Calibration transfer of a Raman spectroscopic quantification method for the assessment of liquid detergent compositions from at-line laboratory to in-line industrial scale.

PubMed

Brouckaert, D; Uyttersprot, J-S; Broeckx, W; De Beer, T

2018-03-01

Calibration transfer or standardisation aims at creating a uniform spectral response on different spectroscopic instruments or under varying conditions, without requiring a full recalibration for each situation. In the current study, this strategy is applied to construct at-line multivariate calibration models and consequently employ them in-line in a continuous industrial production line, using the same spectrometer. Firstly, quantitative multivariate models are constructed at-line at laboratory scale for predicting the concentration of two main ingredients in hard surface cleaners. By regressing the Raman spectra of a set of small-scale calibration samples against their reference concentration values, partial least squares (PLS) models are developed to quantify the surfactant levels in the liquid detergent compositions under investigation. After evaluating the models performance with a set of independent validation samples, a univariate slope/bias correction is applied in view of transporting these at-line calibration models to an in-line manufacturing set-up. This standardisation technique allows a fast and easy transfer of the PLS regression models, by simply correcting the model predictions on the in-line set-up, without adjusting anything to the original multivariate calibration models. An extensive statistical analysis is performed in order to assess the predictive quality of the transferred regression models. Before and after transfer, the R 2 and RMSEP of both models is compared for evaluating if their magnitude is similar. T-tests are then performed to investigate whether the slope and intercept of the transferred regression line are not statistically different from 1 and 0, respectively. Furthermore, it is inspected whether no significant bias can be noted. F-tests are executed as well, for assessing the linearity of the transfer regression line and for investigating the statistical coincidence of the transfer and validation regression line. Finally, a paired t-test is performed to compare the original at-line model to the slope/bias corrected in-line model, using interval hypotheses. It is shown that the calibration models of Surfactant 1 and Surfactant 2 yield satisfactory in-line predictions after slope/bias correction. While Surfactant 1 passes seven out of eight statistical tests, the recommended validation parameters are 100% successful for Surfactant 2. It is hence concluded that the proposed strategy for transferring at-line calibration models to an in-line industrial environment via a univariate slope/bias correction of the predicted values offers a successful standardisation approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptation and application of multivariate AMBI (M-AMBI) in US coastal waters.

PubMed

Pelletier, Marguerite C; Gillett, David J; Hamilton, Anna; Grayson, Treda; Hansen, Virginia; Leppo, Erik W; Weisberg, Stephan B; Borja, Angel

2018-06-01

The multivariate AMBI (M-AMBI) is an extension of the AZTI Marine Biotic Index (AMBI) that has been used extensively in Europe, but not in the United States. In a previous study, we adapted AMBI for use in US coastal waters (US AMBI), but saw biases in salinity and score distribution when compared to locally calibrated indices. In this study we modified M-AMBI for US waters and compared its performance to that of US AMBI. Index performance was evaluated in three ways: 1) concordance with local indices presently being used as management tools in three geographic regions of US coastal waters, 2) classification accuracy for sites defined a priori as good or bad and 3) insensitivity to natural environmental gradients. US M-AMBI was highly correlated with all three local indices and removed the compression in response seen in moderately disturbed sites with US AMBI. US M-AMBI and US AMBI did a similar job correctly classifying sites as good or bad in local validation datasets (83 to 100% accuracy vs. 84 to 95%, respectively). US M-AMBI also removed the salinity bias of US AMBI so that lower salinity sites were not more likely to be incorrectly classified as impaired. The US M-AMBI appears to be an acceptable index for comparing condition across broad-scales such as estuarine and coastal waters surveyed by the US EPA's National Coastal Condition Assessment, and may be applicable to areas of the US coast that do not have a locally derived benthic index.

A Comparison of Three Multivariate Models for Estimating Test Battery Reliability.

ERIC Educational Resources Information Center

Wood, Terry M.; Safrit, Margaret J.

1987-01-01

A comparison of three multivariate models (canonical reliability model, maximum generalizability model, canonical correlation model) for estimating test battery reliability indicated that the maximum generalizability model showed the least degree of bias, smallest errors in estimation, and the greatest relative efficiency across all experimental…

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

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

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

A Study of Item Bias for Attitudinal Measurement Using Maximum Likelihood Factor Analysis.

ERIC Educational Resources Information Center

Mayberry, Paul W.

A technique for detecting item bias that is responsive to attitudinal measurement considerations is a maximum likelihood factor analysis procedure comparing multivariate factor structures across various subpopulations, often referred to as SIFASP. The SIFASP technique allows for factorial model comparisons in the testing of various hypotheses…

Systematic review of the methodological quality of controlled trials evaluating Chinese herbal medicine in patients with rheumatoid arthritis

PubMed Central

Pan, Xin; Lopez-Olivo, Maria A; Song, Juhee; Pratt, Gregory; Suarez-Almazor, Maria E

2017-01-01

Objectives We appraised the methodological and reporting quality of randomised controlled clinical trials (RCTs) evaluating the efficacy and safety of Chinese herbal medicine (CHM) in patients with rheumatoid arthritis (RA). Design For this systematic review, electronic databases were searched from inception until June 2015. The search was limited to humans and non-case report studies, but was not limited by language, year of publication or type of publication. Two independent reviewers selected RCTs, evaluating CHM in RA (herbals and decoctions). Descriptive statistics were used to report on risk of bias and their adherence to reporting standards. Multivariable logistic regression analysis was performed to determine study characteristics associated with high or unclear risk of bias. Results Out of 2342 unique citations, we selected 119 RCTs including 18 919 patients: 10 108 patients received CHM alone and 6550 received one of 11 treatment combinations. A high risk of bias was observed across all domains: 21% had a high risk for selection bias (11% from sequence generation and 30% from allocation concealment), 85% for performance bias, 89% for detection bias, 4% for attrition bias and 40% for reporting bias. In multivariable analysis, fewer authors were associated with selection bias (allocation concealment), performance bias and attrition bias, and earlier year of publication and funding source not reported or disclosed were associated with selection bias (sequence generation). Studies published in non-English language were associated with reporting bias. Poor adherence to recommended reporting standards (<60% of the studies not providing sufficient information) was observed in 11 of the 23 sections evaluated. Limitations Study quality and data extraction were performed by one reviewer and cross-checked by a second reviewer. Translation to English was performed by one reviewer in 85% of the included studies. Conclusions Studies evaluating CHM often fail to meet expected methodological criteria, and high-quality evidence is lacking. PMID:28249848

The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?

PubMed

Maloney, Ryan T

2015-01-01

Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues (J Neurosci 33: 19695-19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies. Copyright © 2015 the American Physiological Society.

Adaptation and application of multivariate AMBI (M-AMBI) in US coastal waters

EPA Science Inventory

The multivariate AMBI (M-AMBI) is an extension of the AZTI Marine Biotic Index (AMBI) that has been used extensively in Europe, but not in the United States. In a previous study, we adapted AMBI for use in US coastal waters (US AMBI), but saw biases in salinity and score distribu...

Sex determination from the femur in Portuguese populations with classical and machine-learning classifiers.

PubMed

Curate, F; Umbelino, C; Perinha, A; Nogueira, C; Silva, A M; Cunha, E

2017-11-01

The assessment of sex is of paramount importance in the establishment of the biological profile of a skeletal individual. Femoral relevance for sex estimation is indisputable, particularly when other exceedingly dimorphic skeletal regions are missing. As such, this study intended to generate population-specific osteometric models for the estimation of sex with the femur and to compare the accuracy of the models obtained through classical and machine-learning classifiers. A set of 15 standard femoral measurements was acquired in a training sample (100 females; 100 males) from the Coimbra Identified Skeletal Collection (University of Coimbra, Portugal) and models for sex classification were produced with logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM), and reduce error pruning trees (REPTree). Under cross-validation, univariable sectioning points generated with REPTree correctly estimated sex in 60.0-87.5% of cases (systematic error ranging from 0.0 to 37.0%), while multivariable models correctly classified sex in 84.0-92.5% of cases (bias from 0.0 to 7.0%). All models were assessed in a holdout sample (24 females; 34 males) from the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal), with an allocation accuracy ranging from 56.9 to 86.2% (bias from 4.4 to 67.0%) in the univariable models, and from 84.5 to 89.7% (bias from 3.7 to 23.3%) in the multivariable models. This study makes available a detailed description of sexual dimorphism in femoral linear dimensions in two Portuguese identified skeletal samples, emphasizing the relevance of the femur for the estimation of sex in skeletal remains in diverse conditions of completeness and preservation. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Post-processing of multi-hydrologic model simulations for improved streamflow projections

NASA Astrophysics Data System (ADS)

khajehei, sepideh; Ahmadalipour, Ali; Moradkhani, Hamid

2016-04-01

Hydrologic model outputs are prone to bias and uncertainty due to knowledge deficiency in model and data. Uncertainty in hydroclimatic projections arises due to uncertainty in hydrologic model as well as the epistemic or aleatory uncertainties in GCM parameterization and development. This study is conducted to: 1) evaluate the recently developed multi-variate post-processing method for historical simulations and 2) assess the effect of post-processing on uncertainty and reliability of future streamflow projections in both high-flow and low-flow conditions. The first objective is performed for historical period of 1970-1999. Future streamflow projections are generated for 10 statistically downscaled GCMs from two widely used downscaling methods: Bias Corrected Statistically Downscaled (BCSD) and Multivariate Adaptive Constructed Analogs (MACA), over the period of 2010-2099 for two representative concentration pathways of RCP4.5 and RCP8.5. Three semi-distributed hydrologic models were employed and calibrated at 1/16 degree latitude-longitude resolution for over 100 points across the Columbia River Basin (CRB) in the pacific northwest USA. Streamflow outputs are post-processed through a Bayesian framework based on copula functions. The post-processing approach is relying on a transfer function developed based on bivariate joint distribution between the observation and simulation in historical period. Results show that application of post-processing technique leads to considerably higher accuracy in historical simulations and also reducing model uncertainty in future streamflow projections.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

Unconscious race and class bias: its association with decision making by trauma and acute care surgeons.

PubMed

Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Freischlag, Julie A; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A

2014-09-01

Recent studies have found that unconscious biases may influence physicians' clinical decision making. The objective of our study was to determine, using clinical vignettes, if unconscious race and class biases exist specifically among trauma/acute care surgeons and, if so, whether those biases impact surgeons' clinical decision making. A prospective Web-based survey was administered to active members of the Eastern Association for the Surgery of Trauma. Participants completed nine clinical vignettes, each with three trauma/acute care surgery management questions. Race Implicit Association Test (IAT) and social class IAT assessments were completed by each participant. Multivariable, ordered logistic regression analysis was then used to determine whether implicit biases reflected on the IAT tests were associated with vignette responses. In total, 248 members of the Eastern Association for the Surgery of Trauma participated. Of these, 79% explicitly stated that they had no race preferences and 55% stated they had no social class preferences. However, 73.5% of the participants had IAT scores demonstrating an unconscious preference toward white persons; 90.7% demonstrated an implicit preference toward upper social class persons. Only 2 of 27 vignette-based clinical decisions were associated with patient race or social class on univariate analyses. Multivariable analyses revealed no relationship between IAT scores and vignette-based clinical assessments. Unconscious preferences for white and upper-class persons are prevalent among trauma and acute care surgeons. In this study, these biases were not statistically significantly associated with clinical decision making. Further study of the factors that may prevent implicit biases from influencing patient management is warranted. Epidemiologic study, level II.

Systematic review of the methodological quality of controlled trials evaluating Chinese herbal medicine in patients with rheumatoid arthritis.

PubMed

Pan, Xin; Lopez-Olivo, Maria A; Song, Juhee; Pratt, Gregory; Suarez-Almazor, Maria E

2017-03-01

We appraised the methodological and reporting quality of randomised controlled clinical trials (RCTs) evaluating the efficacy and safety of Chinese herbal medicine (CHM) in patients with rheumatoid arthritis (RA). For this systematic review, electronic databases were searched from inception until June 2015. The search was limited to humans and non-case report studies, but was not limited by language, year of publication or type of publication. Two independent reviewers selected RCTs, evaluating CHM in RA (herbals and decoctions). Descriptive statistics were used to report on risk of bias and their adherence to reporting standards. Multivariable logistic regression analysis was performed to determine study characteristics associated with high or unclear risk of bias. Out of 2342 unique citations, we selected 119 RCTs including 18 919 patients: 10 108 patients received CHM alone and 6550 received one of 11 treatment combinations. A high risk of bias was observed across all domains: 21% had a high risk for selection bias (11% from sequence generation and 30% from allocation concealment), 85% for performance bias, 89% for detection bias, 4% for attrition bias and 40% for reporting bias. In multivariable analysis, fewer authors were associated with selection bias (allocation concealment), performance bias and attrition bias, and earlier year of publication and funding source not reported or disclosed were associated with selection bias (sequence generation). Studies published in non-English language were associated with reporting bias. Poor adherence to recommended reporting standards (<60% of the studies not providing sufficient information) was observed in 11 of the 23 sections evaluated. Study quality and data extraction were performed by one reviewer and cross-checked by a second reviewer. Translation to English was performed by one reviewer in 85% of the included studies. Studies evaluating CHM often fail to meet expected methodological criteria, and high-quality evidence is lacking. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Traits, States, and Attentional Gates: Temperament and Threat Relevance as Predictors of Attentional Bias to Social Threat

PubMed Central

Helzer, Erik G.; Connor-Smith, Jennifer K.; Reed, Marjorie A.

2009-01-01

This study investigated the influence of situational and dispositional factors on attentional biases toward social threat, and the impact of these attentional biases on distress in a sample of adolescents. Results suggest greater biases for personally-relevant threat cues, as individuals reporting high social stress were vigilant to subliminal social threat cues, but not physical threat cues, and those reporting low social stress showed no attentional biases. Individual differences in fearful temperament and attentional control interacted to influence attentional biases, with fearful temperament predicting biases to supraliminal social threat only for individuals with poor attentional control. Multivariate analyses exploring relations between attentional biases for social threat and symptoms of anxiety and depression revealed that attentional biases alone were rarely related to symptoms. However, biases did interact with social stress, fearful temperament, and attentional control to predict distress. Results are discussed in terms of automatic and effortful cognitive mechanisms underlying threat cue processing. PMID:18791905

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

NASA Astrophysics Data System (ADS)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

Looking at food in sad mood: do attention biases lead emotional eaters into overeating after a negative mood induction?

PubMed

Werthmann, Jessica; Renner, Fritz; Roefs, Anne; Huibers, Marcus J H; Plumanns, Lana; Krott, Nora; Jansen, Anita

2014-04-01

Emotional eating is associated with overeating and the development of obesity. Yet, empirical evidence for individual (trait) differences in emotional eating and cognitive mechanisms that contribute to eating during sad mood remain equivocal. The aim of this study was to test if attention bias for food moderates the effect of self-reported emotional eating during sad mood (vs neutral mood) on actual food intake. It was expected that emotional eating is predictive of elevated attention for food and higher food intake after an experimentally induced sad mood and that attentional maintenance on food predicts food intake during a sad versus a neutral mood. Participants (N = 85) were randomly assigned to one of the two experimental mood induction conditions (sad/neutral). Attentional biases for high caloric foods were measured by eye tracking during a visual probe task with pictorial food and neutral stimuli. Self-reported emotional eating was assessed with the Dutch Eating Behavior Questionnaire (DEBQ) and ad libitum food intake was tested by a disguised food offer. Hierarchical multivariate regression modeling showed that self-reported emotional eating did not account for changes in attention allocation for food or food intake in either condition. Yet, attention maintenance on food cues was significantly related to increased intake specifically in the neutral condition, but not in the sad mood condition. The current findings show that self-reported emotional eating (based on the DEBQ) might not validly predict who overeats when sad, at least not in a laboratory setting with healthy women. Results further suggest that attention maintenance on food relates to eating motivation when in a neutral affective state, and might therefore be a cognitive mechanism contributing to increased food intake in general, but maybe not during sad mood. Copyright © 2014 Elsevier Ltd. All rights reserved.

Performance of the disease risk score in a cohort study with policy-induced selection bias.

PubMed

Tadrous, Mina; Mamdani, Muhammad M; Juurlink, David N; Krahn, Murray D; Lévesque, Linda E; Cadarette, Suzanne M

2015-11-01

To examine the performance of the disease risk score (DRS) in a cohort study with evidence of policy-induced selection bias. We examined two cohorts of new users of bisphosphonates. Estimates for 1-year hip fracture rates between agents using DRS, exposure propensity scores and traditional multivariable analysis were compared. The results for the cohort with no evidence of policy-induced selection bias showed little variation across analyses (-4.1-2.0%). Analysis of the cohort with evidence of policy-induced selection bias showed greater variation (-13.5-8.1%), with the greatest difference seen with DRS analyses. Our findings suggest that caution may be warranted when using DRS methods in cohort studies with policy-induced selection bias, further research is needed.

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

PubMed

Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

2012-07-01

Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

A Comprehensive Review on the Predictive Performance of the Sheiner-Tozer and Derivative Equations for the Correction of Phenytoin Concentrations.

PubMed

Kiang, Tony K L; Ensom, Mary H H

2016-04-01

In settings where free phenytoin concentrations are not available, the Sheiner-Tozer equation-Corrected total phenytoin concentration = Observed total phenytoin concentration/[(0.2 × Albumin) + 0.1]; phenytoin in µg/mL, albumin in g/dL-and its derivative equations are commonly used to correct for altered phenytoin binding to albumin. The objective of this article was to provide a comprehensive and updated review on the predictive performance of these equations in various patient populations. A literature search of PubMed, EMBASE, and Google Scholar was conducted using combinations of the following terms: Sheiner-Tozer, Winter-Tozer, phenytoin, predictive equation, precision, bias, free fraction. All English-language articles up to November 2015 (excluding abstracts) were evaluated. This review shows the Sheiner-Tozer equation to be biased and imprecise in various critical care, head trauma, and general neurology patient populations. Factors contributing to bias and imprecision include the following: albumin concentration, free phenytoin assay temperature, experimental conditions (eg, timing of concentration sampling, steady-state dosing conditions), renal function, age, concomitant medications, and patient type. Although derivative equations using varying albumin coefficients have improved accuracy (without much improvement in precision) in intensive care and elderly patients, these equations still require further validation. Further experiments are also needed to yield derivative equations with good predictive performance in all populations as well as to validate the equations' impact on actual patient efficacy and toxicity outcomes. More complex, multivariate predictive equations may be required to capture all variables that can potentially affect phenytoin pharmacokinetics and clinical therapeutic outcomes. © The Author(s) 2016.

