample, regardless of trait level. This formal test of equivalence provides strong evidence for the common structure of normal and pathological personality and lends further support to the clinical utility of the MPQ. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

A decade of studying implicit racial/ethnic bias in healthcare providers using the implicit association test.

PubMed

Maina, Ivy W; Belton, Tanisha D; Ginzberg, Sara; Singh, Ajit; Johnson, Tiffani J

2018-02-01

Disparities in the care and outcomes of US racial/ethnic minorities are well documented. Research suggests that provider bias plays a role in these disparities. The implicit association test enables measurement of implicit bias via tests of automatic associations between concepts. Hundreds of studies have examined implicit bias in various settings, but relatively few have been conducted in healthcare. The aim of this systematic review is to synthesize the current knowledge on the role of implicit bias in healthcare disparities. A comprehensive literature search of several databases between May 2015 and September 2016 identified 37 qualifying studies. Of these, 31 found evidence of pro-White or light-skin/anti-Black, Hispanic, American Indian or dark-skin bias among a variety of HCPs across multiple levels of training and disciplines. Fourteen studies examined the association between implicit bias and healthcare outcomes using clinical vignettes or simulated patients. Eight found no statistically significant association between implicit bias and patient care while six studies found that higher implicit bias was associated with disparities in treatment recommendations, expectations of therapeutic bonds, pain management, and empathy. All seven studies that examined the impact of implicit provider bias on real-world patient-provider interaction found that providers with stronger implicit bias demonstrated poorer patient-provider communication. Two studies examined the effect of implicit bias on real-world clinical outcomes. One found an association and the other did not. Two studies tested interventions aimed at reducing bias, but only one found a post-intervention reduction in implicit bias. This review reveals a need for more research exploring implicit bias in real-world patient care, potential modifiers and confounders of the effect of implicit bias on care, and strategies aimed at reducing implicit bias and improving patient-provider communication. Future studies have the opportunity to build on this current body of research, and in doing so will enable us to achieve equity in healthcare and outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome.

PubMed

Marine, Rachel; McCarren, Coleen; Vorrasane, Vansay; Nasko, Dan; Crowgey, Erin; Polson, Shawn W; Wommack, K Eric

2014-01-30

Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested. Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes. MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.

The effect of question order on evaluations of test performance: Can the bias dissolve?

PubMed

Bard, Gabriele; Weinstein, Yana

2017-10-01

Question difficulty order has been shown to affect students' global postdictions of test performance. We attempted to eliminate the bias by letting participants experience the question order manipulation multiple times. In all three experiments, participants answered general knowledge questions and self-evaluated their performance. In Experiment 1, participants studied questions and answers in easy-hard or hard-easy question order prior to taking a test in the same order. In Experiment 2, participants took the same test twice in the opposite question order (easy-hard then hard-easy, or hard-easy then easy-hard). In Experiment 3, participants took two different tests in the opposite question order (easy-hard then hard-easy, or hard-easy then easy-hard). In all three experiments, we were unable to eliminate the bias, which suggests that repeated exposure is insufficient to overcome a strong initial anchor.

Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)

A Strategy for Replacing Sum Scoring

ERIC Educational Resources Information Center

Ramsay, James O.; Wiberg, Marie

2017-01-01

This article promotes the use of modern test theory in testing situations where sum scores for binary responses are now used. It directly compares the efficiencies and biases of classical and modern test analyses and finds an improvement in the root mean squared error of ability estimates of about 5% for two designed multiple-choice tests and…

A Comparison of Three Tests of Mediation

ERIC Educational Resources Information Center

Warbasse, Rosalia E.

2009-01-01

A simulation study was conducted to evaluate the performance of three tests of mediation: the bias-corrected and accelerated bootstrap (Efron & Tibshirani, 1993), the asymmetric confidence limits test (MacKinnon, 2008), and a multiple regression approach described by Kenny, Kashy, and Bolger (1998). The evolution of these methods is reviewed and…

Does the IQ God Exist?

ERIC Educational Resources Information Center

Siegel, Linda S.

1995-01-01

Responds to "The Bell Curve" by arguing that IQ is merely a statistical fiction, an artificial construct not corresponding to any real entity. Discusses the "seductive statistical trap of factor analysis" as it relates to IQ tests, multiple intelligences, content and bias of IQ tests, lack of validity of IQ tests for individual…

40 CFR 53.35 - Test procedure for Class II and Class III methods for PM2.5 and PM-2.5

Code of Federal Regulations, 2010 CFR

2010-07-01

... reference method samplers shall be of single-filter design (not multi-filter, sequential sample design... and multiplicative bias (comparative slope and intercept). (1) For each test site, calculate the mean...

40 CFR 53.35 - Test procedure for Class II and Class III methods for PM2.5 and PM-2.5

Code of Federal Regulations, 2011 CFR

2011-07-01

... reference method samplers shall be of single-filter design (not multi-filter, sequential sample design... and multiplicative bias (comparative slope and intercept). (1) For each test site, calculate the mean...

40 CFR 53.35 - Test procedure for Class II and Class III methods for PM2.5 and PM−2.5.

Code of Federal Regulations, 2012 CFR

2012-07-01

... reference method samplers shall be of single-filter design (not multi-filter, sequential sample design... and multiplicative bias (comparative slope and intercept). (1) For each test site, calculate the mean...

Free-energy landscapes from adaptively biased methods: Application to quantum systems

NASA Astrophysics Data System (ADS)

Calvo, F.

2010-10-01

Several parallel adaptive biasing methods are applied to the calculation of free-energy pathways along reaction coordinates, choosing as a difficult example the double-funnel landscape of the 38-atom Lennard-Jones cluster. In the case of classical statistics, the Wang-Landau and adaptively biased molecular-dynamics (ABMD) methods are both found efficient if multiple walkers and replication and deletion schemes are used. An extension of the ABMD technique to quantum systems, implemented through the path-integral MD framework, is presented and tested on Ne38 against the quantum superposition method.

Biased interpretation and memory in children with varying levels of spider fear.

PubMed

Klein, Anke M; Titulaer, Geraldine; Simons, Carlijn; Allart, Esther; de Gier, Erwin; Bögels, Susan M; Becker, Eni S; Rinck, Mike

2014-01-01

This study investigated multiple cognitive biases in children simultaneously, to investigate whether spider-fearful children display an interpretation bias, a recall bias, and source monitoring errors, and whether these biases are specific for spider-related materials. Furthermore, the independent ability of these biases to predict spider fear was investigated. A total of 121 children filled out the Spider Anxiety and Disgust Screening for Children (SADS-C), and they performed an interpretation task, a memory task, and a Behavioural Assessment Test (BAT). As expected, a specific interpretation bias was found: Spider-fearful children showed more negative interpretations of ambiguous spider-related scenarios, but not of other scenarios. We also found specific source monitoring errors: Spider-fearful children made more fear-related source monitoring errors for the spider-related scenarios, but not for the other scenarios. Only limited support was found for a recall bias. Finally, interpretation bias, recall bias, and source monitoring errors predicted unique variance components of spider fear.

An improved standardization procedure to remove systematic low frequency variability biases in GCM simulations

NASA Astrophysics Data System (ADS)

Mehrotra, Rajeshwar; Sharma, Ashish

2012-12-01

The quality of the absolute estimates of general circulation models (GCMs) calls into question the direct use of GCM outputs for climate change impact assessment studies, particularly at regional scales. Statistical correction of GCM output is often necessary when significant systematic biasesoccur between the modeled output and observations. A common procedure is to correct the GCM output by removing the systematic biases in low-order moments relative to observations or to reanalysis data at daily, monthly, or seasonal timescales. In this paper, we present an extension of a recently published nested bias correction (NBC) technique to correct for the low- as well as higher-order moments biases in the GCM-derived variables across selected multiple time-scales. The proposed recursive nested bias correction (RNBC) approach offers an improved basis for applying bias correction at multiple timescales over the original NBC procedure. The method ensures that the bias-corrected series exhibits improvements that are consistently spread over all of the timescales considered. Different variations of the approach starting from the standard NBC to the more complex recursive alternatives are tested to assess their impacts on a range of GCM-simulated atmospheric variables of interest in downscaling applications related to hydrology and water resources. Results of the study suggest that three to five iteration RNBCs are the most effective in removing distributional and persistence related biases across the timescales considered.

A Tale of Two Tests (and of Two Examinees)

ERIC Educational Resources Information Center

Clauser, Amanda L.; Wainer, Howard

2016-01-01

It is widely accepted dogma that consequential decisions are better made with multiple measures, because using but a single one is thought more likely to be laden with biases and errors that can be better controlled with a wider source of evidence for making judgments. Unfortunately, advocates of using multiple measures too rarely provide detailed…

Structural Equivalence of Involvement in Problem Behavior by Adolescents across Racial Groups Using Multiple Group Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Williams, James H.; And Others

1996-01-01

Problem behavior theory predicts that adolescent problem behaviors are manifestations of a single behavioral syndrome. This study tested the validity of the theory across racial groups. Results indicate that multiple pathways are necessary to account for the problem behaviors and they support previous research indicating system response bias in…

Correction for Guessing in the Framework of the 3PL Item Response Theory

ERIC Educational Resources Information Center

Chiu, Ting-Wei

2010-01-01

Guessing behavior is an important topic with regard to assessing proficiency on multiple choice tests, particularly for examinees at lower levels of proficiency due to greater the potential for systematic error or bias which that inflates observed test scores. Methods that incorporate a correction for guessing on high-stakes tests generally rely…

Direct and indirect influences of fate control belief, gambling expectancy bias, and self-efficacy on problem gambling and negative mood among Chinese college students: a multiple mediation analysis.

PubMed

Tang, Catherine So-Kum; Wu, Anise M S

2010-12-01

A multiple mediation model was proposed to integrate core concepts of the social axioms framework and the social cognitive theory in order to understand gambling behavior. It was hypothesized that the influence of general fate control belief on problem gambling and negative mood would be mediated by gambling-specific beliefs. Data from 773 Chinese college recreational gamblers were collected. The bootstrapping procedure was used to test the multiple mediation hypotheses. Significant indirect effects of fate control belief on problem gambling and negative mood through two gambling-specific mediators were found. Gambling expectancy bias was a more salient mediator than gambling self-efficacy. Fate control belief was also found to have a significant direct effect on negative mood. In general, a high level of general fate control belief was related to greater gambling expectancy bias and lower self-efficacy in resisting gambling, which were in turn related to problem gambling and negative mood. Limitations and implications of the study were discussed.

Identifying Sources of Bias in EFL Writing Assessment through Multiple Trait Scoring

ERIC Educational Resources Information Center

Salmani-Nodoushan, Mohammad Ali

2009-01-01

For purposes of the present study, it was hypothesized that field (in)dependence would introduce systematic variance into EFL learners' performance on composition tests. 1743 freshman, sophomore, junior, and senior students all majoring in English at different Iranian universities and colleges took the Group Embedded Figures Test (GEFT). The…

Comment on 3PL IRT Adjustment for Guessing

ERIC Educational Resources Information Center

Chiu, Ting-Wei; Camilli, Gregory

2013-01-01

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

Detecting and removing multiplicative spatial bias in high-throughput screening technologies.

PubMed

Caraus, Iurie; Mazoure, Bogdan; Nadon, Robert; Makarenkov, Vladimir

2017-10-15

Considerable attention has been paid recently to improve data quality in high-throughput screening (HTS) and high-content screening (HCS) technologies widely used in drug development and chemical toxicity research. However, several environmentally- and procedurally-induced spatial biases in experimental HTS and HCS screens decrease measurement accuracy, leading to increased numbers of false positives and false negatives in hit selection. Although effective bias correction methods and software have been developed over the past decades, almost all of these tools have been designed to reduce the effect of additive bias only. Here, we address the case of multiplicative spatial bias. We introduce three new statistical methods meant to reduce multiplicative spatial bias in screening technologies. We assess the performance of the methods with synthetic and real data affected by multiplicative spatial bias, including comparisons with current bias correction methods. We also describe a wider data correction protocol that integrates methods for removing both assay and plate-specific spatial biases, which can be either additive or multiplicative. The methods for removing multiplicative spatial bias and the data correction protocol are effective in detecting and cleaning experimental data generated by screening technologies. As our protocol is of a general nature, it can be used by researchers analyzing current or next-generation high-throughput screens. The AssayCorrector program, implemented in R, is available on CRAN. makarenkov.vladimir@uqam.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Beam test results of a 16 ps timing system based on ultra-fast silicon detectors

DOE PAGES

Cartiglia, N.; Staiano, A.; Sola, V.; ...

2017-04-01

In this paper we report on the timing resolution obtained in a beam test with pions of 180 GeV/c momentum at CERN for the first production of 45 μm thick Ultra-Fast Silicon Detectors (UFSD). UFSD are based on the Low- Gain Avalanche Detector (LGAD) design, employing n-on-p silicon sensors with internal charge multiplication due to the presence of a thin, low-resistivity diffusion layer below the junction. The UFSD used in this test had a pad area of 1.7 mm 2. The gain was measured to vary between 5 and 70 depending on the sensor bias voltage. The experimental setup includedmore » three UFSD and a fast trigger consisting of a quartz bar readout by a SiPM. The timing resolution was determined by doing Gaussian fits to the time-of-flight of the particles between one or more UFSD and the trigger counter. For a single UFSD the resolution was measured to be 34 ps for a bias voltage of 200 V, and 27 ps for a bias voltage of 230 V. For the combination of 3 UFSD the timing resolution was 20 ps for a bias voltage of 200 V, and 16 ps for a bias voltage of 230 V.« less

Beam test results of a 16 ps timing system based on ultra-fast silicon detectors

NASA Astrophysics Data System (ADS)

Cartiglia, N.; Staiano, A.; Sola, V.; Arcidiacono, R.; Cirio, R.; Cenna, F.; Ferrero, M.; Monaco, V.; Mulargia, R.; Obertino, M.; Ravera, F.; Sacchi, R.; Bellora, A.; Durando, S.; Mandurrino, M.; Minafra, N.; Fadeyev, V.; Freeman, P.; Galloway, Z.; Gkougkousis, E.; Grabas, H.; Gruey, B.; Labitan, C. A.; Losakul, R.; Luce, Z.; McKinney-Martinez, F.; Sadrozinski, H. F.-W.; Seiden, A.; Spencer, E.; Wilder, M.; Woods, N.; Zatserklyaniy, A.; Pellegrini, G.; Hidalgo, S.; Carulla, M.; Flores, D.; Merlos, A.; Quirion, D.; Cindro, V.; Kramberger, G.; Mandić, I.; Mikuž, M.; Zavrtanik, M.

2017-04-01

In this paper we report on the timing resolution obtained in a beam test with pions of 180 GeV/c momentum at CERN for the first production of 45 μm thick Ultra-Fast Silicon Detectors (UFSD). UFSD are based on the Low-Gain Avalanche Detector (LGAD) design, employing n-on-p silicon sensors with internal charge multiplication due to the presence of a thin, low-resistivity diffusion layer below the junction. The UFSD used in this test had a pad area of 1.7 mm2. The gain was measured to vary between 5 and 70 depending on the sensor bias voltage. The experimental setup included three UFSD and a fast trigger consisting of a quartz bar readout by a SiPM. The timing resolution was determined by doing Gaussian fits to the time-of-flight of the particles between one or more UFSD and the trigger counter. For a single UFSD the resolution was measured to be 34 ps for a bias voltage of 200 V, and 27 ps for a bias voltage of 230 V. For the combination of 3 UFSD the timing resolution was 20 ps for a bias voltage of 200 V, and 16 ps for a bias voltage of 230 V.

Robust Scale Transformation Methods in IRT True Score Equating under Common-Item Nonequivalent Groups Design

ERIC Educational Resources Information Center

He, Yong

2013-01-01

Common test items play an important role in equating multiple test forms under the common-item nonequivalent groups design. Inconsistent item parameter estimates among common items can lead to large bias in equated scores for IRT true score equating. Current methods extensively focus on detection and elimination of outlying common items, which…

Reactions to the Implicit Association Test as an Educational Tool: A Mixed Methods Study

ERIC Educational Resources Information Center

Hillard, Amy L.; Ryan, Carey S.; Gervais, Sarah J.

2013-01-01

We examined reactions to the Race Implicit Association Test (IAT), which has been widely used but rarely examined as an educational tool to raise awareness about racial bias. College students (N = 172) were assigned to read that the IAT reflected either personal beliefs or both personal and extrapersonal factors (single vs. multiple explanation…

Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items

ERIC Educational Resources Information Center

Mariano, Louis T.; Junker, Brian W.

2007-01-01

When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…

Attention Bias towards Negative Emotional Information and its Relationship with Daily Worry in the Context of Acute Stress: An Eye-Tracking Study

PubMed Central

Macatee, Richard J.; Albanese, Brian J.; Schmidt, Norman B.; Cougle, Jesse R.

2017-01-01

Cognitive theories of anxiety psychopathology cite biased attention towards threat as a central vulnerability and maintaining factor. However, many studies have found threat bias indices to have poor reliability and have failed to observe the theorized relationship between threat bias and anxiety symptoms; this may be due to the non-unitary nature of threat bias and the influence of state-level variables on its expression. Accumulating data suggests that state anxious mood is important for the robust expression of threat bias and for relations to emerge between threat bias and symptoms, though this possibility has not been experimentally tested. Eye-tracking was used to assess multiple forms of threat bias (i.e., early vigilance, sustained attention, facilitated engagement, delayed disengagement) thought to be related to anxiety. A non-clinical sample (N = 165) was recruited to test the hypothesis that biased attention towards threat, but not dysphoric or positive emotional stimuli, during an anxious mood induction, but not at a pre-stress baseline, would prospectively predict greater worry symptoms on days in which more naturalistic stressors occurred. Results revealed the hypothesized moderation effect for sustained attention towards threat after the mood induction but not at baseline, though sustained attention towards dysphoric stimuli also moderated the effect of stressors on worry. Worry-relevant sustained attention towards negative emotional stimuli may be a partially mood-context dependent phenomenon. PMID:28013055

Attention bias towards negative emotional information and its relationship with daily worry in the context of acute stress: An eye-tracking study.

PubMed

Macatee, Richard J; Albanese, Brian J; Schmidt, Norman B; Cougle, Jesse R

2017-03-01

Cognitive theories of anxiety psychopathology cite biased attention towards threat as a central vulnerability and maintaining factor. However, many studies have found threat bias indices to have poor reliability and have failed to observe the theorized relationship between threat bias and anxiety symptoms; this may be due to the non-unitary nature of threat bias and the influence of state-level variables on its expression. Accumulating data suggests that state anxious mood is important for the robust expression of threat bias and for relations to emerge between threat bias and symptoms, though this possibility has not been experimentally tested. Eye-tracking was used to assess multiple forms of threat bias (i.e., early vigilance, sustained attention, facilitated engagement, delayed disengagement) thought to be related to anxiety. A non-clinical sample (N = 165) was recruited to test the hypothesis that biased attention towards threat, but not dysphoric or positive emotional stimuli, during an anxious mood induction, but not at a pre-stress baseline, would prospectively predict greater worry symptoms on days in which more naturalistic stressors occurred. Results revealed the hypothesized moderation effect for sustained attention towards threat after the mood induction but not at baseline, though sustained attention towards dysphoric stimuli also moderated the effect of stressors on worry. Worry-relevant sustained attention towards negative emotional stimuli may be a partially mood-context dependent phenomenon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rater Perceptions of Bias Using the Multiple Mini-Interview Format: A Qualitative Study

ERIC Educational Resources Information Center

Alweis, Richard L.; Fitzpatrick, Caroline; Donato, Anthony A.

2015-01-01

Introduction: The Multiple Mini-Interview (MMI) format appears to mitigate individual rater biases. However, the format itself may introduce structural systematic bias, favoring extroverted personality types. This study aimed to gain a better understanding of these biases from the perspective of the interviewer. Methods: A sample of MMI…

When biased language use is associated with bullying and dominance behavior: the moderating effect of prejudice.

PubMed

Poteat, V Paul; Digiovanni, Craig D

2010-10-01

Biased language related to sexual orientation is used frequently among students and is related to prominent social concerns such as bullying. Prejudice toward gay, lesbian, bisexual, and transgender individuals also has been examined among adolescents, but separately from these behaviors. This study tested whether biased language use was associated with bullying and dominance irrespective of sexual prejudice or if sexual prejudice moderated these associations among 290 high school students (50% female; 56% White). Sexual prejudice was associated with biased language use among boys only. Biased language was associated with bullying regardless of levels of sexual prejudice for boys. However, this association was dependent on sexual prejudice for girls. For dominance behavior, its association with biased language was moderated by sexual prejudice for boys, but not girls. However, girls' engagement in all behaviors was significantly less than boys. These results indicate nuanced ways in which multiple factors contribute to the use of sexual orientation biased language. Also, they underscore the need to address biased language and prejudice as part of anti-bullying programs.

Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

PubMed

Obuchowski, Nancy A; Bullen, Jennifer

2017-01-01

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly.

Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening.

PubMed

Mazoure, Bogdan; Caraus, Iurie; Nadon, Robert; Makarenkov, Vladimir

2018-06-01

Data generated by high-throughput screening (HTS) technologies are prone to spatial bias. Traditionally, bias correction methods used in HTS assume either a simple additive or, more recently, a simple multiplicative spatial bias model. These models do not, however, always provide an accurate correction of measurements in wells located at the intersection of rows and columns affected by spatial bias. The measurements in these wells depend on the nature of interaction between the involved biases. Here, we propose two novel additive and two novel multiplicative spatial bias models accounting for different types of bias interactions. We describe a statistical procedure that allows for detecting and removing different types of additive and multiplicative spatial biases from multiwell plates. We show how this procedure can be applied by analyzing data generated by the four HTS technologies (homogeneous, microorganism, cell-based, and gene expression HTS), the three high-content screening (HCS) technologies (area, intensity, and cell-count HCS), and the only small-molecule microarray technology available in the ChemBank small-molecule screening database. The proposed methods are included in the AssayCorrector program, implemented in R, and available on CRAN.

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

PubMed

Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh

2018-02-01

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Sensitivity and specificity of a digit symbol recognition trial in the identification of response bias.

PubMed

Kim, Nancy; Boone, Kyle B; Victor, Tara; Lu, Po; Keatinge, Carolyn; Mitchell, Cary

2010-08-01

Recently published practice standards recommend that multiple effort indicators be interspersed throughout neuropsychological evaluations to assess for response bias, which is most efficiently accomplished through use of effort indicators from standard cognitive tests already included in test batteries. The present study examined the utility of a timed recognition trial added to standard administration of the WAIS-III Digit Symbol subtest in a large sample of "real world" noncredible patients (n=82) as compared with credible neuropsychology clinic patients (n=89). Scores from the recognition trial were more sensitive in identifying poor effort than were standard Digit Symbol scores, and use of an equation incorporating Digit Symbol Age-Corrected Scaled Scores plus accuracy and time scores from the recognition trial was associated with nearly 80% sensitivity at 88.7% specificity. Thus, inclusion of a brief recognition trial to Digit Symbol administration has the potential to provide accurate assessment of response bias.

The development of comparative bias index

NASA Astrophysics Data System (ADS)

Aimran, Ahmad Nazim; Ahmad, Sabri; Afthanorhan, Asyraf; Awang, Zainudin

2017-08-01

Structural Equation Modeling (SEM) is a second generation statistical analysis techniques developed for analyzing the inter-relationships among multiple variables in a model simultaneously. There are two most common used methods in SEM namely Covariance-Based Structural Equation Modeling (CB-SEM) and Partial Least Square Path Modeling (PLS-PM). There have been continuous debates among researchers in the use of PLS-PM over CB-SEM. While there is few studies were conducted to test the performance of CB-SEM and PLS-PM bias in estimating simulation data. This study intends to patch this problem by a) developing the Comparative Bias Index and b) testing the performance of CB-SEM and PLS-PM using developed index. Based on balanced experimental design, two multivariate normal simulation data with of distinct specifications of size 50, 100, 200 and 500 are generated and analyzed using CB-SEM and PLS-PM.

Aging and visual length discrimination: sequential dependencies, biases, and the effects of multiple implicit standards.

PubMed

Norman, J Farley; Cheeseman, Jacob R; Baxter, Michael W; Thomason, Kelsey E; Adkins, Olivia C; Rogers, Connor E

2014-05-01

Younger (20-25 years of age) and older (61-79 years) adults were evaluated for their ability to visually discriminate length. Almost all experiments that have utilized the method of single stimuli to date have required participants to judge test stimuli relative to a single implicit standard (for a rare exception, see Morgan, On the scaling of size judgements by orientational cues, Vision Research, 1992, 32, 1433-1445). In the current experiments, we not only asked participants to judge lengths relative to a single implicit standard, but they also compared test stimuli to two different implicit standards within the same blocks of trials. We analyzed our participants' judgments to evaluate whether significant sequential dependencies occurred. We found that while individual younger and older adults possessed similar length difference thresholds and exhibited similar overall biases, the judgments of older adults within individual blocks of trials were more strongly biased (than younger adults) by preceding responses (i.e., their judgments on any given trial were more strongly affected by responses to previously viewed stimuli). In addition, the judgments of both younger and older adults were more strongly biased by preceding responses in the blocks of trials with multiple implicit standards. Overall, our results are consistent with the operation of the tracking mechanism described by Criterion-setting theory (Lages and Treisman, Spatial frequency discrimination: Visual long-term memory or criterion setting? Vision Research, 1998, 38, 557-572). Copyright © 2014 Elsevier Ltd. All rights reserved.

40 CFR 53.35 - Test procedure for Class II and Class III methods for PM 2.5 and PM −2.5.

Code of Federal Regulations, 2014 CFR

2014-07-01

... section. All reference method samplers shall be of single-filter design (not multi-filter, sequential sample design). Each candidate method shall be setup and operated in accordance with its associated... precision specified in table C-4 of this subpart. (g) Test for additive and multiplicative bias (comparative...

40 CFR 53.35 - Test procedure for Class II and Class III methods for PM 2.5 and PM −2.5.

Code of Federal Regulations, 2013 CFR

2013-07-01

... section. All reference method samplers shall be of single-filter design (not multi-filter, sequential sample design). Each candidate method shall be setup and operated in accordance with its associated... precision specified in table C-4 of this subpart. (g) Test for additive and multiplicative bias (comparative...

Correction of distortions in distressed mothers' ratings of their preschool children's psychopathology.

PubMed

Müller, Jörg M; Furniss, Tilman

2013-11-30

The often-reported low informant agreement about child psychopathology between multiple informants has lead to various suggestions about how to address discrepant ratings. Among the factors that may lower agreement that have been discussed is informant credibility, reliability, or psychopathology, which is of interest in this paper. We tested three different models, namely, the accuracy, the distortion, and an integrated so-called combined model, that conceptualize parental ratings to assess child psychopathology. The data comprise ratings of child psychopathology from multiple informants (mother, therapist and kindergarten teacher) and ratings of maternal psychopathology. The children were patients in a preschool psychiatry unit (N=247). The results from structural equation modeling show that maternal ratings of child psychopathology were biased by maternal psychopathology (distortion model). Based on this statistical background, we suggest a method to adjust biased maternal ratings. We illustrate the maternal bias by comparing the ratings of mother to expert ratings (combined kindergarten teacher and therapist ratings) and show that the correction equation increases the agreement between maternal and expert ratings. We conclude that this approach may help to reduce misclassification of preschool children as 'clinical' on the basis of biased maternal ratings. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A Solution to Separation and Multicollinearity in Multiple Logistic Regression

PubMed Central

Shen, Jianzhao; Gao, Sujuan

2010-01-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27–38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth’s penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study. PMID:20376286

A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

PubMed

Shen, Jianzhao; Gao, Sujuan

2008-10-01

In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

Modelling multiple sources of dissemination bias in meta-analysis.

PubMed

Bowden, Jack; Jackson, Dan; Thompson, Simon G

2010-03-30

Asymmetry in the funnel plot for a meta-analysis suggests the presence of dissemination bias. This may be caused by publication bias through the decisions of journal editors, by selective reporting of research results by authors or by a combination of both. Typically, study results that are statistically significant or have larger estimated effect sizes are more likely to appear in the published literature, hence giving a biased picture of the evidence-base. Previous statistical approaches for addressing dissemination bias have assumed only a single selection mechanism. Here we consider a more realistic scenario in which multiple dissemination processes, involving both the publishing authors and journals, are operating. In practical applications, the methods can be used to provide sensitivity analyses for the potential effects of multiple dissemination biases operating in meta-analysis.

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.

Implicit bias in healthcare professionals: a systematic review.

PubMed

FitzGerald, Chloë; Hurst, Samia

2017-03-01

Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients. PubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies. Forty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals' attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care. The evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics. Our findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.

Towards a better understanding of the legibility bias in performance assessments: the case of gender-based inferences.

PubMed

Greifeneder, Rainer; Zelt, Sarah; Seele, Tim; Bottenberg, Konstantin; Alt, Alexander

2012-09-01

Handwriting legibility systematically biases evaluations in that highly legible handwriting results in more positive evaluations than less legible handwriting. Because performance assessments in educational contexts are not only based on computerized or multiple choice tests but often include the evaluation of handwritten work samples, understanding the causes of this bias is critical. This research was designed to replicate and extend the legibility bias in two tightly controlled experiments and to explore whether gender-based inferences contribute to its occurrence. A total of 132 students from a German university participated in one pre-test and two independent experiments. Participants were asked to read and evaluate several handwritten essays varying in content quality. Each essay was presented to some participants in highly legible handwriting and to other participants in less legible handwriting. In addition, the assignment of legibility to participant group was reversed from essay to essay, resulting in a mixed-factor design. The legibility bias was replicated in both experiments. Results suggest that gender-based inferences do not account for its occurrence. Rather it appears that fluency from legibility exerts a biasing impact on evaluations of content and author abilities. The legibility bias was shown to be genuine and strong. By refuting a series of alternative explanations, this research contributes to a better understanding of what underlies the legibility bias. The present research may inform those who grade on what to focus and thus help to better allocate cognitive resources when trying to reduce this important source of error. ©2011 The British Psychological Society.

Viewpoint: observations on scaled average bioequivalence.

PubMed

Patterson, Scott D; Jones, Byron

2012-01-01

The two one-sided test procedure (TOST) has been used for average bioequivalence testing since 1992 and is required when marketing new formulations of an approved drug. TOST is known to require comparatively large numbers of subjects to demonstrate bioequivalence for highly variable drugs, defined as those drugs having intra-subject coefficients of variation greater than 30%. However, TOST has been shown to protect public health when multiple generic formulations enter the marketplace following patent expiration. Recently, scaled average bioequivalence (SABE) has been proposed as an alternative statistical analysis procedure for such products by multiple regulatory agencies. SABE testing requires that a three-period partial replicate cross-over or full replicate cross-over design be used. Following a brief summary of SABE analysis methods applied to existing data, we will consider three statistical ramifications of the proposed additional decision rules and the potential impact of implementation of scaled average bioequivalence in the marketplace using simulation. It is found that a constraint being applied is biased, that bias may also result from the common problem of missing data and that the SABE methods allow for much greater changes in exposure when generic-generic switching occurs in the marketplace. Copyright © 2011 John Wiley & Sons, Ltd.

Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters.

PubMed

Bolte, John F B

2016-09-01

Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and WiFi appliances. Further, the possible corrections for biases have not been fully applied. The main findings are that if the biases are not corrected for, the actual exposure will on average be underestimated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bayesian Correction for Misclassification in Multilevel Count Data Models.

PubMed

Nelson, Tyler; Song, Joon Jin; Chin, Yoo-Mi; Stamey, James D

2018-01-01

Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

Three Techniques to Help Students Teach Themselves Concepts in Environmental Geochemistry.

ERIC Educational Resources Information Center

Brown, I. Foster

1984-01-01

Describes techniques in which students learn to: (1) create elemental "fairy tales" based on the geochemical behavior of elements and on imagination to integrate concepts; (2) to visually eliminate problems of bias; and (3) to utilize multiple working hypotheses as a basis for testing concepts of classification and distinguishing…

Redox bias in loss of ignition moisture measurement for relatively pure plutonium-bearing oxide materials.

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

Eller, P. G.; Stakebake, J. L.; Cooper, T. D.

2001-01-01

This paper evaluates potential analytical bias in application of the Loss on Ignition (LOI) technique for moisture measurement to relatively pure (plutonium assay of 80 wt.% or higher) oxides containing uranium that have been stabilized according to stabilization and storage standard DOE-STD-3013-2000 (STD-3013). An immediate application is to Rocky Flats (RF) materials derived from highgrade metal hydriding separations subsequently treated by multiple calcination cycles. Specifically evaluated are weight changes due to oxidatiodreduction of multivalent impurity oxides that could mask true moisture equivalent content measurement. Process knowledge and characterization of materials representing complex-wide materials to be stabilized and packaged according tomore » STD-3013, and particularly for the immediate RF target stream, indicate that oxides of uranium, iron and gallium are the only potential multivalent constituents expected to be present above 0.5 wt.%. The evaluation shows that of these constituents, with few exceptions, only uranium oxides can be present at a sufficient level to produce weight gain biases significant with respect to the LO1 stability test. In general, these formerly high-value, high-actinide content materials are reliably identifiable by process knowledge and measurement. Si&icant bias also requires that UO1 components remain largely unoxidized after calcination and are largely converted to U30s clsning LO1 testing at only slightly higher temperatures. Based on wellestablished literature, it is judged unlikely that this set of conditions will be realized in practice. We conclude that it is very likely that LO1 weight gain bias will be small for the immediate target RF oxide materials containing greater than 80 wt.% plutonium plus a much smaller uranium content. Recommended tests are in progress to confum these expectations and to provide a more authoritative basis for bounding LO1 oxidatiodreduction biases. LO1 bias evaluation is more difficult for lower purity materials and for fuel-type uranium-plutonium oxides. However, even in these cases testing may show that bias effects are manageable.« less

A minimalist approach to bias estimation for passive sensor measurements with targets of opportunity

NASA Astrophysics Data System (ADS)

Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

2013-09-01

In order to carry out data fusion, registration error correction is crucial in multisensor systems. This requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. This paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. The sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

Negatively-marked MCQ assessments that reward partial knowledge do not introduce gender bias yet increase student performance and satisfaction and reduce anxiety.

PubMed

Bond, A Elizabeth; Bodger, Owen; Skibinski, David O F; Jones, D Hugh; Restall, Colin J; Dudley, Edward; van Keulen, Geertje

2013-01-01

Multiple-choice question (MCQ) examinations are increasingly used as the assessment method of theoretical knowledge in large class-size modules in many life science degrees. MCQ-tests can be used to objectively measure factual knowledge, ability and high-level learning outcomes, but may also introduce gender bias in performance dependent on topic, instruction, scoring and difficulty. The 'Single Answer' (SA) test is often used in which students choose one correct answer, in which they are unable to demonstrate partial knowledge. Negatively marking eliminates the chance element of guessing but may be considered unfair. Elimination testing (ET) is an alternative form of MCQ, which discriminates between all levels of knowledge, while rewarding demonstration of partial knowledge. Comparisons of performance and gender bias in negatively marked SA and ET tests have not yet been performed in the life sciences. Our results show that life science students were significantly advantaged by answering the MCQ test in elimination format compared to single answer format under negative marking conditions by rewarding partial knowledge of topics. Importantly, we found no significant difference in performance between genders in either cohort for either MCQ test under negative marking conditions. Surveys showed that students generally preferred ET-style MCQ testing over SA-style testing. Students reported feeling more relaxed taking ET MCQ and more stressed when sitting SA tests, while disagreeing with being distracted by thinking about best tactics for scoring high. Students agreed ET testing improved their critical thinking skills. We conclude that appropriately-designed MCQ tests do not systematically discriminate between genders. We recommend careful consideration in choosing the type of MCQ test, and propose to apply negative scoring conditions to each test type to avoid the introduction of gender bias. The student experience could be improved through the incorporation of the elimination answering methods in MCQ tests via rewarding partial and full knowledge.

Negatively-Marked MCQ Assessments That Reward Partial Knowledge Do Not Introduce Gender Bias Yet Increase Student Performance and Satisfaction and Reduce Anxiety

PubMed Central

Bond, A. Elizabeth; Bodger, Owen; Skibinski, David O. F.; Jones, D. Hugh; Restall, Colin J.; Dudley, Edward; van Keulen, Geertje

2013-01-01

Multiple-choice question (MCQ) examinations are increasingly used as the assessment method of theoretical knowledge in large class-size modules in many life science degrees. MCQ-tests can be used to objectively measure factual knowledge, ability and high-level learning outcomes, but may also introduce gender bias in performance dependent on topic, instruction, scoring and difficulty. The ‘Single Answer’ (SA) test is often used in which students choose one correct answer, in which they are unable to demonstrate partial knowledge. Negatively marking eliminates the chance element of guessing but may be considered unfair. Elimination testing (ET) is an alternative form of MCQ, which discriminates between all levels of knowledge, while rewarding demonstration of partial knowledge. Comparisons of performance and gender bias in negatively marked SA and ET tests have not yet been performed in the life sciences. Our results show that life science students were significantly advantaged by answering the MCQ test in elimination format compared to single answer format under negative marking conditions by rewarding partial knowledge of topics. Importantly, we found no significant difference in performance between genders in either cohort for either MCQ test under negative marking conditions. Surveys showed that students generally preferred ET-style MCQ testing over SA-style testing. Students reported feeling more relaxed taking ET MCQ and more stressed when sitting SA tests, while disagreeing with being distracted by thinking about best tactics for scoring high. Students agreed ET testing improved their critical thinking skills. We conclude that appropriately-designed MCQ tests do not systematically discriminate between genders. We recommend careful consideration in choosing the type of MCQ test, and propose to apply negative scoring conditions to each test type to avoid the introduction of gender bias. The student experience could be improved through the incorporation of the elimination answering methods in MCQ tests via rewarding partial and full knowledge. PMID:23437081

Attachment insecurity, biased perceptions of romantic partners' negative emotions, and hostile relationship behavior.

PubMed

Overall, Nickola C; Fletcher, Garth J O; Simpson, Jeffry A; Fillo, Jennifer

2015-05-01

In the current research, we tested the extent to which attachment insecurity produces inaccurate and biased perceptions of intimate partners' emotions and whether more negative perceptions of partners' emotions elicit the damaging behavior often associated with attachment insecurity. Perceptions of partners' emotions as well as partners' actual emotions were assessed multiple times in couples' conflict discussions (Study 1) and daily during a 3-week period in 2 independent samples (Study 2). Using partners' reports of their own emotional experiences as the accuracy benchmark, we simultaneously tested whether attachment insecurity was associated with the degree to which individuals (a) accurately detected shifts in their partners' negative emotions (tracking accuracy), and (b) perceived their partners were feeling more negative relationship-related emotions than they actually experienced (directional bias). Highly avoidant perceivers were equally accurate at tracking their partners' changing emotions compared to less avoidant individuals (tracking accuracy), but they overestimated the intensity of their partners' negative emotions to a greater extent than less avoidant individuals (directional bias). In addition, more negative perceptions of partners' emotions triggered more hostile and defensive behavior in highly avoidant perceivers both during conflict discussions (Study 1) and in daily life (Study 2). In contrast, attachment anxiety was not associated with tracking accuracy, directional bias, or hostile reactions to perceptions of their partners' negative emotions. These findings demonstrate the importance of assessing biased perceptions in actual relationship interactions and reveal that biased perceptions play an important role in activating the defenses of avoidantly attached people. (c) 2015 APA, all rights reserved).

Dopamine receptor blockade attenuates the general incentive motivational effects of noncontingently delivered rewards and reward-paired cues without affecting their ability to bias action selection.

PubMed

Ostlund, Sean B; Maidment, Nigel T

2012-01-01

Environmental cues affect our behavior in a variety of ways. Despite playing an invaluable role in guiding our daily activities, such cues also appear to trigger the harmful, compulsive behaviors that characterize addiction and other disorders of behavioral control. In instrumental conditioning, rewards and reward-paired cues bias action selection and invigorate reward-seeking behaviors, and appear to do so through distinct neurobehavioral processes. Although reward-paired cues are known to invigorate performance through a dopamine-dependent incentive motivational process, it is not known if dopamine also mediates the influence of rewards and reward-paired cues over action selection. The current study contrasted the effects of systemic administration of the nonspecific dopamine receptor antagonist flupentixol on response invigoration and action bias in Pavlovian-instrumental transfer, a test of cue-elicited responding, and in instrumental reinstatement, a test of noncontingent reward-elicited responding. Hungry rats were trained on two different stimulus-outcome relationships (eg, tone-grain pellets and noise-sucrose solution) and two different action-outcome relationships (eg, left press-grain and right press-sucrose). At test, we found that flupentixol pretreatment blocked the response invigoration generated by the cues but spared their ability to bias action selection to favor the action whose outcome was signaled by the cue being presented. The response-biasing influence of noncontingent reward deliveries was also unaffected by flupentixol. Interestingly, although flupentixol had a modest effect on the immediate response invigoration produced by those rewards, it was particularly potent in countering the lingering enhancement of responding produced by multiple reward deliveries. These findings indicate that dopamine mediates the general incentive motivational effects of noncontingent rewards and reward-paired cues but does not support their ability to bias action selection.

A European multicientre study on the comparison of HBV viral loads between VERIS HBV assay and Roche COBAS® TAQMAN® HBV test, Abbott RealTime HBV assay, Siemens VERSANT HBV assay, and Qiagen artus HBV RG kit.

PubMed

Braun, Patrick; Delgado, Rafael; Drago, Monica; Fanti, Diana; Fleury, Hervé; Izopet, Jacques; Lombardi, Alessandra; Marcos, MaAngeles; Sauné, Karine; O'Shea, Siobhan; Pérez-Rivilla, Alfredo; Ramble, John; Trimoulet, Pascale; Vila, Jordi; Whittaker, Duncan; Artus, Alain; Rhodes, Daniel

2017-10-01

Hepatitis B viral load testing is essential to treatment and monitoring decisions in patients with chronic Hepatitis B. Beckman Coulter has developed the VERIS HBV Assay (Veris) for use on the fully automated DxN VERIS Molecular Diagnostics System. 1 OBJECTIVES: To evaluate the clinical performance of the Veris HBV Assay at multiple EU laboratories STUDY DESIGN: Method comparison was performed with a total of 344 plasma specimens from HBV infected patients tested with Veris and COBAS ® TaqMan ® HBV Test (Cobas), 207 specimens tested with Veris and RealTime HBV Assay (RealTime), 86 specimens tested with Veris and VERSANT ® HBV Assay (Versant), and 74 specimens tested with Veris and artus ® HBV RG PCR kit (artus). Bland-Altman analysis showed average bias of -0.46 log 10 IU/mL between Veris and Cobas, -0.46 log 10 IU/mL between Veris and RealTime, -0.36 log 10 IU/mL between Veris and Versant, and -0.12 log 10 IU/mL between Veris and artus. Bias was consistent across the assay range. Patient monitoring results using Veris demonstrated similar viral load trends over time to Cobas, RealTime, and artus. The VERIS HBV Assay demonstrated comparable clinical performance, with varying degrees of negative bias, compared to other currently marketed assays for HBV DNA monitoring. This negative bias should be taken into consideration if switching monitoring methods to Veris. Copyright © 2017 Elsevier B.V. All rights reserved.

A synthesis of convenience survey and other data to estimate undiagnosed HIV infection among men who have sex with men in England and Wales.

PubMed

Walker, Kate; Seaman, Shaun R; De Angelis, Daniela; Presanis, Anne M; Dodds, Julie P; Johnson, Anne M; Mercey, Danielle; Gill, O Noel; Copas, Andrew J

2011-10-01

Hard-to-reach population subgroups are typically investigated using convenience sampling, which may give biased estimates. Combining information from such surveys, a probability survey and clinic surveillance, can potentially minimize the bias. We developed a methodology to estimate the prevalence of undiagnosed HIV infection among men who have sex with men (MSM) in England and Wales aged 16-44 years in 2003, making fuller use of the available data than earlier work. We performed a synthesis of three data sources: genitourinary medicine clinic surveillance (11 380 tests), a venue-based convenience survey including anonymous HIV testing (3702 MSM) and a general population sexual behaviour survey (134 MSM). A logistic regression model to predict undiagnosed infection was fitted to the convenience survey data and then applied to the MSMs in the population survey to estimate the prevalence of undiagnosed infection in the general MSM population. This estimate was corrected for selection biases in the convenience survey using clinic surveillance data. A sensitivity analysis addressed uncertainty in our assumptions. The estimated prevalence of undiagnosed HIV in MSM was 2.4% [95% confidence interval (95% CI 1.7-3.0%)], and between 1.6% (95% CI 1.1-2.0%) and 3.3% (95% CI 2.4-4.1%) depending on assumptions; corresponding to 5500 (3390-7180), 3610 (2180-4740) and 7570 (4790-9840) men, and undiagnosed fractions of 33, 24 and 40%, respectively. Our estimates are consistent with earlier work that did not make full use of data sources. Reconciling data from multiple sources, including probability-, clinic- and venue-based convenience samples can reduce bias in estimates. This methodology could be applied in other settings to take full advantage of multiple imperfect data sources.

Methods to Quantify Cell Signaling and GPCR Receptor Ligand Bias: Characterization of Drugs that Target the Endocannabinoid Receptors in Huntington's Disease.

PubMed

Bagher, Amina M; Laprairie, Robert B; Kelly, Melanie E M; Denovan-Wright, Eileen M

2018-01-01

G protein-coupled receptors (GPCRs) interact with multiple intracellular effector proteins such that different ligands may preferentially activate one signal pathway over others, a phenomenon known as signaling bias. Signaling bias can be quantified to optimize drug selection for preclinical research. Here, we describe moderate-throughput methods to quantify signaling bias of known and novel compounds. In the example provided, we describe a method to define cannabinoid-signaling bias in a cell culture model of Huntington's disease (HD). Decreasing type 1 cannabinoid receptor (CB 1 ) levels is correlated with chorea and cognitive deficits in HD. There is evidence that elevating CB 1 levels and/or signaling may be beneficial for HD patients while decreasing CB 1 levels and/or signaling may be detrimental. Recent studies have found that Gα i/o -biased CB 1 agonists activate extracellular signal-regulated kinase (ERK), increase CB 1 protein levels, and improve viability of cells expressing mutant huntingtin. In contrast, CB 1 agonists that are β-arrestin1-biased were found to reduce CB 1 protein levels and cell viability. Measuring agonist bias of known and novel CB 1 agonists will provide important data that predict CB 1 -specific agonists that might be beneficial in animal models of HD and, following animal testing, in HD patients. This method can also be applied to study signaling bias for other GPCRs.

The Effect of Amplifier Bias Drift on Differential Magnitude Estimation in Multiple-Star Systems

NASA Astrophysics Data System (ADS)

Tyler, David W.; Muralimanohar, Hariharan; Borelli, Kathy J.

2007-02-01

We show how the temporal drift of CCD amplifier bias can cause significant relative magnitude estimation error in speckle interferometric observations of multiple-star systems. When amplifier bias varies over time, the estimation error arises if the time between acquisition of dark-frame calibration data and science data is long relative to the timescale over which the bias changes. Using analysis, we show that while detector-temperature drift over time causes a variation in accumulated dark current and a residual bias in calibrated imagery, only amplifier bias variations cause a residual bias in the estimated energy spectrum. We then use telescope data taken specifically to investigate this phenomenon to show that for the detector used, temporal bias drift can cause residual energy spectrum bias as large or larger than the mean value of the noise energy spectrum. Finally, we use a computer simulation to demonstrate the effect of residual bias on differential magnitude estimation. A supplemental calibration technique is described in the appendices.

Prevalence Estimation and Validation of New Instruments in Psychiatric Research: An Application of Latent Class Analysis and Sensitivity Analysis

ERIC Educational Resources Information Center

Pence, Brian Wells; Miller, William C.; Gaynes, Bradley N.

2009-01-01

Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to…

Managing wildfire events: risk-based decision making among a group of federal fire managers

Treesearch

Robyn S. Wilson; Patricia L. Winter; Lynn A. Maguire; Timothy Ascher

2011-01-01

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience-based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk-based biases among 206...

Masculinization of Gene Expression Is Associated with Exaggeration of Male Sexual Dimorphism

PubMed Central

Pointer, Marie A.; Harrison, Peter W.; Wright, Alison E.; Mank, Judith E.

2013-01-01

Gene expression differences between the sexes account for the majority of sexually dimorphic phenotypes, and the study of sex-biased gene expression is important for understanding the genetic basis of complex sexual dimorphisms. However, it has been difficult to test the nature of this relationship due to the fact that sexual dimorphism has traditionally been conceptualized as a dichotomy between males and females, rather than an axis with individuals distributed at intermediate points. The wild turkey (Meleagris gallopavo) exhibits just this sort of continuum, with dominant and subordinate males forming a gradient in male secondary sexual characteristics. This makes it possible for the first time to test the correlation between sex-biased gene expression and sexually dimorphic phenotypes, a relationship crucial to molecular studies of sexual selection and sexual conflict. Here, we show that subordinate male transcriptomes show striking multiple concordances with their relative phenotypic sexual dimorphism. Subordinate males were clearly male rather than intersex, and when compared to dominant males, their transcriptomes were simultaneously demasculinized for male-biased genes and feminized for female-biased genes across the majority of the transcriptome. These results provide the first evidence linking sexually dimorphic transcription and sexually dimorphic phenotypes. More importantly, they indicate that evolutionary changes in sexual dimorphism can be achieved by varying the magnitude of sex-bias in expression across a large proportion of the coding content of a genome. PMID:23966876

Masculinization of gene expression is associated with exaggeration of male sexual dimorphism.

PubMed

Pointer, Marie A; Harrison, Peter W; Wright, Alison E; Mank, Judith E

2013-01-01

Gene expression differences between the sexes account for the majority of sexually dimorphic phenotypes, and the study of sex-biased gene expression is important for understanding the genetic basis of complex sexual dimorphisms. However, it has been difficult to test the nature of this relationship due to the fact that sexual dimorphism has traditionally been conceptualized as a dichotomy between males and females, rather than an axis with individuals distributed at intermediate points. The wild turkey (Meleagris gallopavo) exhibits just this sort of continuum, with dominant and subordinate males forming a gradient in male secondary sexual characteristics. This makes it possible for the first time to test the correlation between sex-biased gene expression and sexually dimorphic phenotypes, a relationship crucial to molecular studies of sexual selection and sexual conflict. Here, we show that subordinate male transcriptomes show striking multiple concordances with their relative phenotypic sexual dimorphism. Subordinate males were clearly male rather than intersex, and when compared to dominant males, their transcriptomes were simultaneously demasculinized for male-biased genes and feminized for female-biased genes across the majority of the transcriptome. These results provide the first evidence linking sexually dimorphic transcription and sexually dimorphic phenotypes. More importantly, they indicate that evolutionary changes in sexual dimorphism can be achieved by varying the magnitude of sex-bias in expression across a large proportion of the coding content of a genome.

Individual differences in bodily freezing predict emotional biases in decision making

PubMed Central

Ly, Verena; Huys, Quentin J. M.; Stins, John F.; Roelofs, Karin; Cools, Roshan

2014-01-01

Instrumental decision making has long been argued to be vulnerable to emotional responses. Literature on multiple decision making systems suggests that this emotional biasing might reflect effects of a system that regulates innately specified, evolutionarily preprogrammed responses. To test this hypothesis directly, we investigated whether effects of emotional faces on instrumental action can be predicted by effects of emotional faces on bodily freezing, an innately specified response to aversive relative to appetitive cues. We tested 43 women using a novel emotional decision making task combined with posturography, which involves a force platform to detect small oscillations of the body to accurately quantify postural control in upright stance. On the platform, participants learned whole body approach-avoidance actions based on monetary feedback, while being primed by emotional faces (angry/happy). Our data evidence an emotional biasing of instrumental action. Thus, angry relative to happy faces slowed instrumental approach relative to avoidance responses. Critically, individual differences in this emotional biasing effect were predicted by individual differences in bodily freezing. This result suggests that emotional biasing of instrumental action involves interaction with a system that controls innately specified responses. Furthermore, our findings help bridge (animal and human) decision making and emotion research to advance our mechanistic understanding of decision making anomalies in daily encounters as well as in a wide range of psychopathology. PMID:25071491

Unreliability as a Threat to Understanding Psychopathology: The Cautionary Tale of Attentional Bias

PubMed Central

Rodebaugh, Thomas L.; Scullin, Rachel B.; Langer, Julia K.; Dixon, David J.; Huppert, Jonathan D.; Bernstein, Amit; Zvielli, Ariel; Lenze, Eric J.