Influence of shifting cultivation practices on soil-plant-beetle interactions.

PubMed

Ibrahim, Kalibulla Syed; Momin, Marcy D; Lalrotluanga, R; Rosangliana, David; Ghatak, Souvik; Zothansanga, R; Kumar, Nachimuthu Senthil; Gurusubramanian, Guruswami

2016-08-01

Shifting cultivation (jhum) is a major land use practice in Mizoram. It was considered as an eco-friendly and efficient method when the cycle duration was long (15-30 years), but it poses the problem of land degradation and threat to ecology when shortened (4-5 years) due to increased intensification of farming systems. Studying beetle community structure is very helpful in understanding how shifting cultivation affects the biodiversity features compared to natural forest system. The present study examines the beetle species diversity and estimates the effects of shifting cultivation practices on the beetle assemblages in relation to change in tree species composition and soil nutrients. Scarabaeidae and Carabidae were observed to be the dominant families in the land use systems studied. Shifting cultivation practice significantly (P < 0.05) affected the beetle and tree species diversity as well as the soil nutrients as shown by univariate (one-way analysis of variance (ANOVA), correlation and regression, diversity indices) and multivariate (cluster analysis, principal component analysis (PCA), detrended correspondence analysis (DCA), canonical variate analysis (CVA), permutational multivariate analysis of variance (PERMANOVA), permutational multivariate analysis of dispersion (PERMDISP)) statistical analyses. Besides changing the tree species composition and affecting the soil fertility, shifting cultivation provides less suitable habitat conditions for the beetle species. Bioindicator analysis categorized the beetle species into forest specialists, anthropogenic specialists (shifting cultivation habitat specialist), and habitat generalists. Molecular analysis of bioindicator beetle species was done using mitochondrial cytochrome oxidase subunit I (COI) marker to validate the beetle species and describe genetic variation among them in relation to heterogeneity, transition/transversion bias, codon usage bias, evolutionary distance, and substitution pattern. The present study revealed the fact that shifting cultivation practice significantly affects the beetle species in terms of biodiversity pattern as well as evolutionary features. Spatiotemporal assessment of soil-plant-beetle interactions in shifting cultivation system and their influence in land degradation and ecology will be helpful in making biodiversity conservation decisions in the near future.

Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

PubMed Central

Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida

2016-01-01

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637

Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution

NASA Astrophysics Data System (ADS)

Oh, Seok-Geun; Suh, Myoung-Seok

2017-07-01

The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.

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.

Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction

NASA Astrophysics Data System (ADS)

Vrac, Mathieu

2018-06-01

Climate simulations often suffer from statistical biases with respect to observations or reanalyses. It is therefore common to correct (or adjust) those simulations before using them as inputs into impact models. However, most bias correction (BC) methods are univariate and so do not account for the statistical dependences linking the different locations and/or physical variables of interest. In addition, they are often deterministic, and stochasticity is frequently needed to investigate climate uncertainty and to add constrained randomness to climate simulations that do not possess a realistic variability. This study presents a multivariate method of rank resampling for distributions and dependences (R2D2) bias correction allowing one to adjust not only the univariate distributions but also their inter-variable and inter-site dependence structures. Moreover, the proposed R2D2 method provides some stochasticity since it can generate as many multivariate corrected outputs as the number of statistical dimensions (i.e., number of grid cell × number of climate variables) of the simulations to be corrected. It is based on an assumption of stability in time of the dependence structure - making it possible to deal with a high number of statistical dimensions - that lets the climate model drive the temporal properties and their changes in time. R2D2 is applied on temperature and precipitation reanalysis time series with respect to high-resolution reference data over the southeast of France (1506 grid cell). Bivariate, 1506-dimensional and 3012-dimensional versions of R2D2 are tested over a historical period and compared to a univariate BC. How the different BC methods behave in a climate change context is also illustrated with an application to regional climate simulations over the 2071-2100 period. The results indicate that the 1d-BC basically reproduces the climate model multivariate properties, 2d-R2D2 is only satisfying in the inter-variable context, 1506d-R2D2 strongly improves inter-site properties and 3012d-R2D2 is able to account for both. Applications of the proposed R2D2 method to various climate datasets are relevant for many impact studies. The perspectives of improvements are numerous, such as introducing stochasticity in the dependence itself, questioning its stability assumption, and accounting for temporal properties adjustment while including more physics in the adjustment procedures.

Mate choice for genetic quality when environments vary: suggestions for empirical progress.

PubMed

Bussière, Luc F; Hunt, John; Stölting, Kai N; Jennions, Michael D; Brooks, Robert

2008-09-01

Mate choice for good-genes remains one of the most controversial evolutionary processes ever proposed. This is partly because strong directional choice should theoretically deplete the genetic variation that explains the evolution of this type of female mating preference (the so-called lek paradox). Moreover, good-genes benefits are generally assumed to be too small to outweigh opposing direct selection on females. Here, we review recent progress in the study of mate choice for genetic quality, focussing particularly on the potential for genotype by environment interactions (GEIs) to rescue additive genetic variation for quality, and thereby resolve the lek paradox. We raise five questions that we think will stimulate empirical progress in this field, and suggest directions for research in each area: (1) How is condition-dependence affected by environmental variation? (2) How important are GEIs for maintaining additive genetic variance in condition? (3) How much do GEIs reduce the signalling value of male condition? (4) How does GEI affect the multivariate version of the lek paradox? (5) Have mating biases for high-condition males evolved because of indirect benefits?

The Likelihood of Injury Among Bias Crimes: An Analysis of General and Specific Bias Types.

PubMed

Pezzella, Frank S; Fetzer, Matthew D

2015-06-18

In 2009, President Barack Obama signed the Mathew Sheppard and James Byrd Jr. Hate Crimes Protection act and thereby extended the list of previously protected classes of victims from actual or perceived race, color, religion, national origin, disability and sex orientation to gender and gender identity. Over 45 states, the District of Columbia and the federal government now include hate crime statutes that increase penalties when offenders perpetrate hate crimes against protected classes of victims. Penalty enhancement statutes sanction unlawful bias conduct arguably because they result in more severe injuries relative to non-bias conduct. We contend that physical injuries vary by bias type and are not equally injurious. Data on bias crimes was analyzed from the National Incident Based Reporting System. Descriptive patterns of bias crimes were identified by offense type, bias motivation and major and minor injuries. Using Multivariate analyses, we found an escalating trend of violence against racial minorities. Moreover, relative to non-bias crimes, only anti-White and anti-lesbian bias crimes experienced our two prong "animus" criteria of disproportionate prevalence and severity of injury. However, when compared to anti-White bias, anti-Black bias crimes were more prevalent and likely to suffer serious injuries. Implications for hate crime jurisprudence are discussed. © The Author(s) 2015.

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

Are object- and space-based attentional biases both important to free-viewing perceptual asymmetries?

PubMed

Nicholls, Michael E R; Hughes, Georgina; Mattingley, Jason B; Bradshaw, John L

2004-02-01

In contrast to unilateral neglect patients, who overattend to the right hemispace, normal participants attend more to the left: a phenomenon known as pseudoneglect. Two experiments examined whether pseudoneglect results from object- or space-based attentional biases. Normal participants ( n=38, 22) made luminance judgments for two left/right mirror-reversed luminance gradients (greyscales task). The relative lateral position of the greyscales stimuli was manipulated so that object- and space-based coordinates were congruent or incongruent. A baseline condition was also included. A leftward bias, found for the baseline condition, was annulled in the incongruent condition, demonstrating an opposition of object- and space-based biases. The leftward bias was reduced in the congruent condition where object- and space-based biases were expected to be additive. This effect was attributed to extraneous factors, which were avoided in the second experiment by presenting the greyscales stimuli sequentially. Once again, no bias was observed in the incongruent condition where object- and space-based biases were opposed. The leftward bias in the congruent condition was the same as the baseline. The results can be explained by a combination of space- and object-based biases or by space-based biases alone and are discussed with reference to a variety of models, which describe the distribution of attention across space.

Perceptual asymmetries in greyscales: object-based versus space-based influences.

PubMed

Thomas, Nicole A; Elias, Lorin J

2012-05-01

Neurologically normal individuals exhibit leftward spatial biases, resulting from object- and space-based biases; however their relative contributions to the overall bias remain unknown. Relative position within the display has not often been considered, with similar spatial conditions being collapsed across. Study 1 used the greyscales task to investigate the influence of relative position and object- and space-based contributions. One image in each greyscale pair was shifted towards the left or the right. A leftward object-based bias moderated by a bias to the centre was expected. Results confirmed this as a left object-based bias occurred in the right visual field, where the left side of the greyscale pairs was located in the centre visual field. Further, only lower visual field images exhibited a significant left bias in the left visual field. The left bias was also stronger when images were partially overlapping in the right visual field, demonstrating the importance of examining proximity. The second study examined whether object-based biases were stronger when actual objects, with directional lighting biases, were used. Direction of luminosity was congruent or incongruent with spatial location. A stronger object-based bias emerged overall; however a leftward bias was seen in congruent conditions and a rightward bias was seen in incongruent conditions. In conditions with significant biases, the lower visual field image was chosen most often. Results show that object- and space-based biases both contribute; however stimulus type allows either space- or object-based biases to be stronger. A lower visual field bias also interacts with these biases, leading the left bias to be eliminated under certain conditions. The complex interaction occurring between frame of reference and visual field makes spatial location extremely important in determining the strength of the leftward bias. Copyright © 2010 Elsevier Srl. All rights reserved.

Does parental anxiety cause biases in the processing of child-relevant threat material?

PubMed

Cartwright-Hatton, Sam; Abeles, Paul; Dixon, Clare; Holliday, Christine; Hills, Becky

2014-06-01

Anxiety leads to biases in processing personally relevant information. This study set out to examine whether anxious parents also experience biases in processing child-relevant material. Ninety parents acted as a control condition, or received a social anxiety or child-related anxiety induction. They completed a task examining attentional biases in relation to child-threat words and social-threat words, and a task examining ability to categorize emotion in children's faces and voices. There was a trend indicating group differences in attentional bias towards social-threat words, and this appears to have been only in the social anxiety condition, but not the child anxiety or control conditions. For child-threat words, attentional bias was present in the child anxiety condition, but not the social anxiety or control conditions. In the emotion recognition task, there was no difference between the control and child anxiety conditions, but the social anxiety condition were more likely to erroneously label children's faces and voices as sad. Parents' anxious biases may spill over into their child's world. Parents' anxious biases may spill over into their child's world. Anxious parents may have attentional biases towards threats in their children's environment. Anxious parents may over-attribute negative emotion to children. © 2013 The British Psychological Society.

Effects of poverty and lack of insurance on perceptions of racial and ethnic bias in health care.

PubMed

Stepanikova, Irena; Cook, Karen S

2008-06-01

To investigate whether poverty and lack of insurance are associated with perceived racial and ethnic bias in health care. 2001 Survey on Disparities in Quality of Health Care, a nationally representative telephone survey. We use data on black, Hispanic, and white adults who have a regular physician (N=4,556). We estimate multivariate logistic regression models to examine the effects of poverty and lack of health insurance on perceived racial and ethnic bias in health care for all respondents and by racial, ethnic, and language groups. Controlling for sociodemographic and other factors, uninsured blacks and Hispanics interviewed in English are more likely to report racial and ethnic bias in health care compared with their privately insured counterparts. Poor whites are more likely to report racial and ethnic bias in health care compared with other whites. Good physician-patient communication is negatively associated with perceived racial and ethnic bias. Compared with their more socioeconomically advantaged counterparts, poor whites, uninsured blacks, and some uninsured Hispanics are more likely to perceive that racial and ethnic bias operates in the health care they receive. Providing health insurance for the uninsured may help reduce this perceived bias among some minority groups.

Simultaneous calibration of ensemble river flow predictions over an entire range of lead times

NASA Astrophysics Data System (ADS)

Hemri, S.; Fundel, F.; Zappa, M.

2013-10-01

Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical postprocessing is required. In this work Bayesian model averaging (BMA) is applied to statistically postprocess ensemble runoff raw forecasts for a catchment in Switzerland, at lead times ranging from 1 to 240 h. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the postprocessed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

The Plant Ionome Revisited by the Nutrient Balance Concept

PubMed Central

Parent, Serge-Étienne; Parent, Léon Etienne; Egozcue, Juan José; Rozane, Danilo-Eduardo; Hernandes, Amanda; Lapointe, Line; Hébert-Gentile, Valérie; Naess, Kristine; Marchand, Sébastien; Lafond, Jean; Mattos, Dirceu; Barlow, Philip; Natale, William

2013-01-01

Tissue analysis is commonly used in ecology and agronomy to portray plant nutrient signatures. Nutrient concentration data, or ionomes, belong to the compositional data class, i.e., multivariate data that are proportions of some whole, hence carrying important numerical properties. Statistics computed across raw or ordinary log-transformed nutrient data are intrinsically biased, hence possibly leading to wrong inferences. Our objective was to present a sound and robust approach based on a novel nutrient balance concept to classify plant ionomes. We analyzed leaf N, P, K, Ca, and Mg of two wild and six domesticated fruit species from Canada, Brazil, and New Zealand sampled during reproductive stages. Nutrient concentrations were (1) analyzed without transformation, (2) ordinary log-transformed as commonly but incorrectly applied in practice, (3) additive log-ratio (alr) transformed as surrogate to stoichiometric rules, and (4) converted to isometric log-ratios (ilr) arranged as sound nutrient balance variables. Raw concentration and ordinary log transformation both led to biased multivariate analysis due to redundancy between interacting nutrients. The alr- and ilr-transformed data provided unbiased discriminant analyses of plant ionomes, where wild and domesticated species formed distinct groups and the ionomes of species and cultivars were differentiated without numerical bias. The ilr nutrient balance concept is preferable to alr, because the ilr technique projects the most important interactions between nutrients into a convenient Euclidean space. This novel numerical approach allows rectifying historical biases and supervising phenotypic plasticity in plant nutrition studies. PMID:23526060

Comparing interval estimates for small sample ordinal CFA models

PubMed Central

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research. PMID:26579002

Comparing interval estimates for small sample ordinal CFA models.

PubMed

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research.

Effects of interpretation training on hostile attribution bias and reactivity to interpersonal insult.

PubMed

Hawkins, Kirsten A; Cougle, Jesse R

2013-09-01

Research suggests that individuals high in anger have a bias for attributing hostile intentions to ambiguous situations. The current study tested whether this interpretation bias can be altered to influence anger reactivity to an interpersonal insult using a single-session cognitive bias modification program. One hundred thirty-five undergraduate students were randomized to receive positive training, negative training, or a control condition. Anger reactivity to insult was then assessed. Positive training led to significantly greater increases in positive interpretation bias relative to the negative group, though these increases were only marginally greater than the control group. Negative training led to increased negative interpretation bias relative to other groups. During the insult, participants in the positive condition reported less anger than those in the control condition. Observers rated participants in the positive condition as less irritated than those in the negative condition and more amused than the other two conditions. Though mediation of effects via bias modification was not demonstrated, among the positive condition posttraining interpretation bias was correlated with self-reported anger, suggesting that positive training reduced anger reactivity by influencing interpretation biases. Findings suggest that positive interpretation training may be a promising treatment for reducing anger. However, the current study was conducted with a non-treatment-seeking student sample; further research with a treatment-seeking sample with problematic anger is necessary. Copyright © 2013. Published by Elsevier Ltd.

Improved Correction of Misclassification Bias With Bootstrap Imputation.

PubMed

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Orientation decoding: Sense in spirals?

PubMed

Clifford, Colin W G; Mannion, Damien J

2015-04-15

The orientation of a visual stimulus can be successfully decoded from the multivariate pattern of fMRI activity in human visual cortex. Whether this capacity requires coarse-scale orientation biases is controversial. We and others have advocated the use of spiral stimuli to eliminate a potential coarse-scale bias-the radial bias toward local orientations that are collinear with the centre of gaze-and hence narrow down the potential coarse-scale biases that could contribute to orientation decoding. The usefulness of this strategy is challenged by the computational simulations of Carlson (2014), who reported the ability to successfully decode spirals of opposite sense (opening clockwise or counter-clockwise) from the pooled output of purportedly unbiased orientation filters. Here, we elaborate the mathematical relationship between spirals of opposite sense to confirm that they cannot be discriminated on the basis of the pooled output of unbiased or radially biased orientation filters. We then demonstrate that Carlson's (2014) reported decoding ability is consistent with the presence of inadvertent biases in the set of orientation filters; biases introduced by their digital implementation and unrelated to the brain's processing of orientation. These analyses demonstrate that spirals must be processed with an orientation bias other than the radial bias for successful decoding of spiral sense. Copyright © 2014 Elsevier Inc. All rights reserved.

Interior renovation of a general practitioner office leads to a perceptual bias on patient experience for over one year.

PubMed

Gauthey, Jérôme; Tièche, Raphaël; Streit, Sven

2018-01-01

Measuring patient experience is key when assessing quality of care but can be biased: A perceptual bias occurs when renovations of the interior design of a general practitioner (GP) office improves how patients assessed quality of care. The aim was to assess the length of perceptual bias and if it could be reproduced after a second renovation. A GP office with 2 GPs in Switzerland was renovated twice within 3 years. We assessed patient experience at baseline, 2 months and 14 months after the first and 3 months after the second renovation. Each time, we invited a sample of 180 consecutive patients that anonymously graded patient experience in 4 domains: appearance of the office; qualities of medical assistants and GPs; and general satisfaction. We compared crude mean scores per domain from baseline until follow-up. In a multivariate model, we adjusted for patient's age, gender and for how long patients had been their GP. At baseline, patients aged 60.9 (17.7) years, 52% females. After the first renovation, we found a regression to the baseline level of patient experience after 14 months except for appearance of the office (p<0.001). After the second renovation, patient experience improved again in appearance of the office (p = 0.008), qualities of the GP (p = 0.008), and general satisfaction (p = 0.014). Qualities of the medical assistant showed a slight improvement (p = 0.068). Results were unchanged in the multivariate model. Interior renovation of a GP office probably causes a perceptual bias for >1 year that improves how patients rate quality of care. This bias could be reproduced after a second renovation strengthening a possible causal relationship. These findings imply to appropriately time measurement of patient experience to at least one year after interior renovation of GP practices to avoid environmental changes influences the estimates when measuring patient experience.