2016-01-01

The use of unreliable measures constitutes a threat to our understanding of psychopathology, because advancement of science using both behavioral and biologically-oriented measures can only be certain if such measurements are reliable. Two pillars of NIMH’s portfolio – the Research Domain Criteria (RDoC) initiative for psychopathology and the target engagement initiative in clinical trials – cannot succeed without measures that possess the high reliability necessary for tests involving mediation and selection based on individual differences. We focus on the historical lack of reliability of attentional bias measures as an illustration of how reliability can pose a threat to our understanding. Our own data replicate previous findings of poor reliability for traditionally-used scores, which suggests a serious problem with the ability to test theories regarding attentional bias. This lack of reliability may also suggest problems with the assumption (in both theory and the formula for the scores) that attentional bias is consistent and stable across time. In contrast, measures accounting for attention as a dynamic process in time show good reliability in our data. The field is sorely in need of research reporting findings and reliability for attentional bias scores using multiple methods, including those focusing on dynamic processes over time. We urge researchers to test and report reliability of all measures, considering findings of low reliability not just as a nuisance but as an opportunity to modify and improve upon the underlying theory. Full assessment of reliability of measures will maximize the possibility that RDoC (and psychological science more generally) will succeed. PMID:27322741

Effectiveness of the Comalli Stroop Test as a measure of negative response bias.

PubMed

Arentsen, Timothy J; Boone, Kyle Brauer; Lo, Tracy T Y; Goldberg, Hope E; Cottingham, Maria E; Victor, Tara L; Ziegler, Elizabeth; Zeller, Michelle A

2013-01-01

Practice guidelines recommend the use of multiple performance validity tests (PVTs) to detect noncredible performance during neuropsychological evaluations, and PVTs embedded in standard cognitive tests achieve this goal most efficiently. The present study examined the utility of the Comalli version of the Stroop Test as a measure of response bias in a large sample of "real world" noncredible patients (n = 129) as compared with credible neuropsychology clinic patients (n=233). The credible group performed significantly better than the noncredible group on all trials, but particularly on word-reading (Stroop A) and color-naming (Stroop B); cut-scores for Stroop A and Stroop B trials were associated with moderate sensitivity (49-53%) as compared to the low sensitivity found for the color interference trial (29%). Some types of diagnoses (including learning disability, severe traumatic brain injury, psychosis, and depression), very advanced age (⩾80), and lowered IQ were associated with increased rates of false positive identifications, suggesting the need for some adjustments to cut-offs in these subgroups. Despite some previous reports of an inverted Stroop effect (i.e., color-naming worse than color interference) in noncredible subjects, individual Stroop word reading and color naming trials were much more effective in identifying response bias.

Evaluation of ames Multistix-SG for urine specific gravity versus refractometer specific gravity.

PubMed

Adams, L J

1983-12-01

A comparison of urine specific gravity by a commercially available multiple reagent strip (Multistix-SG; Ames Division, Miles Laboratory) versus refractometer specific gravity (TS Meter; American Optical Corporation) was performed on 214 routine urine specimens. Agreement to +/- 0.005 was found in 72% of the specimens (r = 0.80). Urine specific gravity by the Multistix-SG showed a significant positive bias at urine pHs less than or equal to 6.0 and a negative bias at urine pHs greater than 7.0 in comparison to refractometer specific gravity. At concentrated (specific gravity greater than or equal to 1.020) specific gravities, up to 25% of urine specimens were misclassified as not concentrated by Multistix-SG specific gravity in comparison to refractometer specific gravity. The additional cost of the specific gravity reagent to a multiple reagent test strip in addition to the poor performance relative to refractometer specific gravity leads to the conclusion that including this specific gravity methodology on a multiple reagent strip is neither cost effective nor clinically useful.

Multiple-Choice Exams: An Obstacle for Higher-Level Thinking in Introductory Science Classes

PubMed Central

Stanger-Hall, Kathrin F.

2012-01-01

Learning science requires higher-level (critical) thinking skills that need to be practiced in science classes. This study tested the effect of exam format on critical-thinking skills. Multiple-choice (MC) testing is common in introductory science courses, and students in these classes tend to associate memorization with MC questions and may not see the need to modify their study strategies for critical thinking, because the MC exam format has not changed. To test the effect of exam format, I used two sections of an introductory biology class. One section was assessed with exams in the traditional MC format, the other section was assessed with both MC and constructed-response (CR) questions. The mixed exam format was correlated with significantly more cognitively active study behaviors and a significantly better performance on the cumulative final exam (after accounting for grade point average and gender). There was also less gender-bias in the CR answers. This suggests that the MC-only exam format indeed hinders critical thinking in introductory science classes. Introducing CR questions encouraged students to learn more and to be better critical thinkers and reduced gender bias. However, student resistance increased as students adjusted their perceptions of their own critical-thinking abilities. PMID:22949426

Dynamics of attentional bias to threat in anxious adults: bias towards and/or away?

PubMed

Zvielli, Ariel; Bernstein, Amit; Koster, Ernst H W

2014-01-01

The aim of the present study was to question untested assumptions about the nature of the expression of Attentional Bias (AB) towards and away from threat stimuli. We tested the idea that high trait anxious individuals (N = 106; M(SD)age = 23.9(3.2) years; 68% women) show a stable AB towards multiple categories of threatening information using the emotional visual dot probe task. AB with respect to five categories of threat stimuli (i.e., angry faces, attacking dogs, attacking snakes, pointed weapons, violent scenes) was evaluated. In contrast with current theories, we found that 34% of participants expressed AB towards threat stimuli, 20.8% AB away from threat stimuli, and 34% AB towards some categories of threat stimuli and away from others. The multiple observed expressions of AB were not an artifact of a specific criterion AB score cut-off; not specific to certain categories of threat stimuli; not an artifact of differences in within-subject variability in reaction time; nor accounted for by individual differences in anxiety-related variables. Findings are conceptualized as reflecting the understudied dynamics of AB expression, with implications for AB measurement and quantification, etiology, relations, and intervention research.

Dynamics of Attentional Bias to Threat in Anxious Adults: Bias towards and/or Away?

PubMed Central

Zvielli, Ariel; Bernstein, Amit; Koster, Ernst H. W.

2014-01-01

The aim of the present study was to question untested assumptions about the nature of the expression of Attentional Bias (AB) towards and away from threat stimuli. We tested the idea that high trait anxious individuals (N = 106; M(SD)age = 23.9(3.2) years; 68% women) show a stable AB towards multiple categories of threatening information using the emotional visual dot probe task. AB with respect to five categories of threat stimuli (i.e., angry faces, attacking dogs, attacking snakes, pointed weapons, violent scenes) was evaluated. In contrast with current theories, we found that 34% of participants expressed AB towards threat stimuli, 20.8% AB away from threat stimuli, and 34% AB towards some categories of threat stimuli and away from others. The multiple observed expressions of AB were not an artifact of a specific criterion AB score cut-off; not specific to certain categories of threat stimuli; not an artifact of differences in within-subject variability in reaction time; nor accounted for by individual differences in anxiety-related variables. Findings are conceptualized as reflecting the understudied dynamics of AB expression, with implications for AB measurement and quantification, etiology, relations, and intervention research. PMID:25093664

An examination of racial bias in the Beck Depression Inventory-II.

PubMed

Sashidharan, Tracy; Pawlow, Laura A; Pettibone, Jonathan C

2012-04-01

Historically, many psychological measures were developed and standardized based on a primarily Caucasian population. These tests are subsequently applied to minorities and may be inappropriate and possibly even pathologizing. The widely used Beck Depression Inventory-II (BDI-II) was initially standardized on a sample of Caucasian university students and its use with minorities has only recently been investigated. This study examined the possibility of racial bias in the BDI-II by comparing Caucasian and African American Midwestern university students. A hierarchical multiple regression compared the scores of the BDI-II with a similar measure of depression that is standardized for use with African Americans. There was no evidence of racial bias discovered in the BDI-II in this sample. Implications and future directions of research are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

A European multicientre study on the comparison of HIV-1 viral loads between VERIS HIV-1 Assay and Roche COBAS® TAQMAN® HIV-1 test, Abbott RealTime HIV-1 Assay, and Siemens VERSANT HIV-1 Assay.

PubMed

Braun, Patrick; Delgado, Rafael; Drago, Monica; Fanti, Diana; Fleury, Hervé; Hofmann, Jörg; Izopet, Jacques; Kühn, Sebastian; Lombardi, Alessandra; Mancon, Alessandro; Marcos, Mª Angeles; Mileto, Davide; Sauné, Karine; O'Shea, Siobhan; Pérez-Rivilla, Alfredo; Ramble, John; Trimoulet, Pascale; Vila, Jordi; Whittaker, Duncan; Artus, Alain; Rhodes, Daniel

2017-07-01

Viral load monitoring is essential for patients under treatment for HIV. Beckman Coulter has developed the VERIS HIV-1 Assay for use on the novel, automated DxN VERIS Molecular Diagnostics System. ¥ OBJECTIVES: Evaluation of the clinical performance of the new quantitative VERIS HIV-1 Assay at multiple EU laboratories. Method comparison with the VERIS HIV-1 Assay was performed with 415 specimens at 5 sites tested with COBAS ® AmpliPrep/COBAS ® TaqMan ® HIV-1 Test, v2.0, 169 specimens at 3 sites tested with RealTime HIV-1 Assay, and 202 specimens from 2 sites tested with VERSANT HIV-1 Assay. Patient monitoring sample results from 4 sites were also compared. Bland-Altman analysis showed the average bias between VERIS HIV-1 Assay and COBAS HIV-1 Test, RealTime HIV-1 Assay, and VERSANT HIV-1 Assay to be 0.28, 0.39, and 0.61 log 10 cp/mL, respectively. Bias at low end levels below 1000cp/mL showed predicted bias to be <0.3 log 10 cp/mL for VERIS HIV-1 Assay versus COBAS HIV-1 Test and RealTime HIV-1 Assay, and <0.5 log 10 cp/mL versus VERSANT HIV-1 Assay. Analysis on 174 specimens tested with the 0.175mL volume VERIS HIV-1 Assay and COBAS HIV-1 Test showed average bias of 0.39 log 10 cp/mL. Patient monitoring results using VERIS HIV-1 Assay demonstrated similar viral load trends over time to all comparators. The VERIS HIV-1 Assay for use on the DxN VERIS System demonstrated comparable clinical performance to COBAS ® HIV-1 Test, RealTime HIV-1 Assay, and VERSANT HIV-1 Assay. Copyright © 2017 Elsevier B.V. All rights reserved.

Competing Biases in Mental Arithmetic: When Division Is More and Multiplication Is Less.

PubMed

Shaki, Samuel; Fischer, Martin H

2017-01-01

Mental arithmetic exhibits various biases. Among those is a tendency to overestimate addition and to underestimate subtraction outcomes. Does such "operational momentum" (OM) also affect multiplication and division? Twenty-six adults produced lines whose lengths corresponded to the correct outcomes of multiplication and division problems shown in symbolic format. We found a reliable tendency to over-estimate division outcomes, i.e., reverse OM. We suggest that anchoring on the first operand (a tendency to use this number as a reference for further quantitative reasoning) contributes to cognitive biases in mental arithmetic.

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.

Microwave Comb Generator

NASA Technical Reports Server (NTRS)

Sigman, E. H.

1989-01-01

Stable reference tones aid testing and calibration of microwave receivers. Signal generator puts out stable tones in frequency range of 2 to 10 GHz at all multiples of reference input frequency, at any frequency up to 1 MHz. Called "comb generator" because spectral plot resembles comb. DC reverse-bias current switched on and off at 1 MHz to generate sharp pulses in step-recovery diode. Microwave components mounted on back of special connector containing built-in attenuator. Used in testing microwave and spread-spectrum wide-band receivers.

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.

PubMed

Salim, Agus; Mackinnon, Andrew; Christensen, Helen; Griffiths, Kathleen

2008-09-30

The pre-test-post-test design (PPD) is predominant in trials of psychotherapeutic treatments. Missing data due to withdrawals present an even bigger challenge in assessing treatment effectiveness under the PPD than under designs with more observations since dropout implies an absence of information about response to treatment. When confronted with missing data, often it is reasonable to assume that the mechanism underlying missingness is related to observed but not to unobserved outcomes (missing at random, MAR). Previous simulation and theoretical studies have shown that, under MAR, modern techniques such as maximum-likelihood (ML) based methods and multiple imputation (MI) can be used to produce unbiased estimates of treatment effects. In practice, however, ad hoc methods such as last observation carried forward (LOCF) imputation and complete-case (CC) analysis continue to be used. In order to better understand the behaviour of these methods in the PPD, we compare the performance of traditional approaches (LOCF, CC) and theoretically sound techniques (MI, ML), under various MAR mechanisms. We show that the LOCF method is seriously biased and conclude that its use should be abandoned. Complete-case analysis produces unbiased estimates only when the dropout mechanism does not depend on pre-test values even when dropout is related to fixed covariates including treatment group (covariate-dependent: CD). However, CC analysis is generally biased under MAR. The magnitude of the bias is largest when the correlation of post- and pre-test is relatively low.

Partial Sleep Deprivation Attenuates the Positive Affective System: Effects Across Multiple Measurement Modalities.

PubMed

Finan, Patrick H; Quartana, Phillip J; Remeniuk, Bethany; Garland, Eric L; Rhudy, Jamie L; Hand, Matthew; Irwin, Michael R; Smith, Michael T

2017-01-01

Ample behavioral and neurobiological evidence links sleep and affective functioning. Recent self-report evidence suggests that the affective problems associated with sleep loss may be stronger for positive versus negative affective state and that those effects may be mediated by changes in electroencepholographically measured slow wave sleep (SWS). In the present study, we extend those preliminary findings using multiple measures of affective functioning. In a within-subject randomized crossover experiment, we tested the effects of one night of sleep continuity disruption via forced awakenings (FA) compared to one night of uninterrupted sleep (US) on three measures of positive and negative affective functioning: self-reported affective state, affective pain modulation, and affect-biased attention. The study was set in an inpatient clinical research suite. Healthy, good sleeping adults (N = 45) were included. Results indicated that a single night of sleep continuity disruption attenuated positive affective state via FA-induced reductions in SWS. Additionally, sleep continuity disruption attenuated the inhibition of pain by positive affect as well as attention bias to positive affective stimuli. Negative affective state, negative affective pain facilitation, nor negative attention bias were altered by sleep continuity disruption. The present findings, observed across multiple measures of affective function, suggest that sleep continuity disruption has a stronger influence on the positive affective system relative to the negative affective affective system. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Male-Biased Sexual Size Dimorphism, Resource Defense Polygyny, and Multiple Paternity in the Emei Moustache Toad (Leptobrachium boringii)

PubMed Central

Hudson, Cameron M.; Fu, Jinzhong

2013-01-01

We tested the hypotheses that the Emei moustache toad (Leptobrachium boringii) exhibits resource defense polygyny and that combat led to the evolution of male-biased sexual size dimorphism. Between February and March of 2011 and 2012, 26 female and 55 male L. boringii from Mount Emei UNESCO World Heritage Site, Sichuan, China, were observed throughout the breeding season. Prior to the breeding season, males grow 10–16 keratinized maxillary nuptial spines, which fall off once the season has ended. Throughout this time, males construct and defend aquatic nests where they produce advertisement calls to attract females. In a natural setting, we documented 14 cases involving a total of 22 males where males used their moustaches for aggressive interaction, and nest takeover was observed on seven occasions. Males were also observed to possess injuries resulting from combat. Genetic analysis using microsatellite DNA markers revealed several cases of multiple paternity, both within nest and within clutch. This observation indicated that some alternative male reproductive strategy, such as satellite behaviour, is occurring, which may have led to the multiple paternity. Larger males were observed to mate more frequently, and in multiple nests, suggesting that females are selecting for larger males, or that larger males are more capable of defending high quality territories. PMID:23840725

Lorazepam induces multiple disturbances in selective attention: attentional overload, decrement in target processing efficiency, and shifts in perceptual discrimination and response bias.

PubMed

Michael, George Andrew; Bacon, Elisabeth; Offerlin-Meyer, Isabelle

2007-09-01

There is a general consensus that benzodiazepines affect attentional processes, yet only few studies have tried to investigate these impairments in detail. The purpose of the present study was to investigate the effects of a single dose of Lorazepam on performance in a target cancellation task with important time constraints. We measured correct target detections and correct distractor rejections, misses and false positives. The results show that Lorazepam produces multiple kinds of shifts in performance, which suggests that it impairs multipLe processes: (a) the evolution of performance over time was not the same between the placebo and the Lorazepam groups, with the Lorazepam affecting performance quite early after the beginning of the test. This is suggestive of a depletion of attentional resources during sequential attentional processing; (b) Lorazepam affected differently target and distractor processing, with target detection being the most impaired; (c) misses were more frequent under Lorazepam than under placebo, but no such difference was observed as far as false positives were concerned. Signal detection analyses showed that Lorazepam (d) decreased perceptual discrimination, and (e) reliably increased response bias. Our results bring new insights on the multiple effects of Lorazepam on selective attention which, when combined, may have deleterious effects on human performance.

Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm.

PubMed

Agarwal, Krishna; Macháň, Radek; Prasad, Dilip K

2018-03-21

Localization microscopy and multiple signal classification algorithm use temporal stack of image frames of sparse emissions from fluorophores to provide super-resolution images. Localization microscopy localizes emissions in each image independently and later collates the localizations in all the frames, giving same weight to each frame irrespective of its signal-to-noise ratio. This results in a bias towards frames with low signal-to-noise ratio and causes cluttered background in the super-resolved image. User-defined heuristic computational filters are employed to remove a set of localizations in an attempt to overcome this bias. Multiple signal classification performs eigen-decomposition of the entire stack, irrespective of the relative signal-to-noise ratios of the frames, and uses a threshold to classify eigenimages into signal and null subspaces. This results in under-representation of frames with low signal-to-noise ratio in the signal space and over-representation in the null space. Thus, multiple signal classification algorithms is biased against frames with low signal-to-noise ratio resulting into suppression of the corresponding fluorophores. This paper presents techniques to automatically debias localization microscopy and multiple signal classification algorithm of these biases without compromising their resolution and without employing heuristics, user-defined criteria. The effect of debiasing is demonstrated through five datasets of invitro and fixed cell samples.

Characteristics of bias-based harassment incidents reported by a national sample of U.S. adolescents.

PubMed

Jones, Lisa M; Mitchell, Kimberly J; Turner, Heather A; Ybarra, Michele L

2018-06-01

Using a national sample of youth from the U.S., this paper examines incidents of bias-based harassment by peers that include language about victims' perceived sexual orientation, race/ethnicity, religion, weight or height, or intelligence. Telephone interviews were conducted with youth who were 10-20 years old (n = 791). One in six youth (17%) reported at least one experience with bias-based harassment in the past year. Bias language was a part of over half (52%) of all harassment incidents experienced by youth. Perpetrators of bias-based harassment were similar demographically to perpetrators of non-biased harassment. However, bias-based incidents were more likely to involve multiple perpetrators, longer timeframes and multiple harassment episodes. Even controlling for these related characteristics, the use of bias language in incidents of peer harassment resulted in significantly greater odds that youth felt sad as a result of the victimization, skipped school, avoided school activities, and lost friends, compared to non-biased harassment incidents. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values

NASA Astrophysics Data System (ADS)

López Ríos, Pablo; Monserrat, Bartomeu; Needs, Richard J.

2018-02-01

The thermal lines method for the evaluation of vibrational expectation values of electronic observables [B. Monserrat, Phys. Rev. B 93, 014302 (2016), 10.1103/PhysRevB.93.014302] was recently proposed as a physically motivated approximation offering balance between the accuracy of direct Monte Carlo integration and the low computational cost of using local quadratic approximations. In this paper we reformulate thermal lines as a stochastic implementation of quadrature-grid integration, analyze the analytical form of its bias, and extend the method to multiple-point quadrature grids applicable to any factorizable harmonic or anharmonic nuclear wave function. The bias incurred by thermal lines is found to depend on the local form of the expectation value, and we demonstrate that the use of finer quadrature grids along selected modes can eliminate this bias, while still offering an ˜30 % lower computational cost than direct Monte Carlo integration in our tests.

Virtual Embodiment of White People in a Black Virtual Body Leads to a Sustained Reduction in Their Implicit Racial Bias.

PubMed

Banakou, Domna; Hanumanthu, Parasuram D; Slater, Mel

2016-01-01

Virtual reality can be used to visually substitute a person's body by a life-sized virtual one. Such embodiment results in a perceptual illusion of body ownership over the virtual body (VB). Previous research has shown that the form of the VB can influence implicit attitudes. In particular, embodying White people in a Black virtual body is associated with an immediate decrease in their implicit racial bias against Black people. We tested whether the reduction in implicit bias lasts for at least 1 week and whether it is enhanced by multiple exposures. Two experiments were carried out with a total of 90 female participants where the virtual body was either Black or White. Participants were required to follow a virtual Tai Chi teacher who was either Asian or European Caucasian. Each participant had 1, 2, or 3 exposures separated by days. Implicit racial bias was measured 1 week before their first exposure and 1 week after their last. The results show that implicit bias decreased more for those with the Black virtual body than the White. There was also some evidence of a general decrease in bias independently of body type for which possible explanations are put forward.

Virtual Embodiment of White People in a Black Virtual Body Leads to a Sustained Reduction in Their Implicit Racial Bias

PubMed Central

Banakou, Domna; Hanumanthu, Parasuram D.; Slater, Mel

2016-01-01

Virtual reality can be used to visually substitute a person's body by a life-sized virtual one. Such embodiment results in a perceptual illusion of body ownership over the virtual body (VB). Previous research has shown that the form of the VB can influence implicit attitudes. In particular, embodying White people in a Black virtual body is associated with an immediate decrease in their implicit racial bias against Black people. We tested whether the reduction in implicit bias lasts for at least 1 week and whether it is enhanced by multiple exposures. Two experiments were carried out with a total of 90 female participants where the virtual body was either Black or White. Participants were required to follow a virtual Tai Chi teacher who was either Asian or European Caucasian. Each participant had 1, 2, or 3 exposures separated by days. Implicit racial bias was measured 1 week before their first exposure and 1 week after their last. The results show that implicit bias decreased more for those with the Black virtual body than the White. There was also some evidence of a general decrease in bias independently of body type for which possible explanations are put forward. PMID:27965555

Test Bias and the Culturally Different Early Adolescent.

ERIC Educational Resources Information Center

Roberts, Eileen; DeBlassie, Richard R.

1983-01-01

Defines test bias as a phenomenon in which test scores result in negative outcomes for certain groups, often lower socioeconomic groups and minorities. Discusses three manifestations of test bias including content, atmosphere, and use bias and presents recommendations for remedying bias problems in testing the culturally different. (JAC)

Studying Gender Bias in Physics Grading: The role of teaching experience and country

NASA Astrophysics Data System (ADS)

Hofer, Sarah I.

2015-11-01

The existence of gender-STEM (science, technology, engineering, and mathematics) stereotypes has been repeatedly documented. This article examines physics teachers' gender bias in grading and the influence of teaching experience in Switzerland, Austria, and Germany. In a 2 × 2 between-subjects design, with years of teaching experience included as moderating variable, physics teachers (N = 780) from Switzerland, Austria, and Germany graded a fictive student's answer to a physics test question. While the answer was exactly the same for each teacher, only the student's gender and specialization in languages vs. science were manipulated. Specialization was included to gauge the relative strength of potential gender bias effects. Multiple group regression analyses, with the grade that was awarded as the dependent variable, revealed only partial cross-border generalizability of the effect pattern. While the overall results in fact indicated the existence of a consistent and clear gender bias against girls in the first part of physics teachers' careers that disappeared with increasing teaching experience for Swiss teachers, Austrian teachers, and German female teachers, German male teachers showed no gender bias effects at all. The results are discussed regarding their relevance for educational practice and research.

Atmospheric Multiple Scattering Effects on GLAS Altimetry. Part 2; Analysis of Expected Errors in Antarctic Altitude Measurements

NASA Technical Reports Server (NTRS)

Mahesh, Ashwin; Spinhirne, James D.; Duda, David P.; Eloranta, Edwin W.; Starr, David O'C (Technical Monitor)

2001-01-01

The altimetry bias in GLAS (Geoscience Laser Altimeter System) or other laser altimeters resulting from atmospheric multiple scattering is studied in relationship to current knowledge of cloud properties over the Antarctic Plateau. Estimates of seasonal and interannual changes in the bias are presented. Results show the bias in altitude from multiple scattering in clouds would be a significant error source without correction. The selective use of low optical depth clouds or cloudfree observations, as well as improved analysis of the return pulse such as by the Gaussian method used here, are necessary to minimize the surface altitude errors. The magnitude of the bias is affected by variations in cloud height, cloud effective particle size and optical depth. Interannual variations in these properties as well as in cloud cover fraction could lead to significant year-to-year variations in the altitude bias. Although cloud-free observations reduce biases in surface elevation measurements from space, over Antarctica these may often include near-surface blowing snow, also a source of scattering-induced delay. With careful selection and analysis of data, laser altimetry specifications can be met.

An Item Response Theory Model for Test Bias.

ERIC Educational Resources Information Center

Shealy, Robin; Stout, William

This paper presents a conceptualization of test bias for standardized ability tests which is based on multidimensional, non-parametric, item response theory. An explanation of how individually-biased items can combine through a test score to produce test bias is provided. It is contended that bias, although expressed at the item level, should be…

Parallel, multi-stage processing of colors, faces and shapes in macaque inferior temporal cortex

PubMed Central

Lafer-Sousa, Rosa; Conway, Bevil R.

2014-01-01

Visual-object processing culminates in inferior temporal (IT) cortex. To assess the organization of IT, we measured fMRI responses in alert monkey to achromatic images (faces, fruit, bodies, places) and colored gratings. IT contained multiple color-biased regions, which were typically ventral to face patches and, remarkably, yoked to them, spaced regularly at four locations predicted by known anatomy. Color and face selectivity increased for more anterior regions, indicative of a broad hierarchical arrangement. Responses to non-face shapes were found across IT, but were stronger outside color-biased regions and face patches, consistent with multiple parallel streams. IT also contained multiple coarse eccentricity maps: face patches overlapped central representations; color-biased regions spanned mid-peripheral representations; and place-biased regions overlapped peripheral representations. These results suggest that IT comprises parallel, multi-stage processing networks subject to one organizing principle. PMID:24141314

What is the contribution of different cognitive biases and stressful childhood events to the presence and number of previous depressive episodes?

PubMed

Vrijsen, Janna N; Becker, Eni S; Arias-Vásquez, Alejandro; van Dijk, Maarten K; Speckens, Anne; Oostrom, Iris van

2014-07-30

Negative cognitive biases as well as stressful childhood events are well-known risk factors for depression. Few studies have compared the association of different types of biases and events with depression. The current study examined whether different cognitive biases and stressful childhood events variables were associated with depression and recurrence. Three types of childhood events were assessed in 83 never-depressed and 337 formerly depressed individuals: trauma within the family, trauma outside the family, and adverse events. Furthermore, after a sad mood induction procedure, participants executed a Dot Probe task (selective attentional bias), an Emotional Stroop task (attentional interference bias) and an incidental learning task (memory bias). The association of these measures with case status and recurrence status (one or multiple past episodes) was examined. Negative memory bias and traumatic childhood events within the family were associated with case status, whereas none of the bias measures or childhood events variables were associated with recurrence status. The results indicate that memory bias as well as the experience of aggression and/or abuse within the family during childhood are independently associated with depression. Biases and stressful childhood events did not offer differentiation between individuals with one or multiple past episodes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Biased Tests.

ERIC Educational Resources Information Center

Green, Donald Ross

This paper is concerned with the accusations made by such groups as the Association of Black Psychologists in their call for a moratorium on testing, that standardized tests are biased. A biased test measures one trait in one group of people but a different trait in a second group. Evidence about the amount of bias in tests is thin. Bias must be…

Multiple Levels of Cultural Bias in TESOL Course Books

ERIC Educational Resources Information Center

Sherman, John Eric

2010-01-01

This study investigates the biased treatment of non-native characters in model dialogues in current Teaching English to Speakers of Other Languages (TESOL) course books. Although a plethora of studies have been conducted on gender bias in course books, speaker bias, or labelled "nativism" here, has been largely ignored. This research addresses…

No arousal-biased competition in focused visuospatial attention.

PubMed

Ásgeirsson, Árni Gunnar; Nieuwenhuis, Sander

2017-11-01

Arousal sometimes enhances and sometimes impairs perception and memory. A recent theory attempts to reconcile these findings by proposing that arousal amplifies the competition between stimulus representations, strengthening already strong representations and weakening already weak representations. Here, we report a stringent test of this arousal-biased competition theory in the context of focused visuospatial attention. Participants were required to identify a briefly presented target in the context of multiple distractors, which varied in the degree to which they competed for representation with the target, as revealed by psychophysics. We manipulated arousal using emotionally arousing pictures (Experiment 1), alerting tones (Experiment 2) and white-noise stimulation (Experiment 3), and validated these manipulations with electroencephalography and pupillometry. In none of the experiments did we find evidence that arousal modulated the effect of distractor competition on the accuracy of target identification. Bayesian statistics revealed moderate to strong evidence against arousal-biased competition. Modeling of the psychophysical data based on Bundesen's (1990) theory of visual attention corroborated the conclusion that arousal does not bias competition in focused visuospatial attention. Copyright © 2017 Elsevier B.V. All rights reserved.

The Impact of Sleep-Related Attentional Bias on Polysomnographically Measured Sleep in Primary Insomnia

PubMed Central

Spiegelhalder, Kai; Kyle, Simon D.; Feige, Bernd; Prem, Martin; Nissen, Christoph; Espie, Colin A.; Riemann, Dieter

2010-01-01

Study Objectives: Although sleep-related attentional bias has been shown to be evident in primary insomnia, the association with objectively measured sleep has not been investigated. In the present study, we used polysomnography (PSG) to fill this void. Design: Patients with primary insomnia and healthy controls were studied using a visual dot probe task (VDP) and an emotional Stroop task (EST). Additionally, polysomnography was carried out in a sub-sample (n = 22) of patients in the subsequent night. Setting: Department of Psychiatry and Psychotherapy of the University of Freiburg Medical Center. Participants: Thirty patients with primary insomnia and 30 matched healthy controls. Interventions: N/A Measurements and Results: Patients with primary insomnia demonstrated a significant sleep-related attentional bias compared to controls in the EST but no significant group effects were found for the VDP. VDP attentional bias scores were positively correlated with measures of sleep pressure, including total sleep time, sleep efficiency, and the amount of slow wave sleep. EST attentional bias scores were not correlated with subsequent PSG parameters, and we did not observe a correlation between attentional bias scores on the two tasks. Conclusions: The unexpected relationship between increased attentional bias, in the VDP task, and improved markers of sleep duration and continuity, may be indicative of a homeostatic craving for sleep in those with high attentional bias. This awaits further testing in multiple night studies, to shed light on the mechanisms and implications of sleep-related attentional bias. Citation: Spiegelhalder K; Kyle SD; Feige B; Prem M; Nissen C; Espie CA; Riemann D. The impact of sleep-related attentional bias on polysomnographically measured sleep in primary insomnia. SLEEP 2010;33(1):107-112. PMID:20120627

Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information.

PubMed

Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor

2013-01-01

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.

Test Bias: An Objective Definition for Test Items.

ERIC Educational Resources Information Center

Durovic, Jerry J.

A test bias definition, applicable at the item-level of a test is presented. The definition conceptually equates test bias with measuring different things in different groups, and operationally equates test bias with a difference in item fit to the Rasch Model, greater than one, between groups. It is suggested that the proposed definition avoids…

FEM: Feature-enhanced map

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

Afonine, Pavel V.; Moriarty, Nigel W.; Mustyakimov, Marat

A method is presented that modifies a 2 m F obs- D F modelσ A-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretabilitymore » and decreased model bias compared with the starting 2 m F obs- D F modelσ A-weighted map.« less

FEM: feature-enhanced map

PubMed Central

Afonine, Pavel V.; Moriarty, Nigel W.; Mustyakimov, Marat; Sobolev, Oleg V.; Terwilliger, Thomas C.; Turk, Dusan; Urzhumtsev, Alexandre; Adams, Paul D.

2015-01-01

A method is presented that modifies a 2m F obs − D F model σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2m F obs − D F model σA-weighted map. PMID:25760612

FEM: Feature-enhanced map

DOE PAGES

Afonine, Pavel V.; Moriarty, Nigel W.; Mustyakimov, Marat; ...

2015-02-26

A method is presented that modifies a 2 m F obs- D F modelσ A-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretabilitymore » and decreased model bias compared with the starting 2 m F obs- D F modelσ A-weighted map.« less

Multiple factors influence population sex ratios in the Mojave Desert moss Syntrichia caninervis.

PubMed

Baughman, Jenna T; Payton, Adam C; Paasch, Amber E; Fisher, Kirsten M; McDaniel, Stuart F

2017-05-01

Natural populations of many mosses appear highly female-biased based on the presence of reproductive structures. This bias could be caused by increased male mortality, lower male growth rate, or a higher threshold for achieving sexual maturity in males. Here we test these hypotheses using samples from two populations of the Mojave Desert moss Syntrichia caninervis . We used double-digest restriction-site associated DNA (RAD) sequencing to identify candidate sex-associated loci in a panel of sex-expressing plants. Next, we used putative sex-associated markers to identify the sex of individuals without sex structures. We found a 17:1 patch-level phenotypic female to male sex ratio in the higher elevation site (Wrightwood) and no sex expression at the low elevation site (Phelan). In contrast, on the basis of genetic data, we found a 2:1 female bias at the Wrightwood site and only females at the Phelan site. The relative area occupied by male and female genets was indistinguishable, but males were less genetically diverse. Our data suggest that both male-biased mortality and sexual dimorphism in thresholds for sex expression could explain genetic and phenotypic sex ratio biases and that phenotypic sex expression alone over-estimates the extent of actual sex ratio bias present in these two populations of S. caninervis . © 2017 Botanical Society of America.

Dark Energy Survey Year 1 results: the impact of galaxy neighbours on weak lensing cosmology with IM3SHAPE

NASA Astrophysics Data System (ADS)

Samuroff, S.; Bridle, S. L.; Zuntz, J.; Troxel, M. A.; Gruen, D.; Rollins, R. P.; Bernstein, G. M.; Eifler, T. F.; Huff, E. M.; Kacprzak, T.; Krause, E.; MacCrann, N.; Abdalla, F. B.; Allam, S.; Annis, J.; Bechtol, K.; Benoit-Lévy, A.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Crocce, M.; D'Andrea, C. B.; da Costa, L. N.; Davis, C.; Desai, S.; Doel, P.; Fausti Neto, A.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Honscheid, K.; James, D. J.; Jarvis, M.; Jeltema, T.; Kirk, D.; Kuehn, K.; Kuhlmann, S.; Li, T. S.; Lima, M.; Maia, M. A. G.; March, M.; Marshall, J. L.; Martini, P.; Melchior, P.; Menanteau, F.; Miquel, R.; Nord, B.; Ogando, R. L. C.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Schindler, R.; Schubnell, M.; Sevilla-Noarbe, I.; Sheldon, E.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Tarle, G.; Thomas, D.; Tucker, D. L.; DES Collaboration

2018-04-01

We use a suite of simulated images based on Year 1 of the Dark Energy Survey to explore the impact of galaxy neighbours on shape measurement and shear cosmology. The HOOPOE image simulations include realistic blending, galaxy positions, and spatial variations in depth and point spread function properties. Using the IM3SHAPE maximum-likelihood shape measurement code, we identify four mechanisms by which neighbours can have a non-negligible influence on shear estimation. These effects, if ignored, would contribute a net multiplicative bias of m ˜ 0.03-0.09 in the Year One of the Dark Energy Survey (DES Y1) IM3SHAPE catalogue, though the precise impact will be dependent on both the measurement code and the selection cuts applied. This can be reduced to percentage level or less by removing objects with close neighbours, at a cost to the effective number density of galaxies neff of 30 per cent. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude S8 ≡ σ8(Ωm/0.3)0.5 by 2σ towards low values. Finally, we use the HOOPOE simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the impact on the recovered S8 of ignoring such correlations to be subdominant to statistical error at the current level of precision.

Dark Energy Survey Year 1 results: the impact of galaxy neighbours on weak lensing cosmology with IM3SHAPE

DOE PAGES

Samuroff, S.

2017-12-26

We use a suite of simulated images based on Year 1 of the Dark Energy Survey to explore the impact of galaxy neighbours on shape measurement and shear cosmology. The hoopoe image simulations include realistic blending, galaxy positions, and spatial variations in depth and PSF properties. Using the im3shape maximum-likelihood shape measurement code, we identify four mechanisms by which neighbours can have a non-negligible influence on shear estimation. These effects, if ignored, would contribute a net multiplicative bias ofmore » $$m \\sim 0.03 - 0.09$$ in the DES Y1 im3shape catalogue, though the precise impact will be dependent on both the measurement code and the selection cuts applied. This can be reduced to percentage level or less by removing objects with close neighbours, at a cost to the effective number density of galaxies $$n_\\mathrm{eff}$$ of 30%. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $$S_8\\equiv \\sigma_8 (\\Omega _\\mathrm{m} /0.3)^{0.5}$$ by $$2 \\sigma$$ towards low values. Lastly, we use the hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the impact on the recovered $$S_8$$ of ignoring such correlations to be subdominant to statistical error at the current level of precision.« less

Dark Energy Survey Year 1 results: the impact of galaxy neighbours on weak lensing cosmology with IM3SHAPE

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

Samuroff, S.

We use a suite of simulated images based on Year 1 of the Dark Energy Survey to explore the impact of galaxy neighbours on shape measurement and shear cosmology. The hoopoe image simulations include realistic blending, galaxy positions, and spatial variations in depth and PSF properties. Using the im3shape maximum-likelihood shape measurement code, we identify four mechanisms by which neighbours can have a non-negligible influence on shear estimation. These effects, if ignored, would contribute a net multiplicative bias ofmore » $$m \\sim 0.03 - 0.09$$ in the DES Y1 im3shape catalogue, though the precise impact will be dependent on both the measurement code and the selection cuts applied. This can be reduced to percentage level or less by removing objects with close neighbours, at a cost to the effective number density of galaxies $$n_\\mathrm{eff}$$ of 30%. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $$S_8\\equiv \\sigma_8 (\\Omega _\\mathrm{m} /0.3)^{0.5}$$ by $$2 \\sigma$$ towards low values. Lastly, we use the hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the impact on the recovered $$S_8$$ of ignoring such correlations to be subdominant to statistical error at the current level of precision.« less

A simulation test of the effectiveness of several methods for error-checking non-invasive genetic data

USGS Publications Warehouse

Roon, David A.; Waits, L.P.; Kendall, K.C.

2005-01-01

Non-invasive genetic sampling (NGS) is becoming a popular tool for population estimation. However, multiple NGS studies have demonstrated that polymerase chain reaction (PCR) genotyping errors can bias demographic estimates. These errors can be detected by comprehensive data filters such as the multiple-tubes approach, but this approach is expensive and time consuming as it requires three to eight PCR replicates per locus. Thus, researchers have attempted to correct PCR errors in NGS datasets using non-comprehensive error checking methods, but these approaches have not been evaluated for reliability. We simulated NGS studies with and without PCR error and 'filtered' datasets using non-comprehensive approaches derived from published studies and calculated mark-recapture estimates using CAPTURE. In the absence of data-filtering, simulated error resulted in serious inflations in CAPTURE estimates; some estimates exceeded N by ??? 200%. When data filters were used, CAPTURE estimate reliability varied with per-locus error (E??). At E?? = 0.01, CAPTURE estimates from filtered data displayed < 5% deviance from error-free estimates. When E?? was 0.05 or 0.09, some CAPTURE estimates from filtered data displayed biases in excess of 10%. Biases were positive at high sampling intensities; negative biases were observed at low sampling intensities. We caution researchers against using non-comprehensive data filters in NGS studies, unless they can achieve baseline per-locus error rates below 0.05 and, ideally, near 0.01. However, we suggest that data filters can be combined with careful technique and thoughtful NGS study design to yield accurate demographic information. ?? 2005 The Zoological Society of London.

A Procedure To Detect Test Bias Present Simultaneously in Several Items.

ERIC Educational Resources Information Center

Shealy, Robin; Stout, William

A statistical procedure is presented that is designed to test for unidirectional test bias existing simultaneously in several items of an ability test, based on the assumption that test bias is incipient within the two groups' ability differences. The proposed procedure--Simultaneous Item Bias (SIB)--is based on a multidimensional item response…

The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland.

PubMed

Latkin, Carl A; Edwards, Catie; Davey-Rothwell, Melissa A; Tobin, Karin E

2017-10-01

Social desirability response bias may lead to inaccurate self-reports and erroneous study conclusions. The present study examined the relationship between social desirability response bias and self-reports of mental health, substance use, and social network factors among a community sample of inner-city substance users. The study was conducted in a sample of 591 opiate and cocaine users in Baltimore, Maryland from 2009 to 2013. Modified items from the Marlowe-Crowne Social Desirability Scale were included in the survey, which was conducted face-to-face and using Audio Computer Self Administering Interview (ACASI) methods. There were highly statistically significant differences in levels of social desirability response bias by levels of depressive symptoms, drug use stigma, physical health status, recent opiate and cocaine use, Alcohol Use Disorders Identification Test (AUDIT) scores, and size of social networks. There were no associations between health service utilization measures and social desirability bias. In multiple logistic regression models, even after including the Center for Epidemiologic Studies Depression Scale (CES-D) as a measure of depressive symptomology, social desirability bias was associated with recent drug use and drug user stigma. Social desirability bias was not associated with enrollment in prior research studies. These findings suggest that social desirability bias is associated with key health measures and that the associations are not primarily due to depressive symptoms. Methods are needed to reduce social desirability bias. Such methods may include the wording and prefacing of questions, clearly defining the role of "study participant," and assessing and addressing motivations for socially desirable responses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Perceptual memory drives learning of retinotopic biases for bistable stimuli.

PubMed

Murphy, Aidan P; Leopold, David A; Welchman, Andrew E

2014-01-01

The visual system exploits past experience at multiple timescales to resolve perceptual ambiguity in the retinal image. For example, perception of a bistable stimulus can be biased toward one interpretation over another when preceded by a brief presentation of a disambiguated version of the stimulus (positive priming) or through intermittent presentations of the ambiguous stimulus (stabilization). Similarly, prior presentations of unambiguous stimuli can be used to explicitly "train" a long-lasting association between a percept and a retinal location (perceptual association). These phenonema have typically been regarded as independent processes, with short-term biases attributed to perceptual memory and longer-term biases described as associative learning. Here we tested for interactions between these two forms of experience-dependent perceptual bias and demonstrate that short-term processes strongly influence long-term outcomes. We first demonstrate that the establishment of long-term perceptual contingencies does not require explicit training by unambiguous stimuli, but can arise spontaneously during the periodic presentation of brief, ambiguous stimuli. Using rotating Necker cube stimuli, we observed enduring, retinotopically specific perceptual biases that were expressed from the outset and remained stable for up to 40 min, consistent with the known phenomenon of perceptual stabilization. Further, bias was undiminished after a break period of 5 min, but was readily reset by interposed periods of continuous, as opposed to periodic, ambiguous presentation. Taken together, the results demonstrate that perceptual biases can arise naturally and may principally reflect the brain's tendency to favor recent perceptual interpretation at a given retinal location. Further, they suggest that an association between retinal location and perceptual state, rather than a physical stimulus, is sufficient to generate long-term biases in perceptual organization.

Recalibration of blood analytes over 25 years in the Atherosclerosis Risk in Communities Study: The impact of recalibration on chronic kidney disease prevalence and incidence

PubMed Central

Parrinello, Christina M.; Grams, Morgan E.; Couper, David; Ballantyne, Christie M.; Hoogeveen, Ron C.; Eckfeldt, John H.; Selvin, Elizabeth; Coresh, Josef

2016-01-01

Background Equivalence of laboratory tests over time is important for longitudinal studies. Even a small systematic difference (bias) can result in substantial misclassification. Methods We selected 200 Atherosclerosis Risk in Communities Study participants attending all 5 study visits over 25 years. Eight analytes were re-measured in 2011–13 from stored blood samples from multiple visits: creatinine, uric acid, glucose, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, and high-sensitivity C-reactive protein. Original values were recalibrated to re-measured values using Deming regression. Differences >10% were considered to reflect substantial bias, and correction equations were applied to affected analytes in the total study population. We examined trends in chronic kidney disease (CKD) pre- and post-recalibration. Results Repeat measures were highly correlated with original values (Pearson’s r>0.85 after removing outliers [median 4.5% of paired measurements]), but 2 of 8 analytes (creatinine and uric acid) had differences >10%. Original values of creatinine and uric acid were recalibrated to current values using correction equations. CKD prevalence differed substantially after recalibration of creatinine (visits 1, 2, 4 and 5 pre-recalibration: 21.7%, 36.1%, 3.5%, 29.4%; post-recalibration: 1.3%, 2.2%, 6.4%, 29.4%). For HDL-cholesterol, the current direct enzymatic method differed substantially from magnesium dextran precipitation used during visits 1–4. Conclusions Analytes re-measured in samples stored for ~25 years were highly correlated with original values, but two of the 8 analytes showed substantial bias at multiple visits. Laboratory recalibration improved reproducibility of test results across visits and resulted in substantial differences in CKD prevalence. We demonstrate the importance of consistent recalibration of laboratory assays in a cohort study. PMID:25952043

Validation of continuous particle monitors for personal, indoor, and outdoor exposures.

PubMed

Wallace, Lance A; Wheeler, Amanda J; Kearney, Jill; Van Ryswyk, Keith; You, Hongyu; Kulka, Ryan H; Rasmussen, Pat E; Brook, Jeff R; Xu, Xiaohong

2011-01-01

Continuous monitors can be used to supplement traditional filter-based methods of determining personal exposure to air pollutants. They have the advantages of being able to identify nearby sources and detect temporal changes on a time scale of a few minutes. The Windsor Ontario Exposure Assessment Study (WOEAS) adopted an approach of using multiple continuous monitors to measure indoor, outdoor (near-residential) and personal exposures to PM₂.₅, ultrafine particles and black carbon. About 48 adults and households were sampled for five consecutive 24-h periods in summer and winter 2005, and another 48 asthmatic children for five consecutive 24-h periods in summer and winter 2006. This article addresses the laboratory and field validation of these continuous monitors. A companion article (Wheeler et al., 2010) provides similar analyses for the 24-h integrated methods, as well as providing an overview of the objectives and study design. The four continuous monitors were the DustTrak (Model 8520, TSI, St. Paul, MN, USA) and personal DataRAM (pDR) (ThermoScientific, Waltham, MA, USA) for PM₂.₅; the P-Trak (Model 8525, TSI) for ultrafine particles; and the Aethalometer (AE-42, Magee Scientific, Berkeley, CA, USA) for black carbon (BC). All monitors were tested in multiple co-location studies involving as many as 16 monitors of a given type to determine their limits of detection as well as bias and precision. The effect of concentration and electronic drift on bias and precision were determined from both the collocated studies and the full field study. The effect of rapid changes in environmental conditions on switching an instrument from indoor to outdoor sampling was also studied. The use of multiple instruments for outdoor sampling was valuable in identifying occasional poor performance by one instrument and in better determining local contributions to the spatial variation of particulate pollution. Both the DustTrak and pDR were shown to be in reasonable agreement (R² of 90 and 70%, respectively) with the gravimetric PM₂.₅ method. Both instruments had limits of detection of about 5 μg/m³. The DustTrak and pDR had multiplicative biases of about 2.5 and 1.6, respectively, compared with the gravimetric samplers. However, their average bias-corrected precisions were <10%, indicating that a proper correction for bias would bring them into very good agreement with standard methods. Although no standard methods exist to establish the bias of the Aethalometer and P-Trak, the precision was within 20% for the Aethalometer and within 10% for the P-Trak. These findings suggest that all four instruments can supply useful information in environmental studies.

Effect of Examiner Experience and Technique on the Alternate Cover Test

PubMed Central

Anderson, Heather A.; Manny, Ruth E.; Cotter, Susan A.; Mitchell, G. Lynn; Irani, Jasmine A.

2013-01-01

Purpose To compare the repeatability of the alternate cover test between experienced and inexperienced examiners and the effects of dissociation time and examiner bias. Methods Two sites each had an experienced examiner train 10 subjects (inexperienced examiners) to perform short and long dissociation time alternate cover test protocols at near. Each site conducted testing sessions with an examiner triad (experienced examiner and two inexperienced examiners) who were masked to each other’s results. Each triad performed the alternate cover test on 24 patients using both dissociation protocols. In an attempt to introduce bias, each of the paired inexperienced examiners was given a different graph of phoria distribution for the general population. Analysis techniques that adjust for correlations introduced when multiple measurements are obtained on the same patient were used to investigate the effect of examiner and dissociation time on each outcome. Results The range of measured deviations spanned 27.5 prism diopters (Δ) base-in to 17.5Δ base-out. The absolute mean difference between experienced and inexperienced examiners was 2.28 ± 2.4Δ and at least 60% of differences were ≤2Δ. Larger deviations were measured with the long dissociation protocol for both experienced and inexperienced examiners (mean difference range = 1.17 to 2.14Δ, p < 0.0001). The percentage of measured small deviations (2Δ base-out to 2Δ base-in) did not differ between inexperienced examiners biased with the narrow vs. wide theoretical distributions (p = 0.41). The magnitude and direction of the deviation had no effect on the size of the differences obtained with different examiners or dissociation times. Conclusions Although inexperienced examiners differed significantly from experienced examiners, most differences were <2Δ suggesting good reliability of inexperienced examiners’ measurements. Examiner bias did not have a substantial effect on inexperienced examiner measurements; however, increased dissociation resulted in larger measured deviations for all examiners. PMID:20125058

Initial nonresponse and survey response mode biases in survey research.

PubMed

Chi, Donald L; Chen, Chao Ying

2015-01-01

We evaluated survey response factors (particularly initial nonresponse and survey mode) that may be associated with bias in survey research. We examined prevention-related beliefs and outcomes for initial mail survey responders (n=209), follow-up mail survey responders (n=78), and follow-up telephone survey responders (n=74). The Pearson chi-square test and analysis of variance identified beliefs and behavioral outcomes associated with survey response mode. Follow-up options to the initial mail survey improved response rates (22.0-38.0 percent). Initial mail survey responders more strongly believed topical fluoride protects teeth from cavities than others (P=0.04). A significantly larger proportion of parents completing a follow-up telephone survey (30.8 percent) refused topical fluoride for their child than those completing mail surveys (10.3-10.4 percent) (P<0.0001). Multiple mode surveys with follow-up improve response rates. Initial nonresponse and survey response mode may be associated with biases in survey research. © 2015 American Association of Public Health Dentistry.

Student nurse selection and predictability of academic success: The Multiple Mini Interview project.

PubMed

Gale, Julia; Ooms, Ann; Grant, Robert; Paget, Kris; Marks-Maran, Di

2016-05-01

With recent reports of public enquiries into failure to care, universities are under pressure to ensure that candidates selected for undergraduate nursing programmes demonstrate academic potential as well as characteristics and values such as compassion, empathy and integrity. The Multiple Mini Interview (MMI) was used in one university as a way of ensuring that candidates had the appropriate numeracy and literacy skills as well as a range of communication, empathy, decision-making and problem-solving skills as well as ethical insights and integrity, initiative and team-work. To ascertain whether there is evidence of bias in MMIs (gender, age, nationality and location of secondary education) and to determine the extent to which the MMI is predictive of academic success in nursing. A longitudinal retrospective analysis of student demographics, MMI data and the assessment marks for years 1, 2 and 3. One university in southwest London. One cohort of students who commenced their programme in September 2011, including students in all four fields of nursing (adult, child, mental health and learning disability). Inferential statistics and a Bayesian Multilevel Model. MMI in conjunction with MMI numeracy test and MMI literacy test shows little or no bias in terms of ages, gender, nationality or location of secondary school education. Although MMI in conjunction with numeracy and literacy testing is predictive of academic success, it is only weakly predictive. The MMI used in conjunction with literacy and numeracy testing appears to be a successful technique for selecting candidates for nursing. However, other selection methods such as psychological profiling or testing of emotional intelligence may add to the extent to which selection methods are predictive of academic success on nursing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

PubMed

Lujan, J Luis; Crago, Patrick E

2009-01-01

This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Two Wrongs Make a Right: Addressing Underreporting in Binary Data from Multiple Sources.

PubMed

Cook, Scott J; Blas, Betsabe; Carroll, Raymond J; Sinha, Samiran

2017-04-01

Media-based event data-i.e., data comprised from reporting by media outlets-are widely used in political science research. However, events of interest (e.g., strikes, protests, conflict) are often underreported by these primary and secondary sources, producing incomplete data that risks inconsistency and bias in subsequent analysis. While general strategies exist to help ameliorate this bias, these methods do not make full use of the information often available to researchers. Specifically, much of the event data used in the social sciences is drawn from multiple, overlapping news sources (e.g., Agence France-Presse, Reuters). Therefore, we propose a novel maximum likelihood estimator that corrects for misclassification in data arising from multiple sources. In the most general formulation of our estimator, researchers can specify separate sets of predictors for the true-event model and each of the misclassification models characterizing whether a source fails to report on an event. As such, researchers are able to accurately test theories on both the causes of and reporting on an event of interest. Simulations evidence that our technique regularly out performs current strategies that either neglect misclassification, the unique features of the data-generating process, or both. We also illustrate the utility of this method with a model of repression using the Social Conflict in Africa Database.

Analyzing Test-Taking Behavior: Decision Theory Meets Psychometric Theory.

PubMed

Budescu, David V; Bo, Yuanchao

2015-12-01

We investigate the implications of penalizing incorrect answers to multiple-choice tests, from the perspective of both test-takers and test-makers. To do so, we use a model that combines a well-known item response theory model with prospect theory (Kahneman and Tversky, Prospect theory: An analysis of decision under risk, Econometrica 47:263-91, 1979). Our results reveal that when test-takers are fully informed of the scoring rule, the use of any penalty has detrimental effects for both test-takers (they are always penalized in excess, particularly those who are risk averse and loss averse) and test-makers (the bias of the estimated scores, as well as the variance and skewness of their distribution, increase as a function of the severity of the penalty).

The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

PubMed

Booth, Charlotte; Songco, Annabel; Parsons, Sam; Heathcote, Lauren; Vincent, John; Keers, Robert; Fox, Elaine

2017-12-29

Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.

Measuring Individual Differences in Decision Biases: Methodological Considerations

PubMed Central

Aczel, Balazs; Bago, Bence; Szollosi, Aba; Foldes, Andrei; Lukacs, Bence

2015-01-01

Individual differences in people's susceptibility to heuristics and biases (HB) are often measured by multiple-bias questionnaires consisting of one or a few items for each bias. This research approach relies on the assumptions that (1) different versions of a decision bias task measure are interchangeable as they measure the same cognitive failure; and (2) that some combination of these tasks measures the same underlying construct. Based on these assumptions, in Study 1 we developed two versions of a new decision bias survey for which we modified 13 HB tasks to increase their comparability, construct validity, and the participants' motivation. The analysis of the responses (N = 1279) showed weak internal consistency within the surveys and a great level of discrepancy between the extracted patterns of the underlying factors. To explore these inconsistencies, in Study 2 we used three original examples of HB tasks for each of seven biases. We created three decision bias surveys by allocating one version of each HB task to each survey. The participants' responses (N = 527) showed a similar pattern as in Study 1, questioning the assumption that the different examples of the HB tasks are interchangeable and that they measure the same underlying construct. These results emphasize the need to understand the domain-specificity of cognitive biases as well as the effect of the wording of the cover story and the response mode on bias susceptibility before employing them in multiple-bias questionnaires. PMID:26635677

Flowing Plasma Interaction with an Electric Sail Tether Element

NASA Technical Reports Server (NTRS)

Schneider, Todd; Vaughn, Jason; Wright, Kenneth; Andersen, Allen; Stone, Nobie

2017-01-01

Electric sails are a relatively new concept for providing high speed propellant-less propulsion. Employing multiple tethers biased to high positive voltage levels (kV), electric sails are designed to gain momentum from the solar wind by repelling solar wind protons. To maximize the area of the sail that interacts with the solar wind, electric sails rely on the formation of a large plasma sheath around each small diameter tether. Motivated by interest in advancing the development of electric sails, a set of laboratory tests has been conducted to study the interaction of a drifting plasma with a sheath formed around a small diameter tether element biased at positive voltages. The laboratory test setup was created with Debye length scaling in mind to offer a path to extrapolate (via modeling) to full scale electric sail missions. Using an instrument known as a Differential Ion Flux Probe (DIFP) the interaction between a positively biased tether element and a drifting plasma has been measured for several scenarios. Clear evidence of the tether element sheath deflecting ions has been obtained. Maps of the flow angle downstream from the tether element have been made and they show the influence of the plasma sheath. Finally, electron current collection measurements have been made for a wide range of plasma conditions and tether element bias voltages. The electron collection data will have an impact on electric sail power requirements, as high voltage power supplies and electron guns will have to be sized to accommodate the electron currents collected by each tether.

Standing Up for Learning: A Pilot Investigation on the Neurocognitive Benefits of Stand-Biased School Desks

PubMed Central

Mehta, Ranjana K.; Shortz, Ashley E.; Benden, Mark E.

2015-01-01

Standing desks have proven to be effective and viable solutions to combat sedentary behavior among children during the school day in studies around the world. However, little is known regarding the potential of such interventions on cognitive outcomes in children over time. The purpose of this pilot study was to determine the neurocognitive benefits, i.e., improvements in executive functioning and working memory, of stand-biased desks and explore any associated changes in frontal brain function. 34 freshman high school students were recruited for neurocognitive testing at two time points during the school year: (1) in the fall semester and (2) in the spring semester (after 27.57 (1.63) weeks of continued exposure). Executive function and working memory was evaluated using a computerized neurocognitive test battery, and brain activation patterns of the prefrontal cortex were obtained using functional near infrared spectroscopy. Continued utilization of the stand-biased desks was associated with significant improvements in executive function and working memory capabilities. Changes in corresponding brain activation patterns were also observed. These findings provide the first preliminary evidence on the neurocognitive benefits of standing desks, which to date have focused largely on energy expenditure. Findings obtained here can drive future research with larger samples and multiple schools, with comparison groups that may in turn implicate the importance of stand-biased desks, as simple environmental changes in classrooms, on enhancing children’s cognitive functioning that drive their cognitive development and impact educational outcomes. PMID:26703700

Predictors and mediators of trait anger across the psychosis continuum: The role of attachment style, paranoia and social cognition.

PubMed

Darrell-Berry, Hannah; Bucci, Sandra; Palmier-Claus, Jasper; Emsley, Richard; Drake, Richard; Berry, Katherine

2017-03-01

Anger in the context of psychosis has a significant impact on treatment outcomes and serious implications for risk management. Understanding mechanisms underlying anger will improve interventions and inform strategies for prevention. This study is the first to examine the relationships between anger and key theoretical drivers across different phases of the psychosis continuum. A battery including measures of theory of mind, attachment, hostile attribution bias, paranoia and anger was administered to 174 participants (14 ultra-high risk, 20 first-episode, 20 established psychosis, 120 non-clinical participants). We tested the model that insecure attachment, paranoia, impaired theory of mind and hostile attribution bias would predict trait anger using multiple regression. Attachment avoidance, paranoia and hostile attribution bias were significantly associated with anger but attachment anxiety and theory of mind were not. Mediation analysis showed that paranoia partially mediated the relationship between avoidant attachment and anger but hostile attribution bias did not. Findings emphasise the importance of interventions targeting paranoia to reduce anger and the potential of preventive strategies focused on attachment relationships in early life or adulthood to reduce adult paranoia and anger. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Neurocognitive Basis of Racial Ingroup Bias in Empathy.

PubMed

Han, Shihui

2018-05-01

Racial discrimination in social behavior, although disapproved of by many contemporary cultures, has been widely reported. Because empathy plays a key functional role in social behavior, brain imaging researchers have extensively investigated the neurocognitive underpinnings of racial ingroup bias in empathy. This research has revealed consistent evidence for increased neural responses to the perceived pain of same-race compared with other-race individuals in multiple brain regions and across multiple time-windows. Researchers have also examined neurocognitive, sociocultural, and environmental influences on racial ingroup bias in empathic neural responses, as well as explored possible interventions to reduce racial ingroup bias in empathic brain activity. These findings have important implications for understanding racial ingroup favoritism in social behavior and for improving interracial communication. Copyright © 2018 Elsevier Ltd. All rights reserved.

Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

PubMed

Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

2018-03-01

In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Association between the MMPI-2 restructured form (MMPI-2-RF) and malingered neurocognitive dysfunction among non-head injury disability claimants.

PubMed

Tarescavage, Anthony M; Wygant, Dustin B; Gervais, Roger O; Ben-Porath, Yossef S

2013-01-01

The current study examined the over-reporting Validity Scales of the MMPI-2 Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008/2011) in relation to the Slick, Sherman, and Iverson (1999) criteria for the diagnosis of Malingered Neurocognitive Dysfunction in a sample of 916 consecutive non-head injury disability claimants. The classification of Malingered Neurocognitive Dysfunction was based on scores from several cognitive symptom validity tests and response bias indicators built into traditional neuropsychological tests. Higher scores on MMPI-2-RF Validity Scales, particularly the Response Bias Scale (Gervais, Ben-Porath, Wygant, & Green, 2007), were associated with probable and definite Malingered Neurocognitive Dysfunction. The MMPI-2-RF's Validity Scales classification accuracy of Malingered Neurocognitive Dysfunction improved when multiple scales were interpreted. Additionally, higher scores on MMPI-2-RF substantive scales measuring distress, internalizing dysfunction, thought dysfunction, and social avoidance were associated with probable and definite Malingered Neurocognitive Dysfunction. Implications for clinical practice and future directions are noted.

Correcting bias due to missing stage data in the non-parametric estimation of stage-specific net survival for colorectal cancer using multiple imputation.

PubMed

Falcaro, Milena; Carpenter, James R

2017-06-01

Population-based net survival by tumour stage at diagnosis is a key measure in cancer surveillance. Unfortunately, data on tumour stage are often missing for a non-negligible proportion of patients and the mechanism giving rise to the missingness is usually anything but completely at random. In this setting, restricting analysis to the subset of complete records gives typically biased results. Multiple imputation is a promising practical approach to the issues raised by the missing data, but its use in conjunction with the Pohar-Perme method for estimating net survival has not been formally evaluated. We performed a resampling study using colorectal cancer population-based registry data to evaluate the ability of multiple imputation, used along with the Pohar-Perme method, to deliver unbiased estimates of stage-specific net survival and recover missing stage information. We created 1000 independent data sets, each containing 5000 patients. Stage data were then made missing at random under two scenarios (30% and 50% missingness). Complete records analysis showed substantial bias and poor confidence interval coverage. Across both scenarios our multiple imputation strategy virtually eliminated the bias and greatly improved confidence interval coverage. In the presence of missing stage data complete records analysis often gives severely biased results. We showed that combining multiple imputation with the Pohar-Perme estimator provides a valid practical approach for the estimation of stage-specific colorectal cancer net survival. As usual, when the percentage of missing data is high the results should be interpreted cautiously and sensitivity analyses are recommended. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

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

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

Statistical methods for incomplete data: Some results on model misspecification.

PubMed

McIsaac, Michael; Cook, R J

2017-02-01

Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse probability weighted estimating equations, augmented inverse probability weighted estimating equations and multiple imputation when the requisite auxiliary models are misspecified. We compute limiting values for settings involving binary responses and covariates and illustrate the effects of model misspecification using simulations based on data from a breast cancer clinical trial. We demonstrate that, even when both auxiliary models are misspecified, the asymptotic biases of double-robust augmented inverse probability weighted estimators are often smaller than the asymptotic biases of estimators arising from complete-case analyses, inverse probability weighting or multiple imputation. We further demonstrate that use of inverse probability weighting or multiple imputation with slightly misspecified auxiliary models can actually result in greater asymptotic bias than the use of naïve, complete case analyses. These asymptotic results are shown to be consistent with empirical results from simulation studies.

Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies

PubMed Central

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Tremlett, Helen

2016-01-01

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = −0.002, mean squared error = 0.025; PTDM: bias = −1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995–2008). PMID:27455963

Correcting for bias in the selection and validation of informative diagnostic tests.

PubMed

Robertson, David S; Prevost, A Toby; Bowden, Jack

2015-04-15

When developing a new diagnostic test for a disease, there are often multiple candidate classifiers to choose from, and it is unclear if any will offer an improvement in performance compared with current technology. A two-stage design can be used to select a promising classifier (if one exists) in stage one for definitive validation in stage two. However, estimating the true properties of the chosen classifier is complicated by the first stage selection rules. In particular, the usual maximum likelihood estimator (MLE) that combines data from both stages will be biased high. Consequently, confidence intervals and p-values flowing from the MLE will also be incorrect. Building on the results of Pepe et al. (SIM 28:762-779), we derive the most efficient conditionally unbiased estimator and exact confidence intervals for a classifier's sensitivity in a two-stage design with arbitrary selection rules; the condition being that the trial proceeds to the validation stage. We apply our estimation strategy to data from a recent family history screening tool validation study by Walter et al. (BJGP 63:393-400) and are able to identify and successfully adjust for bias in the tool's estimated sensitivity to detect those at higher risk of breast cancer. © 2015 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Bias-field controlled phasing and power combination of gyromagnetic nonlinear transmission lines

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

Reale, D. V., E-mail: david.reale@ttu.edu; Bragg, J.-W. B.; Gonsalves, N. R.

2014-05-15

Gyromagnetic Nonlinear Transmission Lines (NLTLs) generate microwaves through the damped gyromagnetic precession of the magnetic moments in ferrimagnetic material, and are thus utilized as compact, solid-state, frequency agile, high power microwave (HPM) sources. The output frequency of a NLTL can be adjusted by control of the externally applied bias field and incident voltage pulse without physical alteration to the structure of the device. This property provides a frequency tuning capability not seen in many conventional e-beam based HPM sources. The NLTLs developed and tested are mesoband sources capable of generating MW power levels in the L, S, and C bandsmore » of the microwave spectrum. For an individual NLTL the output power at a given frequency is determined by several factors including the intrinsic properties of the ferrimagnetic material and the transmission line structure. Hence, if higher power levels are to be achieved, it is necessary to combine the outputs of multiple NLTLs. This can be accomplished in free space using antennas or in a transmission line via a power combiner. Using a bias-field controlled delay, a transient, high voltage, coaxial, three port, power combiner was designed and tested. Experimental results are compared with the results of a transient COMSOL simulation to evaluate combiner performance.« less

Bias-field controlled phasing and power combination of gyromagnetic nonlinear transmission lines.

PubMed

Reale, D V; Bragg, J-W B; Gonsalves, N R; Johnson, J M; Neuber, A A; Dickens, J C; Mankowski, J J

2014-05-01

Gyromagnetic Nonlinear Transmission Lines (NLTLs) generate microwaves through the damped gyromagnetic precession of the magnetic moments in ferrimagnetic material, and are thus utilized as compact, solid-state, frequency agile, high power microwave (HPM) sources. The output frequency of a NLTL can be adjusted by control of the externally applied bias field and incident voltage pulse without physical alteration to the structure of the device. This property provides a frequency tuning capability not seen in many conventional e-beam based HPM sources. The NLTLs developed and tested are mesoband sources capable of generating MW power levels in the L, S, and C bands of the microwave spectrum. For an individual NLTL the output power at a given frequency is determined by several factors including the intrinsic properties of the ferrimagnetic material and the transmission line structure. Hence, if higher power levels are to be achieved, it is necessary to combine the outputs of multiple NLTLs. This can be accomplished in free space using antennas or in a transmission line via a power combiner. Using a bias-field controlled delay, a transient, high voltage, coaxial, three port, power combiner was designed and tested. Experimental results are compared with the results of a transient COMSOL simulation to evaluate combiner performance.

Empirical Recommendations for Improving the Stability of the Dot-Probe Task in Clinical Research

PubMed Central

Price, Rebecca B.; Kuckertz, Jennie M.; Siegle, Greg J.; Ladouceur, Cecile D.; Silk, Jennifer S.; Ryan, Neal D.; Dahl, Ronald E.; Amir, Nader

2014-01-01

The dot-probe task has been widely used in research to produce an index of biased attention based on reaction times (RTs). Despite its popularity, very few published studies have examined psychometric properties of the task, including test-retest reliability, and no previous study has examined reliability in clinically anxious samples or systematically explored the effects of task design and analysis decisions on reliability. In the current analysis, we utilized dot-probe data from three studies where attention bias towards threat-related faces was assessed at multiple (≥5) timepoints. Two of the studies were similar (adults with Social Anxiety Disorder, similar design features) while one was much more disparate (pediatric healthy volunteers, distinct task design). We explored the effects of analysis choices (e.g., bias score calculation formula, methods for outlier handling) on reliability and searched for convergence of findings across the three studies. We found that, when considering the three studies concurrently, the most reliable RT bias index utilized data from dot-bottom trials, comparing congruent to incongruent trials, with rescaled outliers, particularly after averaging across more than one assessment point. Although reliability of RT bias indices was moderate to low under most circumstances, within-session variability in bias (attention bias variability; ABV), a recently proposed RT index, was more reliable across sessions. Several eyetracking-based indices of attention bias (available in the pediatric healthy sample only) showed reliability that matched the optimal RT index (ABV). On the basis of these findings, we make specific recommendations to researchers using the dot probe, particularly those wishing to investigate individual differences and/or single-patient applications. PMID:25419646

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.

Bias estimation for moving optical sensor measurements with targets of opportunity

NASA Astrophysics Data System (ADS)

Belfadel, Djedjiga; Osborne, Richard W.; Bar-Shalom, Yaakov

2014-06-01

Integration of space based sensors into a Ballistic Missile Defense System (BMDS) allows for detection and tracking of threats over a larger area than ground based sensors [1]. This paper examines the effect of sensor bias error on the tracking quality of a Space Tracking and Surveillance System (STSS) for the highly non-linear problem of tracking a ballistic missile. The STSS constellation consists of two or more satellites (on known trajectories) for tracking ballistic targets. Each satellite is equipped with an IR sensor that provides azimuth and elevation to the target. The tracking problem is made more difficult due to a constant or slowly varying bias error present in each sensor's line of sight measurements. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. The measurements provided by these sensors are assumed time-coincident (synchronous) and perfectly associated. The line of sight (LOS) measurements from the sensors can be fused into measurements which are the Cartesian target position, i.e., linear in the target state. We evaluate the Cramér-Rao Lower Bound (CRLB) on the covariance of the bias estimates, which serves as a quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the (unknown) trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

Does Test Anxiety Induce Measurement Bias in Cognitive Ability Tests?

ERIC Educational Resources Information Center

Reeve, Charlie L.; Bonaccio, Silvia

2008-01-01

Although test anxiety is typically negatively related to performance on cognitive ability tests, little research has systematically investigated whether differences in test anxiety result in measurement bias on cognitive ability tests. The current paper uses a structural equation modeling technique to explicitly test for measurement bias due to…

Gender Bias in Alberta Social Studies 30 Examinations: Cause and Effect.

ERIC Educational Resources Information Center

Walter, Connie; Young, Beth

1997-01-01

Reports on an exploration of gender bias in the multiple-choice portions of six Canadian social studies examinations. Considers the lack of women's experiences reflected in the questions, formal content, and epistemological stance. Concludes that gender biases do exist in the questions and may have contributed to differences in achievement. (MJP)

Investigating the Stability of Four Methods for Estimating Item Bias.

ERIC Educational Resources Information Center

Perlman, Carole L.; And Others

The reliability of item bias estimates was studied for four methods: (1) the transformed delta method; (2) Shepard's modified delta method; (3) Rasch's one-parameter residual analysis; and (4) the Mantel-Haenszel procedure. Bias statistics were computed for each sample using all methods. Data were from administration of multiple-choice items from…

Improvements in GPS precision: 10 Hz to one day

NASA Astrophysics Data System (ADS)

Choi, Kyuhong

Seeking to understand Global Positioning System (GPS) measurements and the positioning solutions in various time intervals, this dissertation improves the consistency of pseudorange measurements from different receiver types, processes 30 s interval data with optimized filtering techniques, and analyzes very-high-rate data with short arc lengths and baseline noise. The first project studies satellite-dependent biases between C/A and P1 codes. Calibrating these biases reduces the inconsistency of satellite clocks, improving the ambiguity resolution which allows for higher position precision. Receiver-dependent biases for two receivers are compared with the bias products of Center for Orbit Determination in Europe (CODE). Baseline lengths ranging up to ˜2,100km are tested with the receiver-specific biases; they resolve more phase ambiguity by 4.3% than using CODE's products. The second project analyzes 1 s and 30 s interval GPS data of the 2003 Tokachi-Oki earthquake. For 1 Hz positioning, Iterative Tropospheric Estimation (ITE) method improves vertical precision. While equalized sidereal filtering reduces noise for multipath-dominant 30--300 s periods, it can cause long-term drifts in the timeseries. A study of postseismic deformation after the Tokachi-Oki earthquake uses 30 s interval position estimations to test multiple filtering strategies to maximize precision using lower-rate data. On top of the residual stacking, estimation of a random walk constraint of sigmaDelta = 1.80 cm/ hr shows maximum noise reduction capability while retaining the real deformation signal. These techniques enhance our grasp of fault response in the aftermath of great earthquakes. The third project probes noise floor characteristics of very-high-rate (> 1 Hz) GPS data. A hybrid method, designed and tested to resolve phase biases, minimizes computational burdens while keeping the quality of ambiguity-fixed solutions. Noise characteristics are compared after an analysis of 5 and 10 Hz Ashtech MicroZ and ZFX as well as Trimble NetRS receivers. The Trimble NetRS receiver noise has a timeseries standard deviation double that of Ashtech MicroZ receivers. Also, the power spectral density function has a 0.1 Hz peak. Noise power shows white noise for the frequency range from 2 Hz and higher. Each research project assesses the methods to reduce the noises and/or biases in various time intervals. Each method considered in this dissertation will fulfill the needs for scientific applications.

Is it time for studying real-life debiasing? Evaluation of the effectiveness of an analogical intervention technique

PubMed Central

Aczel, Balazs; Bago, Bence; Szollosi, Aba; Foldes, Andrei; Lukacs, Bence

2015-01-01

The aim of this study was to initiate the exploration of debiasing methods applicable in real-life settings for achieving lasting improvement in decision making competence regarding multiple decision biases. Here, we tested the potentials of the analogical encoding method for decision debiasing. The advantage of this method is that it can foster the transfer from learning abstract principles to improving behavioral performance. For the purpose of the study, we devised an analogical debiasing technique for 10 biases (covariation detection, insensitivity to sample size, base rate neglect, regression to the mean, outcome bias, sunk cost fallacy, framing effect, anchoring bias, overconfidence bias, planning fallacy) and assessed the susceptibility of the participants (N = 154) to these biases before and 4 weeks after the training. We also compared the effect of the analogical training to the effect of ‘awareness training’ and a ‘no-training’ control group. Results suggested improved performance of the analogical training group only on tasks where the violations of statistical principles are measured. The interpretation of these findings require further investigation, yet it is possible that analogical training may be the most effective in the case of learning abstract concepts, such as statistical principles, which are otherwise difficult to master. The study encourages a systematic research of debiasing trainings and the development of intervention assessment methods to measure the endurance of behavior change in decision debiasing. PMID:26300816

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Centrality categorization for Rp (d)+A in high-energy collisions

NASA Astrophysics Data System (ADS)

Adare, A.; Aidala, C.; Ajitanand, N. N.; Akiba, Y.; Al-Bataineh, H.; Alexander, J.; Angerami, A.; Aoki, K.; Apadula, N.; Aramaki, Y.; Atomssa, E. T.; Averbeck, R.; Awes, T. C.; Azmoun, B.; Babintsev, V.; Bai, M.; Baksay, G.; Baksay, L.; Barish, K. N.; Bassalleck, B.; Basye, A. T.; Bathe, S.; Baublis, V.; Baumann, C.; Bazilevsky, A.; Belikov, S.; Belmont, R.; Bennett, R.; Bhom, J. H.; Blau, D. S.; Bok, J. S.; Boyle, K.; Brooks, M. L.; Buesching, H.; Bumazhnov, V.; Bunce, G.; Butsyk, S.; Campbell, S.; Caringi, A.; Chen, C.-H.; Chi, C. Y.; Chiu, M.; Choi, I. J.; Choi, J. B.; Choudhury, R. K.; Christiansen, P.; Chujo, T.; Chung, P.; Chvala, O.; Cianciolo, V.; Citron, Z.; Cole, B. A.; Conesa Del Valle, Z.; Connors, M.; Csanád, M.; Csörgő, T.; Dahms, T.; Dairaku, S.; Danchev, I.; Das, K.; Datta, A.; David, G.; Dayananda, M. K.; Denisov, A.; Deshpande, A.; Desmond, E. J.; Dharmawardane, K. V.; Dietzsch, O.; Dion, A.; Donadelli, M.; Drapier, O.; Drees, A.; Drees, K. A.; Durham, J. M.; Durum, A.; Dutta, D.; D'Orazio, L.; Edwards, S.; Efremenko, Y. V.; Ellinghaus, F.; Engelmore, T.; Enokizono, A.; En'yo, H.; Esumi, S.; Fadem, B.; Fields, D. E.; Finger, M.; Finger, M.; Fleuret, F.; Fokin, S. L.; Fraenkel, Z.; Frantz, J. E.; Franz, A.; Frawley, A. D.; Fujiwara, K.; Fukao, Y.; Fusayasu, T.; Garishvili, I.; Glenn, A.; Gong, H.; Gonin, M.; Goto, Y.; Granier de Cassagnac, R.; Grau, N.; Greene, S. V.; Grim, G.; Grosse Perdekamp, M.; Gunji, T.; Gustafsson, H.-Å.; Haggerty, J. S.; Hahn, K. I.; Hamagaki, H.; Hamblen, J.; Han, R.; Hanks, J.; Haslum, E.; Hayano, R.; He, X.; Heffner, M.; Hemmick, T. K.; Hester, T.; Hill, J. C.; Hohlmann, M.; Holzmann, W.; Homma, K.; Hong, B.; Horaguchi, T.; Hornback, D.; Huang, S.; Ichihara, T.; Ichimiya, R.; Ikeda, Y.; Imai, K.; Inaba, M.; Isenhower, D.; Ishihara, M.; Issah, M.; Ivanischev, D.; Iwanaga, Y.; Jacak, B. V.; Jia, J.; Jiang, X.; Jin, J.; Johnson, B. M.; Jones, T.; Joo, K. S.; Jouan, D.; Jumper, D. S.; Kajihara, F.; Kamin, J.; Kang, J. H.; Kapustinsky, J.; Karatsu, K.; Kasai, M.; Kawall, D.; Kawashima, M.; Kazantsev, A. V.; Kempel, T.; Khanzadeev, A.; Kijima, K. M.; Kikuchi, J.; Kim, A.; Kim, B. I.; Kim, D. J.; Kim, E.-J.; Kim, Y.-J.; Kinney, E.; Kiss, Á.; Kistenev, E.; Kleinjan, D.; Kochenda, L.; Komkov, B.; Konno, M.; Koster, J.; Král, A.; Kravitz, A.; Kunde, G. J.; Kurita, K.; Kurosawa, M.; Kwon, Y.; Kyle, G. S.; Lacey, R.; Lai, Y. S.; Lajoie, J. G.; Lebedev, A.; Lee, D. M.; Lee, J.; Lee, K. B.; Lee, K. S.; Leitch, M. J.; Leite, M. A. L.; Li, X.; Lichtenwalner, P.; Liebing, P.; Linden Levy, L. A.; Liška, T.; Liu, H.; Liu, M. X.; Love, B.; Lynch, D.; Maguire, C. F.; Makdisi, Y. I.; Malik, M. D.; Manko, V. I.; Mannel, E.; Mao, Y.; Masui, H.; Matathias, F.; McCumber, M.; McGaughey, P. L.; McGlinchey, D.; Means, N.; Meredith, B.; Miake, Y.; Mibe, T.; Mignerey, A. C.; Miki, K.; Milov, A.; Mitchell, J. T.; Mohanty, A. K.; Moon, H. J.; Morino, Y.; Morreale, A.; Morrison, D. P.; Moukhanova, T. V.; Murakami, T.; Murata, J.; Nagamiya, S.; Nagle, J. L.; Naglis, M.; Nagy, M. I.; Nakagawa, I.; Nakamiya, Y.; Nakamura, K. R.; Nakamura, T.; Nakano, K.; Nam, S.; Newby, J.; Nguyen, M.; Nihashi, M.; Nouicer, R.; Nyanin, A. S.; Oakley, C.; O'Brien, E.; Oda, S. X.; Ogilvie, C. A.; Oka, M.; Okada, K.; Onuki, Y.; Orjuela Koop, J. D.; Oskarsson, A.; Ouchida, M.; Ozawa, K.; Pak, R.; Pantuev, V.; Papavassiliou, V.; Park, I. H.; Park, S. K.; Park, W. J.; Pate, S. F.; Pei, H.; Peng, J.-C.; Pereira, H.; Perepelitsa, D.; Peressounko, D. Yu.; Petti, R.; Pinkenburg, C.; Pisani, R. P.; Proissl, M.; Purschke, M. L.; Qu, H.; Rak, J.; Ravinovich, I.; Read, K. F.; Rembeczki, S.; Reygers, K.; Riabov, V.; Riabov, Y.; Richardson, E.; Roach, D.; Roche, G.; Rolnick, S. D.; Rosati, M.; Rosen, C. A.; Rosendahl, S. S. E.; Ružička, P.; Sahlmueller, B.; Saito, N.; Sakaguchi, T.; Sakashita, K.; Samsonov, V.; Sano, S.; Sato, T.; Sawada, S.; Sedgwick, K.; Seele, J.; Seidl, R.; Seto, R.; Sharma, D.; Shein, I.; Shibata, T.-A.; Shigaki, K.; Shimomura, M.; Shoji, K.; Shukla, P.; Sickles, A.; Silva, C. L.; Silvermyr, D.; Silvestre, C.; Sim, K. S.; Singh, B. K.; Singh, C. P.; Singh, V.; Slunečka, M.; Soltz, R. A.; Sondheim, W. E.; Sorensen, S. P.; Sourikova, I. V.; Stankus, P. W.; Stenlund, E.; Stoll, S. P.; Sugitate, T.; Sukhanov, A.; Sziklai, J.; Takagui, E. M.; Taketani, A.; Tanabe, R.; Tanaka, Y.; Taneja, S.; Tanida, K.; Tannenbaum, M. J.; Tarafdar, S.; Taranenko, A.; Themann, H.; Thomas, D.; Thomas, T. L.; Togawa, M.; Toia, A.; Tomášek, L.; Torii, H.; Towell, R. S.; Tserruya, I.; Tsuchimoto, Y.; Vale, C.; Valle, H.; van Hecke, H. W.; Vazquez-Zambrano, E.; Veicht, A.; Velkovska, J.; Vértesi, R.; Virius, M.; Vrba, V.; Vznuzdaev, E.; Wang, X. R.; Watanabe, D.; Watanabe, K.; Watanabe, Y.; Wei, F.; Wei, R.; Wessels, J.; White, S. N.; Winter, D.; Woody, C. L.; Wright, R. M.; Wysocki, M.; Yamaguchi, Y. L.; Yamaura, K.; Yang, R.; Yanovich, A.; Ying, J.; Yokkaichi, S.; You, Z.; Young, G. R.; Younus, I.; Yushmanov, I. E.; Zajc, W. A.; Zhou, S.; Phenix Collaboration

2014-09-01

High-energy proton- and deuteron-nucleus collisions provide an excellent tool for studying a wide array of physics effects, including modifications of parton distribution functions in nuclei, gluon saturation, and color neutralization and hadronization in a nuclear environment, among others. All of these effects are expected to have a significant dependence on the size of the nuclear target and the impact parameter of the collision, also known as the collision centrality. In this article, we detail a method for determining centrality classes in p (d)+A collisions via cuts on the multiplicity at backward rapidity (i.e., the nucleus-going direction) and for determining systematic uncertainties in this procedure. For d +Au collisions at √sNN =200 GeV we find that the connection to geometry is confirmed by measuring the fraction of events in which a neutron from the deuteron does not interact with the nucleus. As an application, we consider the nuclear modification factors Rp (d)+A, for which there is a bias in the measured centrality-dependent yields owing to auto correlations between the process of interest and the backward-rapidity multiplicity. We determine the bias-correction factors within this framework. This method is further tested using the hijing Monte Carlo generator. We find that for d +Au collisions at √sNN =200 GeV, these bias corrections are small and vary by less than 5% (10%) up to pT=10 (20) GeV/c. In contrast, for p +Pb collisions at √sNN =5.02 TeV we find that these bias factors are an order of magnitude larger and strongly pT dependent, likely attributable to the larger effect of multiparton interactions.

Queries for Bias Testing

NASA Technical Reports Server (NTRS)

Gordon, Diana F.

1992-01-01

Selecting a good bias prior to concept learning can be difficult. Therefore, dynamic bias adjustment is becoming increasingly popular. Current dynamic bias adjustment systems, however, are limited in their ability to identify erroneous assumptions about the relationship between the bias and the target concept. Without proper diagnosis, it is difficult to identify and then remedy faulty assumptions. We have developed an approach that makes these assumptions explicit, actively tests them with queries to an oracle, and adjusts the bias based on the test results.

Incorporating transgenerational testing and epigenetic ...

EPA Pesticide Factsheets

A number of environmental chemicals have been shown to alter markers of epigenetic change. Some published multi-generation rodent studies have identified effects on F2 and greater generations after chemical exposures solely to F0 dams, but were not focused on chemical safety. We were interested in how outcomes related to epigenetic changes could be identified and incorporated into chemical testing and risk assessment. To address this question, we conducted a systematic literature review to identify transgenerational (TG) epigenetic studies in rodents. These were analyzed to characterize the methods and observed outcomes, and to evaluate strengths, limitations, and biases. Our analysis found that test substances were administered to pregnant F0 dams; endpoints assessed in F1 to F4 generation offspring included growth, puberty timing, steroid hormone levels, abdominal adiposity, organ weights, histopathology, and epigenetic biomarkers. Biases were minimized through, e.g., randomization procedures, avoiding sibling or cousin matings, and independent multiple reviews of histopathology data. However, the numbers of litters assigned to control and test groups were not always transparently reported, nested statistical analyses of data was not always utilized to address litter effects, and “blind” testing was seldom performed. Many of these studies identified chemicals or combinations of chemicals that produced TG effects and/or adult-onset diseases, but there is a

Horizontal Contraction of Oceanic Lithosphere Tested Using Azimuths of Transform Faults

NASA Astrophysics Data System (ADS)

Gordon, R. G.; Mishra, J. K.

2012-12-01

A central hypothesis or approximation of plate tectonics is that the plates are rigid, which implies that oceanic lithosphere does not contract horizontally as it cools (hereinafter "no contraction"). An alternative hypothesis is that vertically averaged tensional thermal stress in the competent lithosphere is fully relieved by horizontal thermal contraction (hereinafter "full contraction"). These two hypotheses predict different azimuths for transform faults. We build on prior predictions of horizontal thermal contraction of oceanic lithosphere as a function of age to predict the bias induced in transform-fault azimuths by full contraction for 140 azimuths of transform faults that are globally distributed between 15 plate pairs. Predicted bias increases with the length of adjacent segments of mid-ocean ridges and depends on whether the adjacent ridges are stepped, crenellated, or a combination of the two. All else being equal, the bias decreases with the length of a transform fault and modestly decreases with increasing spreading rate. The value of the bias varies along a transform fault. To correct the observed transform-fault azimuths for the biases, we average the predicted values over the insonified portions of each transform fault. We find the bias to be as large as 2.5°, but more typically is ≤ 1.0°. We test whether correcting for the predicted biases improves the fit to plate motion data. To do so, we determine the sum-squared normalized misfit for various values of γ, which we define to be the fractional multiple of bias predicted for full contraction. γ = 1 corresponds to the full contraction, while γ = 0 corresponds to no contraction. We find that the minimum in sum-squared normalized misfit is obtained for γ = 0.9 ±0.4 (95% confidence limits), which excludes the hypothesis of no contraction, but is consistent with the hypothesis of full contraction. Application of the correction reduces but does not eliminate the longstanding misfit between the azimuth of the Kane transform fault with respect to those of the other North America-Nubia transform faults. We conclude that significant ridge-parallel horizontal thermal contraction occurs in young oceanic lithosphere and that it is accommodated by widening of transform-fault valleys, which causes biases in transform-fault azimuths up to 2.5°.

GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology

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

Mandelbaum, R.; Rowe, B.; Armstrong, R.

2015-05-01

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about amore » spatially varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by ~1 per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the Sérsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods’ results support the simple model in which additive shear biases depend linearly on PSF ellipticity.« less

Cognitive bias modification and CBT as early interventions for adolescent social and test anxiety: Two-year follow-up of a randomized controlled trial.

PubMed

de Hullu, Eva; Sportel, B Esther; Nauta, Maaike H; de Jong, Peter J

2017-06-01

This two-year follow-up study evaluated the long-term outcomes of two early interventions that aimed at reducing social and test anxiety in young adolescents at risk for developing social anxiety disorder. In this RCT, moderately socially anxious adolescents (N=240, mean age 13.6 years) were randomly assigned to a 10-week internet-based multifaceted cognitive bias modification training (CBM), a 10-week school-based cognitive behavioral group training (CBT), or a no-intervention control condition. Using multiple imputation, this study examined the changes in primary and secondary outcome measures from pretest to follow-up in a repeated measures design. Primary outcome: Self-reported social and test anxiety generally decreased from pre-test to two-year follow-up, regardless of treatment condition. The percentage of adolescents who developed a social anxiety disorder was very low (6%) and similar across conditions. Secondary outcome: There were beneficial changes in self-esteem, self-reported prosocial behaviors, and fear of negative evaluation, but none of these were related to treatment condition. Automatic social-threat associations did not significantly change. The CBM intervention was effective in changing interpretative bias as indexed by the Recognition Task but this long-term effect did not transfer to the Adolescent Interpretation and Belief Questionnaire. There was a substantial (50%) though seemingly non-selective attrition at follow-up. This RCT does not support the longer-term efficacy of school-based CBT or CBM as an early intervention for social and test anxiety. Rather, it emphasizes the positive 'natural' course of highly socially anxious adolescents over two years. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology

DOE PAGES

Mandelbaum, Rachel; Rowe, Barnaby; Armstrong, Robert; ...

2015-05-11

The study present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty aboutmore » a spatially varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by ~1 per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the Sérsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods’ results support the simple model in which additive shear biases depend linearly on PSF ellipticity.« less

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

PubMed

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

2018-01-01

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

Salary Equity: Detecting Sex Bias in Salaries among College and University Professors.

ERIC Educational Resources Information Center

Pezzullo, Thomas R., Ed.; Brittingham, Barbara E., Ed.

Sex bias in college faculty salaries is examined in this book. Part 1 contains the following four chapters on the use of multiple regression to detect and estimate sex bias in salaries: "The Assessment of Salary Equity: A Methodology, Alternatives, and a Dilemma" (Thomas R. Pezzullo and Barbara E. Brittingham); "Detection of Sex-Related Salary…

Cultural and Ethnic Bias in Teacher Ratings of Behavior: A Criterion-Focused Review

ERIC Educational Resources Information Center

Mason, Benjamin A.; Gunersel, Adalet Baris; Ney, Emilie A.

2014-01-01

Behavior rating scales are indirect measures of emotional and social functioning used for assessment purposes. Rater bias is systematic error that may compromise the validity of behavior rating scale scores. Teacher bias in ratings of behavior has been investigated in multiple studies, but not yet assessed in a research synthesis that focuses on…

A New Look at Bias in Aptitude Tests.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd

1981-01-01

Statistical bias in measurement and ethnic-group bias in testing are discussed, reviewing predictive and construct validity studies. Item bias is reconceptualized to include distance of item content from respondent's experience. Differing values of mean and standard deviation for bias parameter are analyzed in a simulation. References are…

Bias in Mental Testing.

ERIC Educational Resources Information Center

Jensen, Arthur R.

The first eight chapters of this book introduce the topic of test bias. The basic issues involved in criticisms of mental tests and arguments about test bias include: (1) variety of tests and test items; (2) scaling of scores and the form of the distribution of abilities in the population; (3) quantification of subpopulation differences; (4)…

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.

Attention, interpretation, and memory biases in subclinical depression: a proof-of-principle test of the combined cognitive biases hypothesis.

PubMed

Everaert, Jonas; Duyck, Wouter; Koster, Ernst H W

2014-04-01

Emotional biases in attention, interpretation, and memory are viewed as important cognitive processes underlying symptoms of depression. To date, there is a limited understanding of the interplay among these processing biases. This study tested the dependence of memory on depression-related biases in attention and interpretation. Subclinically depressed and nondepressed participants completed a computerized version of the scrambled sentences test (measuring interpretation bias) while their eye movements were recorded (measuring attention bias). This task was followed by an incidental free recall test of previously constructed interpretations (measuring memory bias). Path analysis revealed a good fit for the model in which selective orienting of attention was associated with interpretation bias, which in turn was associated with a congruent bias in memory. Also, a good fit was observed for a path model in which biases in the maintenance of attention and interpretation were associated with memory bias. Both path models attained a superior fit compared with path models without the theorized functional relations among processing biases. These findings enhance understanding of how mechanisms of attention and interpretation regulate what is remembered. As such, they offer support for the combined cognitive biases hypothesis or the notion that emotionally biased cognitive processes are not isolated mechanisms but instead influence each other. Implications for theoretical models and emotion regulation across the spectrum of depressive symptoms are discussed.

Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations

NASA Astrophysics Data System (ADS)

Liu, Dezi; Fu, Liping; Liu, Xiangkun; Radovich, Mario; Wang, Chao; Pan, Chuzhong; Fan, Zuhui; Covone, Giovanni; Vaccari, Mattia; Botticella, Maria Teresa; Capaccioli, Massimo; De Cicco, Demetra; Grado, Aniello; Miller, Lance; Napolitano, Nicola; Paolillo, Maurizio; Pignata, Giuliano

2018-05-01

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical ugri imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg2 down to rAB ˜ 26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for r-band images with seeing ≤ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of ˜3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of ˜0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to ˜0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.

Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.

2013-09-01

The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.

A unified framework for constructing, tuning and assessing photometric redshift density estimates in a selection bias setting

NASA Astrophysics Data System (ADS)

Freeman, P. E.; Izbicki, R.; Lee, A. B.

2017-07-01

Photometric redshift estimation is an indispensable tool of precision cosmology. One problem that plagues the use of this tool in the era of large-scale sky surveys is that the bright galaxies that are selected for spectroscopic observation do not have properties that match those of (far more numerous) dimmer galaxies; thus, ill-designed empirical methods that produce accurate and precise redshift estimates for the former generally will not produce good estimates for the latter. In this paper, we provide a principled framework for generating conditional density estimates (I.e. photometric redshift PDFs) that takes into account selection bias and the covariate shift that this bias induces. We base our approach on the assumption that the probability that astronomers label a galaxy (I.e. determine its spectroscopic redshift) depends only on its measured (photometric and perhaps other) properties x and not on its true redshift. With this assumption, we can explicitly write down risk functions that allow us to both tune and compare methods for estimating importance weights (I.e. the ratio of densities of unlabelled and labelled galaxies for different values of x) and conditional densities. We also provide a method for combining multiple conditional density estimates for the same galaxy into a single estimate with better properties. We apply our risk functions to an analysis of ≈106 galaxies, mostly observed by Sloan Digital Sky Survey, and demonstrate through multiple diagnostic tests that our method achieves good conditional density estimates for the unlabelled galaxies.

Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters.

PubMed

Chung, SungWon; Lu, Ying; Henry, Roland G

2006-11-01

Bootstrap is an empirical non-parametric statistical technique based on data resampling that has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in tractography and in assessing DTI methods. The current bootstrap method (repetition bootstrap) used for DTI analysis performs resampling within the data sharing common diffusion gradients, requiring multiple acquisitions for each diffusion gradient. Recently, wild bootstrap was proposed that can be applied without multiple acquisitions. In this paper, two new approaches are introduced called residual bootstrap and repetition bootknife. We show that repetition bootknife corrects for the large bias present in the repetition bootstrap method and, therefore, better estimates the standard errors. Like wild bootstrap, residual bootstrap is applicable to single acquisition scheme, and both are based on regression residuals (called model-based resampling). Residual bootstrap is based on the assumption that non-constant variance of measured diffusion-attenuated signals can be modeled, which is actually the assumption behind the widely used weighted least squares solution of diffusion tensor. The performances of these bootstrap approaches were compared in terms of bias, variance, and overall error of bootstrap-estimated standard error by Monte Carlo simulation. We demonstrate that residual bootstrap has smaller biases and overall errors, which enables estimation of uncertainties with higher accuracy. Understanding the properties of these bootstrap procedures will help us to choose the optimal approach for estimating uncertainties that can benefit hypothesis testing based on DTI parameters, probabilistic fiber tracking, and optimizing DTI methods.

Verification and classification bias interactions in diagnostic test accuracy studies for fine-needle aspiration biopsy.

PubMed

Schmidt, Robert L; Walker, Brandon S; Cohen, Michael B

2015-03-01

Reliable estimates of accuracy are important for any diagnostic test. Diagnostic accuracy studies are subject to unique sources of bias. Verification bias and classification bias are 2 sources of bias that commonly occur in diagnostic accuracy studies. Statistical methods are available to estimate the impact of these sources of bias when they occur alone. The impact of interactions when these types of bias occur together has not been investigated. We developed mathematical relationships to show the combined effect of verification bias and classification bias. A wide range of case scenarios were generated to assess the impact of bias components and interactions on total bias. Interactions between verification bias and classification bias caused overestimation of sensitivity and underestimation of specificity. Interactions had more effect on sensitivity than specificity. Sensitivity was overestimated by at least 7% in approximately 6% of the tested scenarios. Specificity was underestimated by at least 7% in less than 0.1% of the scenarios. Interactions between verification bias and classification bias create distortions in accuracy estimates that are greater than would be predicted from each source of bias acting independently. © 2014 American Cancer Society.

Examining publication bias—a simulation-based evaluation of statistical tests on publication bias

PubMed Central

2017-01-01

Background Publication bias is a form of scientific misconduct. It threatens the validity of research results and the credibility of science. Although several tests on publication bias exist, no in-depth evaluations are available that examine which test performs best for different research settings. Methods Four tests on publication bias, Egger’s test (FAT), p-uniform, the test of excess significance (TES), as well as the caliper test, were evaluated in a Monte Carlo simulation. Two different types of publication bias and its degree (0%, 50%, 100%) were simulated. The type of publication bias was defined either as file-drawer, meaning the repeated analysis of new datasets, or p-hacking, meaning the inclusion of covariates in order to obtain a significant result. In addition, the underlying effect (β = 0, 0.5, 1, 1.5), effect heterogeneity, the number of observations in the simulated primary studies (N = 100, 500), and the number of observations for the publication bias tests (K = 100, 1,000) were varied. Results All tests evaluated were able to identify publication bias both in the file-drawer and p-hacking condition. The false positive rates were, with the exception of the 15%- and 20%-caliper test, unbiased. The FAT had the largest statistical power in the file-drawer conditions, whereas under p-hacking the TES was, except under effect heterogeneity, slightly better. The CTs were, however, inferior to the other tests under effect homogeneity and had a decent statistical power only in conditions with 1,000 primary studies. Discussion The FAT is recommended as a test for publication bias in standard meta-analyses with no or only small effect heterogeneity. If two-sided publication bias is suspected as well as under p-hacking the TES is the first alternative to the FAT. The 5%-caliper test is recommended under conditions of effect heterogeneity and a large number of primary studies, which may be found if publication bias is examined in a discipline-wide setting when primary studies cover different research problems. PMID:29204324

Counteracting estimation bias and social influence to improve the wisdom of crowds.

PubMed

Kao, Albert B; Berdahl, Andrew M; Hartnett, Andrew T; Lutz, Matthew J; Bak-Coleman, Joseph B; Ioannou, Christos C; Giam, Xingli; Couzin, Iain D

2018-04-01

Aggregating multiple non-expert opinions into a collective estimate can improve accuracy across many contexts. However, two sources of error can diminish collective wisdom: individual estimation biases and information sharing between individuals. Here, we measure individual biases and social influence rules in multiple experiments involving hundreds of individuals performing a classic numerosity estimation task. We first investigate how existing aggregation methods, such as calculating the arithmetic mean or the median, are influenced by these sources of error. We show that the mean tends to overestimate, and the median underestimate, the true value for a wide range of numerosities. Quantifying estimation bias, and mapping individual bias to collective bias, allows us to develop and validate three new aggregation measures that effectively counter sources of collective estimation error. In addition, we present results from a further experiment that quantifies the social influence rules that individuals employ when incorporating personal estimates with social information. We show that the corrected mean is remarkably robust to social influence, retaining high accuracy in the presence or absence of social influence, across numerosities and across different methods for averaging social information. Using knowledge of estimation biases and social influence rules may therefore be an inexpensive and general strategy to improve the wisdom of crowds. © 2018 The Author(s).

[Meta-analysis for correlation between multiple lung lobe lesions and prognostic influence on acquired pneumonia in hospitalized elderly patients].

PubMed

Huang, Wenjie; Feng, Wei; Li, Yang; Chen, Yu

2014-11-01

To explore the correlation regarding the prognostic influence between multiple lung lobe lesions and acquired pneumonia in hospitalized elderly patients by a Meta-analysis. We collected all studies which investigated the correlation regarding the prognostic effect between multiple lung lobe lesions and acquired pneumonia by searching China National Knowledge Infrastructure, Wanfang Database, Chinese Science and Technology Periodical Database, Chinese Biological Medical Literature Database, PubMed, and EMBase in accordance with the inclusion and exclusion criteria. Th e retrieval limit time of searches was from databases establishment to July 2014. Th e Meta-analysis was performed by using RevMan5.2 soft ware. We calculated the odds ratio (OR) and 95% confidence interval (95% CI) by using heterogeneous tests. Publication bias was assessed by Egger's test and funnel plot, and the sensitivity was analyzed. Ten studies involving 1 836 patients were finally included, with 487 cases (the dead group) and 1 349 controls (the survival group). The Meta-analysis demonstrated that multiple lung lobe lesions was highly correlated with the prognosis for the aged acquired pneumonia (OR=3.22, 95% CI 1.84 to 5.63). Multiple lung lobe lesions increase the risk of death in the prognosis of the aged patients with acquired pneumonia.

SU-F-T-180: Evaluation of a Scintillating Screen Detector for Proton Beam QA and Acceptance Testing

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

Ghebremedhin, A; Taber, M; Koss, P

2016-06-15

Purpose: To test the performance of a commercial scintillating screen detector for acceptance testing and Quality Assurance of a proton pencil beam scanning system. Method: The detector (Lexitek DRD 400) has 40cm × 40cm field, uses a thin scintillator imaged onto a 16-bit scientific CCD with ∼0.5mm resolution. A grid target and LED illuminators are provided for spatial calibration and relative gain correction. The detector mounts to the nozzle with micron precision. Tools are provided for image processing and analysis of single or multiple Gaussian spots. Results: The bias and gain of the detector were studied to measure repeatability andmore » accuracy. Gain measurements were taken with the LED illuminators to measure repeatability and variation of the lens-CCD pair as a function with f-stop. Overall system gain was measured with a passive scattering (broad) beam whose shape is calibrated with EDR film placed in front of the scintillator. To create a large uniform field, overlapping small fields were recorded with the detector translated laterally and stitched together to cover the full field. Due to the long exposures required to obtain multiple spills of the synchrotron and very high detector sensitivity, borated polyethylene shielding was added to reduce direct radiation events hitting the CCD. Measurements with a micro ion chamber were compared to the detector’s spot profile. Software was developed to process arrays of Gaussian spots and to correct for radiation events. Conclusion: The detector background has a fixed bias, a small component linear in time, and is easily corrected. The gain correction method was validated with 2% accuracy. The detector spot profile matches the micro ion chamber data over 4 orders of magnitude. The multiple spot analyses can be easily used with plan data for measuring pencil beam uniformity and for regular QA comparison.« less

Bias in Testing: A Presentation of Selected Methods.

ERIC Educational Resources Information Center

Merz, William R.; Rudner, Lawrence M.

A variety of terms related to test bias or test fairness have been used in a variety of ways, but in this document the "fair use of tests" is defined as equitable selection procedures by means of intact tests, and "test item bias" refers to the study of separate items with respect to the tests of which they are a part. Seven…

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.