Interior renovation of a general practitioner office leads to a perceptual bias on patient experience for over one year

PubMed Central

2018-01-01

Introduction Measuring patient experience is key when assessing quality of care but can be biased: A perceptual bias occurs when renovations of the interior design of a general practitioner (GP) office improves how patients assessed quality of care. The aim was to assess the length of perceptual bias and if it could be reproduced after a second renovation. Methods A GP office with 2 GPs in Switzerland was renovated twice within 3 years. We assessed patient experience at baseline, 2 months and 14 months after the first and 3 months after the second renovation. Each time, we invited a sample of 180 consecutive patients that anonymously graded patient experience in 4 domains: appearance of the office; qualities of medical assistants and GPs; and general satisfaction. We compared crude mean scores per domain from baseline until follow-up. In a multivariate model, we adjusted for patient’s age, gender and for how long patients had been their GP. Results At baseline, patients aged 60.9 (17.7) years, 52% females. After the first renovation, we found a regression to the baseline level of patient experience after 14 months except for appearance of the office (p<0.001). After the second renovation, patient experience improved again in appearance of the office (p = 0.008), qualities of the GP (p = 0.008), and general satisfaction (p = 0.014). Qualities of the medical assistant showed a slight improvement (p = 0.068). Results were unchanged in the multivariate model. Conclusions Interior renovation of a GP office probably causes a perceptual bias for >1 year that improves how patients rate quality of care. This bias could be reproduced after a second renovation strengthening a possible causal relationship. These findings imply to appropriately time measurement of patient experience to at least one year after interior renovation of GP practices to avoid environmental changes influences the estimates when measuring patient experience. PMID:29462196

Accounting for selection and correlation in the analysis of two-stage genome-wide association studies.

PubMed

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

2016-10-01

The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen. 39: (7), 830-832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account. © The Author 2016. Published by Oxford University Press.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

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

PubMed Central

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

2015-01-01

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

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Unconscious race and social class bias among acute care surgical clinicians and clinical treatment decisions.

PubMed

Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A; Freischlag, Julie A

2015-05-01

Significant health inequities persist among minority and socially disadvantaged patients. Better understanding of how unconscious biases affect clinical decision making may help to illuminate clinicians' roles in propagating disparities. To determine whether clinicians' unconscious race and/or social class biases correlate with patient management decisions. We conducted a web-based survey among 230 physicians from surgery and related specialties at an academic, level I trauma center from December 1, 2011, through January 31, 2012. We administered clinical vignettes, each with 3 management questions. Eight vignettes assessed the relationship between unconscious bias and clinical decision making. We performed ordered logistic regression analysis on the Implicit Association Test (IAT) scores and used multivariable analysis to determine whether implicit bias was associated with the vignette responses. Differential response times (D scores) on the IAT as a surrogate for unconscious bias. Patient management vignettes varied by patient race or social class. Resulting D scores were calculated for each management decision. In total, 215 clinicians were included and consisted of 74 attending surgeons, 32 fellows, 86 residents, 19 interns, and 4 physicians with an undetermined level of education. Specialties included surgery (32.1%), anesthesia (18.1%), emergency medicine (18.1%), orthopedics (7.9%), otolaryngology (7.0%), neurosurgery (7.0%), critical care (6.0%), and urology (2.8%); 1.9% did not report a departmental affiliation. Implicit race and social class biases were present in most respondents. Among all clinicians, mean IAT D scores for race and social class were 0.42 (95% CI, 0.37-0.48) and 0.71 (95% CI, 0.65-0.78), respectively. Race and class scores were similar across departments (general surgery, orthopedics, urology, etc), race, or age. Women demonstrated less bias concerning race (mean IAT D score, 0.39 [95% CI, 0.29-0.49]) and social class (mean IAT D score, 0.66 [95% CI, 0.57-0.75]) relative to men (mean IAT D scores, 0.44 [95% CI, 0.37-0.52] and 0.82 [95% CI, 0.75-0.89], respectively). In univariate analyses, we found an association between race/social class bias and 3 of 27 possible patient-care decisions. Multivariable analyses revealed no association between the IAT D scores and vignette-based clinical assessments. Unconscious social class and race biases were not significantly associated with clinical decision making among acute care surgical clinicians. Further studies involving real physician-patient interactions may be warranted.

Self-referent information processing in individuals with bipolar spectrum disorders.

PubMed

Molz Adams, Ashleigh; Shapero, Benjamin G; Pendergast, Laura H; Alloy, Lauren B; Abramson, Lyn Y

2014-01-01

Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M=19.65, SD=1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. © 2013 Elsevier B.V. All rights reserved.

Self-referent information processing in individuals with bipolar spectrum disorders

PubMed Central

Molz Adams, Ashleigh; Shapero, Benjamin G.; Pendergast, Laura H.; Alloy, Lauren B.; Abramson, Lyn Y.

2014-01-01

Background Bipolar spectrum disorders (BSDs) are common and impairing, which has led to an examination of risk factors for their development and maintenance. Historically, research has examined cognitive vulnerabilities to BSDs derived largely from the unipolar depression literature. Specifically, theorists propose that dysfunctional information processing guided by negative self-schemata may be a risk factor for depression. However, few studies have examined whether BSD individuals also show self-referent processing biases. Methods This study examined self-referent information processing differences between 66 individuals with and 58 individuals without a BSD in a young adult sample (age M = 19.65, SD = 1.74; 62% female; 47% Caucasian). Repeated measures multivariate analysis of variance (MANOVA) was conducted to examine multivariate effects of BSD diagnosis on 4 self-referent processing variables (self-referent judgments, response latency, behavioral predictions, and recall) in response to depression-related and nondepression-related stimuli. Results Bipolar individuals endorsed and recalled more negative and fewer positive self-referent adjectives, as well as made more negative and fewer positive behavioral predictions. Many of these information-processing biases were partially, but not fully, mediated by depressive symptoms. Limitations Our sample was not a clinical or treatment-seeking sample, so we cannot generalize our results to clinical BSD samples. No participants had a bipolar I disorder at baseline. Conclusions This study provides further evidence that individuals with BSDs exhibit a negative self-referent information processing bias. This may mean that those with BSDs have selective attention and recall of negative information about themselves, highlighting the need for attention to cognitive biases in therapy. PMID:24074480

Experimental Investigation of DC-Bias Related Core Losses in a Boost Inductor (Postprint)

DTIC Science & Technology

2014-08-01

dc bias-flux conditions. These dc bias conditions result in distorted hysteresis loops , increased core losses, and have been shown to be independent...These dc bias conditions result in dis- torted hysteresis loops , increased core losses, and have been shown to be independent of core material. The...controllable converter load currents, this topology is ideal to study dc-related losses. Inductor core hysteresis loop characterization was accomplished

Three- and 4-year-old children's response tendencies to various interviewers.

PubMed

Okanda, Mako; Kanda, Takayuki; Ishiguro, Hiroshi; Itakura, Shoji

2013-09-01

Unlike young preschoolers, older preschoolers may exhibit a response bias under social pressure from authoritative interviewers. To examine this, 3- and 4-year-old preschoolers were asked yes-no questions about familiar and unfamiliar objects in three conditions. In one condition an adult asked them questions in a live interaction, in a second condition an adult asked questions via video, and in a third condition a robot asked questions via video. The 3-year-olds exhibited a yes bias-a tendency to say "yes"-in nearly all conditions. The only exception was when they were asked questions about unfamiliar objects by the human interviewer via video, where they did not respond in a biased manner. The 4-year-olds exhibited a yes bias in only one condition-when they were questioned by a live human interviewer about both objects. They also exhibited a nay-saying bias when asked questions about unfamiliar objects in both video conditions, and they did not show any response bias in other conditions. The results suggest that the social pressure from an authoritative adult in a live interaction is problematic. Copyright © 2013 Elsevier Inc. All rights reserved.

Apparatus bias and place conditioning with ethanol in mice.

PubMed

Cunningham, Christopher L; Ferree, Nikole K; Howard, MacKenzie A

2003-12-01

Although the distinction between "biased" and "unbiased" is generally recognized as an important methodological issue in place conditioning, previous studies have not adequately addressed the distinction between a biased/unbiased apparatus and a biased/unbiased stimulus assignment procedure. Moreover, a review of the recent literature indicates that many reports (70% of 76 papers published in 2001) fail to provide adequate information about apparatus bias. This issue is important because the mechanisms underlying a drug's effect in the place-conditioning procedure may differ depending on whether the apparatus is biased or unbiased. The present studies were designed to assess the impact of apparatus bias and stimulus assignment procedure on ethanol-induced place conditioning in mice (DBA/2 J). A secondary goal was to compare various dependent variables commonly used to index conditioned place preference. Apparatus bias was manipulated by varying the combination of tactile (floor) cues available during preference tests. Experiment 1 used an unbiased apparatus in which the stimulus alternatives were equally preferred during a pre-test as indicated by the group average. Experiment 2 used a biased apparatus in which one of the stimuli was strongly preferred by most mice (mean % time on cue = 67%) during the pre-test. In both studies, the stimulus paired with drug (CS+) was assigned randomly (i.e., an "unbiased" stimulus assignment procedure). Experimental mice received four pairings of CS+ with ethanol (2 g/kg, i.p.) and four pairings of the alternative stimulus (CS-) with saline; control mice received saline on both types of trial. Each experiment concluded with a 60-min choice test. With the unbiased apparatus (experiment 1), significant place conditioning was obtained regardless of whether drug was paired with the subject's initially preferred or non-preferred stimulus. However, with the biased apparatus (experiment 2), place conditioning was apparent only when ethanol was paired with the initially non-preferred cue, and not when it was paired with the initially preferred cue. These conclusions held regardless of which dependent variable was used to index place conditioning, but only if the counterbalancing factor was included in statistical analyses. These studies indicate that apparatus bias plays a major role in determining whether biased assignment of an ethanol-paired stimulus affects ability to demonstrate conditioned place preference. Ethanol's ability to produce conditioned place preference in an unbiased apparatus, regardless of the direction of the initial cue bias, supports previous studies that interpret such findings as evidence of a primary rewarding drug effect. Moreover, these studies suggest that the asymmetrical outcome observed in the biased apparatus is most likely due to a measurement problem (e.g., ceiling effect) rather than to an interaction between the drug's effect and an unconditioned motivational response (e.g., "anxiety") to the initially non-preferred stimulus. More generally, these findings illustrate the importance of providing clear information on apparatus bias in all place-conditioning studies.

Implicit Physician Biases in Periviability Counseling.

PubMed

Shapiro, Natasha; Wachtel, Elena V; Bailey, Sean M; Espiritu, Michael M

2018-06-01

To assess whether neonatologists show implicit racial and/or socioeconomic biases and whether these are predictive of recommendations at extreme periviability. A nationwide survey using a clinical vignette of a woman in labor at 23 2/7 weeks of gestation asked physicians how likely they were to recommend intensive vs comfort care. Participants were randomized to 1 of 4 versions of the vignette in which racial and socioeconomic stimuli were varied, followed by 2 implicit association tests (IATs). IATs revealed implicit preferences favoring white (mean IAT score = 0.48, P < .001) and greater socioeconomic status (mean IAT score = 0.73, P < .001). Multivariable linear regression analysis showed that physicians with implicit bias toward greater socioeconomic status were more likely than those without bias to recommend comfort care when presented with a patient of high socioeconomic status (P = .037). No significant effect was seen for implicit racial bias. Building on previous demonstrations of unconscious racial and socioeconomic biases among physicians and their predictive validity, our results suggest that unconscious socioeconomic bias influences recommendations when counseling at the limits of viability. Physicians who display a negative socioeconomic bias are less likely to recommend resuscitation when counseling women of high socioeconomic status. The influence of implicit socioeconomic bias on recommendations at periviability may influence neonatal healthcare disparities and should be explored in future studies. Copyright © 2018 Elsevier Inc. All rights reserved.

A retrieval-based approach to eliminating hindsight bias.

PubMed

Van Boekel, Martin; Varma, Keisha; Varma, Sashank

2017-03-01

Individuals exhibit hindsight bias when they are unable to recall their original responses to novel questions after correct answers are provided to them. Prior studies have eliminated hindsight bias by modifying the conditions under which original judgments or correct answers are encoded. Here, we explored whether hindsight bias can be eliminated by manipulating the conditions that hold at retrieval. Our retrieval-based approach predicts that if the conditions at retrieval enable sufficient discrimination of memory representations of original judgments from memory representations of correct answers, then hindsight bias will be reduced or eliminated. Experiment 1 used the standard memory design to replicate the hindsight bias effect in middle-school students. Experiments 2 and 3 modified the retrieval phase of this design, instructing participants beforehand that they would be recalling both their original judgments and the correct answers. As predicted, this enabled participants to form compound retrieval cues that discriminated original judgment traces from correct answer traces, and eliminated hindsight bias. Experiment 4 found that when participants were not instructed beforehand that they would be making both recalls, they did not form discriminating retrieval cues, and hindsight bias returned. These experiments delineate the retrieval conditions that produce-and fail to produce-hindsight bias.

Coupling GIS and multivariate approaches to reference site selection for wadeable stream monitoring.

PubMed

Collier, Kevin J; Haigh, Andy; Kelly, Johlene

2007-04-01

Geographic Information System (GIS) was used to identify potential reference sites for wadeable stream monitoring, and multivariate analyses were applied to test whether invertebrate communities reflected a priori spatial and stream type classifications. We identified potential reference sites in segments with unmodified vegetation cover adjacent to the stream and in >85% of the upstream catchment. We then used various landcover, amenity and environmental impact databases to eliminate sites that had potential anthropogenic influences upstream and that fell into a range of access classes. Each site identified by this process was coded by four dominant stream classes and seven zones, and 119 candidate sites were randomly selected for follow-up assessment. This process yielded 16 sites conforming to reference site criteria using a conditional-probabilistic design, and these were augmented by an additional 14 existing or special interest reference sites. Non-metric multidimensional scaling (NMS) analysis of percent abundance invertebrate data indicated significant differences in community composition among some of the zones and stream classes identified a priori providing qualified support for this framework in reference site selection. NMS analysis of a range standardised condition and diversity metrics derived from the invertebrate data indicated a core set of 26 closely related sites, and four outliers that were considered atypical of reference site conditions and subsequently dropped from the network. Use of GIS linked to stream typology, available spatial databases and aerial photography greatly enhanced the objectivity and efficiency of reference site selection. The multi-metric ordination approach reduced variability among stream types and bias associated with non-random site selection, and provided an effective way to identify representative reference sites.

Analysis of Developmental Data: Comparison Among Alternative Methods

ERIC Educational Resources Information Center

Wilson, Ronald S.

1975-01-01

To examine the ability of the correction factor epsilon to counteract statistical bias in univariate analysis, an analysis of variance (adjusted by epsilon) and a multivariate analysis of variance were performed on the same data. The results indicated that univariate analysis is a fully protected design when used with epsilon. (JMB)

Assessing drought risk under climate change in the US Great Plains via evaporative demand from downscaled GCM projections

NASA Astrophysics Data System (ADS)

Dewes, C.; Rangwala, I.; Hobbins, M.; Barsugli, J. J.

2016-12-01

Drought conditions in the US Great Plains occur primarily in response to periods of low precipitation, but they can be exacerbated by enhanced evaporative demand (E0) during periods of elevated temperatures, radiation, advection, and/or decreased humidity. A number of studies project severe to unprecedented drought conditions for this region later in the 21st century. Yet, we have found that methodological choices in the estimation of E0 and the selection of global climate model (GCM) output account for large uncertainties in projections of drought risk. Furthermore, the coarse resolution of GCMs offers little usability for drought risk assessments applied to socio-ecological systems, and users of climate data for that purpose tend to prefer existing downscaled products. Here we derive a physically based estimation of E0 - the FAO56 Penman-Monteith reference evapotranspiration - using driving variables from the Multivariate Adaptive Constructed Analogs (MACA) dataset, which have a spatial resolution of approximately 4 km. We select downscaled outputs from five CMIP5 GCMs, whereby we aim to represent different scenarios for the future of the Great Plains region (e.g. warm/wet, hot/dry, etc.). While this downscaling methodology removes GCM bias relative to a gridded product for historical data (METDATA), we first examine the remaining bias relative to ground (point) estimates of E0. Next we assess whether the downscaled products preserve the variability of their parent GCMs, in both historical and future (RCP8.5) projections. We then use the E0 estimates to compute multi-scale time series of drought indices such as the Evaporative Demand Drought Index (EDDI) and the Standardized Precipitation-Evaporation Index (SPEI) over the Great Plains region. We also attribute variability and drought anomalies to each of the driving parameters, to tease out the influence of specific model biases and evaluate geographical nuances of E0 drivers. Aside from improved understanding of plausible future drought conditions at higher spatial resolutions, our findings should offer insights on the reliability of downscaled projections for drought risk assessment in socio-ecological applications.

Perceptual other-race training reduces implicit racial bias.