The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

NASA Astrophysics Data System (ADS)

Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

2010-12-01

Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential optimization. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, an OAS spatially variable adjustment with multiplicative factors, ordinary cokriging, and kriging with external drift. In theory, it could be equally applicable to gauge-satellite estimates and other hydrometeorological variables.

Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey.

PubMed

Peyre, Hugo; Leplège, Alain; Coste, Joël

2011-03-01

Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. It remains unclear which of the various methods proposed to deal with missing data performs best in this context. We compared personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques using various realistic simulation scenarios of item missingness in QoL questionnaires constructed within the framework of classical test theory. Samples of 300 and 1,000 subjects were randomly drawn from the 2003 INSEE Decennial Health Survey (of 23,018 subjects representative of the French population and having completed the SF-36) and various patterns of missing data were generated according to three different item non-response rates (3, 6, and 9%) and three types of missing data (Little and Rubin's "missing completely at random," "missing at random," and "missing not at random"). The missing data methods were evaluated in terms of accuracy and precision for the analysis of one descriptive and one association parameter for three different scales of the SF-36. For all item non-response rates and types of missing data, multiple imputation and full information maximum likelihood appeared superior to the personal mean score and especially to hot deck in terms of accuracy and precision; however, the use of personal mean score was associated with insignificant bias (relative bias <2%) in all studied situations. Whereas multiple imputation and full information maximum likelihood are confirmed as reference methods, the personal mean score appears nonetheless appropriate for dealing with items missing from completed SF-36 questionnaires in most situations of routine use. These results can reasonably be extended to other questionnaires constructed according to classical test theory.

Meta‐analysis of test accuracy studies using imputation for partial reporting of multiple thresholds

PubMed Central

Deeks, J.J.; Martin, E.C.; Riley, R.D.

2017-01-01

Introduction For tests reporting continuous results, primary studies usually provide test performance at multiple but often different thresholds. This creates missing data when performing a meta‐analysis at each threshold. A standard meta‐analysis (no imputation [NI]) ignores such missing data. A single imputation (SI) approach was recently proposed to recover missing threshold results. Here, we propose a new method that performs multiple imputation of the missing threshold results using discrete combinations (MIDC). Methods The new MIDC method imputes missing threshold results by randomly selecting from the set of all possible discrete combinations which lie between the results for 2 known bounding thresholds. Imputed and observed results are then synthesised at each threshold. This is repeated multiple times, and the multiple pooled results at each threshold are combined using Rubin's rules to give final estimates. We compared the NI, SI, and MIDC approaches via simulation. Results Both imputation methods outperform the NI method in simulations. There was generally little difference in the SI and MIDC methods, but the latter was noticeably better in terms of estimating the between‐study variances and generally gave better coverage, due to slightly larger standard errors of pooled estimates. Given selective reporting of thresholds, the imputation methods also reduced bias in the summary receiver operating characteristic curve. Simulations demonstrate the imputation methods rely on an equal threshold spacing assumption. A real example is presented. Conclusions The SI and, in particular, MIDC methods can be used to examine the impact of missing threshold results in meta‐analysis of test accuracy studies. PMID:29052347

Are ecstasy users biased toward endorsing somatic mental health symptoms? Results from a general community sample.

PubMed

George, Amanda M; Windsor, Tim D; Rodgers, Bryan

2011-04-01

Whether the reported poorer mental health of ecstasy users is due to a bias in endorsement of somatic symptoms has been postulated, but rarely examined. The purpose of this study is to investigate whether levels of ecstasy use were associated with differential probabilities of endorsing somatic mental health symptoms. Current ecstasy users aged 24-30 years (n = 316) were identified from a population-based Australian study. Measures included frequency of ecstasy, meth/amphetamine, and cannabis use and the Goldberg anxiety/depression symptom scales. Multiple indicator, multiple cause models demonstrated no bias towards endorsing somatic symptoms with higher ecstasy use, both with and without adjustment for gender, cannabis, and meth/amphetamine use. Other studies using alternate measures of mental health should adopt this approach to determine if there is a bias in the endorsement of somatic symptoms among ecstasy users.

Causal inference and the data-fusion problem

PubMed Central

Bareinboim, Elias; Pearl, Judea

2016-01-01

We review concepts, principles, and tools that unify current approaches to causal analysis and attend to new challenges presented by big data. In particular, we address the problem of data fusion—piecing together multiple datasets collected under heterogeneous conditions (i.e., different populations, regimes, and sampling methods) to obtain valid answers to queries of interest. The availability of multiple heterogeneous datasets presents new opportunities to big data analysts, because the knowledge that can be acquired from combined data would not be possible from any individual source alone. However, the biases that emerge in heterogeneous environments require new analytical tools. Some of these biases, including confounding, sampling selection, and cross-population biases, have been addressed in isolation, largely in restricted parametric models. We here present a general, nonparametric framework for handling these biases and, ultimately, a theoretical solution to the problem of data fusion in causal inference tasks. PMID:27382148

Understanding the bias between moisture content by oven drying and water content by Karl Fischer titration at moisture equilibrium

USDA-ARS?s Scientific Manuscript database

Multiple causes of the difference between equilibrium moisture and water content have been found. The errors or biases were traced to the oven drying procedure to determine moisture content. The present paper explains the nature of the biases in oven drying and how it is possible to suppress one ...

Load-carriage distance run and push-ups tests: no body mass bias and occupationally relevant.

PubMed

Vanderburgh, Paul M; Mickley, Nicholas S; Anloague, Philip A

2011-09-01

Recent research has demonstrated body mass (M) bias in military physical fitness tests favoring lighter, not just leaner, service members. Mathematical modeling predicts that a distance run carrying a backpack of 30 lbs would eliminate M-bias. The purpose of this study was to empirically test this prediction for the U.S. Army push-ups and 2-mile run tests. Two tests were performed for both events for each of 56 university Reserve Officer Training Corps male cadets: with (loaded) and without backpack (unloaded). Results indicated significant M-bias in the unloaded and no M-bias in the loaded condition for both events. Allometrically scaled scores for both events were worse in the loaded vs. unloaded conditions, supporting a hypothesis not previously tested. The loaded push-ups and 2-mile run appear to remove M-bias and are probably more occupationally relevant as military personnel are often expected to carry external loads.

Multiple imputation methods for bivariate outcomes in cluster randomised trials.

PubMed

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

2016-09-10

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

Luck, come here! Automatic approach tendencies toward gambling cues in moderate- to high-risk gamblers.

PubMed

Boffo, Marilisa; Smits, Ruby; Salmon, Joshua P; Cowie, Megan E; de Jong, David T H A; Salemink, Elske; Collins, Pam; Stewart, Sherry H; Wiers, Reinout W

2018-02-01

Similar to substance addictions, reward-related cognitive motivational processes, such as selective attention and positive memory biases, have been found in disordered gambling. Despite findings that individuals with substance use problems are biased to approach substance-related cues automatically, no study has yet focused on automatic approach tendencies for motivationally salient gambling cues in problem gamblers. We tested if moderate- to high-risk gamblers show a gambling approach bias and whether this bias was related prospectively to gambling behaviour and problems. Cross-sectional assessment study evaluating the concurrent and longitudinal correlates of gambling approach bias in moderate- to high-risk gamblers compared with non-problem gamblers. Online study throughout the Netherlands. Twenty-six non-treatment-seeking moderate- to high-risk gamblers and 26 non-problem gamblers community-recruited via the internet. Two online assessment sessions 6 months apart, including self-report measures of gambling problems and behaviour (frequency, duration and expenditure) and the gambling approach avoidance task, with stimuli tailored to individual gambling habits. Relative to non-problem gamblers, moderate- to high-risk gamblers revealed a stronger approach bias towards gambling-related stimuli than neutral stimuli (P = 0.03). Gambling approach bias was correlated positively with past-month gambling expenditure at baseline (P = 0.03) and with monthly frequency of gambling at follow-up (P = 0.02). In multiple hierarchical regressions, baseline gambling approach bias predicted monthly frequency positively (P = 0.03) and total duration of gambling episodes (P = 0.01) 6 months later, but not gambling problems or expenditure. In the Netherlands, relative to non-problem gamblers, moderate- to high-risk gamblers appear to have a stronger tendency to approach rather than to avoid gambling-related pictures compared with neutral ones. This gambling approach bias is associated concurrently with past-month gambling expenditure and duration of gambling and has been found to predict persistence in gambling behaviour over time. © 2017 Society for the Study of Addiction.

Shear nulling after PSF Gaussianisation: Moment-based weak lensing measurements with subpercent noise bias

NASA Astrophysics Data System (ADS)

Herbonnet, Ricardo; Buddendiek, Axel; Kuijken, Konrad

2017-03-01

Context. Current optical imaging surveys for cosmology cover large areas of sky. Exploiting the statistical power of these surveys for weak lensing measurements requires shape measurement methods with subpercent systematic errors. Aims: We introduce a new weak lensing shear measurement algorithm, shear nulling after PSF Gaussianisation (SNAPG), designed to avoid the noise biases that affect most other methods. Methods: SNAPG operates on images that have been convolved with a kernel that renders the point spread function (PSF) a circular Gaussian, and uses weighted second moments of the sources. The response of such second moments to a shear of the pre-seeing galaxy image can be predicted analytically, allowing us to construct a shear nulling scheme that finds the shear parameters for which the observed galaxies are consistent with an unsheared, isotropically oriented population of sources. The inverse of this nulling shear is then an estimate of the gravitational lensing shear. Results: We identify the uncertainty of the estimated centre of each galaxy as the source of noise bias, and incorporate an approximate estimate of the centroid covariance into the scheme. We test the method on extensive suites of simulated galaxies of increasing complexity, and find that it is capable of shear measurements with multiplicative bias below 0.5 percent.

Validation of patient health questionnaire (PHQ) for major depression in Chinese outpatients with multiple somatic symptoms: a multicenter cross-sectional study.

PubMed

Xiong, Nana; Fritzsche, Kurt; Wei, Jing; Hong, Xia; Leonhart, Rainer; Zhao, Xudong; Zhang, Lan; Zhu, Liming; Tian, Guoqing; Nolte, Sandra; Fischer, Felix

2015-03-15

Despite the high co-morbidity of depressive symptoms in patients with multiple somatic symptoms, the validity of the 9-item Patient Health Questionnaire (PHQ-9) has not yet been investigated in Chinese patients with multiple somatic symptoms. The multicenter cross-sectional study was conducted in ten outpatient departments located in four cities in China. The psychometric properties of the PHQ-9 were examined by confirmative factor analysis (CFA). Criterion validation was undertaken by comparing results with depression diagnoses obtained from the Mini International Neuropsychiatric Interview (MINI) as the gold standard. Overall, 491 patients were recruited of whom 237 had multiple somatic symptoms (SOM+ group, PHQ-15≥10). Cronbach׳s α of the PHQ-9 was 0.87, 0.87, and 0.90 for SOM+ patients, SOM- patients, and total sample respectively. All items and the total score were moderately correlated. The factor models of PHQ-9 tested by CFA yielded similar diagnostic performance when compared to sum score estimation. Multi-group confirmatory factor analysis based on unidimensional model showed similar psychometric properties over the groups with low and high somatic symptom burden. The optimal cut-off point to detect depression in Chinese outpatients was 10 for PHQ-9 (sensitivity=0.77, specificity=0.76) and 3 for PHQ-2 (sensitivity=0.77, specificity=0.74). Potential selection bias and nonresponse bias with applied sampling method. PHQ-9 (cut-off point=10) and PHQ-2 (cut-off point=3) were reliable and valid to detect major depression in Chinese patients with multiple somatic symptoms. Copyright © 2014 Elsevier B.V. All rights reserved.

Intrinsic frequency biases and profiles across human cortex.

PubMed

Mellem, Monika S; Wohltjen, Sophie; Gotts, Stephen J; Ghuman, Avniel Singh; Martin, Alex

2017-11-01

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical. NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread. Copyright © 2017 the American Physiological Society.

Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation.

PubMed

Szatkiewicz, Jin P; Wang, WeiBo; Sullivan, Patrick F; Wang, Wei; Sun, Wei

2013-02-01

Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth-based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth-based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.

Discrimination, Racial Bias, and Telomere Length in African-American Men

PubMed Central

Chae, David H.; Nuru-Jeter, Amani M.; Adler, Nancy E.; Brody, Gene H.; Lin, Jue; Blackburn, Elizabeth H.; Epel, Elissa S.

2013-01-01

Background Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. Purpose To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Methods Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. Results After controlling for chronologic age, socioeconomic, and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b= −0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Conclusions Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. PMID:24439343

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

PubMed

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

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.

Effect of response format on cognitive reflection: Validating a two- and four-option multiple choice question version of the Cognitive Reflection Test.

PubMed

Sirota, Miroslav; Juanchich, Marie

2018-03-27

The Cognitive Reflection Test, measuring intuition inhibition and cognitive reflection, has become extremely popular because it reliably predicts reasoning performance, decision-making, and beliefs. Across studies, the response format of CRT items sometimes differs, based on the assumed construct equivalence of tests with open-ended versus multiple-choice items (the equivalence hypothesis). Evidence and theoretical reasons, however, suggest that the cognitive processes measured by these response formats and their associated performances might differ (the nonequivalence hypothesis). We tested the two hypotheses experimentally by assessing the performance in tests with different response formats and by comparing their predictive and construct validity. In a between-subjects experiment (n = 452), participants answered stem-equivalent CRT items in an open-ended, a two-option, or a four-option response format and then completed tasks on belief bias, denominator neglect, and paranormal beliefs (benchmark indicators of predictive validity), as well as on actively open-minded thinking and numeracy (benchmark indicators of construct validity). We found no significant differences between the three response formats in the numbers of correct responses, the numbers of intuitive responses (with the exception of the two-option version, which had a higher number than the other tests), and the correlational patterns of the indicators of predictive and construct validity. All three test versions were similarly reliable, but the multiple-choice formats were completed more quickly. We speculate that the specific nature of the CRT items helps build construct equivalence among the different response formats. We recommend using the validated multiple-choice version of the CRT presented here, particularly the four-option CRT, for practical and methodological reasons. Supplementary materials and data are available at https://osf.io/mzhyc/ .

The impact of selection bias on vaccine effectiveness estimates from test-negative studies.

PubMed

Jackson, Michael L; Phillips, C Hallie; Benoit, Joyce; Kiniry, Erika; Madziwa, Lawrence; Nelson, Jennifer C; Jackson, Lisa A

2018-01-29

Estimates of vaccine effectiveness (VE) from test-negative studies may be subject to selection bias. In the context of influenza VE, we used simulations to identify situations in which meaningful selection bias can occur. We also analyzed observational study data for evidence of selection bias. For the simulation study, we defined a hypothetical population whose members are at risk for acute respiratory illness (ARI) due to influenza and other pathogens. An unmeasured "healthcare seeking proclivity" affects both probability of vaccination and probability of seeking care for an ARI. We varied the direction and magnitude of these effects and identified situations where meaningful bias occurred. For the observational study, we reanalyzed data from the United States Influenza VE Network, an ongoing test-negative study. We compared "bias-naïve" VE estimates to bias-adjusted estimates, which used data from the source populations to correct for sampling bias. In the simulation study, an unmeasured care-seeking proclivity could create selection bias if persons with influenza ARI were more (or less) likely to seek care than persons with non-influenza ARI. However, selection bias was only meaningful when rates of care seeking between influenza ARI and non-influenza ARI were very different. In the observational study, the bias-naïve VE estimate of 55% (95% CI, 47--62%) was trivially different from the bias-adjusted VE estimate of 57% (95% CI, 49--63%). In combination, these studies suggest that while selection bias is possible in test-negative VE studies, this bias in unlikely to be meaningful under conditions likely to be encountered in practice. Researchers and public health officials can continue to rely on VE estimates from test-negative studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Memory deficits for facial identity in patients with amnestic mild cognitive impairment (MCI).

PubMed

Savaskan, Egemen; Summermatter, Daniel; Schroeder, Clemens; Schächinger, Hartmut

2018-01-01

Faces are among the most relevant social stimuli revealing an encounter's identity and actual emotional state. Deficits in facial recognition may be an early sign of cognitive decline leading to social deficits. The main objective of the present study is to investigate if individuals with amnestic mild cognitive impairment show recognition deficits in facial identity. Thirty-seven individuals with amnestic mild cognitive impairment, multiple-domain (15 female; age: 75±8 yrs.) and forty-one healthy volunteers (24 female; age 71±6 yrs.) participated. All participants completed a human portrait memory test presenting unfamiliar faces with happy and angry emotional expressions. Five and thirty minutes later, old and new neutral faces were presented, and discrimination sensitivity (d') and response bias (C) were assessed as signal detection parameters of cued facial identity recognition. Memory performance was lower in amnestic mild cognitive impairment as compared to control subjects, mainly because of an altered response bias towards an increased false alarm rate (favoring false OLD ascription of NEW items). In both groups, memory performance declined between the early and later testing session, and was always better for acquired happy than angry faces. Facial identity memory is impaired in patients with amnestic mild cognitive impairment. Liberalization of the response bias may reflect a socially motivated compensatory mechanism maintaining an almost identical recognition hit rate of OLD faces in individuals with amnestic mild cognitive impairment.

Common Scientific and Statistical Errors in Obesity Research

PubMed Central

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

2015-01-01

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

Electrostatic quadrupole array for focusing parallel beams of charged particles

DOEpatents

Brodowski, John

1982-11-23

An array of electrostatic quadrupoles, capable of providing strong electrostatic focusing simultaneously on multiple beams, is easily fabricated from a single array element comprising a support rod and multiple electrodes spaced at intervals along the rod. The rods are secured to four terminals which are isolated by only four insulators. This structure requires bias voltage to be supplied to only two terminals and eliminates the need for individual electrode bias and insulators, as well as increases life by eliminating beam plating of insulators.

Explanation of Two Anomalous Results in Statistical Mediation Analysis

ERIC Educational Resources Information Center

Fritz, Matthew S.; Taylor, Aaron B.; MacKinnon, David P.

2012-01-01

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special…

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

Calabrese, G.; Capineri, L., E-mail: lorenzo.capineri@unifi.it; Granato, M.

This paper describes the design of a system for the characterization of magnetic hysteresis behavior in soft ferrite magnetic cores. The proposed setup can test magnetic materials exciting them with controlled arbitrary magnetic field waveforms, including the capability of providing a DC bias, in a frequency bandwidth up to 500 kHz, with voltages up to 32 V peak-to-peak, and currents up to 10 A peak-to-peak. In order to have an accurate control of the magnetic field waveform, the system is based on a voltage controlled current source. The electronic design is described focusing on closed loop feedback stabilization and passivemore » components choice. The system has real-time hysteretic loop acquisition and visualization. The comparisons between measured hysteresis loops of sample magnetic materials and datasheet available ones are shown. Results showing frequency and thermal behavior of the hysteresis of a test sample prove the system capabilities. Moreover, the B-H loops obtained with a multiple waveforms excitation signal, including DC bias, are reported. The proposal is a low-cost and replicable solution for hysteresis characterization of magnetic materials used in power electronics.« less

"Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias": Correction to Rodebaugh et al. (2016).

PubMed

2016-10-01

Reports an error in "Unreliability as a threat to understanding psychopathology: The cautionary tale of attentional bias" by Thomas L. Rodebaugh, Rachel B. Scullin, Julia K. Langer, David J. Dixon, Jonathan D. Huppert, Amit Bernstein, Ariel Zvielli and Eric J. Lenze ( Journal of Abnormal Psychology , 2016[Aug], Vol 125[6], 840-851). There was an error in the Author Note concerning the support of the MacBrain Face Stimulus Set. The correct statement is provided. (The following abstract of the original article appeared in record 2016-30117-001.) The use of unreliable measures constitutes a threat to our understanding of psychopathology, because advancement of science using both behavioral and biologically oriented measures can only be certain if such measurements are reliable. Two pillars of the National Institute of Mental Health's portfolio-the Research Domain Criteria (RDoC) initiative for psychopathology and the target engagement initiative in clinical trials-cannot succeed without measures that possess the high reliability necessary for tests involving mediation and selection based on individual differences. We focus on the historical lack of reliability of attentional bias measures as an illustration of how reliability can pose a threat to our understanding. Our own data replicate previous findings of poor reliability for traditionally used scores, which suggests a serious problem with the ability to test theories regarding attentional bias. This lack of reliability may also suggest problems with the assumption (in both theory and the formula for the scores) that attentional bias is consistent and stable across time. In contrast, measures accounting for attention as a dynamic process in time show good reliability in our data. The field is sorely in need of research reporting findings and reliability for attentional bias scores using multiple methods, including those focusing on dynamic processes over time. We urge researchers to test and report reliability of all measures, considering findings of low reliability not just as a nuisance but as an opportunity to modify and improve upon the underlying theory. Full assessment of reliability of measures will maximize the possibility that RDoC (and psychological science more generally) will succeed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies.

PubMed

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Tremlett, Helen

2016-08-15

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = -0.002, mean squared error = 0.025; PTDM: bias = -1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995-2008). © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bias in masked word identification: unconscious influences of repetition priming.

PubMed

Masson, Michael E J

2002-12-01

The beneficial influence of a prior study episode on subsequent identification of a word includes a large bias component, revealed in the forced-choice variant of the masked word identification test. In that type of test, subjects show a preference for a studied probe over a nonstudied probe, regardless of which one matches the masked target word. The forced-choice test was used in the present experiments to test the possibility that this bias effect is due to conscious recollection. Results show that bias was strongly attenuated (1) by changes in modality between study and test, and (2) under certain conditions, by using a conceptually driven study task. The bias effect was found only when probes were orthographically similar to one another, as predicted by the counter model (Ratcliff & McKoon, 1997). These results provide strong evidence that the bias effect is not mediated by conscious recollection.

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

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

Samuroff, Simon

This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bandsmore » $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $$1\\sigma$$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $$m \\sim 0.03 - 0.09$$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $$S_8 \\equiv \\sigma_8 (\\omegam /0.3)^{0.5}$$ by $$1.5 \\sigma$$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $$> 2\\sigma$$ bias in $$S_8$$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.« less

Verification bias an underrecognized source of error in assessing the efficacy of medical imaging.

PubMed

Petscavage, Jonelle M; Richardson, Michael L; Carr, Robert B

2011-03-01

Diagnostic tests are validated by comparison against a "gold standard" reference test. When the reference test is invasive or expensive, it may not be applied to all patients. This can result in biased estimates of the sensitivity and specificity of the diagnostic test. This type of bias is called "verification bias," and is a common problem in imaging research. The purpose of our study is to estimate the prevalence of verification bias in the recent radiology literature. All issues of the American Journal of Roentgenology (AJR), Academic Radiology, Radiology, and European Journal of Radiology (EJR) between November 2006 and October 2009 were reviewed for original research articles mentioning sensitivity or specificity as endpoints. Articles were read to determine whether verification bias was present and searched for author recognition of verification bias in the design. During 3 years, these journals published 2969 original research articles. A total of 776 articles used sensitivity or specificity as an outcome. Of these, 211 articles demonstrated potential verification bias. The fraction of articles with potential bias was respectively 36.4%, 23.4%, 29.5%, and 13.4% for AJR, Academic Radiology, Radiology, and EJR. The total fraction of papers with potential bias in which the authors acknowledged this bias was 17.1%. Verification bias is a common and frequently unacknowledged source of error in efficacy studies of diagnostic imaging. Bias can often be eliminated by proper study design. When it cannot be eliminated, it should be estimated and acknowledged. Published by Elsevier Inc.

Inertial sensor self-calibration in a visually-aided navigation approach for a micro-AUV.

PubMed

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P

2015-01-16

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time.

Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV

PubMed Central

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P.

2015-01-01

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time. PMID:25602263

Duct wall impedance control as an advanced concept for acoustic suppression enhancement. [engine noise reduction

NASA Technical Reports Server (NTRS)

Dean, P. D.

1978-01-01

A systems concept procedure is described for the optimization of acoustic duct liner design for both uniform and multisegment types. The concept was implemented by the use of a double reverberant chamber flow duct facility coupled with sophisticated computer control and acoustic analysis systems. The optimization procedure for liner insertion loss was based on the concept of variable liner impedance produced by bias air flow through a multilayer, resonant cavity liner. A multiple microphone technique for in situ wall impedance measurements was used and successfully adapted to produce automated measurements for all liner configurations tested. The complete validation of the systems concept was prevented by the inability to optimize the insertion loss using bias flow induced wall impedance changes. This inability appeared to be a direct function of the presence of a higher order energy carrying modes which were not influenced significantly by the wall impedance changes.

Biased signaling of the proton-sensing receptor OGR1 by benzodiazepines.

PubMed

Pera, Tonio; Deshpande, Deepak A; Ippolito, Michael; Wang, Bin; Gavrila, Adelina; Michael, James V; Nayak, Ajay P; Tompkins, Eric; Farrell, Eleni; Kroeze, Wesley K; Roth, Bryan L; Panettieri, Reynold A; Benovic, Jeffrey L; An, Steven S; Dulin, Nickolai O; Penn, Raymond B

2018-02-01

GPCRs have diverse signaling capabilities, based on their ability to assume various conformations. Moreover, it is now appreciated that certain ligands can promote distinct receptor conformations and thereby bias signaling toward a specific pathway to differentially affect cell function. The recently deorphanized G protein-coupled receptor OGR1 [ovarian cancer G protein-coupled receptor 1 ( GPR68)] exhibits diverse signaling events when stimulated by reductions in extracellular pH. We recently demonstrated airway smooth muscle cells transduce multiple signaling events, reflecting a diverse capacity to couple to multiple G proteins. Moreover, we recently discovered that the benzodiazepine lorazepam, more commonly recognized as an agonist of the γ-aminobutyric acid A (GABA A ) receptor, can function as an allosteric modulator of OGR1 and, similarly, can promote multiple signaling events. In this study, we demonstrated that different benzodiazepines exhibit a range of biases for OGR1, with sulazepam selectively activating the canonical Gs of the G protein signaling pathway, in heterologous expression systems, as well as in several primary cell types. These findings highlight the potential power of biased ligand pharmacology for manipulating receptor signaling qualitatively, to preferentially activate pathways that are therapeutically beneficial.-Pera, T., Deshpande, D. A., Ippolito, M., Wang, B., Gavrila, A., Michael, J. V., Nayak, A. P., Tompkins, E., Farrell, E., Kroeze, W. K., Roth, B. L., Panettieri, R. A. Jr Benovic, J. L., An, S. S., Dulin, N. O., Penn, R. B. Biased signaling of the proton-sensing receptor OGR1 by benzodiazepines.

Rater Biases in Genetically Informative Research Designs: Comment on Bartels, Boomsma, Hudziak, van Beijsterveldt, and van den Oord (2007)

ERIC Educational Resources Information Center

Hoyt, William T.

2007-01-01

Rater biases are of interest to behavior genetic researchers, who often use ratings data as a basis for studying heritability. Inclusion of multiple raters for each sibling pair (M. Bartels, D. I. Boomsma, J. J. Hudziak, T. C. E. M. van Beijsterveldt, & E. J. C. G. van den Oord, 2007) is a promising strategy for controlling bias variance and may…

Behavioral decoding of working memory items inside and outside the focus of attention.

PubMed

Mallett, Remington; Lewis-Peacock, Jarrod A

2018-03-31

How we attend to our thoughts affects how we attend to our environment. Holding information in working memory can automatically bias visual attention toward matching information. By observing attentional biases on reaction times to visual search during a memory delay, it is possible to reconstruct the source of that bias using machine learning techniques and thereby behaviorally decode the content of working memory. Can this be done when more than one item is held in working memory? There is some evidence that multiple items can simultaneously bias attention, but the effects have been inconsistent. One explanation may be that items are stored in different states depending on the current task demands. Recent models propose functionally distinct states of representation for items inside versus outside the focus of attention. Here, we use behavioral decoding to evaluate whether multiple memory items-including temporarily irrelevant items outside the focus of attention-exert biases on visual attention. Only the single item in the focus of attention was decodable. The other item showed a brief attentional bias that dissipated until it returned to the focus of attention. These results support the idea of dynamic, flexible states of working memory across time and priority. © 2018 New York Academy of Sciences.

Influence of δ p-doping on the behaviour of GaAs/AlGaAs SAM-APDs for synchrotron radiation

NASA Astrophysics Data System (ADS)

Steinhartova, T.; Nichetti, C.; Antonelli, M.; Cautero, G.; Menk, R. H.; Pilotto, A.; Driussi, F.; Palestri, P.; Selmi, L.; Koshmak, K.; Nannarone, S.; Arfelli, F.; Dal Zilio, S.; Biasiol, G.

2017-11-01

This work focuses on the development and the characterization of avalanche photodiodes with separated absorption and multiplication regions grown by molecular beam epitaxy. The i-GaAs absorption region is separated from the multiplication region by a δ p-doped layer of carbon atoms, which ensures that after applying a reverse bias, the vast majority of the potential drops in the multiplication region. Therein, thin layers of AlGaAs and GaAs alternate periodically in a so-called staircase structure to create a periodic modulation of the band gap, which under bias enables a well-defined charge multiplication and results in a low multiplication noise. The influence of the concentration of carbon atoms in the δ p-doped layer on the device characteristics was investigated and experimental data are presented together with simulation results.

Characterising bias in regulatory risk and decision analysis: An analysis of heuristics applied in health technology appraisal, chemicals regulation, and climate change governance.

PubMed

MacGillivray, Brian H

2017-08-01

In many environmental and public health domains, heuristic methods of risk and decision analysis must be relied upon, either because problem structures are ambiguous, reliable data is lacking, or decisions are urgent. This introduces an additional source of uncertainty beyond model and measurement error - uncertainty stemming from relying on inexact inference rules. Here we identify and analyse heuristics used to prioritise risk objects, to discriminate between signal and noise, to weight evidence, to construct models, to extrapolate beyond datasets, and to make policy. Some of these heuristics are based on causal generalisations, yet can misfire when these relationships are presumed rather than tested (e.g. surrogates in clinical trials). Others are conventions designed to confer stability to decision analysis, yet which may introduce serious error when applied ritualistically (e.g. significance testing). Some heuristics can be traced back to formal justifications, but only subject to strong assumptions that are often violated in practical applications. Heuristic decision rules (e.g. feasibility rules) in principle act as surrogates for utility maximisation or distributional concerns, yet in practice may neglect costs and benefits, be based on arbitrary thresholds, and be prone to gaming. We highlight the problem of rule-entrenchment, where analytical choices that are in principle contestable are arbitrarily fixed in practice, masking uncertainty and potentially introducing bias. Strategies for making risk and decision analysis more rigorous include: formalising the assumptions and scope conditions under which heuristics should be applied; testing rather than presuming their underlying empirical or theoretical justifications; using sensitivity analysis, simulations, multiple bias analysis, and deductive systems of inference (e.g. directed acyclic graphs) to characterise rule uncertainty and refine heuristics; adopting "recovery schemes" to correct for known biases; and basing decision rules on clearly articulated values and evidence, rather than convention. Copyright © 2017. Published by Elsevier Ltd.

Contingency bias in probability judgement may arise from ambiguity regarding additional causes.

PubMed

Mitchell, Chris J; Griffiths, Oren; More, Pranjal; Lovibond, Peter F

2013-09-01

In laboratory contingency learning tasks, people usually give accurate estimates of the degree of contingency between a cue and an outcome. However, if they are asked to estimate the probability of the outcome in the presence of the cue, they tend to be biased by the probability of the outcome in the absence of the cue. This bias is often attributed to an automatic contingency detection mechanism, which is said to act via an excitatory associative link to activate the outcome representation at the time of testing. We conducted 3 experiments to test alternative accounts of contingency bias. Participants were exposed to the same outcome probability in the presence of the cue, but different outcome probabilities in the absence of the cue. Phrasing the test question in terms of frequency rather than probability and clarifying the test instructions reduced but did not eliminate contingency bias. However, removal of ambiguity regarding the presence of additional causes during the test phase did eliminate contingency bias. We conclude that contingency bias may be due to ambiguity in the test question, and therefore it does not require postulation of a separate associative link-based mechanism.

Multiple calibrator measurements improve accuracy and stability estimates of automated assays.

PubMed

Akbas, Neval; Budd, Jeffrey R; Klee, George G

2016-01-01

The effects of combining multiple calibrations on assay accuracy (bias) and measurement of calibration stability were investigated for total triiodothyronine (TT3), vitamin B12 and luteinizing hormone (LH) using Beckman Coulter's Access 2 analyzer. Three calibration procedures (CC1, CC2 and CC3) combined 12, 34 and 56 calibrator measurements over 1, 2, and 3 days. Bias was calculated between target values and average measured value over 3 consecutive days after calibration. Using regression analysis of calibrator measurements versus measurement date, calibration stability was determined as the maximum number of days before a calibrator measurement exceeded 5% tolerance limits. Competitive assays (TT3, vitamin B12) had positive time regression slopes, while sandwich assay (LH) had a negative slope. Bias values for TT3 were -2.49%, 1.49%, and -0.50% using CC1, CC2 and CC3 respectively, with calibrator stability of 32, 20, and 30 days. Bias values for vitamin B12 were 2.44%, 0.91%, and -0.50%, with calibrator stability of 4, 9, and 12 days. Bias values for LH were 2.26%, 1.44% and -0.29% with calibrator stability of >43, 39 and 36 days. Measured stability was more consistent across calibration procedures using percent change rather than difference from target: 26 days for TT3, 12 days for B12 and 31 days for LH. Averaging over multiple calibrations produced smaller bias, consistent with improved accuracy. Time regression slopes in percent change were unaffected by number of calibration measurements but calibrator stability measured from the target value was highly affected by the calibrator value at time zero.

Helpers' Self-Assessment Biases Before and after Helping Skills Training.

PubMed

Jaeken, Marine; Zech, Emmanuelle; Brison, Céline; Verhofstadt, Lesley L; Van Broeck, Nady; Mikolajczak, Moïra

2017-01-01

Several studies have shown that therapists are generally biased concerning their performed helping skills, as compared to judges' ratings. As clients' ratings of therapists' performance are better predictors of psychotherapy effectiveness than judges' ratings, this study examined the validity and effectiveness of a helping skills training program at reducing novice helpers' self-enhancement biases concerning their helping skills, in comparison to their clients' ratings. Helping skills were assessed by three objective measures (a knowledge multiple choice test, a video test and a role play), as well as by a self- and peer-reported questionnaire. In addition, some performed helping skills' correlates (relationship quality, session quality, and helpers' therapeutic attitudes) were assessed both by helpers and their simulated helpees. Seventy-two sophomores in psychology participated to this study, 37 being assigned to a 12-h helping skills training program, and 35 to a control group. Helpers were expected to assess the aforementioned performed helping skills and correlates as being better than their helpees' assessments at pretest, thus revealing a self-enhancement bias. At posttest, we expected that trained helpers would objectively exhibit better helping skills than untrained helpers while beginning to underestimate their performance, thus indexing a self-diminishment bias. In contrast, we hypothesized that untrained helpers would continue to overestimate their performance. Our hypotheses were only partly confirmed but results reflected a skilled-unaware pattern among trainees. Trained helpers went either from a pretest overestimation to a posttest equivalence (performed helping skills and performed therapeutic attitudes), or from a pretest equivalence to a posttest underestimation (performed session quality and performed therapeutic relationship), as compared to helpees' ratings. Results showed that trained helpers improved on all helping skills objective measures and that helpees' perceptions of their performance had increased at posttest. In conclusion, helping skills training leads helpers not only to improve their helping skills but also to have more doubts about their skills, two variables associated with psychotherapy outcome.

Helpers' Self-Assessment Biases Before and after Helping Skills Training

PubMed Central

Jaeken, Marine; Zech, Emmanuelle; Brison, Céline; Verhofstadt, Lesley L.; Van Broeck, Nady; Mikolajczak, Moïra

2017-01-01

Several studies have shown that therapists are generally biased concerning their performed helping skills, as compared to judges' ratings. As clients' ratings of therapists' performance are better predictors of psychotherapy effectiveness than judges' ratings, this study examined the validity and effectiveness of a helping skills training program at reducing novice helpers' self-enhancement biases concerning their helping skills, in comparison to their clients' ratings. Helping skills were assessed by three objective measures (a knowledge multiple choice test, a video test and a role play), as well as by a self- and peer-reported questionnaire. In addition, some performed helping skills' correlates (relationship quality, session quality, and helpers' therapeutic attitudes) were assessed both by helpers and their simulated helpees. Seventy-two sophomores in psychology participated to this study, 37 being assigned to a 12-h helping skills training program, and 35 to a control group. Helpers were expected to assess the aforementioned performed helping skills and correlates as being better than their helpees' assessments at pretest, thus revealing a self-enhancement bias. At posttest, we expected that trained helpers would objectively exhibit better helping skills than untrained helpers while beginning to underestimate their performance, thus indexing a self-diminishment bias. In contrast, we hypothesized that untrained helpers would continue to overestimate their performance. Our hypotheses were only partly confirmed but results reflected a skilled-unaware pattern among trainees. Trained helpers went either from a pretest overestimation to a posttest equivalence (performed helping skills and performed therapeutic attitudes), or from a pretest equivalence to a posttest underestimation (performed session quality and performed therapeutic relationship), as compared to helpees' ratings. Results showed that trained helpers improved on all helping skills objective measures and that helpees' perceptions of their performance had increased at posttest. In conclusion, helping skills training leads helpers not only to improve their helping skills but also to have more doubts about their skills, two variables associated with psychotherapy outcome. PMID:28861015

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation.

PubMed

Wahl, Simone; Boulesteix, Anne-Laure; Zierer, Astrid; Thorand, Barbara; van de Wiel, Mark A

2016-10-26

Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates are pooled. If the aim is to estimate (added) predictive performance measures, such as (change in) the area under the receiver-operating characteristic curve (AUC), internal validation strategies become desirable in order to correct for optimism. It is not fully understood how internal validation should be combined with multiple imputation. In a comprehensive simulation study and in a real data set based on blood markers as predictors for mortality, we compare three combination strategies: Val-MI, internal validation followed by MI on the training and test parts separately, MI-Val, MI on the full data set followed by internal validation, and MI(-y)-Val, MI on the full data set omitting the outcome followed by internal validation. Different validation strategies, including bootstrap und cross-validation, different (added) performance measures, and various data characteristics are considered, and the strategies are evaluated with regard to bias and mean squared error of the obtained performance estimates. In addition, we elaborate on the number of resamples and imputations to be used, and adopt a strategy for confidence interval construction to incomplete data. Internal validation is essential in order to avoid optimism, with the bootstrap 0.632+ estimate representing a reliable method to correct for optimism. While estimates obtained by MI-Val are optimistically biased, those obtained by MI(-y)-Val tend to be pessimistic in the presence of a true underlying effect. Val-MI provides largely unbiased estimates, with a slight pessimistic bias with increasing true effect size, number of covariates and decreasing sample size. In Val-MI, accuracy of the estimate is more strongly improved by increasing the number of bootstrap draws rather than the number of imputations. With a simple integrated approach, valid confidence intervals for performance estimates can be obtained. When prognostic models are developed on incomplete data, Val-MI represents a valid strategy to obtain estimates of predictive performance measures.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Exploratory Studies of Bias in Achievement Tests.

ERIC Educational Resources Information Center

Green, Donald Ross; Draper, John F.

This paper considers the question of bias in group administered academic achievement tests, bias which is inherent in the instruments themselves. A body of data on the test of performance of three disadvantaged minority groups--northern, urban black; southern, rural black; and, southwestern, Mexican-Americans--as tryout samples in contrast to…

Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study.

PubMed

Phelan, Sean M; Dovidio, John F; Puhl, Rebecca M; Burgess, Diana J; Nelson, David B; Yeazel, Mark W; Hardeman, Rachel; Perry, Sylvia; van Ryn, Michelle

2014-04-01

To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students. A web-based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti-fat attitudes test. A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice. Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact. Copyright © 2013 The Obesity Society.

Biased relevance filtering in the auditory system: A test of confidence-weighted first-impressions.

PubMed

Mullens, D; Winkler, I; Damaso, K; Heathcote, A; Whitson, L; Provost, A; Todd, J

2016-03-01

Although first-impressions are known to impact decision-making and to have prolonged effects on reasoning, it is less well known that the same type of rapidly formed assumptions can explain biases in automatic relevance filtering outside of deliberate behavior. This paper features two studies in which participants have been asked to ignore sequences of sound while focusing attention on a silent movie. The sequences consisted of blocks, each with a high-probability repetition interrupted by rare acoustic deviations (i.e., a sound of different pitch or duration). The probabilities of the two different sounds alternated across the concatenated blocks within the sequence (i.e., short-to-long and long-to-short). The sound probabilities are rapidly and automatically learned for each block and a perceptual inference is formed predicting the most likely characteristics of the upcoming sound. Deviations elicit a prediction-error signal known as mismatch negativity (MMN). Computational models of MMN generally assume that its elicitation is governed by transition statistics that define what sound attributes are most likely to follow the current sound. MMN amplitude reflects prediction confidence, which is derived from the stability of the current transition statistics. However, our prior research showed that MMN amplitude is modulated by a strong first-impression bias that outweighs transition statistics. Here we test the hypothesis that this bias can be attributed to assumptions about predictable vs. unpredictable nature of each tone within the first encountered context, which is weighted by the stability of that context. The results of Study 1 show that this bias is initially prevented if there is no 1:1 mapping between sound attributes and probability, but it returns once the auditory system determines which properties provide the highest predictive value. The results of Study 2 show that confidence in the first-impression bias drops if assumptions about the temporal stability of the transition-statistics are violated. Both studies provide compelling evidence that the auditory system extrapolates patterns on multiple timescales to adjust its response to prediction-errors, while profoundly distorting the effects of transition-statistics by the assumptions formed on the basis of first-impressions. Copyright © 2016 Elsevier B.V. All rights reserved.

Shear Recovery Accuracy in Weak-Lensing Analysis with the Elliptical Gauss-Laguerre Method

NASA Astrophysics Data System (ADS)

Nakajima, Reiko; Bernstein, Gary

2007-04-01

We implement the elliptical Gauss-Laguerre (EGL) galaxy-shape measurement method proposed by Bernstein & Jarvis and quantify the shear recovery accuracy in weak-lensing analysis. This method uses a deconvolution fitting scheme to remove the effects of the point-spread function (PSF). The test simulates >107 noisy galaxy images convolved with anisotropic PSFs and attempts to recover an input shear. The tests are designed to be immune to statistical (random) distributions of shapes, selection biases, and crowding, in order to test more rigorously the effects of detection significance (signal-to-noise ratio [S/N]), PSF, and galaxy resolution. The systematic error in shear recovery is divided into two classes, calibration (multiplicative) and additive, with the latter arising from PSF anisotropy. At S/N > 50, the deconvolution method measures the galaxy shape and input shear to ~1% multiplicative accuracy and suppresses >99% of the PSF anisotropy. These systematic errors increase to ~4% for the worst conditions, with poorly resolved galaxies at S/N simeq 20. The EGL weak-lensing analysis has the best demonstrated accuracy to date, sufficient for the next generation of weak-lensing surveys.

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

NASA Astrophysics Data System (ADS)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

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.

Discrimination, racial bias, and telomere length in African-American men.

PubMed

Chae, David H; Nuru-Jeter, Amani M; Adler, Nancy E; Brody, Gene H; Lin, Jue; Blackburn, Elizabeth H; Epel, Elissa S

2014-02-01

Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. After controlling for chronologic age and socioeconomic and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b=-0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. © 2013 American Journal of Preventive Medicine Published by American Journal of Preventive Medicine All rights reserved.

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

PubMed Central

Verdam, Mathilde G. E.; Oort, Frans J.

2014-01-01

Highlights Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data. A method for the investigation of measurement bias with Kronecker product restricted models. Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions. The use of curves to facilitate substantive interpretation of apparent measurement bias. Assessment of change in common factor means, after accounting for apparent measurement bias. Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks. PMID:25295016

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions.

PubMed

Verdam, Mathilde G E; Oort, Frans J

2014-01-01

Application of Kronecker product to construct parsimonious structural equation models for multivariate longitudinal data.A method for the investigation of measurement bias with Kronecker product restricted models.Application of these methods to health-related quality of life data from bone metastasis patients, collected at 13 consecutive measurement occasions.The use of curves to facilitate substantive interpretation of apparent measurement bias.Assessment of change in common factor means, after accounting for apparent measurement bias.Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks.

Surprise, Memory, and Retrospective Judgment Making: Testing Cognitive Reconstruction Theories of the Hindsight Bias Effect

ERIC Educational Resources Information Center

Ash, Ivan K.

2009-01-01

Hindsight bias has been shown to be a pervasive and potentially harmful decision-making bias. A review of 4 competing cognitive reconstruction theories of hindsight bias revealed conflicting predictions about the role and effect of expectation or surprise in retrospective judgment formation. Two experiments tested these predictions examining the…

Clinical Pharmacology Quality Assurance (CPQA) Program: Models for Longitudinal Analysis of Antiretroviral (ARV) Proficiency Testing for International Laboratories

PubMed Central

DiFrancesco, Robin; Rosenkranz, Susan L.; Taylor, Charlene R.; Pande, Poonam G.; Siminski, Suzanne M.; Jenny, Richard W.; Morse, Gene D.

2013-01-01

Among National Institutes of Health (NIH) HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals (ARV). Drug assay data are, in turn, entered into study-specific datasets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semi-annual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance (CPQA) program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1)assess the precision and accuracy of concentrations reported by individual CPLs; (2)determine factors associated with round-specific and long-term assay accuracy, precision and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21)drug concentration results reported for clinical trial samples by multiple CPLs).Using the CLIA acceptance of meeting criteria for ≥2/3 consecutive rounds, all ten laboratories that participated in three or more rounds per analyte maintained CLIA proficiency. Significant associations were present between magnitude of error and CPL (Kruskal Wallis [KW]p<0.001), and ARV (KW p<0.001). PMID:24052065

Clinical pharmacology quality assurance program: models for longitudinal analysis of antiretroviral proficiency testing for international laboratories.

PubMed

DiFrancesco, Robin; Rosenkranz, Susan L; Taylor, Charlene R; Pande, Poonam G; Siminski, Suzanne M; Jenny, Richard W; Morse, Gene D

2013-10-01

Among National Institutes of Health HIV Research Networks conducting multicenter trials, samples from protocols that span several years are analyzed at multiple clinical pharmacology laboratories (CPLs) for multiple antiretrovirals. Drug assay data are, in turn, entered into study-specific data sets that are used for pharmacokinetic analyses, merged to conduct cross-protocol pharmacokinetic analysis, and integrated with pharmacogenomics research to investigate pharmacokinetic-pharmacogenetic associations. The CPLs participate in a semiannual proficiency testing (PT) program implemented by the Clinical Pharmacology Quality Assurance program. Using results from multiple PT rounds, longitudinal analyses of recovery are reflective of accuracy and precision within/across laboratories. The objectives of this longitudinal analysis of PT across multiple CPLs were to develop and test statistical models that longitudinally: (1) assess the precision and accuracy of concentrations reported by individual CPLs and (2) determine factors associated with round-specific and long-term assay accuracy, precision, and bias using a new regression model. A measure of absolute recovery is explored as a simultaneous measure of accuracy and precision. Overall, the analysis outcomes assured 97% accuracy (±20% of the final target concentration of all (21) drug concentration results reported for clinical trial samples by multiple CPLs). Using the Clinical Laboratory Improvement Act acceptance of meeting criteria for ≥2/3 consecutive rounds, all 10 laboratories that participated in 3 or more rounds per analyte maintained Clinical Laboratory Improvement Act proficiency. Significant associations were present between magnitude of error and CPL (Kruskal-Wallis P < 0.001) and antiretroviral (Kruskal-Wallis P < 0.001).

Study of Bias in 2012-Placement Test through Rasch Model in Terms of Gender Variable

ERIC Educational Resources Information Center

Turkan, Azmi; Cetin, Bayram

2017-01-01

Validity and reliability are among the most crucial characteristics of a test. One of the steps to make sure that a test is valid and reliable is to examine the bias in test items. The purpose of this study was to examine the bias in 2012 Placement Test items in terms of gender variable using Rasch Model in Turkey. The sample of this study was…

Statistics in biomedical laboratory and clinical science: applications, issues and pitfalls.

PubMed

Ludbrook, John

2008-01-01

This review is directed at biomedical scientists who want to gain a better understanding of statistics: what tests to use, when, and why. In my view, even during the planning stage of a study it is very important to seek the advice of a qualified biostatistician. When designing and analyzing a study, it is important to construct and test global hypotheses, rather than to make multiple tests on the data. If the latter cannot be avoided, it is essential to control the risk of making false-positive inferences by applying multiple comparison procedures. For comparing two means or two proportions, it is best to use exact permutation tests rather then the better known, classical, ones. For comparing many means, analysis of variance, often of a complex type, is the most powerful approach. The correlation coefficient should never be used to compare the performances of two methods of measurement, or two measures, because it does not detect bias. Instead the Altman-Bland method of differences or least-products linear regression analysis should be preferred. Finally, the educational value to investigators of interaction with a biostatistician, before, during and after a study, cannot be overemphasized. (c) 2007 S. Karger AG, Basel.

Sociolinguistic and Measurement Considerations for Construction of Armed Services Selection Batteries. Final Report for Period October 1975-June 1977.

ERIC Educational Resources Information Center

Boldt, R. F.; And Others

Test fairness or bias may be defined in many different ways, and the existence of possible bias is difficult to demonstrate. Sociolinguistic analysis may be used to check for fairness or bias in test directions, test content specifications, or test items. Four sociolinguistic principles are held to be relevant for this task: (1) pragmatics--that…

Using multiple travel paths to estimate daily travel distance in arboreal, group-living primates.

PubMed

Steel, Ruth Irene

2015-01-01

Primate field studies often estimate daily travel distance (DTD) in order to estimate energy expenditure and/or test foraging hypotheses. In group-living species, the center of mass (CM) method is traditionally used to measure DTD; a point is marked at the group's perceived center of mass at a set time interval or upon each move, and the distance between consecutive points is measured and summed. However, for groups using multiple travel paths, the CM method potentially creates a central path that is shorter than the individual paths and/or traverses unused areas. These problems may compromise tests of foraging hypotheses, since distance and energy expenditure could be underestimated. To better understand the magnitude of these potential biases, I designed and tested the multiple travel paths (MTP) method, in which DTD was calculated by recording all travel paths taken by the group's members, weighting each path's distance based on its proportional use by the group, and summing the weighted distances. To compare the MTP and CM methods, DTD was calculated using both methods in three groups of Udzungwa red colobus monkeys (Procolobus gordonorum; group size 30-43) for a random sample of 30 days between May 2009 and March 2010. Compared to the CM method, the MTP method provided significantly longer estimates of DTD that were more representative of the actual distance traveled and the areas used by a group. The MTP method is more time-intensive and requires multiple observers compared to the CM method. However, it provides greater accuracy for testing ecological and foraging models.

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 in estimating accuracy of a binary screening test with differential disease verification

PubMed Central

Brinton, John T.; Ringham, Brandy M.; Glueck, Deborah H.

2011-01-01

SUMMARY Sensitivity, specificity, positive and negative predictive value are typically used to quantify the accuracy of a binary screening test. In some studies it may not be ethical or feasible to obtain definitive disease ascertainment for all subjects using a gold standard test. When a gold standard test cannot be used an imperfect reference test that is less than 100% sensitive and specific may be used instead. In breast cancer screening, for example, follow-up for cancer diagnosis is used as an imperfect reference test for women where it is not possible to obtain gold standard results. This incomplete ascertainment of true disease, or differential disease verification, can result in biased estimates of accuracy. In this paper, we derive the apparent accuracy values for studies subject to differential verification. We determine how the bias is affected by the accuracy of the imperfect reference test, the percent who receive the imperfect reference standard test not receiving the gold standard, the prevalence of the disease, and the correlation between the results for the screening test and the imperfect reference test. It is shown that designs with differential disease verification can yield biased estimates of accuracy. Estimates of sensitivity in cancer screening trials may be substantially biased. However, careful design decisions, including selection of the imperfect reference test, can help to minimize bias. A hypothetical breast cancer screening study is used to illustrate the problem. PMID:21495059

Multiple testing with discrete data: Proportion of true null hypotheses and two adaptive FDR procedures.

PubMed

Chen, Xiongzhi; Doerge, Rebecca W; Heyse, Joseph F

2018-05-11

We consider multiple testing with false discovery rate (FDR) control when p values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, that is, an adaptive Benjamini-Hochberg (BH) procedure and an adaptive Benjamini-Hochberg-Heyse (BHH) procedure. We prove that the adaptive BH (aBH) procedure is conservative nonasymptotically. Through simulation studies, we show that these procedures are usually more powerful than their nonadaptive counterparts and that the adaptive BHH procedure is usually more powerful than the aBH procedure and a procedure based on randomized p-value. The adaptive procedures are applied to a study of HIV vaccine efficacy, where they identify more differentially polymorphic positions than the BH procedure at the same FDR level. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Top-down control of visual perception: attention in natural vision.

PubMed

Rolls, Edmund T

2008-01-01

Top-down perceptual influences can bias (or pre-empt) perception. In natural scenes, the receptive fields of neurons in the inferior temporal visual cortex (IT) shrink to become close to the size of objects. This facilitates the read-out of information from the ventral visual system, because the information is primarily about the object at the fovea. Top-down attentional influences are much less evident in natural scenes than when objects are shown against blank backgrounds, though are still present. It is suggested that the reduced receptive-field size in natural scenes, and the effects of top-down attention contribute to change blindness. The receptive fields of IT neurons in complex scenes, though including the fovea, are frequently asymmetric around the fovea, and it is proposed that this is the solution the IT uses to represent multiple objects and their relative spatial positions in a scene. Networks that implement probabilistic decision-making are described, and it is suggested that, when in perceptual systems they take decisions (or 'test hypotheses'), they influence lower-level networks to bias visual perception. Finally, it is shown that similar processes extend to systems involved in the processing of emotion-provoking sensory stimuli, in that word-level cognitive states provide top-down biasing that reaches as far down as the orbitofrontal cortex, where, at the first stage of affective representations, olfactory, taste, flavour, and touch processing is biased (or pre-empted) in humans.

Implicit race attitudes predict trustworthiness judgments and economic trust decisions

PubMed Central

Stanley, Damian A.; Sokol-Hessner, Peter; Banaji, Mahzarin R.; Phelps, Elizabeth A.

2011-01-01

Trust lies at the heart of every social interaction. Each day we face decisions in which we must accurately assess another individual's trustworthiness or risk suffering very real consequences. In a global marketplace of increasing heterogeneity with respect to nationality, race, and multiple other social categories, it is of great value to understand how implicitly held attitudes about group membership may support or undermine social trust and thereby implicitly shape the decisions we make. Recent behavioral and neuroimaging work suggests that a common mechanism may underlie the expression of implicit race bias and evaluations of trustworthiness, although no direct evidence of a connection exists. In two behavioral studies, we investigated the relationship between implicit race attitude (as measured by the Implicit Association Test) and social trust. We demonstrate that race disparity in both an individual's explicit evaluations of trustworthiness and, more crucially, his or her economic decisions to trust is predicted by that person's bias in implicit race attitude. Importantly, this relationship is robust and is independent of the individual's bias in explicit race attitude. These data demonstrate that the extent to which an individual invests in and trusts others with different racial backgrounds is related to the magnitude of that individual's implicit race bias. The core dimension of social trust can be shaped, to some degree, by attitudes that reside outside conscious awareness and intention. PMID:21518877

Implicit race attitudes predict trustworthiness judgments and economic trust decisions.

PubMed

Stanley, Damian A; Sokol-Hessner, Peter; Banaji, Mahzarin R; Phelps, Elizabeth A

2011-05-10

Trust lies at the heart of every social interaction. Each day we face decisions in which we must accurately assess another individual's trustworthiness or risk suffering very real consequences. In a global marketplace of increasing heterogeneity with respect to nationality, race, and multiple other social categories, it is of great value to understand how implicitly held attitudes about group membership may support or undermine social trust and thereby implicitly shape the decisions we make. Recent behavioral and neuroimaging work suggests that a common mechanism may underlie the expression of implicit race bias and evaluations of trustworthiness, although no direct evidence of a connection exists. In two behavioral studies, we investigated the relationship between implicit race attitude (as measured by the Implicit Association Test) and social trust. We demonstrate that race disparity in both an individual's explicit evaluations of trustworthiness and, more crucially, his or her economic decisions to trust is predicted by that person's bias in implicit race attitude. Importantly, this relationship is robust and is independent of the individual's bias in explicit race attitude. These data demonstrate that the extent to which an individual invests in and trusts others with different racial backgrounds is related to the magnitude of that individual's implicit race bias. The core dimension of social trust can be shaped, to some degree, by attitudes that reside outside conscious awareness and intention.

Longitudinal Risk and Resilience Factors Predicting Psychiatric Disruption, Mental Health Service Utilization & Military Retention in OIF National Guard Troops

DTIC Science & Technology

2009-04-01

completing in-person clinical assessments that include structured clinical interviews and psychological testing . As an introduction to the three...coordinator to opt out of the project. 2.2.2. Analyses of Response Bias. To test for response bias, we compared responders and non-responders to the...used to include these subjects without Wave 2 data in the final analyses. 2.3.2. Analyses of Response Bias. To test for response bias at Wave 3

Measuring sexual orientation in adolescent health surveys: evaluation of eight school-based surveys.

PubMed

Saewyc, Elizabeth M; Bauer, Greta R; Skay, Carol L; Bearinger, Linda H; Resnick, Michael D; Reis, Elizabeth; Murphy, Aileen

2004-10-01

To examine the performance of various items measuring sexual orientation within 8 school-based adolescent health surveys in the United States and Canada from 1986 through 1999. Analyses examined nonresponse and unsure responses to sexual orientation items compared with other survey items, demographic differences in responses, tests for response set bias, and congruence of responses to multiple orientation items; analytical methods included frequencies, contingency tables with Chi-square, and ANOVA with least significant differences (LSD)post hoc tests; all analyses were conducted separately by gender. In all surveys, nonresponse rates for orientation questions were similar to other sexual questions, but not higher; younger students, immigrants, and students with learning disabilities were more likely to skip items or select "unsure." Sexual behavior items had the lowest nonresponse, but fewer than half of all students reported sexual behavior, limiting its usefulness for indicating orientation. Item placement in the survey, wording, and response set bias all appeared to influence nonresponse and unsure rates. Specific recommendations include standardizing wording across future surveys, and pilot testing items with diverse ages and ethnic groups of teens before use. All three dimensions of orientation should be assessed where possible; when limited to single items, sexual attraction may be the best choice. Specific wording suggestions are offered for future surveys.

False-positive results in pharmacoepidemiology and pharmacovigilance.

PubMed

Bezin, Julien; Bosco-Levy, Pauline; Pariente, Antoine

2017-09-01

False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed. Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

Detecting Gender Bias Through Test Item Analysis

NASA Astrophysics Data System (ADS)

González-Espada, Wilson J.

2009-03-01

Many physical science and physics instructors might not be trained in pedagogically appropriate test construction methods. This could lead to test items that do not measure what they are intended to measure. A subgroup of these items might show bias against some groups of students. This paper describes how the author became aware of potentially biased items against females in his examinations, which led to the exploration of fundamental issues related to item validity, gender bias, and differential item functioning, or DIF. A brief discussion of DIF in the context of university courses, as well as practical suggestions to detect possible gender-biased items, follows.

Bayesian Estimation of Combined Accuracy for Tests with Verification Bias

PubMed Central

Broemeling, Lyle D.

2011-01-01

This presentation will emphasize the estimation of the combined accuracy of two or more tests when verification bias is present. Verification bias occurs when some of the subjects are not subject to the gold standard. The approach is Bayesian where the estimation of test accuracy is based on the posterior distribution of the relevant parameter. Accuracy of two combined binary tests is estimated employing either “believe the positive” or “believe the negative” rule, then the true and false positive fractions for each rule are computed for two tests. In order to perform the analysis, the missing at random assumption is imposed, and an interesting example is provided by estimating the combined accuracy of CT and MRI to diagnose lung cancer. The Bayesian approach is extended to two ordinal tests when verification bias is present, and the accuracy of the combined tests is based on the ROC area of the risk function. An example involving mammography with two readers with extreme verification bias illustrates the estimation of the combined test accuracy for ordinal tests. PMID:26859487

Increased latencies to respond in a judgment bias test are not associated with pessimistic biases in rats.

PubMed

Barker, Timothy Hugh; Howarth, Gordon Stanley; Whittaker, Alexandra Louise

2018-01-01

Extinction of learning is a common, yet under-reported limitation of judgment bias testing methods Repeated exposure to the ambiguous probe of a judgment bias paradigm encourages the animal to cease display of the required behaviours. However, there remains a need to repeatedly test animals to achieve statistical power. A delicate balance therefore needs to be struck between over- and under-exposure of the animals to the test conditions. This study presents the data of rats, a common animal subject of judgment bias testing. Rats were exposed to the ambiguous probe of a common, active-choice judgment bias test for 11 consecutive days. There was a significant increase in the latency to respond to the ambiguous probe following day 8, with no significant increase experienced for either the positive or less-positive probes. Following day 8 there was a significant increase in both optimistic and pessimistic latencies in response to the ambiguous probe. Therefore, repeated exposure to the ambiguous probe caused an increased latency in response even though optimistic interpretations were recorded. This implies that the use of response latency alone as a measure in judgment bias testing can falsely identify pessimism. Researchers should modify experimental design to include both choice and latency measures. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Nontrivial transition of transmission in a highly open quantum point contact in the quantum Hall regime

NASA Astrophysics Data System (ADS)

Hong, Changki; Park, Jinhong; Chung, Yunchul; Choi, Hyungkook; Umansky, Vladimir

2017-11-01

Transmission through a quantum point contact (QPC) in the quantum Hall regime usually exhibits multiple resonances as a function of gate voltage and high nonlinearity in bias. Such behavior is unpredictable and changes sample by sample. Here, we report the observation of a sharp transition of the transmission through an open QPC at finite bias, which was observed consistently for all the tested QPCs. It is found that the bias dependence of the transition can be fitted to the Fermi-Dirac distribution function through universal scaling. The fitted temperature matches quite nicely to the electron temperature measured via shot-noise thermometry. While the origin of the transition is unclear, we propose a phenomenological model based on our experimental results that may help to understand such a sharp transition. Similar transitions are observed in the fractional quantum Hall regime, and it is found that the temperature of the system can be measured by rescaling the quasiparticle energy with the effective charge (e*=e /3 ). We believe that the observed phenomena can be exploited as a tool for measuring the electron temperature of the system and for studying the quasiparticle charges of the fractional quantum Hall states.

Resolving kangaroo phylogeny and overcoming retrotransposon ascertainment bias.

PubMed

Dodt, William G; Gallus, Susanne; Phillips, Matthew J; Nilsson, Maria A

2017-12-01

Reconstructing phylogeny from retrotransposon insertions is often limited by access to only a single reference genome, whereby support for clades that do not include the reference taxon cannot be directly observed. Here we have developed a new statistical framework that accounts for this ascertainment bias, allowing us to employ phylogenetically powerful retrotransposon markers to explore the radiation of the largest living marsupials, the kangaroos and wallabies of the genera Macropus and Wallabia. An exhaustive in silico screening of the tammar wallaby (Macropus eugenii) reference genome followed by experimental screening revealed 29 phylogenetically informative retrotransposon markers belonging to a family of endogenous retroviruses. We identified robust support for the enigmatic swamp wallaby (Wallabia bicolor) falling within a paraphyletic genus, Macropus. Our statistical approach provides a means to test for incomplete lineage sorting and introgression/hybridization in the presence of the ascertainment bias. Using retrotransposons as "molecular fossils", we reveal one of the most complex patterns of hemiplasy yet identified, during the rapid diversification of kangaroos and wallabies. Ancestral state reconstruction incorporating the new retrotransposon phylogenetic information reveals multiple independent ecological shifts among kangaroos into more open habitats, coinciding with the Pliocene onset of increased aridification in Australia from ~3.6 million years ago.

Robust Analysis of Network-Based Real-Time Kinematic for GNSS-Derived Heights.

PubMed

Bae, Tae-Suk; Grejner-Brzezinska, Dorota; Mader, Gerald; Dennis, Michael

2015-10-26

New guidelines and procedures for real-time (RT) network-based solutions are required in order to support Global Navigation Satellite System (GNSS) derived heights. Two kinds of experiments were carried out to analyze the performance of the network-based real-time kinematic (RTK) solutions. New test marks were installed in different surrounding environments, and the existing GPS benchmarks were used for analyzing the effect of different factors, such as baseline lengths, antenna types, on the final accuracy and reliability of the height estimation. The RT solutions are categorized into three groups: single-base RTK, multiple-epoch network RTK (mRTN), and single-epoch network RTK (sRTN). The RTK solution can be biased up to 9 mm depending on the surrounding environment, but there was no notable bias for a longer reference base station (about 30 km) In addition, the occupation time for the network RTK was investigated in various cases. There is no explicit bias in the solution for different durations, but smoother results were obtained for longer durations. Further investigation is needed into the effect of changing the occupation time between solutions and into the possibility of using single-epoch solutions in precise determination of heights by GNSS.

Understanding and Overcoming Implicit Gender Bias in Plastic Surgery.

PubMed

Phillips, Nicole A; Tannan, Shruti C; Kalliainen, Loree K

2016-11-01

Although explicit sex-based discrimination has largely been deemed unacceptable in professional settings, implicit gender bias persists and results in a significant lack of parity in plastic surgery and beyond. Implicit gender bias is the result of a complex interplay of cultural and societal expectations, learned behaviors, and standardized associations. As such, both male and female surgeons are subject to its influence. A review of the literature was conducted, examining theories of gender bias, current manifestations of gender bias in plastic surgery and other fields, and interventions designed to address gender bias. Multiple studies demonstrate persistent gender bias that impacts female physicians at all levels of training. Several institutions have enacted successful interventions to identify and address gender bias. Explicit gender bias has largely disappeared, yet unconscious or implicit gender bias persists. A wide-scale commitment to addressing implicit gender bias in plastic surgery is necessary and overdue. Recommendations include immediate actions that can be undertaken on an individual basis, and changes that should be implemented at a national and international level by leaders in the field.

Quantile regression models of animal habitat relationships

USGS Publications Warehouse

Cade, Brian S.

2003-01-01

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n, greater number of parameters p, and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F-ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large (N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative (interference interactions) or positive (facilitation interactions), either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Sampling (n = 20 - 300) simulations demonstrated that confidence intervals constructed by inverting rankscore tests provided valid coverage of these biased parameters. Quantile regression was used to estimate effects of physical habitat resources on a bivalve mussel (Macomona liliana) in a New Zealand harbor by modeling the spatial trend surface as a cubic polynomial of location coordinates.

Survey Response-Related Biases in Contingent Valuation: Concepts, Remedies, and Empirical Application to Valuing Aquatic Plant Management

Treesearch

Mark L. Messonnier; John C. Bergstrom; Chrisopher M. Cornwell; R. Jeff Teasley; H. Ken Cordell

2000-01-01

Simple nonresponse and selection biases that may occur in survey research such as contingent valuation applications are discussed and tested. Correction mechanisms for these types of biases are demonstrated. Results indicate the importance of testing and correcting for unit and item nonresponse bias in contingent valuation survey data. When sample nonresponse and...

Cultural Bias in Testing: A Review of Literature and Implications in Music Education

ERIC Educational Resources Information Center

Kruse, Adam J.

2016-01-01

The findings and discussions related to cultural bias in testing have in no way been unanimous. However, the considerations of this area of inquiry may possess meaningful implications for educators of any subject. In this review of literature, I describe the issues, research, and arguments surrounding cultural bias in testing and discuss…

Bias Factors in Mathematics Achievement Tests among Israeli Students from the Former Soviet Union

ERIC Educational Resources Information Center

Levi-Keren, Michal

2016-01-01

This study explains mathematical difficulties of students who immigrated from the Former Soviet Union (FSU) vis-à-vis Israeli students, by identifying the existing bias factors in achievement tests. These factors are irrelevant to the mathematical knowledge being measured, and therefore threaten the test results. The bias factors were identified…

Molecular image-directed biopsies: improving clinical biopsy selection in patients with multiple tumors

NASA Astrophysics Data System (ADS)

Harmon, Stephanie A.; Tuite, Michael J.; Jeraj, Robert

2016-10-01

Site selection for image-guided biopsies in patients with multiple lesions is typically based on clinical feasibility and physician preference. This study outlines the development of a selection algorithm that, in addition to clinical requirements, incorporates quantitative imaging data for automatic identification of candidate lesions for biopsy. The algorithm is designed to rank potential targets by maximizing a lesion-specific score, incorporating various criteria separated into two categories: (1) physician-feasibility category including physician-preferred lesion location and absolute volume scores, and (2) imaging-based category including various modality and application-specific metrics. This platform was benchmarked in two clinical scenarios, a pre-treatment setting and response-based setting using imaging from metastatic prostate cancer patients with high disease burden (multiple lesions) undergoing conventional treatment and receiving whole-body [18F]NaF PET/CT scans pre- and mid-treatment. Targeting of metastatic lesions was robust to different weighting ratios and candidacy for biopsy was physician confirmed. Lesion ranked as top targets for biopsy remained so for all patients in pre-treatment and post-treatment biopsy selection after sensitivity testing was completed for physician-biased or imaging-biased scenarios. After identifying candidates, biopsy feasibility was evaluated by a physician and confirmed for 90% (32/36) of high-ranking lesions, of which all top choices were confirmed. The remaining cases represented lesions with high anatomical difficulty for targeting, such as proximity to sciatic nerve. This newly developed selection method was successfully used to quantitatively identify candidate lesions for biopsies in patients with multiple lesions. In a prospective study, we were able to successfully plan, develop, and implement this technique for the selection of a pre-treatment biopsy location.

Developmental Precursors of Young School-Age Children's Hostile Attribution Bias

ERIC Educational Resources Information Center

Choe, Daniel Ewon; Lane, Jonathan D.; Grabell, Adam S.; Olson, Sheryl L.

2013-01-01

This prospective longitudinal study provides evidence of preschool-age precursors of hostile attribution bias in young school-age children, a topic that has received little empirical attention. We examined multiple risk domains, including laboratory and observational assessments of children's social-cognition, general cognitive functioning,…

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

USGS Publications Warehouse

Clare, John; McKinney, Shawn T.; DePue, John E.; Loftin, Cynthia S.

2017-01-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture–recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.

The relationship between study sponsorship, risks of bias, and research outcomes in atrazine exposure studies conducted in non-human animals: Systematic review and meta-analysis.

PubMed

Bero, L; Anglemyer, A; Vesterinen, H; Krauth, D

2016-01-01

A critical component of systematic review methodology is the assessment of the risks of bias of studies that are included in the review. There is controversy about whether funding source should be included in a risk of bias assessment of animal toxicology studies. To determine whether industry research sponsorship is associated with methodological biases, the results, or conclusions of animal studies examining the effect of exposure to atrazine on reproductive or developmental outcomes. We searched multiple electronic databases and the reference lists of relevant articles to identify original research studies examining the effect of any dose of atrazine exposure at any life stage on reproduction or development in non-human animals. We compared methodological risks of bias, the conclusions of the studies, the statistical significance of the findings, and the magnitude of effect estimates between industry sponsored and non-industry sponsored studies. Fifty-one studies met the inclusion criteria. There were no differences in methodological risks of bias in industry versus non-industry sponsored studies. 39 studies tested environmentally relevant concentrations of atrazine (11 industry sponsored, 24 non-industry sponsored, 4 with no funding disclosures). Non-industry sponsored studies (12/24, 50.0%) were more likely to conclude that atrazine was harmful compared to industry sponsored studies (2/11, 18.1%) (p value=0.07). A higher proportion of non-industry sponsored studies reported statistically significant harmful effects (8/24, 33.3%) compared to industry-sponsored studies (1/11; 9.1%) (p value=0.13). The association of industry sponsorship with decreased effect sizes for harm outcomes was inconclusive. Our findings support the inclusion of research sponsorship as a risk of bias criterion in tools used to assess risks of bias in animal studies for systematic reviews. The reporting of other empirically based risk of bias criteria for animal studies, such as blinded outcome assessment, randomization, and all animals included in analyses, needs to improve to facilitate the assessment of studies for systematic reviews. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Air Force Officer Qualifying Test: Validity, Fairness, and Bias

DTIC Science & Technology

2010-01-01

scores. The Standards for Educational and Psychological Testing (AERA, APA, and NCME, 1999) provides a set of guidelines published and endorsed by the...determining the validity and bias of selection tests falls upon professionals in the discipline of industrial/organizational psychology 20 See Roper v. Dep’t...i). 30 The Air Force Officer Qualifying Test : Validity, Fairness, and Bias and closely related fields (e.g., educational psychology and

A Behaviorally Specific, Empirical Alternative to Bullying: Aggravated Peer Victimization.

PubMed

Finkelhor, David; Shattuck, Anne; Turner, Heather; Hamby, Sherry

2016-11-01

To test a behaviorally specific measure of serious peer victimization, called aggravated peer victimization (APV), using empirically derived aggravating elements of episodes (injury, weapon, bias content, sexual content, multiple perpetrators, and multiple contexts) and compare this measure with the conventional Olweus bullying (OB) measure, which uses repetition and power imbalance as its seriousness criteria. The data for this study come from The National Survey of Children's Exposure to Violence 2014, a study conducted via telephone interviews with a nationally representative sample. This analysis uses the 1,949 youth ages 10-17 from that survey. The APV measure identified twice as many youth with serious episodes involving injury, weapons, sexual assaults, and bias content as the OB measure. In terms of demographic and social characteristics, the groups were very similar. However, the APV explained significantly more of the variation in distress than the OB (R 2  = .19 vs. .12). An empirical approach to identifying the most serious incidents of peer victimization has advantages in identifying more of the youth suffering the effects of peer victimization. Moreover, its behaviorally specific criteria also bypass the difficult challenge of trying to reliably assess what is truly bullying with its ambiguous definitional element of power imbalance. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Air quality and acute deaths in California, 2000-2012.

PubMed

Young, S Stanley; Smith, Richard L; Lopiano, Keneth K

2017-08-01

Many studies have shown an association between air quality and acute deaths, and such associations are widely interpreted as causal. Several factors call causation and even association into question, for example multiple testing and multiple modeling, publication bias and confirmation bias. Many published studies are difficult or impossible to reproduce because of lack of access to confidential data sources. Here we make publically available a dataset containing daily air quality levels, PM 2.5 and ozone, daily temperature levels, minimum and maximum and daily maximum relative humidity levels for the eight most populous California air basins, thirteen years, >2M deaths, over 37,000 exposure days. The data are analyzed using standard time series analysis, and a sensitivity analysis is computed varying model parameters, locations and years. Our analysis finds little evidence for association between air quality and acute deaths. These results are consistent with those for the widely cited NMMAPS dataset when the latter are restricted to California. The daily death variability was mostly explained by time of year or weather variables; Neither PM 2.5 nor ozone added appreciably to the prediction of daily deaths. These results call into question the widespread belief that association between air quality and acute deaths is causal/near-universal. Copyright © 2017 Elsevier Inc. All rights reserved.

Radio weak lensing shear measurement in the visibility domain - II. Source extraction

NASA Astrophysics Data System (ADS)

Rivi, M.; Miller, L.

2018-05-01

This paper extends the method introduced in Rivi et al. (2016b) to measure galaxy ellipticities in the visibility domain for radio weak lensing surveys. In that paper, we focused on the development and testing of the method for the simple case of individual galaxies located at the phase centre, and proposed to extend it to the realistic case of many sources in the field of view by isolating visibilities of each source with a faceting technique. In this second paper, we present a detailed algorithm for source extraction in the visibility domain and show its effectiveness as a function of the source number density by running simulations of SKA1-MID observations in the band 950-1150 MHz and comparing original and measured values of galaxies' ellipticities. Shear measurements from a realistic population of 104 galaxies randomly located in a field of view of 1 \\deg ^2 (i.e. the source density expected for the current radio weak lensing survey proposal with SKA1) are also performed. At SNR ≥ 10, the multiplicative bias is only a factor 1.5 worse than what found when analysing individual sources, and is still comparable to the bias values reported for similar measurement methods at optical wavelengths. The additive bias is unchanged from the case of individual sources, but it is significantly larger than typically found in optical surveys. This bias depends on the shape of the uv coverage and we suggest that a uv-plane weighting scheme to produce a more isotropic shape could reduce and control additive bias.

Effect of Reverse Bias Stress on Leakage Currents and Breakdown Voltages of Solid Tantalum Capacitors

NASA Technical Reports Server (NTRS)

Teverovsky, Alexander A.

2011-01-01

The majority of solid tantalum capacitors are produced by high-temperature sintering of a fine tantalum powder around a tantalum wire followed by electrolytic anodization that forms a thin amorphous Ta2O5 dielectric layer and pyrolysis of manganese nitrite on the oxide to create a conductive manganese dioxide electrode. A contact to tantalum wire is used as anode terminal and to the manganese layer as a cathode terminal of the device. This process results in formation of an asymmetric Ta -- Ta2O5 -- MnO2 capacitor that has different characteristics at forward (positive bias applied to tantalum) and reverse (positive bias applied to manganese cathode) voltages. Reverse bias currents might be several orders of magnitude larger than forward leakage currents so I-V characteristics of tantalum capacitors resemble characteristics of semiconductor rectifiers. Asymmetric I-V characteristics of Ta -- anodic Ta2O5 systems have been observed at different top electrode materials including metals, electrolytes, conductive polymers, and manganese oxide thus indicating that this phenomenon is likely related to the specifics of the Ta -- Ta2O5 interface. There have been multiple attempts to explain rectifying characteristics of capacitors employing anodic tantalum pentoxide dielectrics. A brief review of works related to reverse bias (RB) behavior of tantalum capacitors shows that the mechanism of conduction in Ta -- Ta2O5 systems is still not clear and more testing and analysis is necessary to understand the processes involved. If tantalum capacitors behave just as rectifiers, then the assessment of the safe reverse bias operating conditions would be a relatively simple task. Unfortunately, these parts can degrade with time under reverse bias significantly, and this further complicates analysis of the I-V characteristics and establishing safe operating areas of the parts. On other hand, time dependence of reverse currents might provide additional information for investigation of the processes under reverse bias conditions. In practice, there were instances when, due to unforeseen events, the system operated at conditions when capacitors experience periodically a relatively small reverse bias for some time followed by normal, forward bias conditions. In such a case an assessment should be made on the degree to which these capacitors are degraded by application of low-voltage reverse bias, and whether this degradation can be reversed by normal operating conditions. In this study, reverse currents in different types of tantalum capacitors were monitored at different reverse voltages below 15%VR and temperatures in the range from room to 145 C for up to 150 hours to get better understanding of the degradation process and determine conditions favorable to the unstable mode of operation. The reversibility of RB degradation has been evaluated after operation of the capacitors at forward bias conditions. The effect of reverse bias stress (RBS) on reliability at normal operating conditions was evaluated using highly accelerated life testing at voltages of 1.5VR and 2 VR and by analysis of changes in distributions of breakdown voltages. Possible mechanisms of RB degradation are discussed.

Simulating Streamflow Using Bias-corrected Multiple Satellite Rainfall Products in the Tekeze Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Abitew, T. A.; Roy, T.; Serrat-Capdevila, A.; van Griensven, A.; Bauwens, W.; Valdes, J. B.

2016-12-01

The Tekeze Basin supports one of Africans largest Arch Dam located in northern Ethiopian has vital role in hydropower generation. However, little has been done on the hydrology of the basin due to limited in situ hydroclimatological data. Therefore, the main objective of this research is to simulate streamflow upstream of the Tekeze Dam using Soil and Water Assessment Tool (SWAT) forced by bias-corrected multiple satellite rainfall products (CMORPH, TMPA and PERSIANN-CCS). This talk will present the potential as well as skills of bias-corrected satellite rainfall products for streamflow prediction in in Tropical Africa. Additionally, the SWAT model results will also be compared with previous conceptual Hydrological models (HyMOD and HBV) from SERVIR Streamflow forecasting in African Basin project (http://www.swaat.arizona.edu/index.html).

The continuous end-state comfort effect: weighted integration of multiple biases.

PubMed

Herbort, Oliver; Butz, Martin V

2012-05-01

The grasp orientation when grasping an object is frequently aligned in anticipation of the intended rotation of the object (end-state comfort effect). We analyzed grasp orientation selection in a continuous task to determine the mechanisms underlying the end-state comfort effect. Participants had to grasp a box by a circular handle-which allowed for arbitrary grasp orientations-and then had to rotate the box by various angles. Experiments 1 and 2 revealed both that the rotation's direction considerably determined grasp orientations and that end-postures varied considerably. Experiments 3 and 4 further showed that visual stimuli and initial arm postures biased grasp orientations if the intended rotation could be easily achieved. The data show that end-state comfort but also other factors determine grasp orientation selection. A simple mechanism that integrates multiple weighted biases can account for the data.

Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.

[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.

Filtered cathodic arc deposition with ion-species-selective bias.

PubMed

Anders, André; Pasaja, Nitisak; Sansongsiri, Sakon

2007-06-01

A dual-cathode arc plasma source was combined with a computer-controlled bias amplifier to synchronize substrate bias with the pulsed production of plasma. In this way, bias can be applied in a material-selective way. The principle has been applied to the synthesis of metal-doped diamondlike carbon films, where the bias was applied and adjusted when the carbon plasma was condensing and the substrate was at ground when the metal was incorporated. In doing so, excessive sputtering by energetic metal ions can be avoided while the sp(3)sp(2) ratio can be adjusted. It is shown that the resistivity of the film can be tuned by this species-selective bias; Raman spectroscopy was used to confirm expected changes of the amorphous ta-C:Mo films. The species-selective bias principle could be extended to multiple material plasma sources and complex materials.

The Diagnostic Performance of Stool DNA Testing for Colorectal Cancer: A Systematic Review and Meta-Analysis.

PubMed

Zhai, Rong-Lin; Xu, Fei; Zhang, Pei; Zhang, Wan-Li; Wang, Hui; Wang, Ji-Liang; Cai, Kai-Lin; Long, Yue-Ping; Lu, Xiao-Ming; Tao, Kai-Xiong; Wang, Guo-Bin

2016-02-01

This meta-analysis was designed to evaluate the diagnostic performance of stool DNA testing for colorectal cancer (CRC) and compare the performance between single-gene and multiple-gene tests.MEDLINE, Cochrane, EMBASE databases were searched using keywords colorectal cancers, stool/fecal, sensitivity, specificity, DNA, and screening. Sensitivity analysis, quality assessments, and performance bias were performed for the included studies.Fifty-three studies were included in the analysis with a total sample size of 7524 patients. The studies were heterogeneous with regard to the genes being analyzed for fecal genetic biomarkers of CRC, as well as the laboratory methods being used for each assay. The sensitivity of the different assays ranged from 2% to 100% and the specificity ranged from 81% to 100%. The meta-analysis found that the pooled sensitivities for single- and multigene assays were 48.0% and 77.8%, respectively, while the pooled specificities were 97.0% and 92.7%. Receiver operator curves and diagnostic odds ratios showed no significant difference between both tests with regard to sensitivity or specificity.This meta-analysis revealed that using assays that evaluated multiple genes compared with single-gene assays did not increase the sensitivity or specificity of stool DNA testing in detecting CRC.

A Test for Cluster Bias: Detecting Violations of Measurement Invariance across Clusters in Multilevel Data

ERIC Educational Resources Information Center

Jak, Suzanne; Oort, Frans J.; Dolan, Conor V.

2013-01-01

We present a test for cluster bias, which can be used to detect violations of measurement invariance across clusters in 2-level data. We show how measurement invariance assumptions across clusters imply measurement invariance across levels in a 2-level factor model. Cluster bias is investigated by testing whether the within-level factor loadings…

Anxiety and the Processing of Emotionally Threatening Stimuli: Distinctive Patterns of Selective Attention among High- and Low-Test-Anxious Children.

ERIC Educational Resources Information Center

Vasey, Michael W.; And Others

1996-01-01

Tested for bias toward shifting attention toward threatening stimuli among high-anxious children and away from such stimuli among low-anxious children, ages 11-14. Results supported the predicted attentional bias toward threat cues among high-test-anxious children. Unexpectedly, the predicted attentional bias away from threat cues among…

An inverter-based capacitive trans-impedance amplifier readout with offset cancellation and temporal noise reduction for IR focal plane array

NASA Astrophysics Data System (ADS)

Chen, Hsin-Han; Hsieh, Chih-Cheng

2013-09-01

This paper presents a readout integrated circuit (ROIC) with inverter-based capacitive trans-impedance amplifier (CTIA) and pseudo-multiple sampling technique for infrared focal plane array (IRFPA). The proposed inverter-based CTIA with a coupling capacitor [1], executing auto-zeroing technique to cancel out the varied offset voltage from process variation, is used to substitute differential amplifier in conventional CTIA. The tunable detector bias is applied from a global external bias before exposure. This scheme not only retains stable detector bias voltage and signal injection efficiency, but also reduces the pixel area as well. Pseudo-multiple sampling technique [2] is adopted to reduce the temporal noise of readout circuit. The noise reduction performance is comparable to the conventional multiple sampling operation without need of longer readout time proportional to the number of samples. A CMOS image sensor chip with 55×65 pixel array has been fabricated in 0.18um CMOS technology. It achieves a 12um×12um pixel size, a frame rate of 72 fps, a power-per-pixel of 0.66uW/pixel, and a readout temporal noise of 1.06mVrms (16 times of pseudo-multiple sampling), respectively.

Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior.

PubMed

Poore, Joshua C; Forlines, Clifton L; Miller, Sarah M; Regan, John R; Irvine, John M

2014-12-01

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures-personality, cognitive style, motivated cognition-predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated "top-down" cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains.

Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior

PubMed Central

Forlines, Clifton L.; Miller, Sarah M.; Regan, John R.; Irvine, John M.

2014-01-01

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures—personality, cognitive style, motivated cognition—predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated “top-down” cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains. PMID:25983670

Integrating data types to enhance shoreline change assessments

NASA Astrophysics Data System (ADS)

Long, J.; Henderson, R.; Plant, N. G.; Nelson, P. R.

2016-12-01

Shorelines represent the variable boundary between terrestrial and marine environments. Assessment of geographic and temporal variability in shoreline position and related variability in shoreline change rates are an important part of studies and applications related to impacts from sea-level rise and storms. The results from these assessments are used to quantify future ecosystem services and coastal resilience and guide selection of appropriate coastal restoration and protection designs. But existing assessments typically fail to incorporate all available shoreline observations because they are derived from multiple data types and have different or unknown biases and uncertainties. Shoreline-change research and assessments often focus on either the long-term trajectory using sparse data over multiple decades or shorter-term evolution using data collected more frequently but over a shorter period of time. The combination of data collected with significantly different temporal resolution is not often considered. Also, differences in the definition of the shoreline metric itself can occur, whether using a single or multiple data source(s), due to variation the signal being detected in the data (e.g. instantaneous land/water interface, swash zone, wrack line, or topographic contours). Previous studies have not explored whether more robust shoreline change assessments are possible if all available data are utilized and all uncertainties are considered. In this study, we test the hypothesis that incorporating all available shoreline data will lead to both improved historical assessments and enhance the predictive capability of shoreline-change forecasts. Using over 250 observations of shoreline position at Dauphin Island, Alabama over the last century, we compare shoreline-change rates derived from individual data sources (airborne lidar, satellite, aerial photographs) with an assessment using the combination of all available data. Biases or simple uncertainties in the shoreline metric from different data types and varying temporal/spatial resolution of the data are examined. As part of this test, we also demonstrate application of data assimilation techniques to predict shoreline position by accurately including the uncertainty in each type of data.

Selective attention and drug related attention bias in methadone maintenance patients.

PubMed

Nejati, Majid; Nejati, Vahid; Mohammadi, Mohammad Reza

2011-01-01

One of the main problems of the drug abusers is drug related attention bias, which causes craving, and as a result drive the drug abusers to take narcotics. Methadone is used as a maintenance treatment for drug abusers. The purpose of this study is evaluation of the effect of Methadone maintenance therapy (MMT) on selective attention and drug related attention bias. This study investigated drug cue-related attention bias and selective attention in 16 methadone-maintained patients before and 45 days after methadone therapy period. Stroop color-word test and addiction Stroop test were used as measurement methods. Results show less reaction time and higher accuracy in Color-Word Stroop Test after MMT and less delay for addict related word in addiction Stroop test. It is concluded that methadone can improve selective attention capability and reduce drug related attention bias.

Comparison of two control groups for estimation of oral cholera vaccine effectiveness using a case-control study design.

PubMed

Franke, Molly F; Jerome, J Gregory; Matias, Wilfredo R; Ternier, Ralph; Hilaire, Isabelle J; Harris, Jason B; Ivers, Louise C

2017-10-13

Case-control studies to quantify oral cholera vaccine effectiveness (VE) often rely on neighbors without diarrhea as community controls. Test-negative controls can be easily recruited and may minimize bias due to differential health-seeking behavior and recall. We compared VE estimates derived from community and test-negative controls and conducted bias-indicator analyses to assess potential bias with community controls. From October 2012 through November 2016, patients with acute watery diarrhea were recruited from cholera treatment centers in rural Haiti. Cholera cases had a positive stool culture. Non-cholera diarrhea cases (test-negative controls and non-cholera diarrhea cases for bias-indicator analyses) had a negative culture and rapid test. Up to four community controls were matched to diarrhea cases by age group, time, and neighborhood. Primary analyses included 181 cholera cases, 157 non-cholera diarrhea cases, 716 VE community controls and 625 bias-indicator community controls. VE for self-reported vaccination with two doses was consistent across the two control groups, with statistically significant VE estimates ranging from 72 to 74%. Sensitivity analyses revealed similar, though somewhat attenuated estimates for self-reported two dose VE. Bias-indicator estimates were consistently less than one, with VE estimates ranging from 19 to 43%, some of which were statistically significant. OCV estimates from case-control analyses using community and test-negative controls were similar. While bias-indicator analyses suggested possible over-estimation of VE estimates using community controls, test-negative analyses suggested this bias, if present, was minimal. Test-negative controls can be a valid low-cost and time-efficient alternative to community controls for OCV effectiveness estimation and may be especially relevant in emergency situations. Copyright © 2017. Published by Elsevier Ltd.

Development of an Accelerated Test Design for Predicting the Service Life of the Solar Array at Mead, Nebraska

NASA Technical Reports Server (NTRS)

Gaines, G. B.; Thomas, R. E.; Noel, G. T.; Shilliday, T. S.; Wood, V. E.; Carmichael, D. C.

1979-01-01

An accelerated life test is described which was developed to predict the life of the 25 kW photovoltaic array installed near Mead, Nebraska. A quantitative model for accelerating testing using multiple environmental stresses was used to develop the test design. The model accounts for the effects of thermal stress by a relation of the Arrhenius form. This relation was then corrected for the effects of nonthermal environmental stresses, such as relative humidity, atmospheric pollutants, and ultraviolet radiation. The correction factors for the nonthermal stresses included temperature-dependent exponents to account for the effects of interactions between thermal and nonthermal stresses on the rate of degradation of power output. The test conditions, measurements, and data analyses for the accelerated tests are presented. Constant-temperature, cyclic-temperature, and UV types of tests are specified, incorporating selected levels of relative humidity and chemical contamination and an imposed forward-bias current and static electric field.

Can Children with ADHD Be Motivated to Reduce Bias in Self-Reports of Competence?

ERIC Educational Resources Information Center

Hoza, Betsy; Vaughn, Aaron; Waschbusch, Daniel A.; Murray-Close, Dianna; McCabe, George

2012-01-01

Objective: Our purpose in the current study was to examine whether children with attention-deficit/hyperactivity disorder (ADHD) and comparison children, if adequately motivated, are able to purposefully match their teachers' ratings of competence in multiple domains and whether any reductions in self-perceptual bias normalize self-views in…

Reducing Bias Due to Systematic Attrition in Longitudinal Studies: The Benefits of Multiple Imputation

ERIC Educational Resources Information Center

Asendorpf, Jens B.; van de Schoot, Rens; Denissen, Jaap J. A.; Hutteman, Roos

2014-01-01

Most longitudinal studies are plagued by drop-out related to variables at earlier assessments (systematic attrition). Although systematic attrition is often analysed in longitudinal studies, surprisingly few researchers attempt to reduce biases due to systematic attrition, even though this is possible and nowadays technically easy. This is…

Illustrating, Quantifying, and Correcting for Bias in Post-hoc Analysis of Gene-Based Rare Variant Tests of Association

PubMed Central

Grinde, Kelsey E.; Arbet, Jaron; Green, Alden; O'Connell, Michael; Valcarcel, Alessandra; Westra, Jason; Tintle, Nathan

2017-01-01

To date, gene-based rare variant testing approaches have focused on aggregating information across sets of variants to maximize statistical power in identifying genes showing significant association with diseases. Beyond identifying genes that are associated with diseases, the identification of causal variant(s) in those genes and estimation of their effect is crucial for planning replication studies and characterizing the genetic architecture of the locus. However, we illustrate that straightforward single-marker association statistics can suffer from substantial bias introduced by conditioning on gene-based test significance, due to the phenomenon often referred to as “winner's curse.” We illustrate the ramifications of this bias on variant effect size estimation and variant prioritization/ranking approaches, outline parameters of genetic architecture that affect this bias, and propose a bootstrap resampling method to correct for this bias. We find that our correction method significantly reduces the bias due to winner's curse (average two-fold decrease in bias, p < 2.2 × 10−6) and, consequently, substantially improves mean squared error and variant prioritization/ranking. The method is particularly helpful in adjustment for winner's curse effects when the initial gene-based test has low power and for relatively more common, non-causal variants. Adjustment for winner's curse is recommended for all post-hoc estimation and ranking of variants after a gene-based test. Further work is necessary to continue seeking ways to reduce bias and improve inference in post-hoc analysis of gene-based tests under a wide variety of genetic architectures. PMID:28959274

Racial Bias and Predictive Validity in Testing for Selection.

DTIC Science & Technology

1983-07-01

the inequa - lity rR (P.C) *0 (2) must define test bias. This definition of test bias conforms to the requirements of the Civil Rights Act of 1964 as...of Educational Measurement, 1976, 13, 43-52. Einhorn, H. J., & Bass, A. R. Methodological considerations relevant to discrimination in employment ...34unbiased" selec- tion model: A question of utilities. Journal of Applied Psychology, 1975, 60, 345-351. Guion, R. M. Employment tests and discriminatory

Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics.

PubMed

Galvelis, Raimondas; Sugita, Yuji

2017-06-13

The free energy calculations of complex chemical and biological systems with molecular dynamics (MD) are inefficient due to multiple local minima separated by high-energy barriers. The minima can be escaped using an enhanced sampling method such as metadynamics, which apply bias (i.e., importance sampling) along a set of collective variables (CV), but the maximum number of CVs (or dimensions) is severely limited. We propose a high-dimensional bias potential method (NN2B) based on two machine learning algorithms: the nearest neighbor density estimator (NNDE) and the artificial neural network (ANN) for the bias potential approximation. The bias potential is constructed iteratively from short biased MD simulations accounting for correlation among CVs. Our method is capable of achieving ergodic sampling and calculating free energy of polypeptides with up to 8-dimensional bias potential.

Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies.

PubMed

de Groot, Joris A H; Dendukuri, Nandini; Janssen, Kristel J M; Reitsma, Johannes B; Brophy, James; Joseph, Lawrence; Bossuyt, Patrick M M; Moons, Karel G M

2012-04-15

A key requirement in the design of diagnostic accuracy studies is that all study participants receive both the test under evaluation and the reference standard test. For a variety of practical and ethical reasons, sometimes only a proportion of patients receive the reference standard, which can bias the accuracy estimates. Numerous methods have been described for correcting this partial verification bias or workup bias in individual studies. In this article, the authors describe a Bayesian method for obtaining adjusted results from a diagnostic meta-analysis when partial verification or workup bias is present in a subset of the primary studies. The method corrects for verification bias without having to exclude primary studies with verification bias, thus preserving the main advantages of a meta-analysis: increased precision and better generalizability. The results of this method are compared with the existing methods for dealing with verification bias in diagnostic meta-analyses. For illustration, the authors use empirical data from a systematic review of studies of the accuracy of the immunohistochemistry test for diagnosis of human epidermal growth factor receptor 2 status in breast cancer patients.

Multiple Signal Classification for Determining Direction of Arrival of Frequency Hopping Spread Spectrum Signals

DTIC Science & Technology

2014-03-27

42 4.2.3 Number of Hops Hs . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.2.4 Number of Sensors M... 45 4.5 Standard deviation vs. Ns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.6 Bias...laboratory MTM multiple taper method MUSIC multiple signal classification MVDR minimum variance distortionless reposnse PSK phase shift keying QAM

Establishment of a PID Pass/Fail Test for Crystalline Silicon Modules by Examining Field Performance for Five Years: Preprint

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

Hacke, Peter L

In an experiment with five module designs and multiple replicas, it is found that crystalline silicon cell modules that can pass a criterion of less than 5 percent power degradation in stress test conditions of 60 degrees Celsius, 85 percent relative humidity (RH), 96 h, and nameplate-rated system voltage bias show no power degradation by potential induced degradation in the range of 4-6 years duration in the Florida, USA environment. This data suggests that this chamber stress level is useful as a pass/fail criterion for PID, and will help ensure against degradation by system voltage stress in Florida, or lessmore » stressful climates, for at least 5 years.« less

Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions

PubMed Central

Marinelli, Fabrizio; Faraldo-Gómez, José D.

2015-01-01

We introduce an enhanced-sampling method for molecular dynamics (MD) simulations referred to as ensemble-biased metadynamics (EBMetaD). The method biases a conventional MD simulation to sample a molecular ensemble that is consistent with one or more probability distributions known a priori, e.g., experimental intramolecular distance distributions obtained by double electron-electron resonance or other spectroscopic techniques. To this end, EBMetaD adds an adaptive biasing potential throughout the simulation that discourages sampling of configurations inconsistent with the target probability distributions. The bias introduced is the minimum necessary to fulfill the target distributions, i.e., EBMetaD satisfies the maximum-entropy principle. Unlike other methods, EBMetaD does not require multiple simulation replicas or the introduction of Lagrange multipliers, and is therefore computationally efficient and straightforward in practice. We demonstrate the performance and accuracy of the method for a model system as well as for spin-labeled T4 lysozyme in explicit water, and show how EBMetaD reproduces three double electron-electron resonance distance distributions concurrently within a few tens of nanoseconds of simulation time. EBMetaD is integrated in the open-source PLUMED plug-in (www.plumed-code.org), and can be therefore readily used with multiple MD engines. PMID:26083917

The Role of Response Bias in Perceptual Learning

PubMed Central

2015-01-01

Sensory judgments improve with practice. Such perceptual learning is often thought to reflect an increase in perceptual sensitivity. However, it may also represent a decrease in response bias, with unpracticed observers acting in part on a priori hunches rather than sensory evidence. To examine whether this is the case, 55 observers practiced making a basic auditory judgment (yes/no amplitude-modulation detection or forced-choice frequency/amplitude discrimination) over multiple days. With all tasks, bias was present initially, but decreased with practice. Notably, this was the case even on supposedly “bias-free,” 2-alternative forced-choice, tasks. In those tasks, observers did not favor the same response throughout (stationary bias), but did favor whichever response had been correct on previous trials (nonstationary bias). Means of correcting for bias are described. When applied, these showed that at least 13% of perceptual learning on a forced-choice task was due to reduction in bias. In other situations, changes in bias were shown to obscure the true extent of learning, with changes in estimated sensitivity increasing once bias was corrected for. The possible causes of bias and the implications for our understanding of perceptual learning are discussed. PMID:25867609

Gain properties of doped GaAs/AlGaAs multiple quantum well avalanche photodiode structures

NASA Technical Reports Server (NTRS)

Menkara, H. M.; Wagner, B. K.; Summers, C. J.

1995-01-01

A comprehensive characterization has been made of the static and dynamical response of conventional and multiple quantum well (MQW) avalanche photodiodes (APDs). Comparison of the gain characteristics at low voltages between the MQW and conventional APDs show a direct experimental confirmation of a structure-induced carrier multiplication due to interband impact ionization. Similar studies of the bias dependence of the excess noise characteristics show that the low-voltage gain is primarily due to electron ionization in the MQW-APDS, and to both electron and hole ionization in the conventional APDS. For the doped MQW APDS, the average gain per stage was calculated by comparing gain data with carrier profile measurements, and was found to vary from 1.03 at low bias to 1.09 near avalanche breakdown.

Operation and biasing for single device equivalent to CMOS

DOEpatents

Welch, James D.

2001-01-01

Disclosed are semiconductor devices including at least one junction which is rectifying whether the semiconductor is caused to be N or P-type, by the presence of field induced carriers. In particular, inverting and non-inverting gate voltage channel induced semiconductor single devices with operating characteristics similar to conventional multiple device CMOS systems, which can be operated as modulators, are disclosed as are a non-latching SCR and an approach to blocking parasitic currents. Operation of the gate voltage channel induced semiconductor single devices with operating characteristics similar to multiple device CMOS systems under typical bias schemes is described, and simple demonstrative five mask fabrication procedures for the inverting and non-inverting gate voltage channel induced semiconductor single devices with operating characteristics similar to multiple device CMOS systems are also presented.

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

Optimize of shrink process with X-Y CD bias on hole pattern

NASA Astrophysics Data System (ADS)

Koike, Kyohei; Hara, Arisa; Natori, Sakurako; Yamauchi, Shohei; Yamato, Masatoshi; Oyama, Kenichi; Yaegashi, Hidetami

2017-03-01

Gridded design rules[1] is major process in configuring logic circuit used 193-immersion lithography. In the scaling of grid patterning, we can make 10nm order line and space pattern by using multiple patterning techniques such as self-aligned multiple patterning (SAMP) and litho-etch- litho-etch (LELE)[2][3][4] . On the other hand, Line cut process has some error parameters such as pattern defect, placement error, roughness and X-Y CD bias with the decreasing scale. We tried to cure hole pattern roughness to use additional process such as Line smoothing[5] . Each smoothing process showed different effect. As the result, CDx shrink amount is smaller than CDy without one additional process. In this paper, we will report the pattern controllability comparison of EUV and 193-immersion. And we will discuss optimum method about CD bias on hole pattern.

Displaceable Spur Gear Torque Controlled Driver and Method

NASA Technical Reports Server (NTRS)

Cook, Joseph S., Jr. (Inventor)

1996-01-01

Methods and apparatus are provided for a torque driver including a laterally displaceable gear support member to carry an output spur gear. A biasing assembly biases the output spur gear into engagement with a pinion to which is applied an input torque greater than a desired output torque limit for a threaded fastener such as a nut or screw. A coiled output linkage connects the output spur gear with a fastener adaptor which may be a socket for a nut. A gear tooth profile provides a separation force that overcomes the bias to limit torque at the desired torque limit. Multiple fasteners may be rotated simultaneously to a desired torque limit if additional output spur gears are provided. A gauged selector mechanism is provided to laterally displace multiple driven members for fasteners arranged in differing configurations. The torque limit is selectably adjustable and may be different for fasteners within the same fastener configuration.

Displaceable spur gear torque controlled driver and method

NASA Technical Reports Server (NTRS)

Cook, Joseph S., Jr. (Inventor)

1994-01-01

Methods and apparatus are provided for a torque driver including a laterally displaceable gear support member to carry an output spur gear. A biasing assembly biases the output spur gear into engagement with a pinion to which is applied an input torque greater than a desired output torque limit for a threaded fastener such as a nut or screw. A coiled output linkage connects the output spur gear with a fastener adaptor which may be a socket for a nut. A gear tooth profile provides a separation force that overcomes the bias to limit torque at the desired torque limit. Multiple fasteners may be rotated simultaneously to a desired torque limit if additional output spur gears are provided. A gauged selector mechanism is provided to laterally displace multiple driver members for fasteners arranged in differing configurations. The torque limit is selectably adjustable and may be different for fasteners within the same fastener configuration.

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

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

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

DOE PAGES

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

2017-06-13

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

Probabilistic Multiple-Bias Modeling Applied to the Canadian Data From the Interphone Study of Mobile Phone Use and Risk of Glioma, Meningioma, Acoustic Neuroma, and Parotid Gland Tumors.