PubMed

Lebrecht, Sophie; Pierce, Lara J; Tarr, Michael J; Tanaka, James W

2009-01-01

Implicit racial bias denotes socio-cognitive attitudes towards other-race groups that are exempt from conscious awareness. In parallel, other-race faces are more difficult to differentiate relative to own-race faces--the "Other-Race Effect." To examine the relationship between these two biases, we trained Caucasian subjects to better individuate other-race faces and measured implicit racial bias for those faces both before and after training. Two groups of Caucasian subjects were exposed equally to the same African American faces in a training protocol run over 5 sessions. In the individuation condition, subjects learned to discriminate between African American faces. In the categorization condition, subjects learned to categorize faces as African American or not. For both conditions, both pre- and post-training we measured the Other-Race Effect using old-new recognition and implicit racial biases using a novel implicit social measure--the "Affective Lexical Priming Score" (ALPS). Subjects in the individuation condition, but not in the categorization condition, showed improved discrimination of African American faces with training. Concomitantly, subjects in the individuation condition, but not the categorization condition, showed a reduction in their ALPS. Critically, for the individuation condition only, the degree to which an individual subject's ALPS decreased was significantly correlated with the degree of improvement that subject showed in their ability to differentiate African American faces. Our results establish a causal link between the Other-Race Effect and implicit racial bias. We demonstrate that training that ameliorates the perceptual Other-Race Effect also reduces socio-cognitive implicit racial bias. These findings suggest that implicit racial biases are multifaceted, and include malleable perceptual skills that can be modified with relatively little training.

Terror mismanagement: evidence that mortality salience exacerbates attentional bias in social anxiety.

PubMed

Finch, Emma C; Iverach, Lisa; Menzies, Ross G; Jones, Mark

2016-11-01

Death anxiety is a basic fear underlying a range of psychological conditions, and has been found to increase avoidance in social anxiety. Given that attentional bias is a core feature of social anxiety, the aim of the present study was to examine the impact of mortality salience (MS) on attentional bias in social anxiety. Participants were 36 socially anxious and 37 non-socially anxious individuals, randomly allocated to a MS or control condition. An eye-tracking procedure assessed initial bias towards, and late-stage avoidance of, socially threatening facial expressions. As predicted, socially anxious participants in the MS condition demonstrated significantly more initial bias to social threat than non-socially anxious participants in the MS condition and socially anxious participants in the control condition. However, this effect was not found for late-stage avoidance of social threat. These findings suggest that reminders of death may heighten initial vigilance towards social threat.

Terror mismanagement: evidence that mortality salience exacerbates attentional bias in social anxiety

PubMed Central

Finch, Emma C.; Iverach, Lisa; Menzies, Ross G.; Jones, Mark

2016-01-01

ABSTRACT Death anxiety is a basic fear underlying a range of psychological conditions, and has been found to increase avoidance in social anxiety. Given that attentional bias is a core feature of social anxiety, the aim of the present study was to examine the impact of mortality salience (MS) on attentional bias in social anxiety. Participants were 36 socially anxious and 37 non-socially anxious individuals, randomly allocated to a MS or control condition. An eye-tracking procedure assessed initial bias towards, and late-stage avoidance of, socially threatening facial expressions. As predicted, socially anxious participants in the MS condition demonstrated significantly more initial bias to social threat than non-socially anxious participants in the MS condition and socially anxious participants in the control condition. However, this effect was not found for late-stage avoidance of social threat. These findings suggest that reminders of death may heighten initial vigilance towards social threat. PMID:26211552

Internet-Based Attention Bias Modification for Social Anxiety: A Randomised Controlled Comparison of Training towards Negative and Training Towards Positive Cues

PubMed Central

Boettcher, Johanna; Leek, Linda; Matson, Lisa; Holmes, Emily A.; Browning, Michael; MacLeod, Colin; Andersson, Gerhard; Carlbring, Per

2013-01-01

Biases in attention processes are thought to play a crucial role in the aetiology and maintenance of Social Anxiety Disorder (SAD). The goal of the present study was to examine the efficacy of a programme intended to train attention towards positive cues and a programme intended to train attention towards negative cues. In a randomised, controlled, double-blind design, the impact of these two training conditions on both selective attention and social anxiety were compared to that of a control training condition. A modified dot probe task was used, and delivered via the internet. A total of 129 individuals, diagnosed with SAD, were randomly assigned to one of these three conditions and took part in a 14-day programme with daily training/control sessions. Participants in all three groups did not on average display an attentional bias prior to the training. Critically, results on change in attention bias implied that significantly differential change in selective attention to threat was not detected in the three conditions. However, symptoms of social anxiety reduced significantly from pre- to follow-up-assessment in all three conditions (dwithin  = 0.63–1.24), with the procedure intended to train attention towards threat cues producing, relative to the control condition, a significantly greater reduction of social fears. There were no significant differences in social anxiety outcome between the training condition intended to induce attentional bias towards positive cues and the control condition. To our knowledge, this is the first RCT where a condition intended to induce attention bias to negative cues yielded greater emotional benefits than a control condition. Intriguingly, changes in symptoms are unlikely to be by the mechanism of change in attention processes since there was no change detected in bias per se. Implications of this finding for future research on attention bias modification in social anxiety are discussed. Trial Registration ClinicalTrials.gov NCT01463137 PMID:24098630

Internet-based attention bias modification for social anxiety: a randomised controlled comparison of training towards negative and training towards positive cues.

PubMed

Boettcher, Johanna; Leek, Linda; Matson, Lisa; Holmes, Emily A; Browning, Michael; MacLeod, Colin; Andersson, Gerhard; Carlbring, Per

2013-01-01

Biases in attention processes are thought to play a crucial role in the aetiology and maintenance of Social Anxiety Disorder (SAD). The goal of the present study was to examine the efficacy of a programme intended to train attention towards positive cues and a programme intended to train attention towards negative cues. In a randomised, controlled, double-blind design, the impact of these two training conditions on both selective attention and social anxiety were compared to that of a control training condition. A modified dot probe task was used, and delivered via the internet. A total of 129 individuals, diagnosed with SAD, were randomly assigned to one of these three conditions and took part in a 14-day programme with daily training/control sessions. Participants in all three groups did not on average display an attentional bias prior to the training. Critically, results on change in attention bias implied that significantly differential change in selective attention to threat was not detected in the three conditions. However, symptoms of social anxiety reduced significantly from pre- to follow-up-assessment in all three conditions (dwithin  = 0.63-1.24), with the procedure intended to train attention towards threat cues producing, relative to the control condition, a significantly greater reduction of social fears. There were no significant differences in social anxiety outcome between the training condition intended to induce attentional bias towards positive cues and the control condition. To our knowledge, this is the first RCT where a condition intended to induce attention bias to negative cues yielded greater emotional benefits than a control condition. Intriguingly, changes in symptoms are unlikely to be by the mechanism of change in attention processes since there was no change detected in bias per se. Implications of this finding for future research on attention bias modification in social anxiety are discussed. ClinicalTrials.gov NCT01463137.

Multivariate meta-analysis using individual participant data

PubMed Central

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

2016-01-01

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

Dark skin decreases the accuracy of pulse oximeters at low oxygen saturation: the effects of oximeter probe type and gender.

PubMed

Feiner, John R; Severinghaus, John W; Bickler, Philip E

2007-12-01

Pulse oximetry may overestimate arterial oxyhemoglobin saturation (Sao2) at low Sao2 levels in individuals with darkly pigmented skin, but other factors, such as gender and oximeter probe type, remain less studied. We studied the relationship between skin pigment and oximeter accuracy in 36 subjects (19 males, 17 females) of a range of skin tones. Clip-on type sensors and adhesive/disposable finger probes for the Masimo Radical, Nellcor N-595, and Nonin 9700 were studied. Semisupine subjects breathed air-nitrogen-CO2 mixtures via a mouthpiece to rapidly achieve 2- to 3-min stable plateaus of Sao2. Comparisons of Sao2 measured by pulse oximetry (Spo2) with Sao2 (by Radiometer OSM-3) were used in a multivariate model to assess the source of errors. The mean bias (Spo2 - Sao2) for the 70%-80% saturation range was 2.61% for the Masimo Radical with clip-on sensor, -1.58% for the Radical with disposable sensor, 2.59% for the Nellcor clip, 3.6% for the Nellcor disposable, -0.60% for the Nonin clip, and 2.43% for the Nonin disposable. Dark skin increased bias at low Sao2; greater bias was seen with adhesive/disposable sensors than with the clip-on types. Up to 10% differences in saturation estimates were found among different instruments in dark-skinned subjects at low Sao2. Multivariate analysis indicated that Sao2 level, sensor type, skin color, and gender were predictive of errors in Spo2 estimates at low Sao2 levels. The data suggest that clinically important bias should be considered when monitoring patients with saturations below 80%, especially those with darkly pigmented skin; but further study is needed to confirm these observations in the relevant populations.

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.

Fine-Tuning Cross-Battery Assessment Procedures: After Follow-Up Testing, Use All Valid Scores, Cohesive or Not

ERIC Educational Resources Information Center

Schneider, W. Joel; Roman, Zachary

2018-01-01

We used data simulations to test whether composites consisting of cohesive subtest scores are more accurate than composites consisting of divergent subtest scores. We demonstrate that when multivariate normality holds, divergent and cohesive scores are equally accurate. Furthermore, excluding divergent scores results in biased estimates of…

A General Approach for Estimating Scale Score Reliability for Panel Survey Data

ERIC Educational Resources Information Center

Biemer, Paul P.; Christ, Sharon L.; Wiesen, Christopher A.

2009-01-01

Scale score measures are ubiquitous in the psychological literature and can be used as both dependent and independent variables in data analysis. Poor reliability of scale score measures leads to inflated standard errors and/or biased estimates, particularly in multivariate analysis. Reliability estimation is usually an integral step to assess…

Exploring Sex Differences in Worry with a Cognitive Vulnerability Model

ERIC Educational Resources Information Center

Zalta, Alyson K.; Chambless, Dianne L.

2008-01-01

A multivariate model was developed to examine the relative contributions of mastery, stress, interpretive bias, and coping to sex differences in worry. Rumination was incorporated as a second outcome variable to test the specificity of these associations. Participants included two samples of undergraduates totaling 302 men and 379 women. A path…

A procedure for linking psychosocial job characteristics data to health surveys.

PubMed Central

Schwartz, J E; Pieper, C F; Karasek, R A

1988-01-01

A system is presented for linking information about psychosocial characteristics of job situations to national health surveys. Job information can be imputed to individuals on surveys that contain three-digit US Census occupation codes. Occupational mean scores on psychosocial job characteristics-control over task situation (decision latitude), psychological work load, physical exertion, and other measures-for the linkage system are derived from US national surveys of working conditions (Quality of Employment Surveys 1969, 1972, and 1977). This paper discusses a new method for reducing the biases in multivariate analyses that are likely to arise when utilizing linkage systems based on mean scores. Such biases are reduced by modifying the linkage system to adjust imputed individual scores for demographic factors such as age, education, race, marital status and, implicitly, sex (since men and women have separate linkage data bases). Statistics on the linkage system's efficiency and reliability are reported. All dimensions have high inter-survey reproducibility. Despite their psychosocial nature, decision latitude and physical exertion can be more efficiently imputed with the linkage system than earnings (a non-psychosocial job characteristic). The linkage system presented here is a useful tool for initial epidemiological studies of the consequences of psychosocial job characteristics and constitutes the methodological basis for the subsequent paper. PMID:3389426

Retraining automatic action tendencies changes alcoholic patients' approach bias for alcohol and improves treatment outcome.

PubMed

Wiers, Reinout W; Eberl, Carolin; Rinck, Mike; Becker, Eni S; Lindenmeyer, Johannes

2011-04-01

This study tested the effects of a new cognitive-bias modification (CBM) intervention that targeted an approach bias for alcohol in 214 alcoholic inpatients. Patients were assigned to one of two experimental conditions, in which they were explicitly or implicitly trained to make avoidance movements (pushing a joystick) in response to alcohol pictures, or to one of two control conditions, in which they received no training or sham training. Four brief sessions of experimental CBM preceded regular inpatient treatment. In the experimental conditions only, patients' approach bias changed into an avoidance bias for alcohol. This effect generalized to untrained pictures in the task used in the CBM and to an Implicit Association Test, in which alcohol and soft-drink words were categorized with approach and avoidance words. Patients in the experimental conditions showed better treatment outcomes a year later. These findings indicate that a short intervention can change alcoholics' automatic approach bias for alcohol and may improve treatment outcome.

Aerodynamic parameter estimation via Fourier modulating function techniques

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1995-01-01

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

Science Possible Selves and the Desire to be a Scientist: Mindsets, Gender Bias, and Confidence during Early Adolescence.

PubMed

Hill, Patricia Wonch; McQuillan, Julia; Talbert, Eli; Spiegel, Amy; Gauthier, G Robin; Diamond, Judy

2017-06-01

In the United States, gender gaps in science interest widen during the middle school years. Recent research on adults shows that gender gaps in some academic fields are associated with mindsets about ability and gender-science biases. In a sample of 529 students in a U.S. middle school, we assess how explicit boy-science bias, science confidence, science possible self (belief in being able to become a scientist), and desire to be a scientist vary by gender. Guided by theories and prior research, we use a series of multivariate logistic regression models to examine the relationships between mindsets about ability and these variables. We control for self-reported science grades, social capital, and race/ethnic minority status. Results show that seeing academic ability as innate ("fixed mindsets") is associated with boy-science bias, and that younger girls have less boy-science bias than older girls. Fixed mindsets and boy-science bias are both negatively associated with a science possible self; science confidence is positively associated with a science possible self. In the final model, high science confident and having a science possible self are positively associated with a desire to be a scientist. Facilitating growth mindsets and countering boy-science bias in middle school may be fruitful interventions for widening participation in science careers.

Science Possible Selves and the Desire to be a Scientist: Mindsets, Gender Bias, and Confidence during Early Adolescence

PubMed Central

McQuillan, Julia; Talbert, Eli; Spiegel, Amy; Gauthier, G. Robin; Diamond, Judy

2017-01-01

In the United States, gender gaps in science interest widen during the middle school years. Recent research on adults shows that gender gaps in some academic fields are associated with mindsets about ability and gender-science biases. In a sample of 529 students in a U.S. middle school, we assess how explicit boy-science bias, science confidence, science possible self (belief in being able to become a scientist), and desire to be a scientist vary by gender. Guided by theories and prior research, we use a series of multivariate logistic regression models to examine the relationships between mindsets about ability and these variables. We control for self-reported science grades, social capital, and race/ethnic minority status. Results show that seeing academic ability as innate (“fixed mindsets”) is associated with boy-science bias, and that younger girls have less boy-science bias than older girls. Fixed mindsets and boy-science bias are both negatively associated with a science possible self; science confidence is positively associated with a science possible self. In the final model, high science confident and having a science possible self are positively associated with a desire to be a scientist. Facilitating growth mindsets and countering boy-science bias in middle school may be fruitful interventions for widening participation in science careers. PMID:29527360

Health status measurement in Toxic Oil Syndrome.

PubMed

Gómez de la Cámara, A; Posada de la Paz, M; Abaitua Borda, I; Barainca Oyagüe, M T; Abraira Santos, V; Ruiz-Navarro, M D; Terracini, B

1998-10-01

Toxic Oil Syndrome (TOS) is a previously unreported condition which affected more than 20,000 people in Spain in 1981 and whose natural history is unknown. In 1993-94, a stratified random sample of 1400 survivors was drawn to measure their health status through clinical examination and their self-perception of well-being through the Nottingham Health Profile Questionnaire (NHPQ). Two-thirds of the sample population responded; indirect estimates suggest that selection bias was limited. Clear and intermediate signs of neuropathy were found in one-fifth and one-half of the patients, respectively. One-fourth and one-sixth showed some degree of scleroderma and contractures. All conditions were more frequent in women than in men and in age >50 than in younger ages. Although no concurrent control group was included in the study, prevalences of these conditions are well above expectations and are largely attributable to TOS. NHPQ scores increased with age in both sexes up to age 50, after which they reached a plateau (with values around 48 in men and 62 in women). Scores were associated to the occurrence of peripheral neurological changes, contractures, and scleroderma-like conditions. A multivariate analysis indicated age, sex, and severity of neurological conditions as major determinants of the NHPQ scores. This overall pattern of findings is peculiar to TOS and differs from the typical post-disaster nonspecific syndrome.

The Influence of Respondent Characteristics on the Validity of Self-Reported Survey Responses.

PubMed

Guerard, Barbara; Omachonu, Vincent; Harvey, Raymond A; Hernandez, S Robert; Sen, Bisakha

2016-06-01

To examine concordance between member self-reports and the organization's administrative claims data for two key health factors: number of chronic conditions, and number of prescription drugs. Medicare Advantage plan claims data and member survey data from 2011 to 2012. Mailed surveys to 15,000 members, enrolled minimum 6 months, drawn from a random sample of primary care physician practices with at least 200 members. Descriptive statistics were generated for extent of concordance. Multivariable logistic regressions were used to analyze the association of selected respondent characteristics with likelihood of concordance. Concordance for number of chronic conditions was 58.4 percent, with 27.3 percent under-reporting, 14.2 percent over-reporting. Concordance for number of prescription drugs was 56.6 percent with 38.9 percent under-reporting, 4.5 percent over-reporting. Number of prescriptions and assistance in survey completion were associated with higher likelihood of concordance for chronic conditions. Assistance in survey completion and number of chronic conditions were associated with higher concordance, and age and number of prescriptions were associated with lower concordance, for prescription drugs. Self-reported number of chronic conditions and prescription medications are not in high concordance with claims data. Health care researchers and policy makers using patient self-reported data should be aware of these potential biases. © Health Research and Educational Trust.

Effects of Kindergarten Retention on Children's Social-Emotional Development: An Application of Propensity Score Method to Multivariate, Multilevel Data

ERIC Educational Resources Information Center

Hong, Guanglei; Yu, Bing

2008-01-01

This study examines the effects of kindergarten retention on children's social-emotional development in the early, middle, and late elementary years. Previous studies have generated mixed results partly due to some major methodological challenges, including selection bias, measurement error, and divergent perceptions of multiple respondents in…

Children's Attitudes toward Race and Gender.

ERIC Educational Resources Information Center

Warner, Juliet L.

An implicit assumption in the majority of literature looking at development of prejudice in children is that race prejudice and sex prejudice are equivalent across groups; that is, sex bias is not conditional on race, and likewise race bias is not conditional on sex bias of the child. However, Warner, Fishbein, Ritchey and Case (2001) found strong…

Unconscious gender bias in fame judgments?