PubMed

Momoli, F; Siemiatycki, J; McBride, M L; Parent, M-É; Richardson, L; Bedard, D; Platt, R; Vrijheid, M; Cardis, E; Krewski, D

2017-10-01

We undertook a re-analysis of the Canadian data from the 13-country case-control Interphone Study (2001-2004), in which researchers evaluated the associations of mobile phone use with the risks of brain, acoustic neuroma, and parotid gland tumors. In the main publication of the multinational Interphone Study, investigators concluded that biases and errors prevented a causal interpretation. We applied a probabilistic multiple-bias model to address possible biases simultaneously, using validation data from billing records and nonparticipant questionnaires as information on recall error and selective participation. In our modeling, we sought to adjust for these sources of uncertainty and to facilitate interpretation. For glioma, when comparing those in the highest quartile of use (>558 lifetime hours) to those who were not regular users, the odds ratio was 2.0 (95% confidence interval: 1.2, 3.4). After adjustment for selection and recall biases, the odds ratio was 2.2 (95% limits: 1.3, 4.1). There was little evidence of an increase in the risk of meningioma, acoustic neuroma, or parotid gland tumors in relation to mobile phone use. Adjustments for selection and recall biases did not materially affect interpretation in our results from Canadian data. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.

PubMed

Drakesmith, M; Caeyenberghs, K; Dutt, A; Lewis, G; David, A S; Jones, D K

2015-09-01

Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced by thresholding, making statistical comparisons of network metrics difficult. However, by testing for effects across multiple thresholds using MTPC, true group differences can be robustly identified. Copyright © 2015. Published by Elsevier Inc.

Initial Implementation and Testing of a Tightly-Coupled IMU/Pseudolite System

DTIC Science & Technology

2015-03-26

accelerometer and 26 gyro[30]. f bins = f bias + abias + w f INS (3.2) ωbibins = ωbias + ω b ib + w ω INS (3.3) abias = ȧbias + w a bias (3.4) where f...bins: forces on the force measurements in the INS f bias: bias in the forces abias : accelleration bias wfINS: white guassian noise acting upon the

Comparison of Different Shrinkage Formulas in Estimating Population Multiple Correlation Coefficients.

ERIC Educational Resources Information Center

Carter, David S.

1979-01-01

There are a variety of formulas for reducing the positive bias which occurs in estimating R squared in multiple regression or correlation equations. Five different formulas are evaluated in a Monte Carlo study, and recommendations are made. (JKS)

Social Desirability Bias Against Admitting Anger: Bias in the Test-Taker or Bias in the Test?

PubMed

Fernandez, Ephrem; Woldgabreal, Yilma; Guharajan, Deepan; Day, Andrew; Kiageri, Vasiliki; Ramtahal, Nirvana

2018-05-09

The veracity of self-report is often questioned, especially in anger, which is particularly susceptible to social desirability bias (SDB). However, could tests of SDB be themselves susceptible to bias? This study aimed to replicate the inverse correlation between a common test of SDB and a test of anger, to deconstruct this relationship according to anger-related versus non-anger-related items, and to reevaluate factor structure and reliability of the SDB test. More than 200 students were administered the Marlowe-Crowne Social Desirability Scale Short Version [M-C1(10)] and the Anger Parameters Scale (APS). Results confirmed that anger and SDB scores were significantly and inversely correlated. This intercorrelation became nonsignificant when the 4 anger-related items were omitted from the M-C1(10). Confirmatory factor analyses showed excellent fit for a model comprising anger items of the M-C1(10) but not for models of the entire instrument or nonanger items. The first model also attained high internal consistency. Thus, the significant negative correlation between anger and SDB is attributable to 4 M-C1(10) anger items, for which low ratings are automatically scored as high SDB; this stems from a tenuous assumption that low anger reports are invariably biased. The SDB test risks false positives of faking good and should be used with caution.

Comparison and testing of extended Kalman filters for attitude estimation of the Earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.; Rokni, Mohammad

1990-01-01

The testing and comparison of two Extended Kalman Filters (EKFs) developed for the Earth Radiation Budget Satellite (ERBS) is described. One EKF updates the attitude quaternion using a four component additive error quaternion. This technique is compared to that of a second EKF, which uses a multiplicative error quaternion. A brief development of the multiplicative algorithm is included. The mathematical development of the additive EKF was presented in the 1989 Flight Mechanics/Estimation Theory Symposium along with some preliminary testing results using real spacecraft data. A summary of the additive EKF algorithm is included. The convergence properties, singularity problems, and normalization techniques of the two filters are addressed. Both filters are also compared to those from the ERBS operational ground support software, which uses a batch differential correction algorithm to estimate attitude and gyro biases. Sensitivity studies are performed on the estimation of sensor calibration states. The potential application of the EKF for real time and non-real time ground attitude determination and sensor calibration for future missions such as the Gamma Ray Observatory (GRO) and the Small Explorer Mission (SMEX) is also presented.

Understanding Uncertainties and Biases in Jet Quenching in High-Energy Nucleus-Nucleus Collisions

NASA Astrophysics Data System (ADS)

Heinz, Matthias

2017-09-01

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momenta are reduced by the same fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model from which to sample particle types and a 3-dimensional Boltzmann distribution from which to sample particle momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested first on pure jet events and later on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

An Exploration Based Cognitive Bias Test for Mice: Effects of Handling Method and Stereotypic Behaviour.

PubMed

Novak, Janja; Bailoo, Jeremy D; Melotti, Luca; Rommen, Jonas; Würbel, Hanno

2015-01-01

Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training-a major confound in current cognitive bias paradigms.

An Exploration Based Cognitive Bias Test for Mice: Effects of Handling Method and Stereotypic Behaviour

PubMed Central

Novak, Janja; Bailoo, Jeremy D.; Melotti, Luca; Rommen, Jonas; Würbel, Hanno

2015-01-01

Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training—a major confound in current cognitive bias paradigms. PMID:26154309

Incidental biasing of attention from visual long-term memory.

PubMed

Fan, Judith E; Turk-Browne, Nicholas B

2016-06-01

Holding recently experienced information in mind can help us achieve our current goals. However, such immediate and direct forms of guidance from working memory are less helpful over extended delays or when other related information in long-term memory is useful for reaching these goals. Here we show that information that was encoded in the past but is no longer present or relevant to the task also guides attention. We examined this by associating multiple unique features with novel shapes in visual long-term memory (VLTM), and subsequently testing how memories for these objects biased the deployment of attention. In Experiment 1, VLTM for associated features guided visual search for the shapes, even when these features had never been task-relevant. In Experiment 2, associated features captured attention when presented in isolation during a secondary task that was completely unrelated to the shapes. These findings suggest that long-term memory enables a durable and automatic type of memory-based attentional control. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Multigenerational response to artificial selection for biased clutch sex ratios in Tigriopus californicus populations.

PubMed

Alexander, H J; Richardson, J M L; Anholt, B R

2014-09-01

Polygenic sex determination (PSD) is relatively rare and theoretically evolutionary unstable, yet has been reported across a range of taxa. Evidence for multilocus PSD is provided by (i) large between-family variance in sex ratio, (ii) paternal and maternal effects on family sex ratio and (iii) response to selection for family sex ratio. This study tests the polygenic hypothesis of sex determination in the harpacticoid copepod Tigriopus californicus using the criterion of response to selection. We report the first multigenerational quantitative evidence that clutch sex ratio responds to artificial selection in both directions (selection for male- and female-biased families) and in multiple populations of T. californicus. In the five of six lines that showed a response to selection, realized heritability estimated by multigenerational analysis ranged from 0.24 to 0.58. Divergence of clutch sex ratio between selection lines is rapid, with response to selection detectable within the first four generations of selection. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis-driven selection rules.

PubMed

Robertson, David S; Prevost, A Toby; Bowden, Jack

2016-09-30

Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Semantic Asymmetries Are Modulated by Phonological Asymmetries: Evidence from the Disambiguation of Homophonic versus Heterophonic Homographs

ERIC Educational Resources Information Center

Peleg, Orna; Eviatar, Zohar

2009-01-01

The present study investigated cerebral asymmetries in accessing multiple meanings of two types of homographs: homophonic homographs (e.g., "bank") and heterophonic homographs (e.g., "tear"). Participants read homographs preceded by either a biasing or a non-biasing sentential context and performed a lexical decision on lateralized targets…

Misconceptions and Biases in German Students' Perception of Multiple Energy Sources: Implications for Science Education

ERIC Educational Resources Information Center

Lee, Roh Pin

2016-01-01

Misconceptions and biases in energy perception could influence people's support for developments integral to the success of restructuring a nation's energy system. Science education, in equipping young adults with the cognitive skills and knowledge necessary to navigate in the confusing energy environment, could play a key role in paving the way…

Patient perspectives on racial and ethnic implicit bias in clinical encounters: Implications for curriculum development.

PubMed

Gonzalez, Cristina M; Deno, Maria L; Kintzer, Emily; Marantz, Paul R; Lypson, Monica L; McKee, M Diane

2018-05-20

Patients describe feelings of bias and prejudice in clinical encounters; however, their perspectives on restoring the encounter once bias is perceived are not known. Implicit bias has emerged as a target for curricular interventions. In order to inform the design of novel patient-centered curricular interventions, this study explores patients' perceptions of bias, and suggestions for restoring relationships if bias is perceived. The authors conducted bilingual focus groups with purposive sampling of self-identified Black and Latino community members in the US. Data were analyzed using grounded theory. Ten focus groups (in English (6) and Spanish (4)) with N = 74 participants occurred. Data analysis revealed multiple influences patients' perception of bias in their physician encounters. The theory emerging from the analysis suggests if bias is perceived, the outcome of the encounter can still be positive. A positive or negative outcome depends on whether the physician acknowledges this perceived bias or not, and his or her subsequent actions. Participant lived experience and physician behaviors influence perceptions of bias, however clinical relationships can be restored following perceived bias. Providers might benefit from skill development in the recognition and acknowledgement of perceived bias in order to restore patient-provider relationships. Copyright © 2018 Elsevier B.V. All rights reserved.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, A. T.; Cannon, A. J.

2015-06-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis datasets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical datasets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

NASA Astrophysics Data System (ADS)

Werner, Arelia T.; Cannon, Alex J.

2016-04-01

Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis data sets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical data sets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.

Cognitive Biases in the Interpretation of Autonomic Arousal: A Test of the Construal Bias Hypothesis

ERIC Educational Resources Information Center

Ciani, Keith D.; Easter, Matthew A.; Summers, Jessica J.; Posada, Maria L.

2009-01-01

According to Bandura's construal bias hypothesis, derived from social cognitive theory, persons with the same heightened state of autonomic arousal may experience either pleasant or deleterious emotions depending on the strength of perceived self-efficacy. The current study tested this hypothesis by proposing that college students' preexisting…

The source of the truth bias: Heuristic processing?

PubMed

Street, Chris N H; Masip, Jaume

2015-06-01

People believe others are telling the truth more often than they actually are; this is called the truth bias. Surprisingly, when a speaker is judged at multiple points across their statement the truth bias declines. Previous claims argue this is evidence of a shift from (biased) heuristic processing to (reasoned) analytical processing. In four experiments we contrast the heuristic-analytic model (HAM) with alternative accounts. In Experiment 1, the decrease in truth responding was not the result of speakers appearing more deceptive, but was instead attributable to the rater's processing style. Yet contrary to HAMs, across three experiments we found the decline in bias was not related to the amount of processing time available (Experiments 1-3) or the communication channel (Experiment 2). In Experiment 4 we found support for a new account: that the bias reflects whether raters perceive the statement to be internally consistent. © 2015 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Addressing criticisms of existing predictive bias research: cognitive ability test scores still overpredict African Americans' job performance.

PubMed

Berry, Christopher M; Zhao, Peng

2015-01-01

Predictive bias studies have generally suggested that cognitive ability test scores overpredict job performance of African Americans, meaning these tests are not predictively biased against African Americans. However, at least 2 issues call into question existing over-/underprediction evidence: (a) a bias identified by Aguinis, Culpepper, and Pierce (2010) in the intercept test typically used to assess over-/underprediction and (b) a focus on the level of observed validity instead of operational validity. The present study developed and utilized a method of assessing over-/underprediction that draws on the math of subgroup regression intercept differences, does not rely on the biased intercept test, allows for analysis at the level of operational validity, and can use meta-analytic estimates as input values. Therefore, existing meta-analytic estimates of key parameters, corrected for relevant statistical artifacts, were used to determine whether African American job performance remains overpredicted at the level of operational validity. African American job performance was typically overpredicted by cognitive ability tests across levels of job complexity and across conditions wherein African American and White regression slopes did and did not differ. Because the present study does not rely on the biased intercept test and because appropriate statistical artifact corrections were carried out, the present study's results are not affected by the 2 issues mentioned above. The present study represents strong evidence that cognitive ability tests generally overpredict job performance of African Americans. (c) 2015 APA, all rights reserved.

BIAS: Bioinformatics Integrated Application Software.

PubMed

Finak, G; Godin, N; Hallett, M; Pepin, F; Rajabi, Z; Srivastava, V; Tang, Z

2005-04-15

We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system and supports standards and data-exchange protocols common to Bioinformatics. BIAS is an OpenSource project and is freely available to all interested users at http://www.mcb.mcgill.ca/~bias/. This website also contains a paper containing a more detailed description of BIAS and a sample implementation of a Bayesian network approach for the simultaneous prediction of gene regulation events and of mRNA expression from combinations of gene regulation events. hallett@mcb.mcgill.ca.

Multiple, correlated covariates associated with differential item functioning (DIF): Accounting for language DIF when education levels differ across languages.

PubMed

Gibbons, Laura E; Crane, Paul K; Mehta, Kala M; Pedraza, Otto; Tang, Yuxiao; Manly, Jennifer J; Narasimhalu, Kaavya; Teresi, Jeanne; Jones, Richard N; Mungas, Dan

2011-04-28

Differential item functioning (DIF) occurs when a test item has different statistical properties in subgroups, controlling for the underlying ability measured by the test. DIF assessment is necessary when evaluating measurement bias in tests used across different language groups. However, other factors such as educational attainment can differ across language groups, and DIF due to these other factors may also exist. How to conduct DIF analyses in the presence of multiple, correlated factors remains largely unexplored. This study assessed DIF related to Spanish versus English language in a 44-item object naming test. Data come from a community-based sample of 1,755 Spanish- and English-speaking older adults. We compared simultaneous accounting, a new strategy for handling differences in educational attainment across language groups, with existing methods. Compared to other methods, simultaneously accounting for language- and education-related DIF yielded salient differences in some object naming scores, particularly for Spanish speakers with at least 9 years of education. Accounting for factors that vary across language groups can be important when assessing language DIF. The use of simultaneous accounting will be relevant to other cross-cultural studies in cognition and in other fields, including health-related quality of life.

Multiple, correlated covariates associated with differential item functioning (DIF): Accounting for language DIF when education levels differ across languages

PubMed Central

Gibbons, Laura E.; Crane, Paul K.; Mehta, Kala M.; Pedraza, Otto; Tang, Yuxiao; Manly, Jennifer J.; Narasimhalu, Kaavya; Teresi, Jeanne; Jones, Richard N.; Mungas, Dan

2012-01-01

Differential item functioning (DIF) occurs when a test item has different statistical properties in subgroups, controlling for the underlying ability measured by the test. DIF assessment is necessary when evaluating measurement bias in tests used across different language groups. However, other factors such as educational attainment can differ across language groups, and DIF due to these other factors may also exist. How to conduct DIF analyses in the presence of multiple, correlated factors remains largely unexplored. This study assessed DIF related to Spanish versus English language in a 44-item object naming test. Data come from a community-based sample of 1,755 Spanish- and English-speaking older adults. We compared simultaneous accounting, a new strategy for handling differences in educational attainment across language groups, with existing methods. Compared to other methods, simultaneously accounting for language- and education-related DIF yielded salient differences in some object naming scores, particularly for Spanish speakers with at least 9 years of education. Accounting for factors that vary across language groups can be important when assessing language DIF. The use of simultaneous accounting will be relevant to other cross-cultural studies in cognition and in other fields, including health-related quality of life. PMID:22900138

Residential road traffic noise as a risk factor for hypertension in adults: Systematic review and meta-analysis of analytic studies published in the period 2011-2017.

PubMed

Dzhambov, Angel M; Dimitrova, Donka D

2018-05-07

Multiple cross-sectional studies indicated an association between hypertension and road traffic noise and they were recently synthetized in a WHO systematic evidence review. However, recent years have seen a growing body of high-quality, large-scale research, which is missing from the WHO review. Therefore, we aimed to close that gap by conducting an updated systematic review and meta-analysis on the exposure-response relationship between residential road traffic noise and the risk of hypertension in adults. Studies were identified by searching MEDLINE, EMBASE, the Internet, conference proceedings, reference lists, and expert archives in English, Russian, and Spanish through August 5, 2017. The risk of bias for each extracted estimate and the overall quality of evidence were evaluated using a list of predefined safeguards against bias related to different study characteristics and the Grading of Recommendations Assessment, Development and Evaluation system, respectively. The inverse variance heterogeneity (IVhet) model was used for meta-analysis. The possibility of publication bias was evaluated by funnel and Doi plots, and asymmetry in these was tested with Egger's test and the Luis Furuya-Kanamori index, respectively. Sensitivity analyses included leave-one-out meta-analysis, subgroup meta-analysis with meta-regressions, and non-linear exposure-response meta-analysis. Based on seven cohort and two case-control studies (n = 5 514 555; 14 estimates; L den range ≈ 25-90 dB(A)), we found "low" evidence of RR per 10 dB(A)  = 1.018 (95% CI: 0.984, 1.053), moderate heterogeneity (I 2  = 46%), and no publication bias. In the subgroup of cohort studies, we found "moderate" evidence of RR per 10 dB(A)  = 1.018 (95% CI: 0.987, 1.049), I 2  = 31%, and no publication bias. In conclusion, residential road traffic noise was associated with higher risk of hypertension in adults, but the risk was lower than previously reported in the systematic review literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Highlighting in Early Childhood: Learning Biases Through Attentional Shifting.

PubMed

Burling, Joseph M; Yoshida, Hanako

2017-02-01

The literature on human and animal learning suggests that individuals attend to and act on cues differently based on the order in which they were learned. Recent studies have proposed that one specific type of learning outcome, the highlighting effect, can serve as a framework for understanding a number of early cognitive milestones. However, little is known how this learning effect itself emerges among children, whose memory and attention are much more limited compared to adults. Two experiments were conducted using different versions of the general highlighting paradigm: Experiment 1 tested 3 to 6 year olds with a newly developed image-based version of the paradigm, which was designed specifically to test young children. Experiment 2 tested the validity of an image-based implementation of the highlighting paradigm with adult participants. The results from Experiment 1 provide evidence for the highlighting effect among children 3-6 years old, and they suggest age-related differences in dividing attention among multiple cues during learning. Experiment 2 replicated results from previous studies by showing robust biases for both image-based and text-based versions of the highlighting task. This study suggests that sensitivity to learning order emerges early through the process of cued attention, and the role of the highlighting effect in early language learning is discussed. Copyright © 2016 Cognitive Science Society, Inc.

A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

PubMed

Tang, Jian; Jiang, Xiaoliang

2017-01-01

Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance.

PubMed

Clare, John; McKinney, Shawn T; DePue, John E; Loftin, Cynthia S

2017-10-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters. © 2017 by the Ecological Society of America.

Missing data handling in non-inferiority and equivalence trials: A systematic review.

PubMed

Rabe, Brooke A; Day, Simon; Fiero, Mallorie H; Bell, Melanie L

2018-05-25

Non-inferiority (NI) and equivalence clinical trials test whether a new treatment is therapeutically no worse than, or equivalent to, an existing standard of care. Missing data in clinical trials have been shown to reduce statistical power and potentially bias estimates of effect size; however, in NI and equivalence trials, they present additional issues. For instance, they may decrease sensitivity to differences between treatment groups and bias toward the alternative hypothesis of NI (or equivalence). Our primary aim was to review the extent of and methods for handling missing data (model-based methods, single imputation, multiple imputation, complete case), the analysis sets used (Intention-To-Treat, Per-Protocol, or both), and whether sensitivity analyses were used to explore departures from assumptions about the missing data. We conducted a systematic review of NI and equivalence trials published between May 2015 and April 2016 by searching the PubMed database. Articles were reviewed primarily by 2 reviewers, with 6 articles reviewed by both reviewers to establish consensus. Of 109 selected articles, 93% reported some missing data in the primary outcome. Among those, 50% reported complete case analysis, and 28% reported single imputation approaches for handling missing data. Only 32% reported conducting analyses of both intention-to-treat and per-protocol populations. Only 11% conducted any sensitivity analyses to test assumptions with respect to missing data. Missing data are common in NI and equivalence trials, and they are often handled by methods which may bias estimates and lead to incorrect conclusions. Copyright © 2018 John Wiley & Sons, Ltd.

Multiple-rule bias in the comparison of classification rules

PubMed Central

Yousefi, Mohammadmahdi R.; Hua, Jianping; Dougherty, Edward R.

2011-01-01

Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of reported results. Two approaches contributing to overoptimism in classification are (i) the reporting of results on datasets for which a proposed classification rule performs well and (ii) the comparison of multiple classification rules on a single dataset that purports to show the advantage of a certain rule. Results: This article provides a careful probabilistic analysis of the second issue and the ‘multiple-rule bias’, resulting from choosing a classification rule having minimum estimated error on the dataset. It quantifies this bias corresponding to estimating the expected true error of the classification rule possessing minimum estimated error and it characterizes the bias from estimating the true comparative advantage of the chosen classification rule relative to the others by the estimated comparative advantage on the dataset. The analysis is applied to both synthetic and real data using a number of classification rules and error estimators. Availability: We have implemented in C code the synthetic data distribution model, classification rules, feature selection routines and error estimation methods. The code for multiple-rule analysis is implemented in MATLAB. The source code is available at http://gsp.tamu.edu/Publications/supplementary/yousefi11a/. Supplementary simulation results are also included. Contact: edward@ece.tamu.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21546390

A General Theory of Sexual Differentiation

PubMed Central

Arnold, Arthur P.

2016-01-01

A general theory of mammalian sexual differentiation is proposed. All biological sex differences are the result of the inequality in effects of the sex chromosomes, which are the only factors that differ in XX vs. XY zygotes. This inequality leads to male-specific effects of the Y chromosome, including expression of the testis-determining gene Sry that causes differentiation of testes. Thus, Sry sets up lifelong sex differences in effects of gonadal hormones. Y genes also act outside of the gonads to cause male-specific effects. Differences in the number of X chromosomes between XX and XY cells causes sex differences in expression (1) of Xist, (2) of X genes that escape inactivation, and (2) of parentally imprinted X genes. Sex differences in phenotype are ultimately the result of multiple, independent sex-biasing factors, hormonal and sex chromosomal. These factors act in parallel and in combination to induce sex differences. They can also can offset each other to reduce sex differences. Other mechanisms, operating at the level of populations, cause groups of males to differ on average from groups of females. The theory has advantages for directing attention to inherent sex-biasing factors that operate in many tissues to cause sex differences, to cause sex-biased protection from disease, and to frame questions for further study. PMID:27870435

Manual for the Jet Event and Background Simulation Library(JEBSimLib)

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

Heinz, Matthias; Soltz, Ron; Angerami, Aaron

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

Manual for the Jet Event and Background Simulation Library

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

Heinz, M.; Soltz, R.; Angerami, A.

Jets are the collimated streams of particles resulting from hard scattering in the initial state of high-energy collisions. In heavy-ion collisions, jets interact with the quark-gluon plasma (QGP) before freezeout, providing a probe into the internal structure and properties of the QGP. In order to study jets, background must be subtracted from the measured event, potentially introducing a bias. We aim to understand and quantify this subtraction bias. PYTHIA, a library to simulate pure jet events, is used to simulate a model for a signature with one pure jet (a photon) and one quenched jet, where all quenched particle momentamore » are reduced by a user-de ned constant fraction. Background for the event is simulated using multiplicity values generated by the TRENTO initial state model of heavy-ion collisions fed into a thermal model consisting of a 3-dimensional Boltzmann distribution for particle types and momenta. Data from the simulated events is used to train a statistical model, which computes a posterior distribution of the quench factor for a data set. The model was tested rst on pure jet events and then on full events including the background. This model will allow for a quantitative determination of biases induced by various methods of background subtraction.« less

A general theory of sexual differentiation.

PubMed

Arnold, Arthur P

2017-01-02

A general theory of mammalian sexual differentiation is proposed. All biological sex differences are the result of the inequality in effects of the sex chromosomes, which are the only factors that differ in XX vs. XY zygotes. This inequality leads to male-specific effects of the Y chromosome, including expression of the testis-determining gene Sry that causes differentiation of testes. Thus, Sry sets up lifelong sex differences in effects of gonadal hormones. Y genes also act outside of the gonads to cause male-specific effects. Differences in the number of X chromosomes between XX and XY cells cause sex differences in expression (1) of Xist, (2) of X genes that escape inactivation, and (3) of parentally imprinted X genes. Sex differences in phenotype are ultimately the result of multiple, independent sex-biasing factors, hormonal and sex chromosomal. These factors act in parallel and in combination to induce sex differences. They also can offset each other to reduce sex differences. Other mechanisms, operating at the level of populations, cause groups of males to differ on average from groups of females. The theory frames questions for further study, and directs attention to inherent sex-biasing factors that operate in many tissues to cause sex differences, and to cause sex-biased protection from disease. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

fLPS: Fast discovery of compositional biases for the protein universe.

PubMed

Harrison, Paul M

2017-11-13

Proteins often contain regions that are compositionally biased (CB), i.e., they are made from a small subset of amino-acid residue types. These CB regions can be functionally important, e.g., the prion-forming and prion-like regions that are rich in asparagine and glutamine residues. Here I report a new program fLPS that can rapidly annotate CB regions. It discovers both single-residue and multiple-residue biases. It works through a process of probability minimization. First, contigs are constructed for each amino-acid type out of sequence windows with a low degree of bias; second, these contigs are searched exhaustively for low-probability subsequences (LPSs); third, such LPSs are iteratively assessed for merger into possible multiple-residue biases. At each of these stages, efficiency measures are taken to avoid or delay probability calculations unless/until they are necessary. On a current desktop workstation, the fLPS algorithm can annotate the biased regions of the yeast proteome (>5700 sequences) in <1 s, and of the whole current TrEMBL database (>65 million sequences) in as little as ~1 h, which is >2 times faster than the commonly used program SEG, using default parameters. fLPS discovers both shorter CB regions (of the sort that are often termed 'low-complexity sequence'), and milder biases that may only be detectable over long tracts of sequence. fLPS can readily handle very large protein data sets, such as might come from metagenomics projects. It is useful in searching for proteins with similar CB regions, and for making functional inferences about CB regions for a protein of interest. The fLPS package is available from: http://biology.mcgill.ca/faculty/harrison/flps.html , or https://github.com/pmharrison/flps , or is a supplement to this article.

Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

NASA Technical Reports Server (NTRS)

Bauman, William H., III

2010-01-01

The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind direction indicated the model error increased with the forecast period all four parameters. The hypothesis testing uses statistics to determine the probability that a given hypothesis is true. The goal of using the hypothesis test was to determine if the model bias of any of the parameters assessed throughout the model forecast period was statistically zero. For th is dataset, if this test produced a value >= -1 .96 or <= 1.96 for a data point, then the bias at that point was effectively zero and the model forecast for that point was considered to have no error. A graphical user interface (GUI) was developed so the 45 WS would have an operational tool at their disposal that would be easy to navigate among the multiple stratifications of information to include tower locations, month, model initialization times, sensor heights and onshore/offshore flow. The AMU developed the GUI using HyperText Markup Language (HTML) so the tool could be used in most popular web browsers with computers running different operating systems such as Microsoft Windows and Linux.

Inverse probability weighting estimation of the volume under the ROC surface in the presence of verification bias.

PubMed

Zhang, Ying; Alonzo, Todd A

2016-11-01

In diagnostic medicine, the volume under the receiver operating characteristic (ROC) surface (VUS) is a commonly used index to quantify the ability of a continuous diagnostic test to discriminate between three disease states. In practice, verification of the true disease status may be performed only for a subset of subjects under study since the verification procedure is invasive, risky, or expensive. The selection for disease examination might depend on the results of the diagnostic test and other clinical characteristics of the patients, which in turn can cause bias in estimates of the VUS. This bias is referred to as verification bias. Existing verification bias correction in three-way ROC analysis focuses on ordinal tests. We propose verification bias-correction methods to construct ROC surface and estimate the VUS for a continuous diagnostic test, based on inverse probability weighting. By applying U-statistics theory, we develop asymptotic properties for the estimator. A Jackknife estimator of variance is also derived. Extensive simulation studies are performed to evaluate the performance of the new estimators in terms of bias correction and variance. The proposed methods are used to assess the ability of a biomarker to accurately identify stages of Alzheimer's disease. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Are Culturally Biased Test Useful?

ERIC Educational Resources Information Center

Kelley, H. Paul

1982-01-01

Whether culturally biased tests are useful depends on what is meant by that phrase and the purpose for which the test is to be used. Keeping the distinction between aptitude and achievement in mind, different definitions of fair use of tests come from different sets of societal values. (Author/CM)

Ethnic Group Bias in Intelligence Test Items.

ERIC Educational Resources Information Center

Scheuneman, Janice

In previous studies of ethnic group bias in intelligence test items, the question of bias has been confounded with ability differences between the ethnic group samples compared. The present study is based on a conditional probability model in which an unbiased item is defined as one where the probability of a correct response to an item is the…

DES Y1 Results: Validating Cosmological Parameter Estimation Using Simulated Dark Energy Surveys

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

MacCrann, N.; et al.

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input cosmology is consistent with the combined constraints from multiple simulated DES Y1 realizations in themore » $$\\Omega_m-\\sigma_8$$ plane. For one of the suites, we are able to show with high confidence that any biases in the inferred $$S_8=\\sigma_8(\\Omega_m/0.3)^{0.5}$$ and $$\\Omega_m$$ are smaller than the DES Y1 $$1-\\sigma$$ uncertainties. For the other suite, for which we have fewer realizations, we are unable to be this conclusive; we infer a roughly 70% probability that systematic biases in the recovered $$\\Omega_m$$ and $$S_8$$ are sub-dominant to the DES Y1 uncertainty. As cosmological analyses of this kind become increasingly more precise, validation of parameter inference using survey simulations will be essential to demonstrate robustness.« less

Unpacking the Evidence of Gender Bias

ERIC Educational Resources Information Center

Fulmer, Connie L.

2010-01-01

The purpose of this study was to investigate gender bias in pre-service principals using the Gender-Leader Implicit Association Test. Analyses of student-learning narratives revealed how students made sense of gender bias (biased or not-biased) and how each reacted to evidence (surprised or not-surprised). Two implications were: (1) the need for…

Effect of fenfluramine-derivative diet pills on cardiac valves: a meta-analysis of observational studies.

PubMed

Sachdev, Molly; Miller, William C; Ryan, Thomas; Jollis, James G

2002-12-01

Fenfluramine-derivative diet pills were withdrawn from the market in 1997 because of an association with valvular regurgitation, but subsequent estimates of the prevalence of this condition have varied widely. We systematically reviewed evidence regarding the prevalence of valvular disease after fenfluramine exposure. We searched multiple databases with multiple search terms. Conference proceedings from 1997 onward were searched by index. Authors of eligible studies were contacted to identify unpublished works. Selection criteria were liberally determined. Ten of the identified 11 articles met these criteria. Reviewers assessed the studies' methodologic quality by use of a standard form to evaluate selection, attrition, performance, and detection bias. The studies were analyzed in 2 groups on the basis of length of exposure (<90 days or >90 days). The Mantel-Haenszel method was used to summarize data. Quantitative and qualitative tests for heterogeneity were performed. Tests for publication bias were also done. Tests for heterogeneity were nonsignificant after removing 1 outlier trial. The pooled prevalence of valvular regurgitation meeting Food and Drug Administration criteria (at least mild aortic regurgitation or at least moderate mitral regurgitation) among patients treated for >90 days was 12.0% compared with 5.9% for the unexposed group (prevalence odds ratio 2.2, 95% CI 1.7-2.7). The combined analyses also identified a small but statistically significant increase in mitral regurgitation not previously identified by individual studies (exposed 3.5%, unexposed 1.8%, prevalence odds ratio 1.6, 95% CI 1.05-2.3). Among patients exposed for <90 days, a trend toward more regurgitation was not statistically significant by either combined Food and Drug Administration criteria (exposed 6.8%, unexposed 5.8%, prevalence odds ratio 1.4, 95% CI 0.8-2.4) or by individual valve. These data indicate that fenfluramine-associated valvular regurgitation is less common than initially reported, but still present in 1 of 8 patients treated for >90 days.

Critical Thinking Instruction in English for Academic Purposes Writing Courses: A Dialectical Thinking Approach

ERIC Educational Resources Information Center

Tanaka, Jay; Gilliland, Betsy

2017-01-01

Critical thinking (CT) is usually taught as a list of practical skills for students to master. In this article, the authors argue that CT instruction should go beyond skills to engage students with issues of identifying their own biases and understanding multiple perspectives on issues. This explicit attention to one's own bias is essential for…

Fair Play: A Study of Scientific Workforce Trainers' Experience Playing an Educational Video Game about Racial Bias

ERIC Educational Resources Information Center

Katz, Anna; Carnes, Molly; Gutierrez, Belinda; Savoy, Julia; Samuel, Clem; Filut, Amarette; Pribbenow, Christine Maidl

2017-01-01

Explicit racial bias has decreased in the United States, but racial stereotypes still exist and conspire in multiple ways to perpetuate the underparticipation of Blacks in science careers. Capitalizing on the potential effectiveness of role-playing video games to promote the type of active learning required to increase awareness of and reduce…

Do We Need Multiple Informants When Assessing Autistic Traits? The Degree of Report Bias on Offspring, Self, and Spouse Ratings

ERIC Educational Resources Information Center

Möricke, Esmé; Buitelaar, Jan K.; Rommelse, Nanda N. J.

2016-01-01

This study focused on the degree of report bias in assessing autistic traits. Both parents of 124 preschoolers completed the Social Communication Questionnaire and the Autism-spectrum Quotient. Acceptable agreement existed between mother and father reports of children's mean scores of autistic traits, but interrater reliability for rank-order…

Bias Characterization in Probabilistic Genotype Data and Improved Signal Detection with Multiple Imputation

PubMed Central

Palmer, Cameron; Pe’er, Itsik

2016-01-01

Missing data are an unavoidable component of modern statistical genetics. Different array or sequencing technologies cover different single nucleotide polymorphisms (SNPs), leading to a complicated mosaic pattern of missingness where both individual genotypes and entire SNPs are sporadically absent. Such missing data patterns cannot be ignored without introducing bias, yet cannot be inferred exclusively from nonmissing data. In genome-wide association studies, the accepted solution to missingness is to impute missing data using external reference haplotypes. The resulting probabilistic genotypes may be analyzed in the place of genotype calls. A general-purpose paradigm, called Multiple Imputation (MI), is known to model uncertainty in many contexts, yet it is not widely used in association studies. Here, we undertake a systematic evaluation of existing imputed data analysis methods and MI. We characterize biases related to uncertainty in association studies, and find that bias is introduced both at the imputation level, when imputation algorithms generate inconsistent genotype probabilities, and at the association level, when analysis methods inadequately model genotype uncertainty. We find that MI performs at least as well as existing methods or in some cases much better, and provides a straightforward paradigm for adapting existing genotype association methods to uncertain data. PMID:27310603

Sex Bias in Testing: A Review with Policy Recommendations.

ERIC Educational Resources Information Center

Tittle, Carol Kehr

Educational achievement tests, career interest inventories, and aptitude tests are reviewed for examples of sex bias, and changes in policy concerning the use of these tests are suggested. These suggestions are within the authority and responsibility of local and state educational administrators, teachers, counselors, parents, and students. The…

Psychological Testing of Black People; A Position Paper.

ERIC Educational Resources Information Center

Dent, Harold E.; Williams, Robert L.

The psychological testing of blacks and other minorities inflicts dehumanization upon them by subjecting them to culturally-biased examinations. These tests are defended on "scientific" grounds, although it is evident that they are simply a form of institutionalized racism. Standardized tests of intelligence reflect a middle-class white bias that…

Implicit Messages:A Review of "Bias in Mental Testing."

ERIC Educational Resources Information Center

Scarr, Sandra

1981-01-01

Reviews Arthur Jensen's "Bias in Mental Testing" in terms of its implications for racial genetic inferiority, and offers alternate explanations for racial differences in testing based on data from studies on Black socialization and cultural differences in child rearing. (CM)

Cultural Bias in Standardized Testing: An Anthropological View

ERIC Educational Resources Information Center

Arewa, Ojo

1977-01-01

Since standardized tests are constructed for the purpose of measuring the intellectual capacity of school children from the diverse sociocultural backgrounds in America, one of the main topics of this article concerns the standardization bias inherent in these tests. (Author/AM)

The future in clinical genetics: affective forecasting biases in patient and clinician decision making.

PubMed

Peters, S A; Laham, S M; Pachter, N; Winship, I M

2014-04-01

When clinicians facilitate and patients make decisions about predictive genetic testing, they often base their choices on the predicted emotional consequences of positive and negative test results. Research from psychology and decision making suggests that such predictions may often be biased. Work on affective forecasting-predicting one's future emotional states-shows that people tend to overestimate the impact of (especially negative) emotional events on their well-being; a phenomenon termed the impact bias. In this article, we review the causes and consequences of the impact bias in medical decision making, with a focus on applying such findings to predictive testing in clinical genetics. We also recommend strategies for reducing the impact bias and consider the ethical and practical implications of doing so. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Creation and Delphi-method refinement of pediatric disaster triage simulations.

PubMed

Cicero, Mark X; Brown, Linda; Overly, Frank; Yarzebski, Jorge; Meckler, Garth; Fuchs, Susan; Tomassoni, Anthony; Aghababian, Richard; Chung, Sarita; Garrett, Andrew; Fagbuyi, Daniel; Adelgais, Kathleen; Goldman, Ran; Parker, James; Auerbach, Marc; Riera, Antonio; Cone, David; Baum, Carl R

2014-01-01

There is a need for rigorously designed pediatric disaster triage (PDT) training simulations for paramedics. First, we sought to design three multiple patient incidents for EMS provider training simulations. Our second objective was to determine the appropriate interventions and triage level for each victim in each of the simulations and develop evaluation instruments for each simulation. The final objective was to ensure that each simulation and evaluation tool was free of bias toward any specific PDT strategy. We created mixed-methods disaster simulation scenarios with pediatric victims: a school shooting, a school bus crash, and a multiple-victim house fire. Standardized patients, high-fidelity manikins, and low-fidelity manikins were used to portray the victims. Each simulation had similar acuity of injuries and 10 victims. Examples include children with special health-care needs, gunshot wounds, and smoke inhalation. Checklist-based evaluation tools and behaviorally anchored global assessments of function were created for each simulation. Eight physicians and paramedics from areas with differing PDT strategies were recruited as Subject Matter Experts (SMEs) for a modified Delphi iterative critique of the simulations and evaluation tools. The modified Delphi was managed with an online survey tool. The SMEs provided an expected triage category for each patient. The target for modified Delphi consensus was ≥85%. Using Likert scales and free text, the SMEs assessed the validity of the simulations, including instances of bias toward a specific PDT strategy, clarity of learning objectives, and the correlation of the evaluation tools to the learning objectives and scenarios. After two rounds of the modified Delphi, consensus for expected triage level was >85% for 28 of 30 victims, with the remaining two achieving >85% consensus after three Delphi iterations. To achieve consensus, we amended 11 instances of bias toward a specific PDT strategy and corrected 10 instances of noncorrelation between evaluations and simulation. The modified Delphi process, used to derive novel PDT simulation and evaluation tools, yielded a high degree of consensus among the SMEs, and eliminated biases toward specific PDT strategies in the evaluations. The simulations and evaluation tools may now be tested for reliability and validity as part of a prehospital PDT curriculum.

Ethnicity and gender in late childhood and early adolescence: group identity and awareness of bias.

PubMed

Brown, Christia Spears; Alabi, Basirat O; Huynh, Virginia W; Masten, Carrie L

2011-03-01

The current study examined awareness of gender and ethnic bias and gender and ethnic identity in 350 African American, White/European American, and Latino/Hispanic students (Mage = 11.21 years, SD = 1.59) from the 4th, 6th, and 8th grades of diverse middle and elementary schools. The study collected (a) qualitative data to best capture the types of bias that were most salient to children and (b) daily diaries and individual measures to examine the multiple components of children's gender and ethnic identities. Results revealed ethnic, gender, and grade-level differences in awareness of ethnic and gender bias. Overall, more children were aware of gender bias than ethnic bias. This effect was most pronounced among White/European American youths. Among those in 4th grade, African American and Latino youths were more likely to be aware of ethnic bias than were White/European American youths. Analyses also examined how awareness of bias was related to gender and ethnic identity. For example, children who had a salient and important gender identity, and a devalued ethnic identity, were less likely than other children to be aware of ethnic bias. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Publication bias and the failure of replication in experimental psychology.

PubMed

Francis, Gregory

2012-12-01

Replication of empirical findings plays a fundamental role in science. Among experimental psychologists, successful replication enhances belief in a finding, while a failure to replicate is often interpreted to mean that one of the experiments is flawed. This view is wrong. Because experimental psychology uses statistics, empirical findings should appear with predictable probabilities. In a misguided effort to demonstrate successful replication of empirical findings and avoid failures to replicate, experimental psychologists sometimes report too many positive results. Rather than strengthen confidence in an effect, too much successful replication actually indicates publication bias, which invalidates entire sets of experimental findings. Researchers cannot judge the validity of a set of biased experiments because the experiment set may consist entirely of type I errors. This article shows how an investigation of the effect sizes from reported experiments can test for publication bias by looking for too much successful replication. Simulated experiments demonstrate that the publication bias test is able to discriminate biased experiment sets from unbiased experiment sets, but it is conservative about reporting bias. The test is then applied to several studies of prominent phenomena that highlight how publication bias contaminates some findings in experimental psychology. Additional simulated experiments demonstrate that using Bayesian methods of data analysis can reduce (and in some cases, eliminate) the occurrence of publication bias. Such methods should be part of a systematic process to remove publication bias from experimental psychology and reinstate the important role of replication as a final arbiter of scientific findings.

Strengthening forensic DNA decision making through a better understanding of the influence of cognitive bias.

PubMed

Jeanguenat, Amy M; Budowle, Bruce; Dror, Itiel E

2017-11-01

Cognitive bias may influence process flows and decision making steps in forensic DNA analyses and interpretation. Currently, seven sources of bias have been identified that may affect forensic decision making with roots in human nature; environment, culture, and experience; and case specific information. Most of the literature and research on cognitive bias in forensic science has focused on patterned evidence; however, forensic DNA testing is not immune to bias, especially when subjective interpretation is involved. DNA testing can be strengthened by recognizing the existence of bias, evaluating where it influences decision making, and, when applicable, implementing practices to reduce or control its effects. Elements that may improve forensic decision making regarding bias include cognitively informed education and training, quality assurance procedures, review processes, analysis and interpretation, and context management of irrelevant information. Although bias exists, reliable results often can be (and have been) produced. However, at times bias can (and has) impacted the interpretation of DNA results negatively. Therefore, being aware of the dangers of bias and implementing measures to control its potential impact should be considered. Measures and procedures that handicap the workings of the crime laboratory or add little value to improving the operation are not advocated, but simple yet effective measures are suggested. This article is meant to raise awareness of cognitive bias contamination in forensic DNA testing and to give laboratories possible pathways to make sound decisions to address its influences. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

PubMed

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

Lossy compression of weak lensing data

DOE PAGES

Vanderveld, R. Ali; Bernstein, Gary M.; Stoughton, Chris; ...

2011-07-12

Future orbiting observatories will survey large areas of sky in order to constrain the physics of dark matter and dark energy using weak gravitational lensing and other methods. Lossy compression of the resultant data will improve the cost and feasibility of transmitting the images through the space communication network. We evaluate the consequences of the lossy compression algorithm of Bernstein et al. (2010) for the high-precision measurement of weak-lensing galaxy ellipticities. This square-root algorithm compresses each pixel independently, and the information discarded is by construction less than the Poisson error from photon shot noise. For simulated space-based images (without cosmicmore » rays) digitized to the typical 16 bits per pixel, application of the lossy compression followed by image-wise lossless compression yields images with only 2.4 bits per pixel, a factor of 6.7 compression. We demonstrate that this compression introduces no bias in the sky background. The compression introduces a small amount of additional digitization noise to the images, and we demonstrate a corresponding small increase in ellipticity measurement noise. The ellipticity measurement method is biased by the addition of noise, so the additional digitization noise is expected to induce a multiplicative bias on the galaxies measured ellipticities. After correcting for this known noise-induced bias, we find a residual multiplicative ellipticity bias of m {approx} -4 x 10 -4. This bias is small when compared to the many other issues that precision weak lensing surveys must confront, and furthermore we expect it to be reduced further with better calibration of ellipticity measurement methods.« less

The Subjective and Objective Interface of Bias Detection on Language Tests

ERIC Educational Resources Information Center

Ross, Steven J.; Okabe, Junko

2006-01-01

Test validity is predicated on there being a lack of bias in tasks, items, or test content. It is well-known that factors such as test candidates' mother tongue, life experiences, and socialization practices of the wider community may serve to inject subtle interactions between individuals' background and the test content. When the gender of the…

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

PubMed Central

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

PubMed

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys.

PubMed

Reniers, Georges; Eaton, Jeffrey

2009-03-13

To assess the relationship between prior knowledge of one's HIV status and the likelihood to refuse HIV testing in populations-based surveys and explore its potential for producing bias in HIV prevalence estimates. Using longitudinal survey data from Malawi, we estimate the relationship between prior knowledge of HIV-positive status and subsequent refusal of an HIV test. We use that parameter to develop a heuristic model of refusal bias that is applied to six Demographic and Health Surveys, in which refusal by HIV status is not observed. The model only adjusts for refusal bias conditional on a completed interview. Ecologically, HIV prevalence, prior testing rates and refusal for HIV testing are highly correlated. Malawian data further suggest that amongst individuals who know their status, HIV-positive individuals are 4.62 (95% confidence interval, 2.60-8.21) times more likely to refuse testing than HIV-negative ones. On the basis of that parameter and other inputs from the Demographic and Health Surveys, our model predicts downward bias in national HIV prevalence estimates ranging from 1.5% (95% confidence interval, 0.7-2.9) for Senegal to 13.3% (95% confidence interval, 7.2-19.6) for Malawi. In absolute terms, bias in HIV prevalence estimates is negligible for Senegal but 1.6 (95% confidence interval, 0.8-2.3) percentage points for Malawi. Downward bias is more severe in urban populations. Because refusal rates are higher in men, seroprevalence surveys also tend to overestimate the female-to-male ratio of infections. Prior knowledge of HIV status informs decisions to participate in seroprevalence surveys. Informed refusals may produce bias in estimates of HIV prevalence and the sex ratio of infections.

Choice Inconsistencies among the Elderly: Evidence from Plan Choice in the Medicare Part D Program: Comment.

PubMed

Ketcham, Jonathan D; Kuminoff, Nicolai V; Powers, Christopher A

2016-12-01

Consumers' enrollment decisions in Medicare Part D can be explained by Abaluck and Gruber’s (2011) model of utility maximization with psychological biases or by a neoclassical version of their model that precludes such biases. We evaluate these competing hypotheses by applying nonparametric tests of utility maximization and model validation tests to administrative data. We find that 79 percent of enrollment decisions from 2006 to 2010 satisfied basic axioms of consumer theory under the assumption of full information. The validation tests provide evidence against widespread psychological biases. In particular, we find that precluding psychological biases improves the structural model's out-of-sample predictions for consumer behavior.

Maximum Likelihood Item Easiness Models for Test Theory Without an Answer Key

PubMed Central

Batchelder, William H.

2014-01-01

Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce two extensions to the basic model in order to account for item rating easiness/difficulty. The first extension is a multiplicative model and the second is an additive model. We show how the multiplicative model is related to the Rasch model. We describe several maximum-likelihood estimation procedures for the models and discuss issues of model fit and identifiability. We describe how the CCT models could be used to give alternative consensus-based measures of reliability. We demonstrate the utility of both the basic and extended models on a set of essay rating data and give ideas for future research. PMID:29795812

The frequency of item writing flaws in multiple-choice questions used in high stakes nursing assessments.

PubMed

Tarrant, Marie; Knierim, Aimee; Hayes, Sasha K; Ware, James

2006-12-01

Multiple-choice questions are a common assessment method in nursing examinations. Few nurse educators, however, have formal preparation in constructing multiple-choice questions. Consequently, questions used in baccalaureate nursing assessments often contain item-writing flaws, or violations to accepted item-writing guidelines. In one nursing department, 2770 MCQs were collected from tests and examinations administered over a five-year period from 2001 to 2005. Questions were evaluated for 19 frequently occurring item-writing flaws, for cognitive level, for question source, and for the distribution of correct answers. Results show that almost half (46.2%) of the questions contained violations of item-writing guidelines and over 90% were written at low cognitive levels. Only a small proportion of questions were teacher generated (14.1%), while 36.2% were taken from testbanks and almost half (49.4%) had no source identified. MCQs written at a lower cognitive level were significantly more likely to contain item-writing flaws. While there was no relationship between the source of the question and item-writing flaws, teacher-generated questions were more likely to be written at higher cognitive levels (p<0.001). Correct answers were evenly distributed across all four options and no bias was noted in the placement of correct options. Further training in item-writing is recommended for all faculty members who are responsible for developing tests. Pre-test review and quality assessment is also recommended to reduce the occurrence of item-writing flaws and to improve the quality of test questions.

Unconscious memory bias in depression: perceptual and conceptual processes.

PubMed

Watkins, P C; Martin, C K; Stern, L D

2000-05-01

Mood-congruent memory (MCM) bias in depression was investigated using 4 different implicit memory tests. Two of the implicit tests were perceptually driven, and 2 were conceptually driven. Depressed participants and nondepressed controls were assigned to 1 of 4 implicit memory tests after studying positive and negative adjectives. Results showed no MCM bias in the perceptually driven tests. MCM was demonstrated in 1 of the conceptually driven tests, but only for adjectives that were conceptually encoded. Results support the theory that mood-congruent processes in depression are limited to conceptual processing. However, activation of conceptual processes may not be sufficient for demonstrating mood congruency.

Bias in Examination Test Banks that Accompany Cost Accounting Texts.

ERIC Educational Resources Information Center

Clute, Ronald C.; McGrail, George R.

1989-01-01

Eight text banks that accompany cost accounting textbooks were evaluated for the presence of bias in the distribution of correct responses. All but one were found to have considerable bias, and three of eight were found to have significant choice bias. (SK)

Comparing State SAT Scores: Problems, Biases, and Corrections.

ERIC Educational Resources Information Center

Gohmann, Stephen F.

1988-01-01

One method to correct for selection bias in comparing Scholastic Aptitude Test (SAT) scores among states is presented, which is a modification of J. J. Heckman's Selection Bias Correction (1976, 1979). Empirical results suggest that sample selection bias is present in SAT score regressions. (SLD)

Question format shifts bias away from the emphasised response in tests of recognition memory.

PubMed

Mill, Ravi D; O'Connor, Akira R

2014-11-01

The question asked to interrogate memory has potential to influence response bias at retrieval, yet has not been systematically investigated. According to framing effects in the field of eyewitness testimony, retrieval cueing effects in cognitive psychology and the acquiescence bias in questionnaire responding, the question should establish a confirmatory bias. Conversely, according to findings from the rewarded decision-making literature involving mixed incentives, the question should establish a disconfirmatory bias. Across three experiments (ns=90 [online], 29 [laboratory] and 29 [laboratory]) we demonstrate a disconfirmatory bias - "old?" decreased old responding. This bias is underpinned by a goal-driven mechanism wherein participants seek to maximise emphasised response accuracy at the expense of frequency. Moreover, we demonstrate that disconfirmatory biases can be generated without explicit reference to the goal state. We conclude that subtle aspects of the test environment influence retrieval to a greater extent than has been previously considered. Copyright © 2014 Elsevier Inc. All rights reserved.

Mood-congruent attention and memory bias in dysphoria: Exploring the coherence among information-processing biases.

PubMed

Koster, Ernst H W; De Raedt, Rudi; Leyman, Lemke; De Lissnyder, Evi

2010-03-01

Recent studies indicate that depression is characterized by mood-congruent attention bias at later stages of information-processing. Moreover, depression has been associated with enhanced recall of negative information. The present study tested the coherence between attention and memory bias in dysphoria. Stable dysphoric (n = 41) and non-dysphoric (n = 41) undergraduates first performed a spatial cueing task that included negative, positive, and neutral words. Words were presented for 250 ms under conditions that allowed or prevented elaborate processing. Memory for the words presented in the cueing task was tested using incidental free recall. Dysphoric individuals exhibited an attention bias for negative words in the condition that allowed elaborate processing, with the attention bias for negative words predicting free recall of negative words. Results demonstrate the coherence of attention and memory bias in dysphoric individuals and provide suggestions on the influence of attention bias on further processing of negative material. 2009 Elsevier Ltd. All rights reserved.