PubMed

Buchner, A; Wippich, W

1996-01-01

In two experiments the conditions of, and the processes leading to, gender biases in fame judgments were investigated. In Experiment 1, the gender bias was not reduced in a condition that alerted participants to the gender of the names. In Experiment 2, participants' sex-role orientation, but not their gender, was related to the gender bias. The process dissociation procedure was used in both experiments in an attempt to separate conscious and unconscious memory processes contributing to the gender bias. Using L.L. Jacoby's 1991) original measurement model there appeared to be evidence for unconscious influences on the gender bias in fame judgments. Unfortunately, this evidence disappeared when a model was used that takes guessing and, hence, response biases into account, which confirms that measurement models that ignore response biases in the process dissociation procedure may lead to erroneous conclusions.

Attention Bias Modification for Major Depressive Disorder: Effects on Attention Bias, Resting State Connectivity, and Symptom Change

PubMed Central

Beevers, Christopher G.; Clasen, Peter C.; Enock, Philip M.; Schnyer, David M.

2015-01-01

Cognitive theories of depression posit that selective attention for negative information contributes to the maintenance of depression. The current study experimentally tested this idea by randomly assigning adults with Major Depressive Disorder (MDD) to four weeks of computer-based attention bias modification designed to reduce negative attention bias or four weeks of placebo attention training. Findings indicate that compared to placebo training, attention bias modification reduced negative attention bias and increased resting-state connectivity within a neural circuit (i.e., middle frontal gyrus and dorsal anterior cingulate cortex) that supports control over emotional information. Further, pre- to post-training change in negative attention bias was significantly correlated with depression symptom change only in the active training condition. Exploratory analyses indicated that pre- to post-training changes in resting state connectivity within a circuit associated with sustained attention to visual information (i.e., precuenus and middle frontal gyrus) contributed to symptom improvement in the placebo condition. Importantly, depression symptoms did not change differentially between the training groups—overall, a 40% decrease in symptoms was observed across attention training conditions. Findings suggest that negative attention bias is associated with the maintenance of depression; however, general attentional control may also maintain depression symptoms, as evidenced by resting state connectivity and depression symptom improvement in the placebo training condition. PMID:25894440

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.

Mind-Body Practices and the Self: Yoga and Meditation Do Not Quiet the Ego but Instead Boost Self-Enhancement.

PubMed

Gebauer, Jochen E; Nehrlich, Andreas D; Stahlberg, Dagmar; Sedikides, Constantine; Hackenschmidt, Anke; Schick, Doreen; Stegmaier, Clara A; Windfelder, Cara C; Bruk, Anna; Mander, Johannes

2018-06-01

Mind-body practices enjoy immense public and scientific interest. Yoga and meditation are highly popular. Purportedly, they foster well-being by curtailing self-enhancement bias. However, this "ego-quieting" effect contradicts an apparent psychological universal, the self-centrality principle. According to this principle, practicing any skill renders that skill self-central, and self-centrality breeds self-enhancement bias. We examined those opposing predictions in the first tests of mind-body practices' self-enhancement effects. In Experiment 1, we followed 93 yoga students over 15 weeks, assessing self-centrality and self-enhancement bias after yoga practice (yoga condition, n = 246) and without practice (control condition, n = 231). In Experiment 2, we followed 162 meditators over 4 weeks (meditation condition: n = 246; control condition: n = 245). Self-enhancement bias was higher in the yoga (Experiment 1) and meditation (Experiment 2) conditions, and those effects were mediated by greater self-centrality. Additionally, greater self-enhancement bias mediated mind-body practices' well-being benefits. Evidently, neither yoga nor meditation fully quiet the ego; to the contrary, they boost self-enhancement.

Asymmetry of Reinforcement and Punishment in Human Choice

PubMed Central

Rasmussen, Erin B; Newland, M Christopher

2008-01-01

The hypothesis that a penny lost is valued more highly than a penny earned was tested in human choice. Five participants clicked a computer mouse under concurrent variable-interval schedules of monetary reinforcement. In the no-punishment condition, the schedules arranged monetary gain. In the punishment conditions, a schedule of monetary loss was superimposed on one response alternative. Deviations from generalized matching using the free parameters c (sensitivity to reinforcement) and log k (bias) were compared in the no-punishment and punishment conditions. The no-punishment conditions yielded values of log k that approximated zero for all participants, indicating no bias. In the punishment condition, values of log k deviated substantially from zero, revealing a 3-fold bias toward the unpunished alternative. Moreover, the c parameters were substantially smaller in punished conditions. The values for bias and sensitivity under punishment did not change significantly when the measure of net reinforcers (gains minus losses) was applied to the analysis. These results mean that punishment reduced the sensitivity of behavior to reinforcement and biased performance toward the unpunished alternative. We concluded that a single punisher subtracted more value than a single reinforcer added, indicating an asymmetry in the law of effect. PMID:18422016

Experimental and theoretical determination of sea-state bias in radar altimetry

NASA Technical Reports Server (NTRS)

Stewart, Robert H.

1991-01-01

The major unknown error in radar altimetry is due to waves on the sea surface which cause the mean radar-reflecting surface to be displaced from mean sea level. This is the electromagnetic bias. The primary motivation for the project was to understand the causes of the bias so that the error it produces in radar altimetry could be calculated and removed from altimeter measurements made from space by the Topex/Poseidon altimetric satellite. The goals of the project were: (1) observe radar scatter at vertical incidence using a simple radar on a platform for a wide variety of environmental conditions at the same time wind and wave conditions were measured; (2) calculate electromagnetic bias from the radar observations; (3) investigate the limitations of the present theory describing radar scatter at vertical incidence; (4) compare measured electromagnetic bias with bias calculated from theory using measurements of wind and waves made at the time of the radar measurements; and (5) if possible, extend the theory so bias can be calculated for a wider range of environmental conditions.

Bias modification training can alter approach bias and chocolate consumption.

PubMed

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

2016-01-01

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

Multivariate meta-analysis using individual participant data.

PubMed

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

2015-06-01

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

An attitude of gratitude: The effects of body-focused gratitude on weight bias internalization and body image.

PubMed

Dunaev, Jamie; Markey, Charlotte H; Brochu, Paula M

2018-06-01

Internalized weight bias and body dissatisfaction are associated with a number of negative psychological and physical health outcomes. The current study examined the effectiveness of body-focused gratitude, through a short writing exercise, as a strategy to reduce internalized weight bias and improve body image. Young adults (M age  = 22.71, SD = 2.08, 51.2% female) were randomly assigned to either a body gratitude condition (n = 185) or a control condition (n = 184). Results indicated that participants in the gratitude condition reported significantly lower weight bias internalization and significantly more favorable appearance evaluation and greater body satisfaction when compared to the control condition. These effects were in the small range (ds = 0.27-0.33), and neither gender nor BMI moderated these effects. These findings provide preliminary support for body-focused gratitude writing exercises as an effective individual-level strategy for both reducing internalized weight bias and improving body image. Copyright © 2018 Elsevier Ltd. All rights reserved.

Aperture Synthesis Shows Perceptual Integration of Geometrical Form Across Saccades.

PubMed

Schreiber, Kai; Morgan, Michael

2018-03-01

We investigated the perceptual bias in perceived relative lengths in the Brentano version of the Müller-Lyer arrowheads figure. The magnitude of the bias was measured both under normal whole-figure viewing condition and under an aperture viewing condition, where participants moved their gaze around the figure but could see only one arrowhead at a time through a Gaussian-weighted contrast window. The extent of the perceptual bias was similar under the two conditions. The stimuli were presented on a CRT in a light-proof room with room-lights off, but visual context was provided by a rectangular frame surrounding the figure. The frame was either stationary with respect to the figure or moved in such a manner that the bias would be counteracted if the observer were locating features with respect to the frame. Biases were reduced in the latter condition. We conclude that integration occurs over saccades, but largely in an external visual framework, rather than in a body-centered frame using an extraretinal signal.

Uncertainty Analysis of Instrument Calibration and Application

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Predictors of Major Depression and Posttraumatic Stress Disorder Following Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

PubMed

Cnossen, Maryse C; Scholten, Annemieke C; Lingsma, Hester F; Synnot, Anneliese; Haagsma, Juanita; Steyerberg, Prof Ewout W; Polinder, Suzanne

2017-01-01

Although major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) are prevalent after traumatic brain injury (TBI), little is known about which patients are at risk for developing them. The authors systematically reviewed the literature on predictors and multivariable models for MDD and PTSD after TBI. The authors included 26 observational studies. MDD was associated with female gender, preinjury depression, postinjury unemployment, and lower brain volume, whereas PTSD was related to shorter posttraumatic amnesia, memory of the traumatic event, and early posttraumatic symptoms. Risk of bias ratings for most studies were acceptable, although studies that developed a multivariable model suffered from methodological shortcomings.

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods

PubMed Central

Stukel, Thérèse A.; Fisher, Elliott S; Wennberg, David E.; Alter, David A.; Gottlieb, Daniel J.; Vermeulen, Marian J.

2007-01-01

Context Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases. Objective To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis. Design, Setting, and Patients A national cohort of 122 124 patients who were elderly (aged 65–84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994–1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission. Main Outcome Measure Risk-adjusted relative mortality rate using each of the analytic methods. Results Patients who received cardiac catheterization (n=73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50–0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53–0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52–0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79–0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21 %. Conclusions Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions. PMID:17227979

The impact of non-response bias due to sampling in public health studies: A comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health.

PubMed

Cheung, Kei Long; Ten Klooster, Peter M; Smit, Cees; de Vries, Hein; Pieterse, Marcel E

2017-03-23

In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the mandatory sample. No moderating effects were found for sampling method on associations between variables. This is one of first studies to provide strong evidence that voluntary recruitment may lead to a strong non-response bias in health-related prevalence estimates in adolescents, as compared to mandatory recruitment. The resulting underestimation in prevalence of health behaviours and well-being measures appeared large, up to a four-fold lower proportion for self-reported alcohol consumption. Correlations between variables, though, appeared to be insensitive to sampling bias.

Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math.

PubMed

Raizada, Rajeev D S; Tsao, Feng-Ming; Liu, Huei-Mei; Holloway, Ian D; Ansari, Daniel; Kuhl, Patricia K

2010-05-15

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain-behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI. Multivariate pattern-based fMRI analysis methods use classifiers to analyse multiple voxels together, but can also introduce selection bias via data-reduction steps as feature selection of voxels, pre-selecting activated regions, or principal components analysis. We show here that strong brain-behaviour links can be revealed without any voxel selection or data reduction, using just plain linear regression as a classifier applied to the whole brain at once, i.e. treating each entire brain volume as a single multi-voxel pattern. The brain-behaviour correlations emerged despite the fact that the classifier was not provided with any information at all about subjects' behaviour, but instead was given only the neural data and its condition-labels. Surprisingly, more powerful classifiers such as a linear SVM and regularised logistic regression produce very similar results. We discuss some possible reasons why the very simple brain-wide linear regression model is able to find correlations with behaviour that are as strong as those obtained on the one hand from a specific ROI and on the other hand from more complex classifiers. In a manner which is unencumbered by arbitrary choices, our approach offers a method for investigating connections between brain and behaviour which is simple, rigorous and direct. Copyright (c) 2010 Elsevier Inc. All rights reserved.

A multistate dynamic site occupancy model for spatially aggregated sessile communities

USGS Publications Warehouse

Fukaya, Keiichi; Royle, J. Andrew; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2017-01-01

Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations.We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error.By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account.Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.

Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math

PubMed Central

Raizada, Rajeev D.S.; Tsao, Feng-Ming; Liu, Huei-Mei; Holloway, Ian D.; Ansari, Daniel; Kuhl, Patricia K.

2010-01-01

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain–behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI. Multivariate pattern-based fMRI analysis methods use classifiers to analyse multiple voxels together, but can also introduce selection bias via data-reduction steps as feature selection of voxels, pre-selecting activated regions, or principal components analysis. We show here that strong brain–behaviour links can be revealed without any voxel selection or data reduction, using just plain linear regression as a classifier applied to the whole brain at once, i.e. treating each entire brain volume as a single multi-voxel pattern. The brain–behaviour correlations emerged despite the fact that the classifier was not provided with any information at all about subjects' behaviour, but instead was given only the neural data and its condition-labels. Surprisingly, more powerful classifiers such as a linear SVM and regularised logistic regression produce very similar results. We discuss some possible reasons why the very simple brain-wide linear regression model is able to find correlations with behaviour that are as strong as those obtained on the one hand from a specific ROI and on the other hand from more complex classifiers. In a manner which is unencumbered by arbitrary choices, our approach offers a method for investigating connections between brain and behaviour which is simple, rigorous and direct. PMID:20132896

Thinking in Black and White: Conscious thought increases racially biased judgments through biased face memory.

PubMed

Strick, Madelijn; Stoeckart, Peter F; Dijksterhuis, Ap

2015-11-01

It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiments 1 and 2, university students formed impressions of Black and White housemate candidates. They judged the candidates either immediately (immediate decision condition), thought about their judgments for a few minutes (conscious thought condition), or performed an unrelated task for a few minutes (unconscious thought condition). Conscious thinkers and immediate decision-makers showed a stronger face memory bias than unconscious thinkers, and this mediated increased judgment bias, although not all results were significant. Experiment 3 used a new, different paradigm and showed that a Black male was remembered as darker after a period of conscious thought than after a period of unconscious thought. Implications for racial prejudice are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

Korn, Edward L; Freidlin, Boris

2017-06-01

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

Medical School Factors Associated with Changes in Implicit and Explicit Bias Against Gay and Lesbian People among 3492 Graduating Medical Students.

PubMed

Phelan, Sean M; Burke, Sara E; Hardeman, Rachel R; White, Richard O; Przedworski, Julia; Dovidio, John F; Perry, Sylvia P; Plankey, Michael; A Cunningham, Brooke; Finstad, Deborah; W Yeazel, Mark; van Ryn, Michelle

2017-11-01

Implicit and explicit bias among providers can influence the quality of healthcare. Efforts to address sexual orientation bias in new physicians are hampered by a lack of knowledge of school factors that influence bias among students. To determine whether medical school curriculum, role modeling, diversity climate, and contact with sexual minorities predict bias among graduating students against gay and lesbian people. Prospective cohort study. A sample of 4732 first-year medical students was recruited from a stratified random sample of 49 US medical schools in the fall of 2010 (81% response; 55% of eligible), of which 94.5% (4473) identified as heterosexual. Seventy-eight percent of baseline respondents (3492) completed a follow-up survey in their final semester (spring 2014). Medical school predictors included formal curriculum, role modeling, diversity climate, and contact with sexual minorities. Outcomes were year 4 implicit and explicit bias against gay men and lesbian women, adjusted for bias at year 1. In multivariate models, lower explicit bias against gay men and lesbian women was associated with more favorable contact with LGBT faculty, residents, students, and patients, and perceived skill and preparedness for providing care to LGBT patients. Greater explicit bias against lesbian women was associated with discrimination reported by sexual minority students (b = 1.43 [0.16, 2.71]; p = 0.03). Lower implicit sexual orientation bias was associated with more frequent contact with LGBT faculty, residents, students, and patients (b = -0.04 [-0.07, -0.01); p = 0.008). Greater implicit bias was associated with more faculty role modeling of discriminatory behavior (b = 0.34 [0.11, 0.57); p = 0.004). Medical schools may reduce bias against sexual minority patients by reducing negative role modeling, improving the diversity climate, and improving student preparedness to care for this population.

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

2006-01-01

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Effects of standard and explicit cognitive bias modification and computer-administered cognitive-behaviour therapy on cognitive biases and social anxiety.

PubMed

Mobini, Sirous; Mackintosh, Bundy; Illingworth, Jo; Gega, Lina; Langdon, Peter; Hoppitt, Laura

2014-06-01

This study examines the effects of a single session of Cognitive Bias Modification to induce positive Interpretative bias (CBM-I) using standard or explicit instructions and an analogue of computer-administered CBT (c-CBT) program on modifying cognitive biases and social anxiety. A sample of 76 volunteers with social anxiety attended a research site. At both pre- and post-test, participants completed two computer-administered tests of interpretative and attentional biases and a self-report measure of social anxiety. Participants in the training conditions completed a single session of either standard or explicit CBM-I positive training and a c-CBT program. Participants in the Control (no training) condition completed a CBM-I neutral task matched the active CBM-I intervention in format and duration but did not encourage positive disambiguation of socially ambiguous or threatening scenarios. Participants in both CBM-I programs (either standard or explicit instructions) and the c-CBT condition exhibited more positive interpretations of ambiguous social scenarios at post-test and one-week follow-up as compared to the Control condition. Moreover, the results showed that CBM-I and c-CBT, to some extent, changed negative attention biases in a positive direction. Furthermore, the results showed that both CBM-I training conditions and c-CBT reduced social anxiety symptoms at one-week follow-up. This study used a single session of CBM-I training, however multi-sessions intervention might result in more endurable positive CBM-I changes. A computerised single session of CBM-I and an analogue of c-CBT program reduced negative interpretative biases and social anxiety. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effects of standard and explicit cognitive bias modification and computer-administered cognitive-behaviour therapy on cognitive biases and social anxiety☆

PubMed Central

Mobini, Sirous; Mackintosh, Bundy; Illingworth, Jo; Gega, Lina; Langdon, Peter; Hoppitt, Laura

2014-01-01

Background and objectives This study examines the effects of a single session of Cognitive Bias Modification to induce positive Interpretative bias (CBM-I) using standard or explicit instructions and an analogue of computer-administered CBT (c-CBT) program on modifying cognitive biases and social anxiety. Methods A sample of 76 volunteers with social anxiety attended a research site. At both pre- and post-test, participants completed two computer-administered tests of interpretative and attentional biases and a self-report measure of social anxiety. Participants in the training conditions completed a single session of either standard or explicit CBM-I positive training and a c-CBT program. Participants in the Control (no training) condition completed a CBM-I neutral task matched the active CBM-I intervention in format and duration but did not encourage positive disambiguation of socially ambiguous or threatening scenarios. Results Participants in both CBM-I programs (either standard or explicit instructions) and the c-CBT condition exhibited more positive interpretations of ambiguous social scenarios at post-test and one-week follow-up as compared to the Control condition. Moreover, the results showed that CBM-I and c-CBT, to some extent, changed negative attention biases in a positive direction. Furthermore, the results showed that both CBM-I training conditions and c-CBT reduced social anxiety symptoms at one-week follow-up. Limitations This study used a single session of CBM-I training, however multi-sessions intervention might result in more endurable positive CBM-I changes. Conclusions A computerised single session of CBM-I and an analogue of c-CBT program reduced negative interpretative biases and social anxiety. PMID:24412966

A New Multivariate Approach in Generating Ensemble Meteorological Forcings for Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2015-04-01

Producing reliable and accurate hydrologic ensemble forecasts are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model structure, and model parameters. Producing reliable and skillful precipitation ensemble forecasts is one approach to reduce the total uncertainty in hydrological applications. Currently, National Weather Prediction (NWP) models are developing ensemble forecasts for various temporal ranges. It is proven that raw products from NWP models are biased in mean and spread. Given the above state, there is a need for methods that are able to generate reliable ensemble forecasts for hydrological applications. One of the common techniques is to apply statistical procedures in order to generate ensemble forecast from NWP-generated single-value forecasts. The procedure is based on the bivariate probability distribution between the observation and single-value precipitation forecast. However, one of the assumptions of the current method is fitting Gaussian distribution to the marginal distributions of observed and modeled climate variable. Here, we have described and evaluated a Bayesian approach based on Copula functions to develop an ensemble precipitation forecast from the conditional distribution of single-value precipitation forecasts. Copula functions are known as the multivariate joint distribution of univariate marginal distributions, which are presented as an alternative procedure in capturing the uncertainties related to meteorological forcing. Copulas are capable of modeling the joint distribution of two variables with any level of correlation and dependency. This study is conducted over a sub-basin in the Columbia River Basin in USA using the monthly precipitation forecasts from Climate Forecast System (CFS) with 0.5x0.5 Deg. spatial resolution to reproduce the observations. The verification is conducted on a different period and the superiority of the procedure is compared with Ensemble Pre-Processor approach currently used by National Weather Service River Forecast Centers in USA.

In Utero Exposure to Histological Chorioamnionitis Primes the Exometabolomic Profiles of Preterm CD4+ T Lymphocytes.

PubMed

Matta, Poojitha; Sherrod, Stacy D; Marasco, Christina C; Moore, Daniel J; McLean, John A; Weitkamp, Joern-Hendrik

2017-11-01

Histological chorioamnionitis (HCA) is an intrauterine inflammatory condition that increases the risk for preterm birth, death, and disability because of persistent systemic and localized inflammation. The immunological mechanisms sustaining this response in the preterm newborn remain unclear. We sought to determine the consequences of HCA exposure on the fetal CD4 + T lymphocyte exometabolome. We cultured naive CD4 + T lymphocytes from HCA-positive and -negative preterm infants matched for gestational age, sex, race, prenatal steroid exposure, and delivery mode. We collected conditioned media samples before and after a 6-h in vitro activation of naive CD4 + T lymphocytes with soluble staphylococcal enterotoxin B and anti-CD28. We analyzed samples by ultraperformance liquid chromatography ion mobility-mass spectrometry. We determined the impact of HCA on the CD4 + T lymphocyte exometabolome and identified potential biomarker metabolites by multivariate statistical analyses. We discovered that: 1) CD4 + T lymphocytes exposed to HCA exhibit divergent exometabolomic profiles in both naive and activated states; 2) ∼30% of detected metabolites differentially expressed in response to activation were unique to HCA-positive CD4 + T lymphocytes; 3) metabolic pathways associated with glutathione detoxification and tryptophan degradation were altered in HCA-positive CD4 + T lymphocytes; and 4) flow cytometry and cytokine analyses suggested a bias toward a T H 1-biased immune response in HCA-positive samples. HCA exposure primes the neonatal adaptive immune processes by inducing changes to the exometabolomic profile of fetal CD4 + T lymphocytes. These exometabolomic changes may link HCA exposure to T H 1 polarization of the neonatal adaptive immune response. Copyright © 2017 by The American Association of Immunologists, Inc.

Effects of biases in domain wall network evolution. II. Quantitative analysis

NASA Astrophysics Data System (ADS)

Correia, J. R. C. C. C.; Leite, I. S. C. R.; Martins, C. J. A. P.

2018-04-01

Domain walls form at phase transitions which break discrete symmetries. In a cosmological context, they often overclose the Universe (contrary to observational evidence), although one may prevent this by introducing biases or forcing anisotropic evolution of the walls. In a previous work [Correia et al., Phys. Rev. D 90, 023521 (2014), 10.1103/PhysRevD.90.023521], we numerically studied the evolution of various types of biased domain wall networks in the early Universe, confirming that anisotropic networks ultimately reach scaling while those with a biased potential or biased initial conditions decay. We also found that the analytic decay law obtained by Hindmarsh was in good agreement with simulations of biased potentials, but not of biased initial conditions, and suggested that the difference was related to the Gaussian approximation underlying the analytic law. Here, we extend our previous work in several ways. For the cases of biased potential and biased initial conditions, we study in detail the field distributions in the simulations, confirming that the validity (or not) of the Gaussian approximation is the key difference between the two cases. For anisotropic walls, we carry out a more extensive set of numerical simulations and compare them to the canonical velocity-dependent one-scale model for domain walls, finding that the model accurately predicts the linear scaling regime after isotropization. Overall, our analysis provides a quantitative description of the cosmological evolution of these networks.

Attention bias modification training under working memory load increases the magnitude of change in attentional bias.

PubMed

Clarke, Patrick J F; Branson, Sonya; Chen, Nigel T M; Van Bockstaele, Bram; Salemink, Elske; MacLeod, Colin; Notebaert, Lies

2017-12-01

Attention bias modification (ABM) procedures have shown promise as a therapeutic intervention, however current ABM procedures have proven inconsistent in their ability to reliably achieve the requisite change in attentional bias needed to produce emotional benefits. This highlights the need to better understand the precise task conditions that facilitate the intended change in attention bias in order to realise the therapeutic potential of ABM procedures. Based on the observation that change in attentional bias occurs largely outside conscious awareness, the aim of the current study was to determine if an ABM procedure delivered under conditions likely to preclude explicit awareness of the experimental contingency, via the addition of a working memory load, would contribute to greater change in attentional bias. Bias change was assessed among 122 participants in response to one of four ABM tasks given by the two experimental factors of ABM training procedure delivered either with or without working memory load, and training direction of either attend-negative or avoid-negative. Findings revealed that avoid-negative ABM procedure under working memory load resulted in significantly greater reductions in attentional bias compared to the equivalent no-load condition. The current findings will require replication with clinical samples to determine the utility of the current task for achieving emotional benefits. These present findings are consistent with the position that the addition of a working memory load may facilitate change in attentional bias in response to an ABM training procedure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Do horses with poor welfare show 'pessimistic' cognitive biases?

PubMed

Henry, S; Fureix, C; Rowberry, R; Bateson, M; Hausberger, M

2017-02-01

This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.

Do horses with poor welfare show `pessimistic' cognitive biases?

NASA Astrophysics Data System (ADS)

Henry, S.; Fureix, C.; Rowberry, R.; Bateson, M.; Hausberger, M.

2017-02-01

This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations ( e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions ( e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food (`positive' location) or unpalatable food (`negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.

Training interpretation biases among individuals with body dysmorphic disorder symptoms.

PubMed

Premo, Julie E; Sarfan, Laurel D; Clerkin, Elise M

2016-03-01

The current study provided an initial test of a Cognitive Bias Modification for Interpretations (CBM-I) training paradigm among a sample with elevated BDD symptoms (N=86). As expected, BDD-relevant interpretations were reduced among participants who completed a positive (vs. comparison) training program. Results also pointed to the intriguing possibility that modifying biased appearance-relevant interpretations is causally related to changes in biased, socially relevant interpretations. Further, providing support for cognitive behavioral models, residual change in interpretations was associated with some aspects of in vivo stressor responding. However, contrary to expectations there were no significant effects of condition on emotional vulnerability to a BDD stressor, potentially because participants in both training conditions experienced reductions in biased socially-threatening interpretations following training (suggesting that the "comparison" condition was not inert). These findings have meaningful theoretical and clinical implications, and fit with transdiagnostic conceptualizations of psychopathology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Utilization of Prosodic Information in Syntactic Ambiguity Resolution

PubMed Central

2010-01-01

Two self paced listening experiments examined the role of prosodic phrasing in syntactic ambiguity resolution. In Experiment 1, the stimuli consisted of early closure sentences (e.g., “While the parents watched, the child sang a song.”) containing transitive-biased subordinate verbs paired with plausible direct objects or intransitive-biased subordinate verbs paired with implausible direct objects. Experiment 2 also contained early closure sentences with transitively and intransitive-biased subordinate verbs, but the subordinate verbs were always followed by plausible direct objects. In both experiments, there were two prosodic conditions. In the subject-biased prosodic condition, an intonational phrase boundary marked the clausal boundary following the subordinate verb. In the object-biased prosodic condition, the clause boundary was unmarked. The results indicate that lexical and prosodic cues interact at the subordinate verb and plausibility further affects processing at the ambiguous noun. Results are discussed with respect to models of the role of prosody in sentence comprehension. PMID:20033849

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.

Treatment of patent ductus arteriosus and neonatal mortality/morbidities: adjustment for treatment selection bias.

PubMed

Mirea, Lucia; Sankaran, Koravangattu; Seshia, Mary; Ohlsson, Arne; Allen, Alexander C; Aziz, Khalid; Lee, Shoo K; Shah, Prakesh S

2012-10-01

To examine the association between treatment for patent ductus arteriosus (PDA) and neonatal outcomes in preterm infants, after adjustment for treatment selection bias. Secondary analyses were conducted using data collected by the Canadian Neonatal Network for neonates born at a gestational age ≤ 32 weeks and admitted to neonatal intensive care units in Canada between 2004 and 2008. Infants who had PDA and survived beyond 72 hours were included in multivariable logistic regression analyses that compared mortality or any severe neonatal morbidity (intraventricular hemorrhage grades ≥ 3, retinopathy of prematurity stages ≥ 3, bronchopulmonary dysplasia, or necrotizing enterocolitis stages ≥ 2) between treatment groups (conservative management, indomethacin only, surgical ligation only, or both indomethacin and ligation). Propensity scores (PS) were estimated for each pair of treatment comparisons, and used in PS-adjusted and PS-matched analyses. Among 3556 eligible infants with a diagnosis of PDA, 577 (16%) were conservatively managed, 2026 (57%) received indomethacin only, 327 (9%) underwent ligation only, and 626 (18%) were treated with both indomethacin and ligation. All multivariable and PS-based analyses detected significantly higher mortality/morbidities for surgically ligated infants, irrespective of prior indomethacin treatment (OR ranged from 1.25-2.35) compared with infants managed conservatively or those who received only indomethacin. No significant differences were detected between infants treated with only indomethacin and those managed conservatively. Surgical ligation of PDA in preterm neonates was associated with increased neonatal mortality/morbidity in all analyses adjusted for measured confounders that attempt to account for treatment selection bias. Copyright © 2012 Mosby, Inc. All rights reserved.

Willingness to treat drug dependence and depression: comparisons of future health professionals

PubMed Central

Ahmedani, Brian K; Kubiak, Sheryl Pimlott; Rios-Bedoya, Carlos F; Mickus, Maureen; Anthony, James C

2011-01-01

Purpose Stigma-related feelings, including degree of enthusiasm and willingness to work with alcohol, drug, and mental disorder (ADM) patients, as well as anticipated success in such work, will be required for the United States to be successful in its new initiatives for ADM screening, brief intervention, and effective referral to treatment and rehabilitation services (SBIRT). This study investigates students of medicine and social work with respect to their stigma-related feelings and degree of enthusiasm or willingness to treat patients affected by alcohol dependence, nicotine dependence, or major depression. Inference is strengthened by an anonymous online survey approach, with use of randomized reinforcers to gain at least partial experimental control of nonparticipation biases that otherwise are present in student survey data. Material and methods All students on required course rosters were asked to participate in a two-part in-class and online assessment; 222 participated, with a gradient of participation induced via randomly drawn reinforcers for online survey participation. Between-group comparisons were made with a multivariate generalized linear model and generalized estimating equations approach that adjusts for covariates. Results Medical and social work students did not differ from each other with respect to their willingness to treat patients affected by major depression, alcohol dependence, or nicotine dependence, but together were less willing to treat nicotine and alcohol dependence-affected patients as compared to depression-affected patients. Personal history was not associated with the students’ willingness to treat, but men were less willing to treat. Drawing strength from the randomized reinforcer experimental design nested within this survey approach, the study evidence suggests potential nonparticipation bias in standard surveys on this topic. Conclusion These results indicate that future health professionals may prefer to treat depression as opposed to drug dependence conditions. For SBIRT success, curriculum change with educational interventions may be needed to increase willingness to treat patients with neuropsychiatric conditions such as drug dependence. Future research requires attention to a possible problem of nonparticipation bias in surveys of this type. PMID:21731413

How to lose weight bias fast! Evaluating a brief anti-weight bias intervention.

PubMed

Diedrichs, Phillippa C; Barlow, Fiona Kate

2011-11-01

Although experiencing weight bias is associated with poor physical and psychological health, health professionals often stigmatize overweight and obese clients. The objective of this study was to evaluate a brief educational intervention that aimed to reduce weight bias among Australian pre-service health students by challenging beliefs about the controllability of weight. Non-equivalent group comparison trial. Undergraduate psychology students were assigned to an intervention (n= 30), control (n= 35), or comparison (n= 20) condition. The intervention condition received a lecture on obesity, weight bias, and the multiple determinants of weight; the comparison condition received a lecture on obesity and the behavioural determinants of weight; and the control condition received no lecture. Beliefs about the controllability of weight and attitudes towards overweight and obese people were assessed 1 week pre-intervention, immediately post-intervention, and 3 weeks post-intervention. After receiving the lecture, participants in the intervention group were less likely to believe that weight is solely within individual control and were also less likely to hold negative attitudes towards overweight and obese people and rate them as unattractive. These changes were maintained 3 weeks post-intervention. There were no such changes in the control or comparison groups. Disparagement of overweight and obese peoples' social character increased over time for participants in the control condition but did not change in the comparison or intervention groups. This study provides evidence that brief, education-based anti-weight bias interventions show success in challenging weight controllability beliefs and reducing weight bias among pre-service health students. ©2011 The British Psychological Society.

Ametropia, retinal anatomy, and OCT abnormality patterns in glaucoma. 1. Impacts of refractive error and interartery angle

NASA Astrophysics Data System (ADS)

Elze, Tobias; Baniasadi, Neda; Jin, Qingying; Wang, Hui; Wang, Mengyu

2017-12-01

Retinal nerve fiber layer thickness (RNFLT) measured by optical coherence tomography (OCT) is widely used in clinical practice to support glaucoma diagnosis. Clinicians frequently interpret peripapillary RNFLT areas marked as abnormal by OCT machines. However, presently, clinical OCT machines do not take individual retinal anatomy variation into account, and according diagnostic biases have been shown particularly for patients with ametropia. The angle between the two major temporal retinal arteries (interartery angle, IAA) is considered a fundamental retinal ametropia marker. Here, we analyze peripapillary spectral domain OCT RNFLT scans of 691 glaucoma patients and apply multivariate logistic regression to quantitatively compare the diagnostic bias of spherical equivalent (SE) of refractive error and IAA and to identify the precise retinal locations of false-positive/negative abnormality marks. Independent of glaucoma severity (visual field mean deviation), IAA/SE variations biased abnormality marks on OCT RNFLT printouts at 36.7%/22.9% of the peripapillary area, respectively. 17.2% of the biases due to SE are not explained by IAA variation, particularly in inferonasal areas. To conclude, the inclusion of SE and IAA in OCT RNFLT norms would help to increase diagnostic accuracy. Our detailed location maps may help clinicians to reduce diagnostic bias while interpreting retinal OCT scans.

Coarse-Scale Biases for Spirals and Orientation in Human Visual Cortex

PubMed Central

Heeger, David J.

2013-01-01

Multivariate decoding analyses are widely applied to functional magnetic resonance imaging (fMRI) data, but there is controversy over their interpretation. Orientation decoding in primary visual cortex (V1) reflects coarse-scale biases, including an over-representation of radial orientations. But fMRI responses to clockwise and counter-clockwise spirals can also be decoded. Because these stimuli are matched for radial orientation, while differing in local orientation, it has been argued that fine-scale columnar selectivity for orientation contributes to orientation decoding. We measured fMRI responses in human V1 to both oriented gratings and spirals. Responses to oriented gratings exhibited a complex topography, including a radial bias that was most pronounced in the peripheral representation, and a near-vertical bias that was most pronounced near the foveal representation. Responses to clockwise and counter-clockwise spirals also exhibited coarse-scale organization, at the scale of entire visual quadrants. The preference of each voxel for clockwise or counter-clockwise spirals was predicted from the preferences of that voxel for orientation and spatial position (i.e., within the retinotopic map). Our results demonstrate a bias for local stimulus orientation that has a coarse spatial scale, is robust across stimulus classes (spirals and gratings), and suffices to explain decoding from fMRI responses in V1. PMID:24336733

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.

Implicit interpretation biases affect emotional vulnerability: a training study.

PubMed

Tran, Tanya B; Siemer, Matthias; Joormann, Jutta

2011-04-01

Cognitive theories of emotion propose that the interpretation of emotion-eliciting situations crucially shapes affective responses. Implicit or automatic biases in these interpretations may hinder emotion regulation and thereby increase risk for the onset and maintenance of psychological disorders. In this study, participants were randomly assigned to a positive or negative interpretation bias training using ambiguous social scenarios. After the completion of the training, a stress task was administered and changes in positive and negative affect and self-esteem were assessed. The results demonstrate that the interpretation bias training was successful in that participants exhibited a tendency to interpret novel scenarios in accordance with their training condition. Importantly, the positive training condition also had a protective effect on self-esteem. Participants in this condition did not exhibit a decrease in self-esteem after the stress task, whereas participants in the negative condition did. These results demonstrate that implicit cognitive biases can be trained and that this training affects self-esteem. Implications of these findings for research on psychopathology and emotion regulation are discussed. © 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

Testing neuropsychological hypotheses for cognitive deficits in psychopathic criminals: a study of global-local processing.