Cognitive Bias in Systems Verification

NASA Technical Reports Server (NTRS)

Larson, Steve

2012-01-01

Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.

Patterns of oribatid mite species diversity: testing the effects of elevation, area and sampling effort.

PubMed

Mumladze, Levan; Murvanidze, Maka; Maraun, Mark

2017-07-01

Elevational gradients in species diversity and species area relationships are two well established patterns that are not mutually exclusive in space and time. Elevation and area are both considered as good proxies to detect and characterize the patterns of species diversity distribution. However, such studies are hampered by the incomplete biodiversity data available for ecologists, which may affect the pattern perceptions. Using the large dataset of oribatid mite communities sampled in Georgia, we tested the effects of altitude and area on species distribution using various approaches, while explicitly considering the biases from sampling effort. Our results showed that elevation and area are strongly correlated (with increasing absolute elevation, land area decreases) and both have strong linear effects on species diversity distribution when studied separately. Approaches based on multiple regression and direct removal of co-varied factors, indicated that the effect of area can actually override the effect of elevation in describing the oribatid species diversity distribution along with elevation. On the other hand, the bias of sampling proved significant in perception of elevational species richness pattern with less effect on elevational species area relationship. We suggest that the sampling alone may be responsible for patterns observed and thus should be considered in ecological studies when eligible.

Why do we have such difficulty assessing aerosol impacts in Southeast Asia? Examining the representativeness of regional in situ, remote sensing, and modeling data using examples from a recent field trial

NASA Astrophysics Data System (ADS)

Reid, J.; Hyer, E. J.; Lagrosas, N.; Salinas Cortijo, S. V.; Campbell, J. R.; Chew, B.; Cook, J.; Di Girolamo, L.; Kuciauskas, A. P.; Johnson, R. S.; Jonsson, H.; Lynch, P.; Sessions, W.; Simpas, J. B.; Turk, F. J.; Wang, J.

2012-12-01

Southeast Asia faces numerous climate change issues, and the interaction between aerosol particles, clouds, and precipitation is thought to impact the environment in this region at both weather and climate scales. Aerosol particles have direct radiative effects, indirect effects through interaction with clouds and precipitation, and also act as a tracer for other processes affecting the carbon cycle or atmospheric chemistry. Southeast Asia also hosts some of the most complex meteorological phenomenon of the world, challenging in situ, remote sensing and modeling systems. Indeed, there is more diversity in satellite based aerosol, fire, cloud, and precipitation products in Southeast Asia than perhaps anywhere else in the world outside of the poles. In addition to serious direct challenges to aerosol observability in Southeast Asia, such as persistent ubiquitous cloud cover, there are also contextual biases (such as for aerosol retrievals the classic clear sky bias). Contextual bias affects the representativeness of nearly all aerosol assessments in Southeast Asia. As part of the 7 Southeast Asian Studies (7SEAS) program, a small intensive study was conducted in Singapore and the Palawan Archipelago in September 2011 to study the flow of biomass burning smoke through the South China/East Sea and into the summertime monsoonal trough. Analysis of field data coupled with multiple satellite and model products allowed us to investigate questions on the representativeness of data and to what extent they capture the 'true' state of the meteorological and aerosol environment. Four specific representativeness issues are presented based on IOP examples: 1) Individual biases in retrievals or model simulations; 2) Sampling biases at short time scales based on product coverage; 3) Temporal and spatial scale biases inherent in large and point based measurements; 4) Contextual biases that develop from the aggregation of data products. Considering all four of these issues we conclude with a discussion of strategies for hypothesis testing and the development of regional state vectors with realistic uncertainties.

Biases in attention, interpretation, memory, and associations in children with varying levels of spider fear: Inter-relations and prediction of behavior.

PubMed

Klein, Anke M; van Niekerk, Rianne; Ten Brink, Giovanni; Rapee, Ronald M; Hudson, Jennifer L; Bögels, Susan M; Becker, Eni S; Rinck, Mike

2017-03-01

Cognitive theories suggest that cognitive biases may be related and together influence the anxiety response. However, little is known about the interrelations of cognitive bias tasks and whether they allow for an improved prediction of fear-related behavior in addition to self-reports. This study simultaneously addressed several types of cognitive biases in children, to investigate attention bias, interpretation bias, memory bias and fear-related associations, their interrelations and the prediction of behavior. Eighty-one children varying in their levels of spider fear completed the Spider Anxiety and Disgust Screening for Children and performed two Emotional Stroop tasks, a Free Recall task, an interpretation task including size and distance indication, an Affective Priming Task, and a Behavioral Assessment Test. We found an attention bias, interpretation bias, and fear-related associations, but no evidence for a memory bias. The biases showed little overlap. Attention bias, interpretation bias, and fear-related associations predicted unique variance in avoidance of spiders. Interpretation bias and fear-related associations remained significant predictors, even when self-reported fear was included as a predictor. Children were not seeking help for their spider fear and were not tested on clinical levels of spider phobia. This is the first study to find evidence that different cognitive biases each predict unique variance in avoidance behavior. Furthermore, it is also the first study in which we found evidence for a relation between fear of spiders and size and distance indication. We showed that this bias is distinct from other cognitive biases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stressors and anxiety in dementia caregiving: multiple mediation analysis of rumination, experiential avoidance, and leisure.

PubMed

Romero-Moreno, R; Losada, A; Márquez-González, M; Mausbach, B T

2016-11-01

Despite the robust associations between stressors and anxiety in dementia caregiving, there is a lack of research examining which factors contribute to explain this relationship. This study was designed to test a multiple mediation model of behavioral and psychological symptoms of dementia (BPSD) and anxiety that proposes higher levels of rumination and experiential avoidance and lower levels of leisure satisfaction as potential mediating variables. The sample consisted of 256 family caregivers. In order to test a simultaneously parallel multiple mediation model of the BPSD to anxiety pathway, a PROCESS method was used and bias-corrected and accelerated bootstrapping method was used to test confidence intervals. Higher levels of stressors significantly predicted anxiety. Greater stressors significantly predicted higher levels of rumination and experiential avoidance, and lower levels of leisure satisfaction. These three coping variables significantly predicted anxiety. Finally, rumination, experiential avoidance, and leisure satisfaction significantly mediated the link between stressors and anxiety. The explained variance for the final model was 47.09%. Significant contrasts were found between rumination and leisure satisfaction, with rumination being a significantly higher mediator. The results suggest that caregivers' experiential avoidance, rumination, and leisure satisfaction may function as mechanisms through which BPSD influence on caregivers' anxiety. Training caregivers in reducing their levels of experiential avoidance and rumination by techniques that foster their ability of acceptance of their negative internal experiences, and increase their level of leisure satisfaction, may be helpful to reduce their anxiety symptoms developed by stressors.

Explanation of Two Anomalous Results in Statistical Mediation Analysis.

PubMed

Fritz, Matthew S; Taylor, Aaron B; Mackinnon, David P

2012-01-01

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M , a , increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y , b , was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a . Implications of these findings are discussed.

Perceived reachability in single- and multiple-degree-of-freedom workspaces.

PubMed

Gabbard, Carl; Ammar, Diala; Lee, Sunghan

2006-11-01

In comparisons of perceived (imagined) and actual reaches, investigators consistently find a tendency to overestimate. A primary explanation for that phenomenon is that individuals reach as a "whole-body engagement" involving multiple degrees of freedom (m-df). The authors examined right-handers (N = 28) in 1-df and m-df workspaces by having them judge the reachability of targets at midline, right, and left visual fields. Response profiles were similar for total error. Both conditions reflected an overestimation bias, although the bias was significantly greater in the m-df condition. Midline responses differed (greater overestimation) from those of right and left visual fields, which were similar. Although the authors would have predicted better performance in the m-df condition, it seems plausible that if individuals think in terms of m-df, they may feel more confident in that condition and thereby exhibit greater overestimation. Furthermore, the authors speculate that the reduced bias at the side fields may be attributed to a more conservative strategy based in part on perceived reach constraints.

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.

Avalanche multiplication in AlGaN-based heterostructures for the ultraviolet spectral range

NASA Astrophysics Data System (ADS)

Hahn, L.; Fuchs, F.; Kirste, L.; Driad, R.; Rutz, F.; Passow, T.; Köhler, K.; Rehm, R.; Ambacher, O.

2018-04-01

AlxGa1-xN based avalanche photodiodes grown on sapphire substrate with Al-contents of x = 0.65 and x = 0.60 have been examined under back- and frontside illumination with respect to their avalanche gain properties. The photodetectors suitable for the solar-blind ultraviolet spectral regime show avalanche gain for voltages in excess of 30 V reverse bias in the linear gain mode. Devices with a mesa diameter of 100 μm exhibit stable avalanche gain below the break through threshold voltage, exceeding a multiplication gain of 5500 at 84 V reverse bias. A dark current below 1 pA can be found for reverse voltages up to 60 V.

Biased Metropolis Sampling for Rugged Free Energy Landscapes

NASA Astrophysics Data System (ADS)

Berg, Bernd A.

2003-11-01

Metropolis simulations of all-atom models of peptides (i.e. small proteins) are considered. Inspired by the funnel picture of Bryngelson and Wolyness, a transformation of the updating probabilities of the dihedral angles is defined, which uses probability densities from a higher temperature to improve the algorithmic performance at a lower temperature. The method is suitable for canonical as well as for generalized ensemble simulations. A simple approximation to the full transformation is tested at room temperature for Met-Enkephalin in vacuum. Integrated autocorrelation times are found to be reduced by factors close to two and a similar improvement due to generalized ensemble methods enters multiplicatively.

Shared Dosimetry Error in Epidemiological Dose-Response Analyses

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

Stram, Daniel O.; Preston, Dale L.; Sokolnikov, Mikhail

2015-03-23

Radiation dose reconstruction systems for large-scale epidemiological studies are sophisticated both in providing estimates of dose and in representing dosimetry uncertainty. For example, a computer program was used by the Hanford Thyroid Disease Study to provide 100 realizations of possible dose to study participants. The variation in realizations reflected the range of possible dose for each cohort member consistent with the data on dose determinates in the cohort. Another example is the Mayak Worker Dosimetry System 2013 which estimates both external and internal exposures and provides multiple realizations of "possible" dose history to workers given dose determinants. This paper takesmore » up the problem of dealing with complex dosimetry systems that provide multiple realizations of dose in an epidemiologic analysis. In this paper we derive expected scores and the information matrix for a model used widely in radiation epidemiology, namely the linear excess relative risk (ERR) model that allows for a linear dose response (risk in relation to radiation) and distinguishes between modifiers of background rates and of the excess risk due to exposure. We show that treating the mean dose for each individual (calculated by averaging over the realizations) as if it was true dose (ignoring both shared and unshared dosimetry errors) gives asymptotically unbiased estimates (i.e. the score has expectation zero) and valid tests of the null hypothesis that the ERR slope β is zero. Although the score is unbiased the information matrix (and hence the standard errors of the estimate of β) is biased for β≠0 when ignoring errors in dose estimates, and we show how to adjust the information matrix to remove this bias, using the multiple realizations of dose. Use of these methods for several studies, including the Mayak Worker Cohort and the U.S. Atomic Veterans Study, is discussed.« less

How many mailouts? Could attempts to increase the response rate in the Iraq war cohort study be counterproductive?

PubMed Central

Tate, A Rosemary; Jones, Margaret; Hull, Lisa; Fear, Nicola T; Rona, Roberto; Wessely, Simon; Hotopf, Matthew

2007-01-01

Background Low response and reporting errors are major concerns for survey epidemiologists. However, while nonresponse is commonly investigated, the effects of misclassification are often ignored, possibly because they are hard to quantify. We investigate both sources of bias in a recent study of the effects of deployment to the 2003 Iraq war on the health of UK military personnel, and attempt to determine whether improving response rates by multiple mailouts was associated with increased misclassification error and hence increased bias in the results. Methods Data for 17,162 UK military personnel were used to determine factors related to response and inverse probability weights were used to assess nonresponse bias. The percentages of inconsistent and missing answers to health questions from the 10,234 responders were used as measures of misclassification in a simulation of the 'true' relative risks that would have been observed if misclassification had not been present. Simulated and observed relative risks of multiple physical symptoms and post-traumatic stress disorder (PTSD) were compared across response waves (number of contact attempts). Results Age, rank, gender, ethnic group, enlistment type (regular/reservist) and contact address (military or civilian), but not fitness, were significantly related to response. Weighting for nonresponse had little effect on the relative risks. Of the respondents, 88% had responded by wave 2. Missing answers (total 3%) increased significantly (p < 0.001) between waves 1 and 4 from 2.4% to 7.3%, and the percentage with discrepant answers (total 14%) increased from 12.8% to 16.3% (p = 0.007). However, the adjusted relative risks decreased only slightly from 1.24 to 1.22 for multiple physical symptoms and from 1.12 to 1.09 for PTSD, and showed a similar pattern to those simulated. Conclusion Bias due to nonresponse appears to be small in this study, and increasing the response rates had little effect on the results. Although misclassification is difficult to assess, the results suggest that bias due to reporting errors could be greater than bias caused by nonresponse. Resources might be better spent on improving and validating the data, rather than on increasing the response rate. PMID:18045472

Solving the problem of comparing whole bacterial genomes across different sequencing platforms.

PubMed

Kaas, Rolf S; Leekitcharoenphon, Pimlapas; Aarestrup, Frank M; Lund, Ole

2014-01-01

Whole genome sequencing (WGS) shows great potential for real-time monitoring and identification of infectious disease outbreaks. However, rapid and reliable comparison of data generated in multiple laboratories and using multiple technologies is essential. So far studies have focused on using one technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial data sets and sequenced on three different platforms (Illumina, 454, Ion Torrent). We show that the methods are able to overcome the systematic biases caused by the sequencers and infer the expected phylogenies. It is concluded that the cause of the success of these new procedures is due to a validation of all informative sites that are included in the analysis. The procedures are available as web tools.

Distribution of model uncertainty across multiple data streams

NASA Astrophysics Data System (ADS)

Wutzler, Thomas

2014-05-01

When confronting biogeochemical models with a diversity of observational data streams, we are faced with the problem of weighing the data streams. Without weighing or multiple blocked cost functions, model uncertainty is allocated to the sparse data streams and possible bias in processes that are strongly constraint is exported to processes that are constrained by sparse data streams only. In this study we propose an approach that aims at making model uncertainty a factor of observations uncertainty, that is constant over all data streams. Further we propose an implementation based on Monte-Carlo Markov chain sampling combined with simulated annealing that is able to determine this variance factor. The method is exemplified both with very simple models, artificial data and with an inversion of the DALEC ecosystem carbon model against multiple observations of Howland forest. We argue that the presented approach is able to help and maybe resolve the problem of bias export to sparse data streams.

Using local multiplicity to improve effect estimation from a hypothesis-generating pharmacogenetics study.

PubMed

Zou, W; Ouyang, H

2016-02-01

We propose a multiple estimation adjustment (MEA) method to correct effect overestimation due to selection bias from a hypothesis-generating study (HGS) in pharmacogenetics. MEA uses a hierarchical Bayesian approach to model individual effect estimates from maximal likelihood estimation (MLE) in a region jointly and shrinks them toward the regional effect. Unlike many methods that model a fixed selection scheme, MEA capitalizes on local multiplicity independent of selection. We compared mean square errors (MSEs) in simulated HGSs from naive MLE, MEA and a conditional likelihood adjustment (CLA) method that model threshold selection bias. We observed that MEA effectively reduced MSE from MLE on null effects with or without selection, and had a clear advantage over CLA on extreme MLE estimates from null effects under lenient threshold selection in small samples, which are common among 'top' associations from a pharmacogenetics HGS.

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.

The role of guessing and boundaries on date estimation biases.

PubMed

Lee, Peter James; Brown, Norman R

2004-08-01

This study investigates the causes of event-dating biases. Two hundred participants provided knowledge ratings and date estimates for 64 news events. Four independent groups dated the same events under different boundary constraints. Analysis across all responses showed that forward telescoping decreased with boundary age, concurring with the boundary-effects model. With guesses removed from the data set, backward telescoping was greatly reduced, but forward telescoping was unaffected by boundaries. This dissociation indicates that multiple factors (e.g., guessing and reconstructive strategies) are responsible for different dating biases and argue against a boundary explanation of forward telescoping.

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.

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis shows that terrestrial carbon and water cycle simulations in monsoon Asia were greatly improved, and the use of multiple satellite observations with this framework is an effective way for improving terrestrial biosphere models.

Accuracy of p53 Codon 72 Polymorphism Status Determined by Multiple Laboratory Methods: A Latent Class Model Analysis

PubMed Central

Walter, Stephen D.; Riddell, Corinne A.; Rabachini, Tatiana; Villa, Luisa L.; Franco, Eduardo L.

2013-01-01

Introduction Studies on the association of a polymorphism in codon 72 of the p53 tumour suppressor gene (rs1042522) with cervical neoplasia have inconsistent results. While several methods for genotyping p53 exist, they vary in accuracy and are often discrepant. Methods We used latent class models (LCM) to examine the accuracy of six methods for p53 determination, all conducted by the same laboratory. We also examined the association of p53 with cytological cervical abnormalities, recognising potential test inaccuracy. Results Pairwise disagreement between laboratory methods occurred approximately 10% of the time. Given the estimated true p53 status of each woman, we found that each laboratory method is most likely to classify a woman to her correct status. Arg/Arg women had the highest risk of squamous intraepithelial lesions (SIL). Test accuracy was independent of cytology. There was no strong evidence for correlations of test errors. Discussion Empirical analyses ignore possible laboratory errors, and so are inherently biased, but test accuracy estimated by the LCM approach is unbiased when model assumptions are met. LCM analysis avoids ambiguities arising from empirical test discrepancies, obviating the need to regard any of the methods as a “gold” standard measurement. The methods we presented here to analyse the p53 data can be applied in many other situations where multiple tests exist, but where none of them is a gold standard. PMID:23441193

Heuristics and bias in rectal surgery.

PubMed

MacDermid, Ewan; Young, Christopher J; Moug, Susan J; Anderson, Robert G; Shepherd, Heather L

2017-08-01

Deciding to defunction after anterior resection can be difficult, requiring cognitive tools or heuristics. From our previous work, increasing age and risk-taking propensity were identified as heuristic biases for surgeons in Australia and New Zealand (CSSANZ), and inversely proportional to the likelihood of creating defunctioning stomas. We aimed to assess these factors for colorectal surgeons in the British Isles, and identify other potential biases. The Association of Coloproctology of Great Britain and Ireland (ACPGBI) was invited to complete an online survey. Questions included demographics, risk-taking propensity, sensitivity to professional criticism, self-perception of anastomotic leak rate and propensity for creating defunctioning stomas. Chi-squared testing was used to assess differences between ACPGBI and CSSANZ respondents. Multiple regression analysis identified independent surgeon predictors of stoma formation. One hundred fifty (19.2%) eligible members of the ACPGBI replied. Demographics between ACPGBI and CSSANZ groups were well-matched. Significantly more ACPGBI surgeons admitted to anastomotic leak in the last year (p < 0.001). ACPGBI surgeon age over 50 (p = 0.02), higher risk-taking propensity across several domains (p = 0.044), self-belief in a lower-than-average anastomotic leak rate (p = 0.02) and belief that the average risk of leak after anterior resection is 8% or lower (p = 0.007) were all independent predictors of less frequent stoma formation. Sensitivity to criticism from colleagues was not a predictor of stoma formation. Unrecognised surgeon factors including age, everyday risk-taking, self-belief in surgical ability and lower probability bias of anastomotic leak appear to exert an effect on decision-making in rectal surgery.

When experience meets language statistics: Individual variability in processing English compound words.

PubMed

Falkauskas, Kaitlin; Kuperman, Victor

2015-11-01

Statistical patterns of language use demonstrably affect language comprehension and language production. This study set out to determine whether the variable amount of exposure to such patterns leads to individual differences in reading behavior as measured via eye-movements. Previous studies have demonstrated that more proficient readers are less influenced by distributional biases in language (e.g., frequency, predictability, transitional probability) than poor readers. We hypothesized that a probabilistic bias that is characteristic of written but not spoken language would preferentially affect readers with greater exposure to printed materials in general and to the specific pattern engendering the bias. Readers of varying reading experience were presented with sentences including English compound words that can occur in 2 spelling formats with differing probabilities: concatenated (windowsill, used 40% of the time) or spaced (window sill, 60%). Linear mixed effects multiple regression models fitted to the eye-movement measures showed that the probabilistic bias toward the presented spelling had a stronger facilitatory effect on compounds that occurred more frequently (in any spelling) or belonged to larger morphological families, and on readers with higher scores on a test of exposure-to-print. Thus, the amount of support toward the compound's spelling is effectively exploited when reading, but only when the spelling patterns are entrenched in an individual's mental lexicon via overall exposure to print and to compounds with alternating spelling. We argue that research on the interplay of language use and structure is incomplete without proper characterization of how particular individuals, with varying levels of experience and skill, learn these language structures. (c) 2015 APA, all rights reserved).

When experience meets language statistics: Individual variability in processing English compound words

PubMed Central

Falkauskas, Kaitlin; Kuperman, Victor

2015-01-01

Statistical patterns of language use demonstrably affect language comprehension and language production. This study set out to determine whether the variable amount of exposure to such patterns leads to individual differences in reading behaviour as measured via eye-movements. Previous studies have demonstrated that more proficient readers are less influenced by distributional biases in language (e.g. frequency, predictability, transitional probability) than poor readers. We hypothesized that a probabilistic bias that is characteristic of written but not spoken language would preferentially affect readers with greater exposure to printed materials in general and to the specific pattern engendering the bias. Readers of varying reading experience were presented with sentences including English compound words that can occur in two spelling formats with differing probabilities: concatenated (windowsill, used 40% of the time) or spaced (window sill, 60%). Linear mixed effects multiple regression models fitted to the eye-movement measures showed that the probabilistic bias towards the presented spelling had a stronger facilitatory effect on compounds that occurred more frequently (in any spelling) or belonged to larger morphological families, and on readers with higher scores on a test of exposure-to-print. Thus, the amount of support towards the compound’s spelling is effectively exploited when reading, but only when the spelling patterns are entrenched in an individual’s mental lexicon via overall exposure to print and to compounds with alternating spelling. We argue that research on the interplay of language use and structure is incomplete without proper characterization of how particular individuals, with varying levels of experience and skill, learn these language structures. PMID:26076328

Model-Based Control of Observer Bias for the Analysis of Presence-Only Data in Ecology

PubMed Central

Warton, David I.; Renner, Ian W.; Ramp, Daniel

2013-01-01

Presence-only data, where information is available concerning species presence but not species absence, are subject to bias due to observers being more likely to visit and record sightings at some locations than others (hereafter “observer bias”). In this paper, we describe and evaluate a model-based approach to accounting for observer bias directly – by modelling presence locations as a function of known observer bias variables (such as accessibility variables) in addition to environmental variables, then conditioning on a common level of bias to make predictions of species occurrence free of such observer bias. We implement this idea using point process models with a LASSO penalty, a new presence-only method related to maximum entropy modelling, that implicitly addresses the “pseudo-absence problem” of where to locate pseudo-absences (and how many). The proposed method of bias-correction is evaluated using systematically collected presence/absence data for 62 plant species endemic to the Blue Mountains near Sydney, Australia. It is shown that modelling and controlling for observer bias significantly improves the accuracy of predictions made using presence-only data, and usually improves predictions as compared to pseudo-absence or “inventory” methods of bias correction based on absences from non-target species. Future research will consider the potential for improving the proposed bias-correction approach by estimating the observer bias simultaneously across multiple species. PMID:24260167

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

An approach for estimating measurement uncertainty in medical laboratories using data from long-term quality control and external quality assessment schemes.

PubMed

Padoan, Andrea; Antonelli, Giorgia; Aita, Ada; Sciacovelli, Laura; Plebani, Mario

2017-10-26

The present study was prompted by the ISO 15189 requirements that medical laboratories should estimate measurement uncertainty (MU). The method used to estimate MU included the: a) identification of quantitative tests, b) classification of tests in relation to their clinical purpose, and c) identification of criteria to estimate the different MU components. Imprecision was estimated using long-term internal quality control (IQC) results of the year 2016, while external quality assessment schemes (EQAs) results obtained in the period 2015-2016 were used to estimate bias and bias uncertainty. A total of 263 measurement procedures (MPs) were analyzed. On the basis of test purpose, in 51 MPs imprecision only was used to estimate MU; in the remaining MPs, the bias component was not estimable for 22 MPs because EQAs results did not provide reliable statistics. For a total of 28 MPs, two or more MU values were calculated on the basis of analyte concentration levels. Overall, results showed that uncertainty of bias is a minor factor contributing to MU, the bias component being the most relevant contributor to all the studied sample matrices. The model chosen for MU estimation allowed us to derive a standardized approach for bias calculation, with respect to the fitness-for-purpose of test results. Measurement uncertainty estimation could readily be implemented in medical laboratories as a useful tool in monitoring the analytical quality of test results since they are calculated using a combination of both the long-term imprecision IQC results and bias, on the basis of EQAs results.

A robust method using propensity score stratification for correcting verification bias for binary tests

PubMed Central

He, Hua; McDermott, Michael P.

2012-01-01

Sensitivity and specificity are common measures of the accuracy of a diagnostic test. The usual estimators of these quantities are unbiased if data on the diagnostic test result and the true disease status are obtained from all subjects in an appropriately selected sample. In some studies, verification of the true disease status is performed only for a subset of subjects, possibly depending on the result of the diagnostic test and other characteristics of the subjects. Estimators of sensitivity and specificity based on this subset of subjects are typically biased; this is known as verification bias. Methods have been proposed to correct verification bias under the assumption that the missing data on disease status are missing at random (MAR), that is, the probability of missingness depends on the true (missing) disease status only through the test result and observed covariate information. When some of the covariates are continuous, or the number of covariates is relatively large, the existing methods require parametric models for the probability of disease or the probability of verification (given the test result and covariates), and hence are subject to model misspecification. We propose a new method for correcting verification bias based on the propensity score, defined as the predicted probability of verification given the test result and observed covariates. This is estimated separately for those with positive and negative test results. The new method classifies the verified sample into several subsamples that have homogeneous propensity scores and allows correction for verification bias. Simulation studies demonstrate that the new estimators are more robust to model misspecification than existing methods, but still perform well when the models for the probability of disease and probability of verification are correctly specified. PMID:21856650

Occupancy Modeling for Improved Accuracy and Understanding of Pathogen Prevalence and Dynamics

PubMed Central

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmon Oncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population: Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/ metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%. PMID:25738709

Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics

USGS Publications Warehouse

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmonOncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population:Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.

Total dose bias dependency and ELDRS effects in bipolar linear devices

NASA Technical Reports Server (NTRS)

Yui, C. C.; McClure, S. S.; Rex, B. G.; Lehman, J. M.; Minto, T. D.; Wiedeman, M.

2002-01-01

Total dose tests of several bipolar linear devices show sensitivity to both dose rate and bias during exposure. All devices exhibited Enhanced Low Dose Rate Sensitivity (ELDRS). An accelerated ELDRS test method for three different devices demonstrate results similar to tests at low dose rate. Behavior and critical parameters from these tests are compared and discussed.

Traumatogenic Processes and Pathways to Mental Health Outcomes for Sexual Minorities Exposed to Bias Crime Information.

PubMed

Lannert, Brittany K

2015-07-01

Vicarious traumatization of nonvictim members of communities targeted by bias crimes has been suggested by previous qualitative studies and often dominates public discussion following bias events, but proximal and distal responses of community members have yet to be comprehensively modeled, and quantitative research on vicarious responses is scarce. This comprehensive review integrates theoretical and empirical literatures in social, clinical, and physiological psychology in the development of a model of affective, cognitive, and physiological responses of lesbian, gay, and bisexual individuals upon exposure to information about bias crimes. Extant qualitative research in vicarious response to bias crimes is reviewed in light of theoretical implications and methodological limitations. Potential pathways to mental health outcomes are outlined, including accumulative effects of anticipatory defensive responding, multiplicative effects of minority stress, and putative traumatogenic physiological and cognitive processes of threat. Methodological considerations, future research directions, and clinical implications are also discussed. © The Author(s) 2014.

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.

bcROCsurface: an R package for correcting verification bias in estimation of the ROC surface and its volume for continuous diagnostic tests.

PubMed

To Duc, Khanh

2017-11-18

Receiver operating characteristic (ROC) surface analysis is usually employed to assess the accuracy of a medical diagnostic test when there are three ordered disease status (e.g. non-diseased, intermediate, diseased). In practice, verification bias can occur due to missingness of the true disease status and can lead to a distorted conclusion on diagnostic accuracy. In such situations, bias-corrected inference tools are required. This paper introduce an R package, named bcROCsurface, which provides utility functions for verification bias-corrected ROC surface analysis. The shiny web application of the correction for verification bias in estimation of the ROC surface analysis is also developed. bcROCsurface may become an important tool for the statistical evaluation of three-class diagnostic markers in presence of verification bias. The R package, readme and example data are available on CRAN. The web interface enables users less familiar with R to evaluate the accuracy of diagnostic tests, and can be found at http://khanhtoduc.shinyapps.io/bcROCsurface_shiny/ .

Model selection with multiple regression on distance matrices leads to incorrect inferences.

PubMed

Franckowiak, Ryan P; Panasci, Michael; Jarvis, Karl J; Acuña-Rodriguez, Ian S; Landguth, Erin L; Fortin, Marie-Josée; Wagner, Helene H

2017-01-01

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Mapping diffuse photosynthetically active radiation from satellite data in Thailand

NASA Astrophysics Data System (ADS)

Choosri, P.; Janjai, S.; Nunez, M.; Buntoung, S.; Charuchittipan, D.

2017-12-01

In this paper, calculation of monthly average hourly diffuse photosynthetically active radiation (PAR) using satellite data is proposed. Diffuse PAR was analyzed at four stations in Thailand. A radiative transfer model was used for calculating the diffuse PAR for cloudless sky conditions. Differences between the diffuse PAR under all sky conditions obtained from the ground-based measurements and those from the model are representative of cloud effects. Two models are developed, one describing diffuse PAR only as a function of solar zenith angle, and the second one as a multiple linear regression with solar zenith angle and satellite reflectivity acting linearly and aerosol optical depth acting in logarithmic functions. When tested with an independent data set, the multiple regression model performed best with a higher coefficient of variance R2 (0.78 vs. 0.70), lower root mean square difference (RMSD) (12.92% vs. 13.05%) and the same mean bias difference (MBD) of -2.20%. Results from the multiple regression model are used to map diffuse PAR throughout the country as monthly averages of hourly data.

Racial and Ethnic Bias in Test Construction. Final Report.

ERIC Educational Resources Information Center

Green, Donald Ross

To determine if tryout samples typically used for item selection contribute to test bias against minority groups, item analyses were made of the California Achievement Tests using seven subgroups of the standardization sample: Northern White Suburban, Northern Black Urban, Southern White Suburban, Southern Black Rural, Southern White Rural,…

Racial and Ethnic Bias in Test Construction.

ERIC Educational Resources Information Center

Green, Donald Ross

To determine if tryout samples typically used for item selection contribute to test bias against minority groups, item analyses were made of the California Achievement Tests using seven sub-groups of the standardization sample: Northern White Suburban, Northern Black Urban, Southern White Suburban, Southern Black Rural, Southern White Rural,…

Development of an accelerated reliability test schedule for terrestrial solar cells

NASA Technical Reports Server (NTRS)

Lathrop, J. W.; Prince, J. L.

1981-01-01

An accelerated test schedule using a minimum amount of tests and a minimum number of cells has been developed on the basis of stress test results obtained from more than 1500 cells of seven different cell types. The proposed tests, which include bias-temperature, bias-temperature-humidity, power cycle, thermal cycle, and thermal shock tests, use as little as 10 and up to 25 cells, depending on the test type.

Factorial Invariance of Woodcock-Johnson III Scores for African Americans and Caucasian Americans

ERIC Educational Resources Information Center

Edwards, Oliver W.; Oakland, Thomas D.

2006-01-01

Bias in testing has been of interest to psychologists and other test users since the origin of testing. New or revised tests often are subject to analyses that help examine the degree of bias in reference to group membership based on gender, language use, and race/ethnicity. The pervasive use of intelligence test data when making critical and, at…

A cautionary note on substituting spatial subunits for repeated temporal sampling in studies of site occupancy

USGS Publications Warehouse

Kendall, William L.; White, Gary C.

2009-01-01

1. Assessing the probability that a given site is occupied by a species of interest is important to resource managers, as well as metapopulation or landscape ecologists. Managers require accurate estimates of the state of the system, in order to make informed decisions. Models that yield estimates of occupancy, while accounting for imperfect detection, have proven useful by removing a potentially important source of bias. To account for detection probability, multiple independent searches per site for the species are required, under the assumption that the species is available for detection during each search of an occupied site. 2. We demonstrate that when multiple samples per site are defined by searching different locations within a site, absence of the species from a subset of these spatial subunits induces estimation bias when locations are exhaustively assessed or sampled without replacement. 3. We further demonstrate that this bias can be removed by choosing sampling locations with replacement, or if the species is highly mobile over a short period of time. 4. Resampling an existing data set does not mitigate bias due to exhaustive assessment of locations or sampling without replacement. 5. Synthesis and applications. Selecting sampling locations for presence/absence surveys with replacement is practical in most cases. Such an adjustment to field methods will prevent one source of bias, and therefore produce more robust statistical inferences about species occupancy. This will in turn permit managers to make resource decisions based on better knowledge of the state of the system.

Do people with and without medical conditions respond similarly to the short health anxiety inventory? An assessment of differential item functioning using item response theory.

PubMed

LeBouthillier, Daniel M; Thibodeau, Michel A; Alberts, Nicole M; Hadjistavropoulos, Heather D; Asmundson, Gordon J G

2015-04-01

Individuals with medical conditions are likely to have elevated health anxiety; however, research has not demonstrated how medical status impacts response patterns on health anxiety measures. Measurement bias can undermine the validity of a questionnaire by overestimating or underestimating scores in groups of individuals. We investigated whether the Short Health Anxiety Inventory (SHAI), a widely-used measure of health anxiety, exhibits medical condition-based bias on item and subscale levels, and whether the SHAI subscales adequately assess the health anxiety continuum. Data were from 963 individuals with diabetes, breast cancer, or multiple sclerosis, and 372 healthy individuals. Mantel-Haenszel tests and item characteristic curves were used to classify the severity of item-level differential item functioning in all three medical groups compared to the healthy group. Test characteristic curves were used to assess scale-level differential item functioning and whether the SHAI subscales adequately assess the health anxiety continuum. Nine out of 14 items exhibited differential item functioning. Two items exhibited differential item functioning in all medical groups compared to the healthy group. In both Thought Intrusion and Fear of Illness subscales, differential item functioning was associated with mildly deflated scores in medical groups with very high levels of the latent traits. Fear of Illness items poorly discriminated between individuals with low and very low levels of the latent trait. While individuals with medical conditions may respond differentially to some items, clinicians and researchers can confidently use the SHAI with a variety of medical populations without concern of significant bias. Copyright © 2015 Elsevier Inc. All rights reserved.

Motor Decisions Are Not Black and White: Selecting Actions in the “Gray Zone”

PubMed Central

Comalli, D. M.; Persand, D.; Adolph, K. E.

2017-01-01

In many situations, multiple actions are possible to achieve a goal. How do people select a particular action among equally possible alternatives? In six experiments, we determined whether action selection is consistent and biased toward one decision by observing participants’ decisions to go over or under a horizontal bar set at varying heights. We assessed the height at which participants transitioned from going over to under the bar within a “gray zone”—the range of bar heights at which going over and under were both possible. In Experiment 1, participants’ transition points were consistently located near the upper boundary of the gray zone, indicating a bias to go over rather than under the bar. Moreover, transitional behaviors were clustered tightly into a small region, indicating that decisions were highly consistent. Subsequent experiments examined potential influences on action selection. In Experiment 2, participants wore ankle weights to increase the cost of going over the bar. In Experiment 3, they were tested on a padded surface that made crawling under the bar more comfortable. In Experiment 4, we introduced a secondary task that required participants to crawl immediately after navigating the bar. None of these manipulations altered participants’ decisions relative to Experiment 1. In Experiment 5, participants started in a crawling position, which led to significantly lower transition points. In Experiment 6, we tested 5- to 6-year-old children as in Experiment 1 to determine the effects of social pressure on action selection. Children displayed lower transition points, larger transition regions, and reduced ability to go over the bar compared to adults. Across experiments, results indicate that adults have a strong and robust bias for upright locomotion. PMID:28293691

Neural correlates of visuospatial bias in patients with left hemisphere stroke: a causal functional contribution analysis based on game theory.

PubMed

Malherbe, C; Umarova, R M; Zavaglia, M; Kaller, C P; Beume, L; Thomalla, G; Weiller, C; Hilgetag, C C

2017-10-12

Stroke patients frequently display spatial neglect, an inability to report, or respond to, relevant stimuli in the contralesional space. Although this syndrome is widely considered to result from the dysfunction of a large-scale attention network, the individual contributions of damaged grey and white matter regions to neglect are still being disputed. Moreover, while the neuroanatomy of neglect in right hemispheric lesions is well studied, the contributions of left hemispheric brain regions to visuospatial processing are less well understood. To address this question, 128 left hemisphere acute stroke patients were investigated with respect to left- and rightward spatial biases measured as severity of deviation in the line bisection test and as Center of Cancellation (CoC) in the Bells Test. Causal functional contributions and interactions of nine predefined grey and white matter regions of interest in visuospatial processing were assessed using Multi-perturbation Shapley value Analysis (MSA). MSA, an inference approach based on game theory, constitutes a robust and exact multivariate mathematical method for inferring functional contributions from multi-lesion patterns. According to the analysis of performance in the Bells test, leftward attentional bias (contralesional deficit) was associated with contributions of the left superior temporal gyrus and rightward attentional bias with contributions of the left inferior parietal lobe, whereas the arcuate fascicle was contributed to both contra- and ipsilesional bias. Leftward and rightward deviations in the line bisection test were related to contributions of the superior longitudinal fascicle and the inferior parietal lobe, correspondingly. Thus, Bells test and line bisection tests, as well as ipsi- and contralesional attentional biases in these tests, have distinct neural correlates. Our findings demonstrate the contribution of different grey and white matter structures to contra- and ipsilesional spatial biases as revealed by left hemisphere stroke. The results provide new insights into the role of the left hemisphere in visuospatial processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple vaccinations, health, and recall bias within UK armed forces deployed to Iraq: cohort study.

PubMed

Murphy, Dominic; Hotopf, Matthew; Wessely, Simon

2008-06-30

To assess the relation between self reported number of vaccinations received and health, and between numbers of vaccinations recorded from individuals' medical records and health. First phase of a cohort study. UK armed forces personnel. 4882 randomly selected military personnel deployed to Iraq since 2003 and a subset of 378 whose vaccination records were accessed. Psychological distress, fatigue, symptoms of post-traumatic stress disorder, health perception, and multiple physical symptoms. Personnel who reported receiving two or more vaccinations on a single day were more likely to report symptoms of fatigue (adjusted risk ratio 1.17, 95% confidence interval 1.05 to 1.30), show caseness according to the general health questionnaire (1.31, 1.13 to 1.53), and have multiple physical symptoms (1.32, 1.08 to 1.60). These associations were no longer significant when number of vaccinations recorded in individuals' medical records was used as the independent variable. Multiple vaccinations given to personnel in the UK armed forces in preparation for deployment to Iraq are not associated with adverse health consequences when vaccinations are recorded objectively from medical records. Adverse health consequences associated with self reported multiple vaccinations could be explained by recall bias.

Caste-biased gene expression in a facultatively eusocial bee suggests a role for genetic accommodation in the evolution of eusociality

PubMed Central

Kingwell, Callum J.; Wcislo, William T.; Robinson, Gene E.

2017-01-01

Developmental plasticity may accelerate the evolution of phenotypic novelty through genetic accommodation, but studies of genetic accommodation often lack knowledge of the ancestral state to place selected traits in an evolutionary context. A promising approach for assessing genetic accommodation involves using a comparative framework to ask whether ancestral plasticity is related to the evolution of a particular trait. Bees are an excellent group for such comparisons because caste-based societies (eusociality) have evolved multiple times independently and extant species exhibit different modes of eusociality. We measured brain and abdominal gene expression in a facultatively eusocial bee, Megalopta genalis, and assessed whether plasticity in this species is functionally linked to eusocial traits in other bee lineages. Caste-biased abdominal genes in M. genalis overlapped significantly with caste-biased genes in obligately eusocial bees. Moreover, caste-biased genes in M. genalis overlapped significantly with genes shown to be rapidly evolving in multiple studies of 10 bee species, particularly for genes in the glycolysis pathway and other genes involved in metabolism. These results provide support for the idea that eusociality can evolve via genetic accommodation, with plasticity in facultatively eusocial species like M. genalis providing a substrate for selection during the evolution of caste in obligately eusocial lineages. PMID:28053060

Caste-biased gene expression in a facultatively eusocial bee suggests a role for genetic accommodation in the evolution of eusociality.

PubMed

Jones, Beryl M; Kingwell, Callum J; Wcislo, William T; Robinson, Gene E

2017-01-11

Developmental plasticity may accelerate the evolution of phenotypic novelty through genetic accommodation, but studies of genetic accommodation often lack knowledge of the ancestral state to place selected traits in an evolutionary context. A promising approach for assessing genetic accommodation involves using a comparative framework to ask whether ancestral plasticity is related to the evolution of a particular trait. Bees are an excellent group for such comparisons because caste-based societies (eusociality) have evolved multiple times independently and extant species exhibit different modes of eusociality. We measured brain and abdominal gene expression in a facultatively eusocial bee, Megalopta genalis, and assessed whether plasticity in this species is functionally linked to eusocial traits in other bee lineages. Caste-biased abdominal genes in M. genalis overlapped significantly with caste-biased genes in obligately eusocial bees. Moreover, caste-biased genes in M. genalis overlapped significantly with genes shown to be rapidly evolving in multiple studies of 10 bee species, particularly for genes in the glycolysis pathway and other genes involved in metabolism. These results provide support for the idea that eusociality can evolve via genetic accommodation, with plasticity in facultatively eusocial species like M. genalis providing a substrate for selection during the evolution of caste in obligately eusocial lineages. © 2017 The Author(s).

The Relationship History Calendar: Improving the Scope and Quality of Data on Youth Sexual Behavior*

PubMed Central

Luke, Nancy; Clark, Shelley; Zulu, Eliya

2012-01-01

Most survey data on sexual activities are obtained via face-to-face interviews, which are prone to misreporting of socially unacceptable behaviors. Demographers have developed various private response methods to minimize social desirability bias and improve the quality of reporting; however, these methods often limit the complexity of information collected. We designed a life history calendar—the Relationship History Calendar (RHC)—to increase the scope of data collected on sexual relationships and behavior while enhancing their quality. The RHC records detailed, 10-year retrospective information on sexual relationship histories. The structure and interview procedure draw on qualitative techniques, which could reduce social desirability bias. We evaluate the quality of data collected with the RHC compared to a standard face-to-face survey instrument through a field experiment conducted among 1275 youth in Kisumu, Kenya. The results suggest that the RHC reduces social desirability bias and improves reporting on multiple measures, including higher rates of abstinence among males and multiple recent sexual partnerships among females. The RHC fosters higher levels of rapport and respondent enjoyment, which appear to be the mechanisms through which social desirability bias is minimized. The RHC is an excellent alternative to private response methods and could potentially be adapted into large-scale surveys. PMID:21732169

The relationship history calendar: improving the scope and quality of data on youth sexual behavior.

PubMed

Luke, Nancy; Clark, Shelley; Zulu, Eliya M

2011-08-01

Most survey data on sexual activities are obtained via face-to-face interviews, which are prone to misreporting of socially unacceptable behaviors. Demographers have developed various private response methods to minimize social desirability bias and improve the quality of reporting; however, these methods often limit the complexity of information collected. We designed a life history calendar-the Relationship History Calendar (RHC)-to increase the scope of data collected on sexual relationships and behavior while enhancing their quality. The RHC records detailed, 10-year retrospective information on sexual relationship histories. The structure and interview procedure draw on qualitative techniques, which could reduce social desirability bias. We compare the quality of data collected with the RHC with a standard face-to-face survey instrument through a field experiment conducted among 1,275 youth in Kisumu, Kenya. The results suggest that the RHC reduces social desirability bias and improves reporting on multiple measures, including higher rates of abstinence among males and multiple recent sexual partnerships among females. The RHC fosters higher levels of rapport and respondent enjoyment, which appear to be the mechanisms through which social desirability bias is minimized. The RHC is an excellent alternative to private response methods and could potentially be adapted for large-scale surveys.

A pilot study of attention bias subtypes: examining their relation to cognitive bias and their change following cognitive behavioral therapy.

PubMed

Calamaras, Martha R; Tone, Erin B; Anderson, Page L

2012-07-01

The present investigation examined (a) whether a clinical sample of individuals with social anxiety disorder (SAD) comprises two distinct groups based on attention bias for social threat (vigilant, avoidant), (b) the relation between attention bias and cognitive bias, specifically estimates of the probability that negative social events will occur (probability bias), and (c) specific changes in attention bias following cognitive behavioral therapy for social anxiety. Participants were 24 individuals (nfemale = 7, nmale = 17; mage = 41) who met diagnostic criteria for SAD and sought treatment for fear of public speaking. Hypotheses were tested using t tests, linear regression analyses, and a mixed design analysis of variance. Results yielded evidence of 2 pretreatment groups (vigilant and avoidant). There was a significant positive correlation between vigilance for (but not avoidance of) threat and probability bias (R = .561, p < .05). After 8 weeks of treatment, the direction of change in attention bias differed between groups, such that the vigilant group became less vigilant and the avoidant group became less avoidant, with the avoidant group showing a significant change in attention bias from pretreatment to posttreatment. These findings provide very preliminary support for the idea that individuals with SAD may differ according to type attention bias, avoidant or vigilant, as these biases changed in different ways following cognitive-behavioral therapy for SAD. Further research is needed to replicate and extend these findings in order to evaluate whether SAD comprises subgroups of attentional biases. © 2012 Wiley Periodicals, Inc.

Dynamics of multiple infection and within-host competition by the anther-smut pathogen.

PubMed

Hood, M E

2003-07-01

Infection of one host by multiple pathogen genotypes represents an important area of pathogen ecology and evolution that lacks a broad empirical foundation. Multiple infection of Silene latifolia by Microbotryum violaceum was studied under field and greenhouse conditions using the natural polymorphism for mating-type bias as a marker. Field transmission resulted in frequent multiple infection, and each stem of the host was infected independently. Within-host diversity of infections equaled that of nearby inoculum sources by the end of the growing season. The number of diseased stems per plant was positively correlated with multiple infection and with overwintering mortality. As a result, multiply infected plants were largely purged from the population, and there was lower within-host pathogen diversity in the second season. However, among plants with a given number of diseased stems, multiply infected plants had a lower risk of overwintering mortality. Following simultaneous and sequential inoculation, strong competitive exclusion was demonstrated, and the first infection had a significant advantage. Dynamics of multiple infection initially included components of coinfection models for virulence evolution and then components of superinfection models after systemic colonization. Furthermore, there was evidence for an advantage of genotypes with mating-type bias, which may contribute to maintenance of this polymorphism in natural populations.

Psychodiagnostic and Psychotherapeutic Judgments: Expectation-Based Biases in Covariation Assessment.

ERIC Educational Resources Information Center

Alloy, Lauren B.

This paper considers three clinical judgment biases in clinical inference: (1) illusory correlation bias, the report by clinicians of a correlation between psychodiagnostic test signs and patient's symptoms which are not correlated or are correlated to a smaller degree than that reported; (2) labeling bias, the tendency of exposure to diagnositc…

Stator for a rotating electrical machine having multiple control windings

DOEpatents

Shah, Manoj R.; Lewandowski, Chad R.

2001-07-17

A rotating electric machine is provided which includes multiple independent control windings for compensating for rotor imbalances and for levitating/centering the rotor. The multiple independent control windings are placed at different axial locations along the rotor to oppose forces created by imbalances at different axial locations along the rotor. The multiple control windings can also be used to levitate/center the rotor with a relatively small magnetic field per unit area since the rotor and/or the main power winding provides the bias field.

A Comment on Early Student Blunders on Computer-Based Adaptive Tests

ERIC Educational Resources Information Center

Green, Bert F.

2011-01-01

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the "bias" can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not…

Bias-motivated bullying and psychosocial problems: implications for HIV risk behaviors among young men who have sex with men.

PubMed

Li, Michael Jonathan; Distefano, Anthony; Mouttapa, Michele; Gill, Jasmeet K

2014-02-01

The present study aimed to determine whether the experience of bias-motivated bullying was associated with behaviors known to increase the risk of HIV infection among young men who have sex with men (YMSM) aged 18-29, and to assess whether the psychosocial problems moderated this relationship. Using an Internet-based direct marketing approach in sampling, we recruited 545 YMSM residing in the USA to complete an online questionnaire. Multiple linear regression analyses tested three regression models where we controlled for sociodemographics. The first model indicated that bullying during high school was associated with unprotected receptive anal intercourse within the past 12 months, while the second model indicated that bullying after high school was associated with engaging in anal intercourse while under the influence of drugs or alcohol in the past 12 months. In the final regression model, our composite measure of HIV risk behavior was found to be associated with lifetime verbal harassment. None of the psychosocial problems measured in this study - depression, low self-esteem, and internalized homonegativity - moderated any of the associations between bias-motivated bullying victimization and HIV risk behaviors in our regression models. Still, these findings provide novel evidence that bullying prevention programs in schools and communities should be included in comprehensive approaches to HIV prevention among YMSM.

Reproductive and resource benefits to large female body size in a mammal with female-biased sexual size dimorphism

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

Fokidis, H.B., T.S. Risch and T.C. Glenn

Factors underlying the evolution of female-biased sexual size dimorphism in mammals are poorly understood. In an effort to better understand these factors we tested whether larger female southern flying squirrels, Glaucomys volans, gained reproductive advantages (larger litters or more male mates) and direct resource benefits, such as larger home ranges or access to more food (i.e. mast-producing trees). As dimorphism can vary with age in precocial breeding species, we compared females during their first reproduction and during a subsequent breeding attempt. Females were not significantly larger or heavier than males at first reproduction, but became about 7% heavier and 22%more » larger than males at subsequent breeding. Larger females produced larger litters and had home ranges containing a greater proportion of upland hardwood trees. Female body size was not associated with either multiple male mating or home range size, but females with larger home ranges had higher indexes of body condition. Females in precocial breeding flying squirrels initiate reproduction before sexual size dimorphism is evident, and thus, may be allocating resources to both reproduction and growth simultaneously, or delaying growth entirely. Larger females produce more pups and have access to more food resources. Thus, selection for increased female size may partly explain how female-biased sexual size dimorphism is maintained in this species.« less

Divorce and infidelity are associated with skewed adult sex ratios in birds.

PubMed

Liker, András; Freckleton, Robert P; Székely, Tamás

2014-04-14

Adult sex ratio (ASR) is a fundamental concept in population demography, and recent theory suggests that ASR plays a central role in social behavior, mating systems, and parental care. Unbalanced ASRs are predicted to influence pair-bond and mating behavior, since the rarer sex in the population has more potential partners to mate with than the more common sex. Here we use phylogenetic comparative analyses to test whether ASR is related to three major aspects of mating behavior: divorce, social polygamy, and pair-bond infidelity. ASR is strongly correlated with long-term pair bonds, since the divorce rate is higher in species with a female-biased sex ratio, indicating that mate change by pair members and/or breaking of pair bonds by unmated individuals is more frequent when females outnumber males. Short-term pair bonds are also associated with unbalanced ASRs: males are more commonly polygamous when females outnumber males, and conversely, females are more polygamous when males outnumber females. Furthermore, infidelity increases with male-biased ASR in socially monogamous birds, suggesting that male coercion and/or female willingness to cheat the partner are facilitated by male-biased ASR. Our results provide the first comprehensive support for the proposition that ASR influences multiple aspects of pair-bond and mating behavior in wild populations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cognitive bias in back pain patients attending osteopathy: testing the enmeshment model in reference to future thinking.