PubMed

Kosson, David S; Miller, Sarah K; Byrnes, Katherine A; Leveroni, Catherine L

2007-03-01

Competing hypotheses about neuropsychological mechanisms underlying psychopathy are seldom examined in the same study. We tested the left hemisphere activation hypothesis and the response modulation hypothesis of psychopathy in 172 inmates completing a global-local processing task under local bias, global bias, and neutral conditions. Consistent with the left hemisphere activation hypothesis, planned comparisons showed that psychopathic inmates classified local targets more slowly than nonpsychopathic inmates in a local bias condition and exhibited a trend toward similar deficits for global targets in this condition. However, contrary to the response modulation hypothesis, psychopaths were no slower to respond to local targets in a global bias condition. Because psychopathic inmates were not generally slower to respond to local targets, results are also not consistent with a general left hemisphere dysfunction account. Correlational analyses also indicated deficits specific to conditions presenting most targets at the local level initially. Implications for neuropsychological conceptualizations of psychopathy are considered.

Lineup identification by children: effects of clothing bias.

PubMed

Freire, Alejo; Lee, Kang; Williamson, Karen S; Stuart, Sarah J E; Lindsay, R C L

2004-06-01

This study examined effects of clothing cues on children's identification accuracy from lineups. Four- to 14-year-olds (n = 228) saw 12 video clips of individuals, each wearing a distinctly colored shirt. After watching each clip children were presented with a target-present or target-absent photo lineup. Three clothing conditions were included. In 2 conditions all lineup members wore the same colored shirt; in the third, biased condition, the shirt color of only one individual matched that seen in the preceding clip (the target in target-present trials and the replacement in target-absent trials). Correct identifications of the target in target-present trials were most frequent in the biased condition, whereas in target-absent trials the biased condition led to more false identifications of the target replacement. Older children were more accurate than younger children, both in choosing the target from target-present lineups and rejecting target-absent lineups. These findings suggest that a simple clothing cue such as shirt color can have a significant impact on children's lineup identification accuracy.

Lineup Identification by Children: Effects of Clothing Bias

PubMed Central

Freire, Alejo; Lee, Kang; Williamson, Karen S.; Stuart, Sarah J. E.; Lindsay, R. C. L.

2008-01-01

This study examined effects of clothing cues on children's identification accuracy from lineups. Four- to 14-year-olds (n = 228) saw 12 video clips of individuals, each wearing a distinctly colored shirt. After watching each clip children were presented with a target-present or target-absent photo lineup. Three clothing conditions were included. In 2 conditions all lineup members wore the same colored shirt; in the third, biased condition, the shirt color of only one individual matched that seen in the preceding clip (the target in target-present trials and the replacement in target-absent trials). Correct identifications of the target in target-present trials were most frequent in the biased condition, whereas in target-absent trials the biased condition led to more false identifications of the target replacement. Older children were more accurate than younger children, both in choosing the target from target-present lineups and rejecting target-absent lineups. These findings suggest that a simple clothing cue such as shirt color can have a significant impact on children's lineup identification accuracy. PMID:15264450

Attentional bias to emotional stimuli is altered during moderate- but not high-intensity exercise.

PubMed

Tian, Qu; Smith, J Carson

2011-12-01

Little is known regarding how attention to emotional stimuli is affected during simultaneously performed exercise. Attentional biases to emotional face stimuli were assessed in 34 college students (17 women) using the dot-probe task during counterbalanced conditions of moderate- (heart rate at 45% peak oxygen consumption) and high-intensity exercise (heart rate at 80% peak oxygen consumption) compared with seated rest. The dot-probe task consisted of 1 emotional face (pleasant or unpleasant) paired with a neutral face for 1,000 ms; 256 trials (128 trials for each valence) were presented during each condition. Each condition lasted approximately 10 min. Participants were instructed to perform each trial of the dot-probe task as quickly and accurately as possible during the exercise and rest conditions. During moderate-intensity exercise, participants exhibited significantly greater attentional bias scores to pleasant compared with unpleasant faces (p < .01), whereas attentional bias scores to emotional faces did not differ at rest or during high-intensity exercise (p > .05). In addition, the attentional bias to unpleasant faces was significantly reduced during moderate-intensity exercise compared with that during rest (p < .05). These results provide behavioral evidence that during exercise at a moderate intensity, there is a shift in attention allocation toward pleasant emotional stimuli and away from unpleasant emotional stimuli. Future work is needed to determine whether acute exercise may be an effective treatment approach to reduce negative bias or enhance positive bias in individuals diagnosed with mood or anxiety disorders, or whether attentional bias during exercise predicts adherence to exercise. (c) 2011 APA, all rights reserved.

Racial Bias in Neural Response for Pain Is Modulated by Minimal Group

PubMed Central

Shen, Fengtao; Hu, Yang; Fan, Mingxia; Wang, Huimin; Wang, Zhaoxin

2018-01-01

Whether empathic racial bias could be modulated is a subject of intense interest. The present study was carried out to explore whether empathic racial bias for pain is modulated by minimal group. Chinese/Western faces with neutral expressions receiving painful (needle penetration) or non-painful (Q-tip touch) stimulation were presented. Participants were asked to rate the pain intensity felt by Chinese/Western models of ingroup/outgroup members. Their implicit racial bias were also measured. Two lines of evidence indicated that the anterior cingulate cortex (ACC) was modulated by racial bias: (1) Chinese models elicited stronger activity than Western did in the ACC, and (2) activity in the ACC was modulated by implicit racial bias. Whereas the right anterior insula (rAI) were modulated by ingroup bias, in which ingroup member elicited stronger activity than outgroup member did. Furthermore, activity in the ACC was modulated by activity of rAI (i.e., ingroup bias) in the pain condition, while activity in the rAI was modulated by activity of ACC (i.e., racial bias) in the nopain condition. Our results provide evidence that there are different neural correlates for racial bias and ingroup bias, and neural racial bias for pain can be modulated by minimal group. PMID:29379429

Racial Bias in Neural Response for Pain Is Modulated by Minimal Group.

PubMed

Shen, Fengtao; Hu, Yang; Fan, Mingxia; Wang, Huimin; Wang, Zhaoxin

2017-01-01

Whether empathic racial bias could be modulated is a subject of intense interest. The present study was carried out to explore whether empathic racial bias for pain is modulated by minimal group. Chinese/Western faces with neutral expressions receiving painful (needle penetration) or non-painful (Q-tip touch) stimulation were presented. Participants were asked to rate the pain intensity felt by Chinese/Western models of ingroup/outgroup members. Their implicit racial bias were also measured. Two lines of evidence indicated that the anterior cingulate cortex (ACC) was modulated by racial bias: (1) Chinese models elicited stronger activity than Western did in the ACC, and (2) activity in the ACC was modulated by implicit racial bias. Whereas the right anterior insula (rAI) were modulated by ingroup bias, in which ingroup member elicited stronger activity than outgroup member did. Furthermore, activity in the ACC was modulated by activity of rAI (i.e., ingroup bias) in the pain condition, while activity in the rAI was modulated by activity of ACC (i.e., racial bias) in the nopain condition. Our results provide evidence that there are different neural correlates for racial bias and ingroup bias, and neural racial bias for pain can be modulated by minimal group.

Codon usage bias reveals genomic adaptations to environmental conditions in an acidophilic consortium.

PubMed

Hart, Andrew; Cortés, María Paz; Latorre, Mauricio; Martinez, Servet

2018-01-01

The analysis of codon usage bias has been widely used to characterize different communities of microorganisms. In this context, the aim of this work was to study the codon usage bias in a natural consortium of five acidophilic bacteria used for biomining. The codon usage bias of the consortium was contrasted with genes from an alternative collection of acidophilic reference strains and metagenome samples. Results indicate that acidophilic bacteria preferentially have low codon usage bias, consistent with both their capacity to live in a wide range of habitats and their slow growth rate, a characteristic probably acquired independently from their phylogenetic relationships. In addition, the analysis showed significant differences in the unique sets of genes from the autotrophic species of the consortium in relation to other acidophilic organisms, principally in genes which code for proteins involved in metal and oxidative stress resistance. The lower values of codon usage bias obtained in this unique set of genes suggest higher transcriptional adaptation to living in extreme conditions, which was probably acquired as a measure for resisting the elevated metal conditions present in the mine.

Omission bias and perceived intention in children and adults.

PubMed

Hayashi, Hajimu

2015-06-01

Omission bias refers to the tendency to judge acts of commission as morally worse than equivalent acts of omission. Children aged 7-8 and 11-12 years, as well as adults, made moral judgements about acts of commission and omission in two conditions in which the protagonist obtained a self-directed benefit. In the antisocial condition, the other person was harmed; in the selfish condition, the other person was not harmed. The results showed that adults and both age groups of children judged that the agent who did something (act of commission) was morally worse than the agent who did nothing (omission) for both antisocial and selfish conditions, although this judgement tendency was clearer in the selfish condition than in the antisocial condition. Agent intention was held constant across commission and omission, but most participants rated the intention of the agent who did something as stronger than that of the agent who did nothing. These results suggest that omission bias occurs regardless of differences in age and situation. In addition, perceived intention appears to change in conjunction with omission bias. © 2015 The British Psychological Society.

Longitudinal assessment of treatment effects on pulmonary ventilation using 1H/3He MRI multivariate templates

NASA Astrophysics Data System (ADS)

Tustison, Nicholas J.; Contrella, Benjamin; Altes, Talissa A.; Avants, Brian B.; de Lange, Eduard E.; Mugler, John P.

2013-03-01

The utitlity of pulmonary functional imaging techniques, such as hyperpolarized 3He MRI, has encouraged their inclusion in research studies for longitudinal assessment of disease progression and the study of treatment effects. We present methodology for performing voxelwise statistical analysis of ventilation maps derived from hyper­ polarized 3He MRI which incorporates multivariate template construction using simultaneous acquisition of IH and 3He images. Additional processing steps include intensity normalization, bias correction, 4-D longitudinal segmentation, and generation of expected ventilation maps prior to voxelwise regression analysis. Analysis is demonstrated on a cohort of eight individuals with diagnosed cystic fibrosis (CF) undergoing treatment imaged five times every two weeks with a prescribed treatment schedule.

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

PubMed

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

2016-12-01

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

Brief time course of trait anxiety-related attentional bias to fear-conditioned stimuli: Evidence from the dual-RSVP task.

PubMed

Booth, Robert W

2017-03-01

Attentional bias to threat is a much-studied feature of anxiety; it is typically assessed using response time (RT) tasks such as the dot probe. Findings regarding the time course of attentional bias have been inconsistent, possibly because RT tasks are sensitive to processes downstream of attention. Attentional bias was assessed using an accuracy-based task in which participants detected a single digit in two simultaneous rapid serial visual presentation (RSVP) streams of letters. Before the target, two coloured shapes were presented simultaneously, one in each RSVP stream; one shape had previously been associated with threat through Pavlovian fear conditioning. Attentional bias was indicated wherever participants identified targets in the threat's RSVP stream more accurately than targets in the other RSVP stream. In 87 unselected undergraduates, trait anxiety only predicted attentional bias when the target was presented immediately following the shapes, i.e. 160 ms later; by 320 ms the bias had disappeared. This suggests attentional bias in anxiety can be extremely brief and transitory. This initial study utilised an analogue sample, and was unable to physiologically verify the efficacy of the conditioning. The next steps will be to verify these results in a sample of diagnosed anxious patients, and to use alternative threat stimuli. The results of studies using response time to assess the time course of attentional bias may partially reflect later processes such as decision making and response preparation. This may limit the efficacy of therapies aiming to retrain attentional biases using response time tasks. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Probing the influence of unconscious fear-conditioned visual stimuli on eye movements.

PubMed

Madipakkam, Apoorva Rajiv; Rothkirch, Marcus; Wilbertz, Gregor; Sterzer, Philipp

2016-11-01

Efficient threat detection from the environment is critical for survival. Accordingly, fear-conditioned stimuli receive prioritized processing and capture overt and covert attention. However, it is unknown whether eye movements are influenced by unconscious fear-conditioned stimuli. We performed a classical fear-conditioning procedure and subsequently recorded participants' eye movements while they were exposed to fear-conditioned stimuli that were rendered invisible using interocular suppression. Chance-level performance in a forced-choice-task demonstrated unawareness of the stimuli. Differential skin conductance responses and a change in participants' fearfulness ratings of the stimuli indicated the effectiveness of conditioning. However, eye movements were not biased towards the fear-conditioned stimulus. Preliminary evidence suggests a relation between the strength of conditioning and the saccadic bias to the fear-conditioned stimulus. Our findings provide no strong evidence for a saccadic bias towards unconscious fear-conditioned stimuli but tentative evidence suggests that such an effect may depend on the strength of the conditioned response. Copyright © 2016 Elsevier Inc. All rights reserved.

A clock-aided positioning algorithm based on Kalman model of GNSS receiver clock bias

NASA Astrophysics Data System (ADS)

Zhu, Lingyao; Li, Zishen; Yuan, Hong

2017-10-01

The modeling and forecasting of the receiver clock bias is of practical significance, including the improvement of positioning accuracy, etc. When the clock frequency of the receiver is stable, the model can be established according to the historical clock bias data and the clock bias of the following time can be predicted. For this, we adopted the Kalman model to predict the receiver clock bias based on the calculated clock bias data obtained from the laboratory via sliding mode. Meanwhile, the relevant clock-aided positioning algorithm was presented. The results show that: the Kalman model can be used in practical work; and that under the condition that only 3 satellite signal can be received, this clock-aided positioning results can meet the needs of civilian users, which improves the continuity of positioning in harsh conditions.

[Relationship between Life Habits and Constitution Types of Chinese Medicine in the Senile Living at Home in Beijing Downtown].

PubMed

Shi, Mai; Liu, Zhao-lan; Xu, Mei-yan; Chen, Jie; Lin, Bing; Yu, Yong-chao; Ma, Xiao-tao

2016-05-01

To investigate the distribution of constitution types of Chinese medicine (CM) in the elderly living at home in Beijing downtown, and to explore its relationship with life habits. A total of 3894 senile more than 60 years old were enrolled in this study. Their constitution types of CM were typed using CM constitution questionnaire. Meanwhile, their demographic features, disease condition, diet habits, exercise habits, sleep habits, and so on were investigated. Multivariate Logistic regression analysis was used to evaluate the relationship between life habits and constitution types of CM. The number of mild type constitution senile was 1111 (28.53%) and the number of biased constitutions 2783 (71.47%). Biased constitutions of the top three were qi deficiency constitution (662, 17.00%), yang deficiency constitution (445, 11.43%), and blood stasis constitution (363, 9.32%). Univariate analysis showed that different habits of diet, exercise, and sleep exist among the senile of different constitutions (P < 0.05). By taking mild type constitution, multivariate Logistic regression analysis (except demographic indices and chronic history) showed that significantly positive correlation existed between qi deficiency constitution and favor for hot food (OR = 1.349, P = 0.015), yang deficiency constitution and favor for hot food (OR = 2.448, P < 0.01), phlegm-wetness constitution and favor for barbecue food (OR = 2.144, P = 0.003), wet-heat constitution and favor for sweet food (OR = 1.355, P = 0.032), wet-heat constitution and favor for tea (OR = 1.359, P = 0.047), blood stasis constitution and favor for hot food (OR = 1.422, P = 0.017), and qi depression constitution and favor for hot food (OR = 1.446, P = 0.031). Regular exercise had negative correlation with qi deficiency constitution (OR = 0.397, P < 0.01), yang deficiency constitution (OR = 0.522, P < 0.01) , phlegm-wetness constitution (OR = 0.475, P < 0.01), wet-heat constitution (OR = 0.647, P = 0.015), blood stasis constitution (OR = 0.608, P = 0.001), qi depression constitution (OR = 0.541, P = 0.001), and special diathesis constitution (OR = 0.466, P < 0.01). Early sleep and rise habit had negative with phlegm-wetness constitution (OR = 0.414, P < 0.01), wet-heat constitution (OR = 0.536, P = 0.015), blood stasis constitution (OR = 0.515, P = 0.004), and special diathesis constitution (OR = 0.526, P = 0.039). Different constitution types of CM might be highly related to specific life habits. Cultivating better life habits can improve biased constitutions of CM.

The influence of anticipatory processing on attentional biases in social anxiety.

PubMed

Mills, Adam C; Grant, DeMond M; Judah, Matt R; White, Evan J

2014-09-01

Research on cognitive theories of social anxiety disorder (SAD) has identified individual processes that influence this condition (e.g., cognitive biases, repetitive negative thinking), but few studies have attempted to examine the interaction between these processes. For example, attentional biases and anticipatory processing are theoretically related and have been found to influence symptoms of SAD, but they rarely have been studied together (i.e., Clark & Wells, 1995). Therefore, the goal of the current study was to examine the effect of anticipatory processing on attentional bias for internal (i.e., heart rate feedback) and external (i.e., emotional faces) threat information. A sample of 59 participants high (HSA) and low (LSA) in social anxiety symptoms engaged in a modified dot-probe task prior to (Time 1) and after (Time 2) an anticipatory processing or distraction task. HSAs who anticipated experienced an increase in attentional bias for internal information from Time 1 to Time 2, whereas HSAs in the distraction condition and LSAs in either condition experienced no changes. No changes in biases were found for HSAs for external biases, but LSAs who engaged in the distraction task became less avoidant of emotional faces from Time 1 to Time 2. This suggests that anticipatory processing results in an activation of attentional biases for physiological information as suggested by Clark and Wells. Copyright © 2014. Published by Elsevier Ltd.

Importance of Preserving Cross-correlation in developing Statistically Downscaled Climate Forcings and in estimating Land-surface Fluxes and States

NASA Astrophysics Data System (ADS)

Das Bhowmik, R.; Arumugam, S.