PubMed

Read, Jessica; Pincus, Tamar

2004-12-01

Depressive symptoms are common in chronic pain. Previous research has found differences in information-processing biases in depressed pain patients and depressed people without pain. The schema enmeshment model of pain (SEMP) has been proposed to explain chronic pain patients' information-processing biases. Negative future thinking is common in depression but has not been explored in relation to chronic pain and information-processing models. The study aimed to test the SEMP with reference to future thinking. An information-processing paradigm compared endorsement and recall bias between depressed and non-depressed chronic low back pain patients and control participants. Twenty-five depressed and 35 non-depressed chronic low back pain patients and 25 control participants (student osteopaths) were recruited from an osteopathy practice. Participants were asked to endorse positive and negative ill-health, depression-related, and neutral (control) adjectives, encoded in reference to either current or future time-frame. Incidental recall of the adjectives was then tested. While the expected hypothesis of a recall bias by depressed pain patients towards ill-health stimuli in the current condition was confirmed, the recall bias was not present in the future condition. Additionally, patterns of endorsement and recall bias differed. Results extend understanding of future thinking in chronic pain within the context of the SEMP.

Effects of Estimation Bias on Multiple-Category Classification with an IRT-Based Adaptive Classification Procedure

ERIC Educational Resources Information Center

Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R.

2006-01-01

The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…

Normalization Ridge Regression in Practice II: The Estimation of Multiple Feedback Linkages.

ERIC Educational Resources Information Center

Bulcock, J. W.

The use of the two-stage least squares (2 SLS) procedure for estimating nonrecursive social science models is often impractical when multiple feedback linkages are required. This is because 2 SLS is extremely sensitive to multicollinearity. The standard statistical solution to the multicollinearity problem is a biased, variance reduced procedure…

Highly stable thin film transistors using multilayer channel structure

NASA Astrophysics Data System (ADS)

Nayak, Pradipta K.; Wang, Zhenwei; Anjum, D. H.; Hedhili, M. N.; Alshareef, H. N.

2015-03-01

We report highly stable gate-bias stress performance of thin film transistors (TFTs) using zinc oxide (ZnO)/hafnium oxide (HfO2) multilayer structure as the channel layer. Positive and negative gate-bias stress stability of the TFTs was measured at room temperature and at 60 °C. A tremendous improvement in gate-bias stress stability was obtained in case of the TFT with multiple layers of ZnO embedded between HfO2 layers compared to the TFT with a single layer of ZnO as the semiconductor. The ultra-thin HfO2 layers act as passivation layers, which prevent the adsorption of oxygen and water molecules in the ZnO layer and hence significantly improve the gate-bias stress stability of ZnO TFTs.

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

Nayak, Pradipta K.; Wang, Zhenwei; Anjum, D. H.

We report highly stable gate-bias stress performance of thin film transistors (TFTs) using zinc oxide (ZnO)/hafnium oxide (HfO{sub 2}) multilayer structure as the channel layer. Positive and negative gate-bias stress stability of the TFTs was measured at room temperature and at 60 °C. A tremendous improvement in gate-bias stress stability was obtained in case of the TFT with multiple layers of ZnO embedded between HfO{sub 2} layers compared to the TFT with a single layer of ZnO as the semiconductor. The ultra-thin HfO{sub 2} layers act as passivation layers, which prevent the adsorption of oxygen and water molecules in the ZnOmore » layer and hence significantly improve the gate-bias stress stability of ZnO TFTs.« less

Winning the genetic lottery: biasing birth sex ratio results in more grandchildren.

PubMed

Thogerson, Collette M; Brady, Colleen M; Howard, Richard D; Mason, Georgia J; Pajor, Edmond A; Vicino, Greg A; Garner, Joseph P

2013-01-01

Population dynamics predicts that on average parents should invest equally in male and female offspring; similarly, the physiology of mammalian sex determination is supposedly stochastic, producing equal numbers of sons and daughters. However, a high quality parent can maximize fitness by biasing their birth sex ratio (SR) to the sex with the greatest potential to disproportionately outperform peers. All SR manipulation theories share a fundamental prediction: grandparents who bias birth SR should produce more grandoffspring via the favored sex. The celebrated examples of biased birth SRs in nature consistent with SR manipulation theories provide compelling circumstantial evidence. However, this prediction has never been directly tested in mammals, primarily because the complete three-generation pedigrees needed to test whether individual favored offspring produce more grandoffspring for the biasing grandparent are essentially impossible to obtain in nature. Three-generation pedigrees were constructed using 90 years of captive breeding records from 198 mammalian species. Male and female grandparents consistently biased their birth SR toward the sex that maximized second-generation success. The most strongly male-biased granddams and grandsires produced respectively 29% and 25% more grandoffspring than non-skewing conspecifics. The sons of the most male-biasing granddams were 2.7 times as fecund as those of granddams with a 50∶50 bias (similar results are seen in grandsires). Daughters of the strongest female-biasing granddams were 1.2 times as fecund as those of non-biasing females (this effect is not seen in grandsires). To our knowledge, these results are the first formal test of the hypothesis that birth SR manipulation is adaptive in mammals in terms of grandchildren produced, showing that SR manipulation can explain biased birth SR in general across mammalian species. These findings also have practical implications: parental control of birth SR has the potential to accelerate genetic loss and risk of extinction within captive populations of endangered species.

Bias in Prediction: A Test of Three Models with Elementary School Children

ERIC Educational Resources Information Center

Frazer, William G.; And Others

1975-01-01

Explores the differences among the traditional single-equation prediction model of test bias, the Cleary and the Thorndike model in a situation involving typical educational variables with young female and male children. (Author/DEP)

Zooming into creativity: individual differences in attentional global-local biases are linked to creative thinking.

PubMed

Zmigrod, Sharon; Zmigrod, Leor; Hommel, Bernhard

2015-01-01

While recent studies have investigated how processes underlying human creativity are affected by particular visual-attentional states, we tested the impact of more stable attention-related preferences. These were assessed by means of Navon's global-local task, in which participants respond to the global or local features of large letters constructed from smaller letters. Three standard measures were derived from this task: the sizes of the global precedence effect, the global interference effect (i.e., the impact of incongruent letters at the global level on local processing), and the local interference effect (i.e., the impact of incongruent letters at the local level on global processing). These measures were correlated with performance in a convergent-thinking creativity task (the Remote Associates Task), a divergent-thinking creativity task (the Alternate Uses Task), and a measure of fluid intelligence (Raven's matrices). Flexibility in divergent thinking was predicted by the local interference effect while convergent thinking was predicted by intelligence only. We conclude that a stronger attentional bias to visual information about the "bigger picture" promotes cognitive flexibility in searching for multiple solutions.

Maximum saliency bias in binocular fusion

NASA Astrophysics Data System (ADS)

Lu, Yuhao; Stafford, Tom; Fox, Charles

2016-07-01

Subjective experience at any instant consists of a single ("unitary"), coherent interpretation of sense data rather than a "Bayesian blur" of alternatives. However, computation of Bayes-optimal actions has no role for unitary perception, instead being required to integrate over every possible action-percept pair to maximise expected utility. So what is the role of unitary coherent percepts, and how are they computed? Recent work provided objective evidence for non-Bayes-optimal, unitary coherent, perception and action in humans; and further suggested that the percept selected is not the maximum a posteriori percept but is instead affected by utility. The present study uses a binocular fusion task first to reproduce the same effect in a new domain, and second, to test multiple hypotheses about exactly how utility may affect the percept. After accounting for high experimental noise, it finds that both Bayes optimality (maximise expected utility) and the previously proposed maximum-utility hypothesis are outperformed in fitting the data by a modified maximum-salience hypothesis, using unsigned utility magnitudes in place of signed utilities in the bias function.

Bias correction for magnetic resonance images via joint entropy regularization.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Luo, Jianhua; Huang, Qiu; Feng, Dagan; Li, Yuanxiang

2014-01-01

Due to the imperfections of the radio frequency (RF) coil or object-dependent electrodynamic interactions, magnetic resonance (MR) images often suffer from a smooth and biologically meaningless bias field, which causes severe troubles for subsequent processing and quantitative analysis. To effectively restore the original signal, this paper simultaneously exploits the spatial and gradient features of the corrupted MR images for bias correction via the joint entropy regularization. With both isotropic and anisotropic total variation (TV) considered, two nonparametric bias correction algorithms have been proposed, namely IsoTVBiasC and AniTVBiasC. These two methods have been applied to simulated images under various noise levels and bias field corruption and also tested on real MR data. The test results show that the proposed two methods can effectively remove the bias field and also present comparable performance compared to the state-of-the-art methods.

Bias to experience approaching motion in a three-dimensional virtual environment.

PubMed

Lewis, Clifford F; McBeath, Michael K

2004-01-01

We used two-frame apparent motion in a three-dimensional virtual environment to test whether observers had biases to experience approaching or receding motion in depth. Observers viewed a tunnel of tiles receding in depth, that moved ambiguously either toward or away from them. We found that observers exhibited biases to experience approaching motion. The strengths of the biases were decreased when stimuli pointed away, but size of the display screen had no effect. Tests with diamond-shaped tiles that varied in the degree of pointing asymmetry resulted in a linear trend in which the bias was strongest for stimuli pointing toward the viewer, and weakest for stimuli pointing away. We show that the overall bias to experience approaching motion is consistent with a computational strategy of matching corresponding features between adjacent foreshortened stimuli in consecutive visual frames. We conclude that there are both adaptational and geometric reasons to favor the experience of approaching motion.

Equity in Testing after Golden Rule.

ERIC Educational Resources Information Center

Goldstein, Harvey

The use of "bias elimination procedures" to reduce the racial bias of test items is discussed. These procedures were forwarded by G. R. Anrig (1988) and R. L. Linn and F. Drasgow (1987). Anrig stated that subjects who "know the same amount about a test item" should have a similar chance of answering it correctly…

Selection Bias in College Admissions Test Scores

ERIC Educational Resources Information Center

Clark, Melissa; Rothstein, Jesse; Schanzenbach, Diane Whitmore

2009-01-01

Data from college admissions tests can provide a valuable measure of student achievement, but the non-representativeness of test-takers is an important concern. We examine selectivity bias in both state-level and school-level SAT and ACT averages. The degree of selectivity may differ importantly across and within schools, and across and within…

IQ Testing and Minority School Children: Imperatives for Change.

ERIC Educational Resources Information Center

Barnes, Edward

The inadequacy and misuse of intelligence testing for minority group children are examined. IQ test items, norms, examining procedures, and language usage are discussed in terms of their bias against minority children. The implications of this bias for the classroom teacher are explored with the view that teacher mental sets are powerful mediators…

Introducing "Emotioncy" as a Potential Source of Test Bias: A Mixed Rasch Modeling Study

ERIC Educational Resources Information Center

Pishghadam, Reza; Baghaei, Purya; Seyednozadi, Zahra

2017-01-01

This article attempts to present emotioncy as a potential source of test bias to inform the analysis of test item performance. Emotioncy is defined as a hierarchy, ranging from "exvolvement" (auditory, visual, and kinesthetic) to "involvement" (inner and arch), to emphasize the emotions evoked by the senses. This study…

A novel biasing dependent circuit model of resonant cavity enhanced avalanche photodetectors (RCE-APDs)

NASA Astrophysics Data System (ADS)

Abdelhamid, Mostafa R.; El-Batawy, Yasser M.; Deen, M. Jamal

2018-02-01

In Resonant Cavity Enhanced Photodetectors (RCE-PDs), the trade-off between the bandwidth and the quantum efficiency in the conventional photodetectors is overcome. In RCE-PDs, large bandwidth can be achieved using a thin absorption layer while the use of a resonant cavity allows for multiple passes of light in the absorption which boosts the quantum efficiency. In this paper, a complete bias-dependent model for the Resonant Cavity Enhanced-Separated Absorption Graded Charge Multiplication-Avalanche Photodetector (RCE-SAGCM-APD) is presented. The proposed model takes into account the case of drift velocities other than the saturation velocity, thus modeling this effect on the photodetector different design parameters such as Gain, Bandwidth and Gain-Bandwidth product.

Administration of serotonin inhibitor p-Chlorophenylalanine induces pessimistic-like judgement bias in sheep.

PubMed

Doyle, Rebecca E; Hinch, Geoff N; Fisher, Andrew D; Boissy, Alain; Henshall, John M; Lee, Caroline

2011-02-01

Judgement bias has potential as a measure of affective state in animals. The serotonergic system may be one mechanism involved with the formation of negative judgement biases. It was hypothesised that depletion of brain serotonin would induce negative judgement biases in sheep. A dose response trial established that 40 mg/kg of p-Chlorophenylalanine (pCPA) administered to sheep for 3 days did not affect feeding motivation or locomotion required for testing judgement biases. Thirty Merino ewes (10 months old) were trained to an operant task for 3 weeks. Sheep learnt to approach a bucket when it was placed in one corner of the testing facility to receive a feed reward (go response), and not approach it when in the alternate corner (no-go response) to avoid a negative reinforcer (exposure to a dog). Following training, 15 sheep were treated with pCPA (40 mg/kg daily) for an extended duration (5 days). Treated and control sheep were tested for judgement bias following 3 and 5 days of treatment, and again 5 days after cessation of treatment. Testing involved the bucket being presented in ambiguous locations between the two learnt locations, and the response of the sheep (go/no-go) measured their judgement of the bucket locations. Following 5 days of treatment, pCPA-treated sheep approached the most positive ambiguous location significantly less than control sheep, suggesting a pessimistic-like bias (treatment × bucket location interaction F(1,124.6)=49.97, p=0.011). A trend towards a significant interaction was still evident 5 days after the cessation of pCPA treatment (p=0.068), however no significant interaction was seen on day 3 of testing (p=0.867). These results support the suggestion that judgement bias is a cognitive measure of affective state, and that the serotonergic pathway may be involved. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Impact of Software Settings on Multiple-Breath Washout Outcomes.

PubMed

Summermatter, Selina; Singer, Florian; Latzin, Philipp; Yammine, Sophie

2015-01-01

Multiple-breath washout (MBW) is an attractive test to assess ventilation inhomogeneity, a marker of peripheral lung disease. Standardization of MBW is hampered as little data exists on possible measurement bias. We aimed to identify potential sources of measurement bias based on MBW software settings. We used unprocessed data from nitrogen (N2) MBW (Exhalyzer D, Eco Medics AG) applied in 30 children aged 5-18 years: 10 with CF, 10 formerly preterm, and 10 healthy controls. This setup calculates the tracer gas N2 mainly from measured O2 and CO2concentrations. The following software settings for MBW signal processing were changed by at least 5 units or >10% in both directions or completely switched off: (i) environmental conditions, (ii) apparatus dead space, (iii) O2 and CO2 signal correction, and (iv) signal alignment (delay time). Primary outcome was the change in lung clearance index (LCI) compared to LCI calculated with the settings as recommended. A change in LCI exceeding 10% was considered relevant. Changes in both environmental and dead space settings resulted in uniform but modest LCI changes and exceeded >10% in only two measurements. Changes in signal alignment and O2 signal correction had the most relevant impact on LCI. Decrease of O2 delay time by 40 ms (7%) lead to a mean LCI increase of 12%, with >10% LCI change in 60% of the children. Increase of O2 delay time by 40 ms resulted in mean LCI decrease of 9% with LCI changing >10% in 43% of the children. Accurate LCI results depend crucially on signal processing settings in MBW software. Especially correct signal delay times are possible sources of incorrect LCI measurements. Algorithms of signal processing and signal alignment should thus be optimized to avoid susceptibility of MBW measurements to this significant measurement bias.

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

A Bayesian hierarchical approach to galaxy-galaxy lensing

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Leauthaud, Alexie

2018-07-01

We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter haloes and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does not resort to stacking the weak lensing signal in bins, and thus allows for a more efficient use of the information content in the data. Our method is particularly useful for constraining scaling relations between two or more galaxy properties and dark matter halo mass, and can also be used to constrain the intrinsic scatter in these scaling relations. We show that, if observational scatter is not properly accounted for, the traditional stacking method can produce biased results when exploring correlations between multiple galaxy properties and halo mass. For example, this bias can affect studies of the joint correlation between galaxy mass, halo mass, and galaxy size, or galaxy colour. In contrast, our method easily and efficiently handles the intrinsic and observational scatter in multiple galaxy properties and halo mass. We test our method on mocks with varying degrees of complexity. We find that we can recover the mean halo mass and concentration, each with a 0.1 dex accuracy, and the intrinsic scatter in halo mass with a 0.05 dex accuracy. In its current version, our method will be most useful for studying the weak lensing signal around central galaxies in groups and clusters, as well as massive galaxies samples with log M* > 11, which have low satellite fractions.

A Bayesian Hierarchical Approach to Galaxy-Galaxy Lensing

NASA Astrophysics Data System (ADS)

Sonnenfeld, Alessandro; Leauthaud, Alexie

2018-04-01

We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter halos and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does not resort to stacking the weak lensing signal in bins, and thus allows for a more efficient use of the information content in the data. Our method is particularly useful for constraining scaling relations between two or more galaxy properties and dark matter halo mass, and can also be used to constrain the intrinsic scatter in these scaling relations. We show that, if observational scatter is not properly accounted for, the traditional stacking method can produce biased results when exploring correlations between multiple galaxy properties and halo mass. For example, this bias can affect studies of the joint correlation between galaxy mass, halo mass, and galaxy size, or galaxy colour. In contrast, our method easily and efficiently handles the intrinsic and observational scatter in multiple galaxy properties and halo mass. We test our method on mocks with varying degrees of complexity. We find that we can recover the mean halo mass and concentration, each with a 0.1 dex accuracy, and the intrinsic scatter in halo mass with a 0.05 dex accuracy. In its current version, our method will be most useful for studying the weak lensing signal around central galaxies in groups and clusters, as well as massive galaxies samples with log M* > 11, which have low satellite fractions.

Development and validation of a Response Bias Scale (RBS) for the MMPI-2.

PubMed

Gervais, Roger O; Ben-Porath, Yossef S; Wygant, Dustin B; Green, Paul

2007-06-01

This study describes the development of a Minnesota Multiphasic Personality Inventory (MMPI-2) scale designed to detect negative response bias in forensic neuropsychological or disability assessment settings. The Response Bias Scale (RBS) consists of 28 MMPI-2 items that discriminated between persons who passed or failed the Word Memory Test (WMT), Computerized Assessment of Response Bias (CARB), and/or Test of Memory Malingering (TOMM) in a sample of 1,212 nonhead-injury disability claimants. Incremental validity of the RBS was evaluated by comparing its ability to detect poor performance on four separate symptom validity tests with that of the F and F(P) scales and the Fake Bad Scale (FBS). The RBS consistently outperformed F, F(P), and FBS. Study results suggest that the RBS may be a useful addition to existing MMPI-2 validity scales and indices in detecting symptom complaints predominantly associated with cognitive response bias and overreporting in forensic neuropsychological and disability assessment settings.

Effects of imperfect test sensitivity and specificity on observational studies of influenza vaccine effectiveness.

PubMed

Jackson, Michael L; Rothman, Kenneth J

2015-03-10

The recently developed test-negative design is now standard for observational studies of influenza vaccine effectiveness (VE). It is unclear how influenza test misclassification biases test-negative VE estimates relative to VE estimates from traditional cohort or case-control studies. We simulated populations whose members may develop acute respiratory illness (ARI) due to influenza and to non-influenza pathogens. In these simulations, vaccination reduces the risk of influenza but not of non-influenza ARI. Influenza test sensitivity and specificity, risks of influenza and non-influenza ARI, and VE were varied across the simulations. In each simulation, we estimated influenza VE using a cohort design, a case-control design, and a test-negative design. In the absence of influenza test misclassification, all three designs accurately estimated influenza VE. In the presence of misclassification, all three designs underestimated VE. Bias in VE estimates was slightly greater in the test-negative design than in cohort or case-control designs. Assuming the use of highly sensitive and specific reverse-transcriptase polymerase chain reaction tests for influenza, bias in the test-negative studies was trivial across a wide range of realistic values for VE. Although influenza test misclassification causes more bias in test-negative studies than in traditional cohort or case-control studies, the difference is trivial for realistic combinations of attack rates, test sensitivity/specificity, and VE. Copyright © 2015 Elsevier Ltd. All rights reserved.

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Multiple Imputation of Cognitive Performance as a Repeatedly Measured Outcome

PubMed Central

Rawlings, Andreea M.; Sang, Yingying; Sharrett, A. Richey; Coresh, Josef; Griswold, Michael; Kucharska-Newton, Anna M.; Palta, Priya; Wruck, Lisa M.; Gross, Alden L.; Deal, Jennifer A.; Power, Melinda C.; Bandeen-Roche, Karen

2016-01-01

Background Longitudinal studies of cognitive performance are sensitive to dropout, as participants experiencing cognitive deficits are less likely to attend study visits, which may bias estimated associations between exposures of interest and cognitive decline. Multiple imputation is a powerful tool for handling missing data, however its use for missing cognitive outcome measures in longitudinal analyses remains limited. Methods We use multiple imputation by chained equations (MICE) to impute cognitive performance scores of participants who did not attend the 2011-2013 exam of the Atherosclerosis Risk in Communities Study. We examined the validity of imputed scores using observed and simulated data under varying assumptions. We examined differences in the estimated association between diabetes at baseline and 20-year cognitive decline with and without imputed values. Lastly, we discuss how different analytic methods (mixed models and models fit using generalized estimate equations) and choice of for whom to impute result in different estimands. Results Validation using observed data showed MICE produced unbiased imputations. Simulations showed a substantial reduction in the bias of the 20-year association between diabetes and cognitive decline comparing MICE (3-4% bias) to analyses of available data only (16-23% bias) in a construct where missingness was strongly informative but realistic. Associations between diabetes and 20-year cognitive decline were substantially stronger with MICE than in available-case analyses. Conclusions Our study suggests when informative data are available for non-examined participants, MICE can be an effective tool for imputing cognitive performance and improving assessment of cognitive decline, though careful thought should be given to target imputation population and analytic model chosen, as they may yield different estimands. PMID:27619926

Testing for Bias against Female Test Takers of the Graduate Management Admissions Test and Potential Impact on Admissions to Graduate Programs in Business.

ERIC Educational Resources Information Center

Wright, Robert E.; Bachrach, Daniel G.

2003-01-01

Graduate Management Admission Test (GMAT) scores and grade point average in graduate core courses were compared for 190 male and 144 female business administration students. No significant differences in course performance were found, but males had been admitted with significantly higher GMAT scores, suggesting a bias against women. (Contains 27…

The impact of mass deworming programmes on schooling and economic development: an appraisal of long-term studies

PubMed Central

Jullien, Sophie; Sinclair, David; Garner, Paul

2016-01-01

Abstract Background: Documents from advocacy and fund-raising organizations for child mass deworming programmes in low- and middle-income countries cite unpublished economic studies claiming long-term effects on health, schooling and economic development. Methods: To summarize and appraise these studies, we searched for and included all long-term follow-up studies based on cluster-randomized trials included in a 2015 Cochrane review on deworming. We used Cochrane methods to assess risk of bias, and appraised the credibility of the main findings. Where necessary we contacted study authors for clarifications. Results: We identified three studies (Baird 2016, Ozier 2016 and Croke 2014) evaluating effects more than 9 years after cluster-randomized trials in Kenya and Uganda. Baird and Croke evaluate short additional exposures to deworming programmes in settings where all children were dewormed multiple times. Ozier evaluates potential spin-off effects to infants living in areas with school-based deworming. None of the studies used pre-planned protocols nor blinded the analysis to treatment allocation. Baird 2016 has been presented online in six iterations. The work is at high risk of reporting bias and selective reporting, and there are substantive changes between versions. The main cited effects on secondary school attendance and job sector allocation are from post hoc subgroup analyses, which the study was not powered to assess. The study did not find any evidence of effect on nutritional status, cognitive tests or school grades achieved, but these are not reported in the abstracts. Ozier 2016 has been presented online in four iterations, without substantive differences between versions. Higher cognitive test scores were associated with deworming, but the appropriate analysis was underpowered to reliably detect these effects. The size of the stated effect seems inconsistent with the short and indirect nature of the exposure to deworming, and a causal pathway for this effect is unclear. Croke 2014 uses a data set unrelated to the base trial, to report improvements in English and maths test scores. The analysis is at high risk of attrition bias, due to loss of clusters, and is substantially underpowered to assess these effects. Conclusions: In the context of reliable epidemiological methods, all three studies are at risk of substantial methodological bias. They therefore help in generating hypotheses, but should not be considered to provide reliable evidence of effects. PMID:28161712

PubMed Central

PANATTO, D.; ARATA, L.; BEVILACQUA, I.; APPRATO, L.; GASPARINI, R.; AMICIZIA, D.

2015-01-01

Summary Introduction. Health-related knowledge is often assessed through multiple-choice tests. Among the different types of formats, researchers may opt to use multiple-mark items, i.e. with more than one correct answer. Although multiple-mark items have long been used in the academic setting – sometimes with scant or inconclusive results – little is known about the implementation of this format in research on in-field health education and promotion. Methods. A study population of secondary school students completed a survey on nutrition-related knowledge, followed by a single- lecture intervention. Answers were scored by means of eight different scoring algorithms and analyzed from the perspective of classical test theory. The same survey was re-administered to a sample of the students in order to evaluate the short-term change in their knowledge. Results. In all, 286 questionnaires were analyzed. Partial scoring algorithms displayed better psychometric characteristics than the dichotomous rule. In particular, the algorithm proposed by Ripkey and the balanced rule showed greater internal consistency and relative efficiency in scoring multiple-mark items. A penalizing algorithm in which the proportion of marked distracters was subtracted from that of marked correct answers was the only one that highlighted a significant difference in performance between natives and immigrants, probably owing to its slightly better discriminatory ability. This algorithm was also associated with the largest effect size in the pre-/post-intervention score change. Discussion. The choice of an appropriate rule for scoring multiple- mark items in research on health education and promotion should consider not only the psychometric properties of single algorithms but also the study aims and outcomes, since scoring rules differ in terms of biasness, reliability, difficulty, sensitivity to guessing and discrimination. PMID:26900331

Measurement and control of bias in patient reported outcomes using multidimensional item response theory.

PubMed

Dowling, N Maritza; Bolt, Daniel M; Deng, Sien; Li, Chenxi

2016-05-26

Patient-reported outcome (PRO) measures play a key role in the advancement of patient-centered care research. The accuracy of inferences, relevance of predictions, and the true nature of the associations made with PRO data depend on the validity of these measures. Errors inherent to self-report measures can seriously bias the estimation of constructs assessed by the scale. A well-documented disadvantage of self-report measures is their sensitivity to response style (RS) effects such as the respondent's tendency to select the extremes of a rating scale. Although the biasing effect of extreme responding on constructs measured by self-reported tools has been widely acknowledged and studied across disciplines, little attention has been given to the development and systematic application of methodologies to assess and control for this effect in PRO measures. We review the methodological approaches that have been proposed to study extreme RS effects (ERS). We applied a multidimensional item response theory model to simultaneously estimate and correct for the impact of ERS on trait estimation in a PRO instrument. Model estimates were used to study the biasing effects of ERS on sum scores for individuals with the same amount of the targeted trait but different levels of ERS. We evaluated the effect of joint estimation of multiple scales and ERS on trait estimates and demonstrated the biasing effects of ERS on these trait estimates when used as explanatory variables. A four-dimensional model accounting for ERS bias provided a better fit to the response data. Increasing levels of ERS showed bias in total scores as a function of trait estimates. The effect of ERS was greater when the pattern of extreme responding was the same across multiple scales modeled jointly. The estimated item category intercepts provided evidence of content independent category selection. Uncorrected trait estimates used as explanatory variables in prediction models showed downward bias. A comprehensive evaluation of the psychometric quality and soundness of PRO assessment measures should incorporate the study of ERS as a potential nuisance dimension affecting the accuracy and validity of scores and the impact of PRO data in clinical research and decision making.

Bias in the physical examination of patients with lumbar radiculopathy

PubMed Central

2010-01-01

Background No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. Methods This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing. Results The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Conclusions Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated sensory deficit on examination is used in medical decision-making. Further studies of bias should include surgical clinic populations and other common diagnoses including shoulder, knee and hip pathology. PMID:21118558

Bias in the physical examination of patients with lumbar radiculopathy.

PubMed

Suri, Pradeep; Hunter, David J; Katz, Jeffrey N; Li, Ling; Rainville, James

2010-11-30

No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing. The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated sensory deficit on examination is used in medical decision-making. Further studies of bias should include surgical clinic populations and other common diagnoses including shoulder, knee and hip pathology.

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.

Do Health Claims and Front-of-Pack Labels Lead to a Positivity Bias in Unhealthy Foods?

PubMed Central

Talati, Zenobia; Pettigrew, Simone; Dixon, Helen; Neal, Bruce; Ball, Kylie; Hughes, Clare

2016-01-01

Health claims and front-of-pack labels (FoPLs) may lead consumers to hold more positive attitudes and show a greater willingness to buy food products, regardless of their actual healthiness. A potential negative consequence of this positivity bias is the increased consumption of unhealthy foods. This study investigated whether a positivity bias would occur in unhealthy variations of four products (cookies, corn flakes, pizzas and yoghurts) that featured different health claim conditions (no claim, nutrient claim, general level health claim, and higher level health claim) and FoPL conditions (no FoPL, the Daily Intake Guide (DIG), Multiple Traffic Lights (MTL), and the Health Star Rating (HSR)). Positivity bias was assessed via measures of perceived healthiness, global evaluations (incorporating taste, quality, convenience, etc.) and willingness to buy. On the whole, health claims did not produce a positivity bias, while FoPLs did, with the DIG being the most likely to elicit this bias. The HSR most frequently led to lower ratings of unhealthy foods than the DIG and MTL, suggesting that this FoPL has the lowest risk of creating an inaccurate positivity bias in unhealthy foods. PMID:27918426

Who can escape the natural number bias in rational number tasks? A study involving students and experts.

PubMed

Obersteiner, Andreas; Hoof, Jo Van; Verschaffel, Lieven; Dooren, Wim Van

2016-08-01

Many learners have difficulties with rational number tasks because they persistently rely on their natural number knowledge, which is not always applicable. Studies show that such a natural number bias can mislead not only children but also educated adults. It is still unclear whether and under what conditions mathematical expertise enables people to be completely unaffected by such a bias on tasks in which people with less expertise are clearly biased. We compared the performance of eighth-grade students and expert mathematicians on the same set of algebraic expression problems that addressed the effect of arithmetic operations (multiplication and division). Using accuracy and response time measures, we found clear evidence for a natural number bias in students but no traces of a bias in experts. The data suggested that whereas students based their answers on their intuitions about natural numbers, expert mathematicians relied on their skilled intuitions about algebraic expressions. We conclude that it is possible for experts to be unaffected by the natural number bias on rational number tasks when they use strategies that do not involve natural numbers. © 2015 The British Psychological Society.

Selection Bias in College Admissions Test Scores. NBER Working Paper No. 14265

ERIC Educational Resources Information Center

Clark, Melissa; Rothstein, Jesse; Schanzenbach, Diane Whitmore

2008-01-01

Data from college admissions tests can provide a valuable measure of student achievement, but the non-representativeness of test-takers is an important concern. We examine selectivity bias in both state-level and school-level SAT and ACT averages. The degree of selectivity may differ importantly across and within schools, and across and within…

The Model Identification Test: Perceptual Bias of Elementary School Children Using a Limited Verbal Evaluation Instrument

ERIC Educational Resources Information Center

McIntyre, Patrick J.

1974-01-01

Reported is a study to verify the pattern of bias associated with the Model Identification Test and to determine its source. This instrument is a limited verbal science test designed to determine the knowledge possessed by elementary school children of selected concepts related to "the particle nature of matter." (PEB)

Comparison of Procedures for Detecting Test-Item Bias with Both Internal and External Ability Criteria.

ERIC Educational Resources Information Center

Shepard, Lorrie, And Others

1981-01-01

Sixteen approaches for detecting item bias were compared on samples of Black, White, and Chicano elementary school pupils using the Lorge-Thorndike and Raven's Coloured Progressive Matrices tests. Recommendations for practical use are made. (JKS)

Bias in the Counseling Process: How to Recognize and Avoid It.

ERIC Educational Resources Information Center

Morrow, Kelly A.; Deidan, Cecilia T.

1992-01-01

Notes that counselors' vulnerability to inferential bias during counseling process may result in misdiagnosis and improper interventions. Discusses these inferential biases: availability and representativeness heuristics; fundamental attribution error; anchoring, prior knowledge, and labeling; confirmatory hypothesis testing; and reconstructive…

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

A semiconductor nanowire Josephson junction microwave laser

NASA Astrophysics Data System (ADS)

Cassidy, Maja; Uilhoorn, Willemijn; Kroll, James; de Jong, Damaz; van Woerkom, David; Nygard, Jesper; Krogstrup, Peter; Kouwenhoven, Leo

We present measurements of microwave lasing from a single Al/InAs/Al nanowire Josephson junction strongly coupled to a high quality factor superconducting cavity. Application of a DC bias voltage to the Josephson junction results in photon emission into the cavity when the bias voltage is equal to a multiple of the cavity frequency. At large voltage biases, the strong non-linearity of the circuit allows for efficient down conversion of high frequency microwave photons down to multiple photons at the fundamental frequency of the cavity. In this regime, the emission linewidth narrows significantly below the bare cavity linewidth to < 10 kHz and real time analysis of the emission statistics shows above threshold lasing with a power conversion efficiency > 50%. The junction-cavity coupling and laser emission can be tuned rapidly via an external gate, making it suitable to be integrated into a scalable qubit architecture as a versatile source of coherent microwave radiation. This work has been supported by the Netherlands Organisation for Scientific Research (NWO/OCW), Foundation for Fundamental Research on Matter (FOM), European Research Council (ERC), and Microsoft Corporation Station Q.

Bias-corrected diagnostic performance of the naked-eye single-tube red-cell osmotic fragility test (NESTROFT): an effective screening tool for beta-thalassemia.

PubMed

Mamtani, Manju; Jawahirani, Anil; Das, Kishor; Rughwani, Vinky; Kulkarni, Hemant

2006-08-01

It is being increasingly recognized that a majority of the countries in the thalassemia-belt need a cost-effective screening program as the first step towards control of thalassemia. Although the naked eye single tube red cell osmotic fragility test (NESTROFT) has been considered to be a very effective screening tool for beta-thalassemia trait, assessment of its diagnostic performance has been affected with the reference test- and verification-bias. Here, we set out to provide estimates of sensitivity and specificity of NESTROFT corrected for these potential biases. We conducted a cross-sectional diagnostic test evaluation study using data from 1563 subjects from Central India with a high prevalence of beta-thalassemia. We used latent class modelling after ensuring its validity to account for the reference test bias and global sensitivity analysis to control the verification bias. We also compared the results of latent class modelling with those of five discriminant indexes. We observed that across a range of cut-offs for the mean corpuscular volume (MCV) and the hemoglobin A2 (HbA2) concentration the average sensitivity and specificity of NESTROFT obtained from latent class modelling was 99.8 and 83.7%, respectively. These estimates were comparable to those characterizing the diagnostic performance of HbA2, which is considered by many as the reference test to detect beta-thalassemia. After correction for the verification bias these estimates were 93.4 and 97.2%, respectively. Combined with the inexpensive and quick disposition of NESTROFT, these results strongly support its candidature as a screening tool-especially in the resource-poor and high-prevalence settings.

Opportunistic biases: Their origins, effects, and an integrated solution.

PubMed

DeCoster, Jamie; Sparks, Erin A; Sparks, Jordan C; Sparks, Glenn G; Sparks, Cheri W

2015-09-01

Researchers commonly explore their data in multiple ways before deciding which analyses they will include in the final versions of their papers. While this improves the chances of researchers finding publishable results, it introduces an "opportunistic bias," such that the reported relations are stronger or otherwise more supportive of the researcher's theories than they would be without the exploratory process. The magnitudes of opportunistic biases can often be stronger than those of the effects being investigated, leading to invalid conclusions and a lack of clarity in research results. Authors typically do not report their exploratory procedures, so opportunistic biases are very difficult to detect just by reading the final version of a research report. In this article, we explain how a number of accepted research practices can lead to opportunistic biases, discuss the prevalence of these practices in psychology, consider the different effects that opportunistic biases have on psychological science, evaluate the strategies that methodologists have proposed to prevent or correct for the effects of these biases, and introduce an integrated solution to reduce the prevalence and influence of opportunistic biases. The recent prominence of articles discussing questionable research practices both in scientific journals and in the public media underscores the importance of understanding how opportunistic biases are created and how we might undo their effects. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

"TNOs are Cool": A survey of the trans-Neptunian region. XIII. Statistical analysis of multiple trans-Neptunian objects observed with Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Kovalenko, I. D.; Doressoundiram, A.; Lellouch, E.; Vilenius, E.; Müller, T.; Stansberry, J.

2017-11-01

Context. Gravitationally bound multiple systems provide an opportunity to estimate the mean bulk density of the objects, whereas this characteristic is not available for single objects. Being a primitive population of the outer solar system, binary and multiple trans-Neptunian objects (TNOs) provide unique information about bulk density and internal structure, improving our understanding of their formation and evolution. Aims: The goal of this work is to analyse parameters of multiple trans-Neptunian systems, observed with Herschel and Spitzer space telescopes. Particularly, statistical analysis is done for radiometric size and geometric albedo, obtained from photometric observations, and for estimated bulk density. Methods: We use Monte Carlo simulation to estimate the real size distribution of TNOs. For this purpose, we expand the dataset of diameters by adopting the Minor Planet Center database list with available values of the absolute magnitude therein, and the albedo distribution derived from Herschel radiometric measurements. We use the 2-sample Anderson-Darling non-parametric statistical method for testing whether two samples of diameters, for binary and single TNOs, come from the same distribution. Additionally, we use the Spearman's coefficient as a measure of rank correlations between parameters. Uncertainties of estimated parameters together with lack of data are taken into account. Conclusions about correlations between parameters are based on statistical hypothesis testing. Results: We have found that the difference in size distributions of multiple and single TNOs is biased by small objects. The test on correlations between parameters shows that the effective diameter of binary TNOs strongly correlates with heliocentric orbital inclination and with magnitude difference between components of binary system. The correlation between diameter and magnitude difference implies that small and large binaries are formed by different mechanisms. Furthermore, the statistical test indicates, although not significant with the sample size, that a moderately strong correlation exists between diameter and bulk density. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Effects of Text-Belief Consistency and Reading Task on the Strategic Validation of Multiple Texts

ERIC Educational Resources Information Center

Maier, Johanna; Richter, Tobias

2016-01-01

In the comprehension of multiple controversial scientific texts, readers with strong prior beliefs tend to construct a one-sided mental representation that is biased towards belief-consistent information. In the present study, we examined whether an argument in contrast to a summary task instruction can increase the resource allocation to and…

Comprehension of Multiple Documents with Conflicting Information: A Two-Step Model of Validation

ERIC Educational Resources Information Center

Richter, Tobias; Maier, Johanna

2017-01-01

In this article, we examine the cognitive processes that are involved when readers comprehend conflicting information in multiple texts. Starting from the notion of routine validation during comprehension, we argue that readers' prior beliefs may lead to a biased processing of conflicting information and a one-sided mental model of controversial…

Multimodal Likelihoods in Educational Assessment: Will the Real Maximum Likelihood Score Please Stand up?

ERIC Educational Resources Information Center

Wothke, Werner; Burket, George; Chen, Li-Sue; Gao, Furong; Shu, Lianghua; Chia, Mike

2011-01-01

It has been known for some time that item response theory (IRT) models may exhibit a likelihood function of a respondent's ability which may have multiple modes, flat modes, or both. These conditions, often associated with guessing of multiple-choice (MC) questions, can introduce uncertainty and bias to ability estimation by maximum likelihood…

Valence-Dependent Belief Updating: Computational Validation

PubMed Central

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments. PMID:28706499

Valence-Dependent Belief Updating: Computational Validation.

PubMed

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments.

Spatial Correlation Bias in Thermochronologically Derived Late Cenozoic Erosion Histories

NASA Astrophysics Data System (ADS)

Schildgen, T. F.; van Der Beek, P.; Sinclair, H. D.; Thiede, R. C.

2017-12-01

The potential link between erosion rates at the Earth's surface and changes in global climate has intrigued geoscientists for decades, as such a coupling has implications for the influence of silicate weathering and organic-carbon burial on climate, as well as the role of Quaternary glaciations on landscape evolution. A global increase in late-Cenozoic erosion rates in response to a cooling, more variable climate has been proposed based on a compilation of deposition rates in sedimentary basins worldwide. However, it has been argued that the stratigraphic record could show an apparent increase in rates toward the present due to a preservation bias linked to stochastic erosional events, depositional hiatuses, and varying measurement intervals. More recently, a global compilation of thermochronology data has been used to infer a nearly two-fold increase in erosion rates from mountainous landscapes over the late Cenozoic. It is contended that this result is free of the biases that affect sedimentary records. Here, we test this assumption and demonstrate that in addition to the bias resulting from the relative timescales over which thermochronological data are averaged, there is a bias associated with spatial variations in exhumation rates among points that are combined to derive exhumation histories. Whether one or multiple thermochronological systems are used to reconstruct an erosion history, there is always an apparent increase in rates toward the present when combining data that have not shared a common exhumation history (e.g., samples collected from different sides of an active tectonic boundary). Such unwarranted combinations commonly arise when inversions of thermochronological data are performed using an a priori scheme that combines data points according to an assumed spatial correlation structure. We find that in nearly all cases where such inversions have been performed, spatial gradients in erosion rates are converted into apparent temporal increases. On a global scale, currently available thermochronology data provide limited resolution concerning the impact of late Cenozoic climate change on erosion rates. These results, combined with previous analyses of bias in the sedimentary record, call into question the evidence presented to date for a worldwide increase in late Cenozoic erosion rates.

Comparison of single cell sequencing data between two whole genome amplification methods on two sequencing platforms.

PubMed

Chen, DaYang; Zhen, HeFu; Qiu, Yong; Liu, Ping; Zeng, Peng; Xia, Jun; Shi, QianYu; Xie, Lin; Zhu, Zhu; Gao, Ya; Huang, GuoDong; Wang, Jian; Yang, HuanMing; Chen, Fang

2018-03-21

Research based on a strategy of single-cell low-coverage whole genome sequencing (SLWGS) has enabled better reproducibility and accuracy for detection of copy number variations (CNVs). The whole genome amplification (WGA) method and sequencing platform are critical factors for successful SLWGS (<0.1 × coverage). In this study, we compared single cell and multiple cells sequencing data produced by the HiSeq2000 and Ion Proton platforms using two WGA kits and then comprehensively evaluated the GC-bias, reproducibility, uniformity and CNV detection among different experimental combinations. Our analysis demonstrated that the PicoPLEX WGA Kit resulted in higher reproducibility, lower sequencing error frequency but more GC-bias than the GenomePlex Single Cell WGA Kit (WGA4 kit) independent of the cell number on the HiSeq2000 platform. While on the Ion Proton platform, the WGA4 kit (both single cell and multiple cells) had higher uniformity and less GC-bias but lower reproducibility than those of the PicoPLEX WGA Kit. Moreover, on these two sequencing platforms, depending on cell number, the performance of the two WGA kits was different for both sensitivity and specificity on CNV detection. The results can help researchers who plan to use SLWGS on single or multiple cells to select appropriate experimental conditions for their applications.

Implicit Racial Biases in Preschool Children and Adults from Asia and Africa

ERIC Educational Resources Information Center

Qian, Miao K.; Heyman, Gail D.; Quinn, Paul C.; Messi, Francoise A.; Fu, Genyue; Lee, Kang

2016-01-01

This research used an Implicit Racial Bias Test to investigate implicit racial biases among 3- to 5-year-olds and adult participants in China (N = 213) and Cameroon (N = 257). In both cultures, participants displayed high levels of racial biases that remained stable between 3 and 5 years of age. Unlike adults, young children's implicit racial…

Further tests of entreaties to avoid hypothetical bias in referendum contingent valuation

Treesearch

Thomas C. Brown; Icek Ajzen; Daniel Hrubes

2003-01-01

Over-estimation of willingness to pay in contingent markets has been attributed largely to hypothetical bias. One promising approach for avoiding hypothetical bias is to tell respondents enough about such bias that they self-correct for it. A script designed for this purpose by Cummings and Taylor was used in hypothetical referenda that differed in payment amount. In...

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

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

Walker, Anthony P; Hanson, Paul J; DeKauwe, Martin G

2014-01-01

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often relatedmore » to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.« less

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.

Multivariate Statistics Applied to Seismic Phase Picking

NASA Astrophysics Data System (ADS)

Velasco, A. A.; Zeiler, C. P.; Anderson, D.; Pingitore, N. E.

2008-12-01

The initial effort of the Seismogram Picking Error from Analyst Review (SPEAR) project has been to establish a common set of seismograms to be picked by the seismological community. Currently we have 13 analysts from 4 institutions that have provided picks on the set of 26 seismograms. In comparing the picks thus far, we have identified consistent biases between picks from different institutions; effects of the experience of analysts; and the impact of signal-to-noise on picks. The institutional bias in picks brings up the important concern that picks will not be the same between different catalogs. This difference means less precision and accuracy when combing picks from multiple institutions. We also note that depending on the experience level of the analyst making picks for a catalog the error could fluctuate dramatically. However, the experience level is based off of number of years in picking seismograms and this may not be an appropriate criterion for determining an analyst's precision. The common data set of seismograms provides a means to test an analyst's level of precision and biases. The analyst is also limited by the quality of the signal and we show that the signal-to-noise ratio and pick error are correlated to the location, size and distance of the event. This makes the standard estimate of picking error based on SNR more complex because additional constraints are needed to accurately constrain the measurement error. We propose to extend the current measurement of error by adding the additional constraints of institutional bias and event characteristics to the standard SNR measurement. We use multivariate statistics to model the data and provide constraints to accurately assess earthquake location and measurement errors.

Explaining Differential Reporting of Victimization between Parents and Children: A Consideration of Social Biases.

PubMed

John, Sufna Gheyara; DiLalla, Lisabeth F

2013-09-01

Studies have shown that children and parents provide different reports of children's victimization, with children often reporting more victimization. However, the reason for this differential reporting is unclear. This study explored two types of social biases (emotion recognition and perceived impairment) in parents and children as possible reasons underlying differential reporting. Six- to 10-year-old children and one of their parents were tested in a lab. Testing included subjective measures of parent alexithymic traits, child perceived impairment from victimization, and child- and parent-reported frequency of children's peer victimization and internalizing and externalizing difficulties. Parents and children also completed an objective measure of emotion recognition. Both types of social bias significantly predicted reports of children's peer victimization frequency as well as internalizing and externalizing difficulties, as rated by parents and children. Moreover, child perceived impairment bias, rather than parent emotion bias, best predicted differential reporting of peer victimization. Finally, a significant interaction demonstrated that the influence of child perceived impairment bias on differential reporting was most salient in the presence of parent emotion bias. This underscores the importance of expanding interventions for victimized youth to include the restructuring of social biases.

Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation.

PubMed

Usmanova, Dinara R; Bogatyreva, Natalya S; Ariño Bernad, Joan; Eremina, Aleksandra A; Gorshkova, Anastasiya A; Kanevskiy, German M; Lonishin, Lyubov R; Meister, Alexander V; Yakupova, Alisa G; Kondrashov, Fyodor A; Ivankov, Dmitry N

2018-05-02

Computational prediction of the effect of mutations on protein stability is used by researchers in many fields. The utility of the prediction methods is affected by their accuracy and bias. Bias, a systematic shift of the predicted change of stability, has been noted as an issue for several methods, but has not been investigated systematically. Presence of the bias may lead to misleading results especially when exploring the effects of combination of different mutations. Here we use a protocol to measure the bias as a function of the number of introduced mutations. It is based on a self-consistency test of the reciprocity the effect of a mutation. An advantage of the used approach is that it relies solely on crystal structures without experimentally measured stability values. We applied the protocol to four popular algorithms predicting change of protein stability upon mutation, FoldX, Eris, Rosetta, and I-Mutant, and found an inherent bias. For one program, FoldX, we manage to substantially reduce the bias using additional relaxation by Modeller. Authors using algorithms for predicting effects of mutations should be aware of the bias described here. ivankov13@gmail.com. Supplementary data are available at Bioinformatics online.

Is the General Self-Efficacy Scale a Reliable Measure to be used in Cross-Cultural Studies? Results from Brazil, Germany and Colombia.

PubMed

Damásio, Bruno F; Valentini, Felipe; Núñes-Rodriguez, Susana I; Kliem, Soeren; Koller, Sílvia H; Hinz, Andreas; Brähler, Elmar; Finck, Carolyn; Zenger, Markus

2016-05-26

This study evaluated cross-cultural measurement invariance for the General Self-efficacy Scale (GSES) in a large Brazilian (N = 2.394) and representative German (N = 2.046) and Colombian (N = 1.500) samples. Initially, multiple-indicators multiple-causes (MIMIC) analyses showed that sex and age were biasing items responses on the total sample (2 and 10 items, respectively). After controlling for these two covariates, a multigroup confirmatory factor analysis (MGCFA) was employed. Configural invariance was attested. However, metric invariance was not supported for five items, in a total of 10, and scalar invariance was not supported for all items. We also evaluated the differences between the latent scores estimated by two models: MIMIC and MGCFA unconstraining the non-equivalent parameters across countries. The average difference was equal to |.07| on the estimation of the latent scores, and 22.8% of the scores were biased in at least .10 standardized points. Bias effects were above the mean for the German group, which the average difference was equal to |.09|, and 33.7% of the scores were biased in at least .10. In synthesis, the GSES did not provide evidence of measurement invariance to be employed in this cross-cultural study. More than that, our results showed that even when controlling for sex and age effects, the absence of control on items parameters in the MGCFA analyses across countries would implicate in bias of the latent scores estimation, with a higher effect for the German population.

Attitudes Toward Obese Persons and Weight Locus of Control in Chinese Nurses: A Cross-sectional Survey.

PubMed

Wang, Yan; Ding, Ye; Song, Daoping; Zhu, Daqiao; Wang, Jianrong

2016-01-01

Obese individuals frequently experience weight-related bias or discrimination-even in healthcare settings. Although obesity bias has been associated with several demographic factors, little is known about the association of weight locus of control with bias against overweight persons or about weight bias among Chinese health professionals. The aim of the study was to examine attitudes toward obese patients in a sample of Chinese registered nurses (RNs) and the relationship between weight bias and nurses' weight locus of control. RNs working in nine community health service centers across Shanghai, China, answered three self-report questionnaires: The Attitudes Toward Obese Persons Scale (ATOP), the External Weight Locus of Control Subscale (eWLOC) from the Dieting Belief Scale, and a sociodemographic profile. Hierarchical, stepwise, multiple regression was used to predict ATOP scores. From among 385 invited, a total of 297 RNs took part in the study (77.1% response rate). Participants scored an average of 71.04 on the ATOP, indicating slightly positive attitudes toward obese persons, and 30.08 on the eWLOC, indicating a belief in the uncontrollability of body weight. Using hierarchical, stepwise, multiple regression, two predictors of ATOP scores were statistically significant (eWLOC scores and status as a specialist rather than generalist nurse), but explained variance was low. Chinese RNs seemed to have relatively neutral or even slightly positive attitudes toward obese persons. Those nurses who believed that obesity was beyond the individual's control or worked in specialties were more likely to have positive attitudes toward obese people. Improved understanding of the comprehensive etiology of obesity is needed.

Comparing Perceptions with Actual Reports of Close Friend's HIV Testing Behavior Among Urban Tanzanian Men.

PubMed

Mulawa, Marta; Yamanis, Thespina J; Balvanz, Peter; Kajula, Lusajo J; Maman, Suzanne

2016-09-01

Men have lower rates of HIV testing and higher rates of AIDS-related mortality compared to women in sub-Saharan Africa. To assess whether there is an opportunity to increase men's uptake of testing by correcting misperceptions about testing norms, we compare men's perceptions of their closest friend's HIV testing behaviors with the friend's actual testing self-report using a unique dataset of men sampled within their social networks (n = 59) in Dar es Salaam, Tanzania. We examine the accuracy and bias of perceptions among men who have tested for HIV (n = 391) and compare them to the perceptions among men who never tested (n = 432). We found that testers and non-testers did not differ in the accuracy of their perceptions, though non-testers were strongly biased towards assuming that their closest friends had not tested. Our results lend support to social norms approaches designed to correct the biased misperceptions of non-testers to promote men's HIV testing.