2015-12-01

Multivariate downscaling techniques exhibited superiority over univariate regression schemes in terms of preserving cross-correlations between multiple variables- precipitation and temperature - from GCMs. This study focuses on two aspects: (a) develop an analytical solutions on estimating biases in cross-correlations from univariate downscaling approaches and (b) quantify the uncertainty in land-surface states and fluxes due to biases in cross-correlations in downscaled climate forcings. Both these aspects are evaluated using climate forcings available from both historical climate simulations and CMIP5 hindcasts over the entire US. The analytical solution basically relates the univariate regression parameters, co-efficient of determination of regression and the co-variance ratio between GCM and downscaled values. The analytical solutions are compared with the downscaled univariate forcings by choosing the desired p-value (Type-1 error) in preserving the observed cross-correlation. . For quantifying the impacts of biases on cross-correlation on estimating streamflow and groundwater, we corrupt the downscaled climate forcings with different cross-correlation structure.

Motion Direction Biases and Decoding in Human Visual Cortex

PubMed Central

Wang, Helena X.; Merriam, Elisha P.; Freeman, Jeremy

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity. PMID:25209297

Associations between workplace factors and carpal tunnel syndrome: A multi-site cross sectional study.

PubMed

Fan, Z Joyce; Harris-Adamson, Carisa; Gerr, Fred; Eisen, Ellen A; Hegmann, Kurt T; Bao, Stephen; Silverstein, Barbara; Evanoff, Bradley; Dale, Ann Marie; Thiese, Matthew S; Garg, Arun; Kapellusch, Jay; Burt, Susan; Merlino, Linda; Rempel, David

2015-05-01

Few large epidemiologic studies have used rigorous case criteria, individual-level exposure measurements, and appropriate control for confounders to examine associations between workplace psychosocial and biomechanical factors and carpal tunnel syndrome (CTS). Pooling data from five independent research studies, we assessed associations between prevalent CTS and personal, work psychosocial, and biomechanical factors while adjusting for confounders using multivariable logistic regression. Prevalent CTS was associated with personal factors of older age, obesity, female sex, medical conditions, previous distal upper extremity disorders, workplace measures of peak forceful hand activity, a composite measure of force and repetition (ACGIH Threshold Limit Value for Hand Activity Level), and hand vibration. In this cross-sectional analysis of production and service workers, CTS prevalence was associated with workplace and biomechanical factors. The findings were similar to those from a prospective analysis of the same cohort with differences that may be due to recall bias and other factors. © 2015 Wiley Periodicals, Inc.

Design of adaptive control systems by means of self-adjusting transversal filters

NASA Technical Reports Server (NTRS)

Merhav, S. J.

1986-01-01

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

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

USGS Publications Warehouse

Langtimm, Catherine A.

2008-01-01

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

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Linear Regression Quantile Mapping (RQM) - A new approach to bias correction with consistent quantile trends

NASA Astrophysics Data System (ADS)

Passow, Christian; Donner, Reik

2017-04-01

Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016

Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

NASA Astrophysics Data System (ADS)

Manzanas, R.; Gutiérrez, J. M.

2018-05-01

This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981-2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile-quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.

Framing obesity a disease: Indirect effects of affect and controllability beliefs on weight bias.

PubMed

Nutter, Sarah; Alberga, Angela S; MacInnis, Cara; Ellard, John H; Russell-Mayhew, Shelly

2018-05-24

Obesity has been declared a disease by the American and Canadian Medical Associations. Although these declarations sparked much debate as to the impact of framing obesity as a disease on weight bias, strong empirical research is needed to examine this impact. The current study examined the impact of framing obesity a disease on weight bias, focusing on moderating and mediating processes. A sample of 309 participants living in the United States or Canada was recruited from Crowdflower. Participants completed measures of demographics, ideology, general attitudes, and previous contact quality and quantity with people living with obesity. Participants then read one of three articles as part of an experimental manipulation framing obesity as a disease, obesity not as a disease, and a control article unrelated to obesity. Post-manipulation included measures of affect, disgust, empathy, blame, and weight bias. Orthogonal contrasts were used to compare the obesity-disease condition to the obesity-not-disease condition and control condition. The manipulation had a direct effect on affect (emotions), such that affect toward individuals with obesity was more positive in the obesity-disease condition than the obesity-not-disease and control condition combined. Exploration of moderating effects revealed that both the belief in a just world and weight satisfaction moderated the relationship between the obesity-disease manipulation and blame for obesity. Two models of indirect effects on weight bias were also examined, which demonstrated that the obesity-disease manipulation predicted less weight bias through more positive affect (model 1) as well as less weight bias through decreased blame among individuals high in belief in a just world (model 2). This study further highlights the complex effects of declaring obesity a disease, uncovering a new direction for future research into the role of affect as well as indirect effects of characterising obesity a disease on weight bias.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

PubMed

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

2018-07-01

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

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

Audibility and visual biasing in speech perception

NASA Astrophysics Data System (ADS)

Clement, Bart Richard

Although speech perception has been considered a predominantly auditory phenomenon, large benefits from vision in degraded acoustic conditions suggest integration of audition and vision. More direct evidence of this comes from studies of audiovisual disparity that demonstrate vision can bias and even dominate perception (McGurk & MacDonald, 1976). It has been observed that hearing-impaired listeners demonstrate more visual biasing than normally hearing listeners (Walden et al., 1990). It is argued here that stimulus audibility must be equated across groups before true differences can be established. In the present investigation, effects of visual biasing on perception were examined as audibility was degraded for 12 young normally hearing listeners. Biasing was determined by quantifying the degree to which listener identification functions for a single synthetic auditory /ba-da-ga/ continuum changed across two conditions: (1)an auditory-only listening condition; and (2)an auditory-visual condition in which every item of the continuum was synchronized with visual articulations of the consonant-vowel (CV) tokens /ba/ and /ga/, as spoken by each of two talkers. Audibility was altered by presenting the conditions in quiet and in noise at each of three signal-to- noise (S/N) ratios. For the visual-/ba/ context, large effects of audibility were found. As audibility decreased, visual biasing increased. A large talker effect also was found, with one talker eliciting more biasing than the other. An independent lipreading measure demonstrated that this talker was more visually intelligible than the other. For the visual-/ga/ context, audibility and talker effects were less robust, possibly obscured by strong listener effects, which were characterized by marked differences in perceptual processing patterns among participants. Some demonstrated substantial biasing whereas others demonstrated little, indicating a strong reliance on audition even in severely degraded acoustic conditions. Listener effects were not correlated with lipreading performance. The large effect of audibility suggests that conclusions regarding an increased reliance on vision among hearing- impaired listeners were premature, and that accurate comparisons only can be made after equating audibility. Further, if after such control, individual hearing- impaired listeners demonstrate the processing differences that were demonstrated in the present investigation, then these findings have the potential to impact aural rehabilitation strategies.

Analysis of threats to research validity introduced by audio recording clinic visits: Selection bias, Hawthorne effect, both, or neither?

PubMed Central

Henry, Stephen G.; Jerant, Anthony; Iosif, Ana-Maria; Feldman, Mitchell D.; Cipri, Camille; Kravitz, Richard L.

2015-01-01

Objective To identify factors associated with participant consent to record visits; to estimate effects of recording on patient-clinician interactions Methods Secondary analysis of data from a randomized trial studying communication about depression; participants were asked for optional consent to audio record study visits. Multiple logistic regression was used to model likelihood of patient and clinician consent. Multivariable regression and propensity score analyses were used to estimate effects of audio recording on 6 dependent variables: discussion of depressive symptoms, preventive health, and depression diagnosis; depression treatment recommendations; visit length; visit difficulty. Results Of 867 visits involving 135 primary care clinicians, 39% were recorded. For clinicians, only working in academic settings (P=0.003) and having worked longer at their current practice (P=0.02) were associated with increased likelihood of consent. For patients, white race (P=0.002) and diabetes (P=0.03) were associated with increased likelihood of consent. Neither multivariable regression nor propensity score analyses revealed any significant effects of recording on the variables examined. Conclusion Few clinician or patient characteristics were significantly associated with consent. Audio recording had no significant effect on any dependent variables. Practice Implications Benefits of recording clinic visits likely outweigh the risks of bias in this setting. PMID:25837372

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

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

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

How to explain receptivity to conjunction-fallacy inhibition training: evidence from the Iowa gambling task.

PubMed

Cassotti, Mathieu; Moutier, Sylvain

2010-04-01

Intuitive predictions and judgments under conditions of uncertainty are often mediated by judgment heuristics that sometimes lead to biases. Using the classical conjunction bias example, the present study examines the relationship between receptivity to metacognitive executive training and emotion-based learning ability indexed by Iowa Gambling Task (IGT) performance. After completing a computerised version of the IGT, participants were trained to avoid conjunction bias on a frequency judgment task derived from the works of Tversky and Kahneman. Pre- and post-test performances were assessed via another probability judgment task. Results clearly showed that participants who produced a biased answer despite the experimental training (individual patterns of the biased --> biased type) mainly had less emotion-based learning ability in IGT. Better emotion-based learning ability was observed in participants whose response pattern was biased --> logical. These findings argue in favour of the capacity of the human mind/brain to overcome reasoning bias when trained under executive programming conditions and as a function of emotional warning sensitivity. Copyright 2009 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-01-01

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

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.

A laboratory study of the electromagnetic bias of rough surface scattering by water waves

NASA Technical Reports Server (NTRS)

Parsons, Chester L.; Miller, Lee S.

1990-01-01

The design, development, and use of a focused-beam radar to measure the electromagnetic bias introduced by the scattering of radar waves by a roughened water surface are discussed. The bias measurements were made over wide ranges of environmental conditions in a wavetank laboratory. Wave-elevation data were provided by standard laboratory capacitance probes. Backscattered radar power measurements coincident in time and space with the elevation data were produced by the radar. The two data sets are histogrammed to produce probability density functions for elevation and radar reflectivity, from which the electromagnetic bias is computed. The experimental results demonstrate that the electromagnetic bias is quite variable over the wide range of environmental conditions that can be produced in the laboratory. The data suggest that the bias is dependent upon the local wind field and on the amplitude and frequency of any background wave field that is present.

A simplified parsimonious higher order multivariate Markov chain model with new convergence condition

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a simplified parsimonious higher-order multivariate Markov chain model with new convergence condition. (TPHOMMCM-NCC). Moreover, estimation method of the parameters in TPHOMMCM-NCC is give. Numerical experiments illustrate the effectiveness of TPHOMMCM-NCC.

An evaluation of bias in propensity score-adjusted non-linear regression models.

PubMed

Wan, Fei; Mitra, Nandita

2018-03-01

Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

Social biases modulate the loss of redundant forms in the cultural evolution of language.

PubMed

Roberts, Gareth; Fedzechkina, Maryia

2018-02-01

According to the competitive exclusion principle (Gause, 1934), competition for the same niche must eventually lead one competitor to extinction or the occupation of a new niche. This principle applies in both biology and the cultural evolution of language, where different words and structures compete for the same function or meaning (Aronoff, 2016). Across languages, for example, word order trades off with case marking as a means of indicating who did what to whom in a sentence. Previous experimental work has shed light on how such trade-offs come about as languages adapt to human biases through learning and production, with biases becoming amplified through iterated learning over generations. At the same time, a large body of work has documented the impact of social biases on language change. However, little work has investigated how social biases interact with learning and production biases. In particular, the social dimension of language may provide alternative niches for otherwise redundant forms, preventing or slowing their extinction. We tested this hypothesis in an iterated-learning experiment in which participants were exposed to a language with two dialects, both of which had fixed word order, but differed in whether they employed case markers. In one condition, we biased participants socially towards speakers of the dialect that employed case; in other conditions we provided no bias, or biased participants for or against the dialect without case. As expected under our hypothesis, the use of case markers declined over time in all conditions, but the social bias in favor of case-dialect speakers slowed the decline. Copyright © 2017 Elsevier B.V. All rights reserved.

Industry Bias in Randomized Controlled Trials in General and Abdominal Surgery: An Empirical Study.

PubMed

Probst, Pascal; Knebel, Phillip; Grummich, Kathrin; Tenckhoff, Solveig; Ulrich, Alexis; Büchler, Markus W; Diener, Markus K

2016-07-01

Industry sponsorship has been identified as a source of bias in several fields of medical science. To date, the influence of industry sponsorship in the field of general and abdominal surgery has not been evaluated. A systematic literature search (1985-2014) was performed in the Cochrane Library, MEDLINE, and EMBASE to identify randomized controlled trials in general and abdominal surgery. Information on funding source, outcome, and methodological quality was extracted. Association of industry sponsorship and positive outcome was expressed as odds ratio (OR) with 95% confidence interval (CI). A χ test and a multivariate logistic regression analysis with study characteristics and known sources of bias were performed. A total of 7934 articles were screened and 165 randomized controlled trials were included. No difference in methodological quality was found. Industry-funded trials more often presented statistically significant results for the primary endpoint (OR, 2.44; CI, 1.04-5.71; P = 0.04). Eighty-eight of 115 (76.5%) industry-funded trials and 19 of 50 (38.0%) non-industry-funded trials reported a positive outcome (OR, 5.32; CI, 2.60-10.88; P < 0.001). Industry-funded trials more often reported a positive outcome without statistical justification (OR, 5.79; CI, 2.13-15.68; P < 0.001). In a multivariate analysis, funding source remained significantly associated with reporting of positive outcome (P < 0.001). Industry funding of surgical trials leads to exaggerated positive reporting of outcomes. This study emphasizes the necessity for declaration of funding source. Industry involvement in surgical research has to ensure scientific integrity and independence and has to be based on full transparency.

Causation in risk assessment and management: models, inference, biases, and a microbial risk-benefit case study.

PubMed

Cox, L A; Ricci, P F

2005-04-01

Causal inference of exposure-response relations from data is a challenging aspect of risk assessment with important implications for public and private risk management. Such inference, which is fundamentally empirical and based on exposure (or dose)-response models, seldom arises from a single set of data; rather, it requires integrating heterogeneous information from diverse sources and disciplines including epidemiology, toxicology, and cell and molecular biology. The causal aspects we discuss focus on these three aspects: drawing sound inferences about causal relations from one or more observational studies; addressing and resolving biases that can affect a single multivariate empirical exposure-response study; and applying the results from these considerations to the microbiological risk management of human health risks and benefits of a ban on antibiotic use in animals, in the context of banning enrofloxacin or macrolides, antibiotics used against bacterial illnesses in poultry, and the effects of such bans on changing the risk of human food-borne campylobacteriosis infections. The purposes of this paper are to describe novel causal methods for assessing empirical causation and inference; exemplify how to deal with biases that routinely arise in multivariate exposure- or dose-response modeling; and provide a simplified discussion of a case study of causal inference using microbial risk analysis as an example. The case study supports the conclusion that the human health benefits from a ban are unlikely to be greater than the excess human health risks that it could create, even when accounting for uncertainty. We conclude that quantitative causal analysis of risks is a preferable to qualitative assessments because it does not involve unjustified loss of information and is sound under the inferential use of risk results by management.

Maximizing potential impact of experimental research into cognitive processes in health psychology: A systematic approach to material development.

PubMed

Hughes, Alicia M; Gordon, Rola; Chalder, Trudie; Hirsch, Colette R; Moss-Morris, Rona

2016-11-01

There is an abundance of research into cognitive processing biases in clinical psychology including the potential for applying cognitive bias modification techniques to assess the causal role of biases in maintaining anxiety and depression. Within the health psychology field, there is burgeoning interest in applying these experimental methods to assess potential cognitive biases in relation to physical health conditions and health-related behaviours. Experimental research in these areas could inform theoretical development by enabling measurement of implicit cognitive processes that may underlie unhelpful illness beliefs and help drive health-related behaviours. However, to date, there has been no systematic approach to adapting existing experimental paradigms for use within physical health research. Many studies fail to report how materials were developed for the population of interest or have used untested materials developed ad hoc. The lack of protocol for developing stimuli specificity has contributed to large heterogeneity in methodologies and findings. In this article, we emphasize the need for standardized methods for stimuli development and replication in experimental work, particularly as it extends beyond its original anxiety and depression scope to other physical conditions. We briefly describe the paradigms commonly used to assess cognitive biases in attention and interpretation and then describe the steps involved in comprehensive/robust stimuli development for attention and interpretation paradigms using illustrative examples from two conditions: chronic fatigue syndrome and breast cancer. This article highlights the value of preforming rigorous stimuli development and provides tools to aid researchers engage in this process. We believe this work is worthwhile to establish a body of high-quality and replicable experimental research within the health psychology literature. Statement of contribution What is already known on this subject? Cognitive biases (e.g., tendencies to attend to negative information and/or interpret ambiguous information in negative ways) have a causal role in maintaining anxiety and depression. There is mixed evidence of cognitive biases in physical health conditions and chronic illness; one reason for this may be the heterogeneous stimuli used to assess attention and interpretation biases in these conditions. What does this study add? Steps for comprehensive/robust stimuli development for attention and interpretation paradigms are presented. Illustrative examples are provided from two conditions: chronic fatigue syndrome and breast cancer. We provide tools to help researchers develop condition-specific materials for experimental studies. © 2016 The British Psychological Society.

The adaptive significance of sensory bias in a foraging context: floral colour preferences in the bumblebee Bombus terrestris.

PubMed

Raine, Nigel E; Chittka, Lars

2007-06-20

Innate sensory biases could play an important role in helping naïve animals to find food. As inexperienced bees are known to have strong innate colour biases we investigated whether bumblebee (Bombus terrestris) colonies with stronger biases for the most rewarding flower colour (violet) foraged more successfully in their local flora. To test the adaptive significance of variation in innate colour bias, we compared the performance of colour-naïve bees, from nine bumblebee colonies raised from local wild-caught queens, in a laboratory colour bias paradigm using violet (bee UV-blue) and blue (bee blue) artificial flowers. The foraging performance of the same colonies was assessed under field conditions. Colonies with a stronger innate bias for violet over blue flowers in the laboratory harvested more nectar per unit time under field conditions. In fact, the colony with the strongest bias for violet (over blue) brought in 41% more nectar than the colony with the least strong bias. As violet flowers in the local area produce more nectar than blue flowers (the next most rewarding flower colour), these data are consistent with the hypothesis that local variation in flower traits could drive selection for innate colour biases.

The Adaptive Significance of Sensory Bias in a Foraging Context: Floral Colour Preferences in the Bumblebee Bombus terrestris

PubMed Central

Raine, Nigel E.; Chittka, Lars

2007-01-01

Innate sensory biases could play an important role in helping naïve animals to find food. As inexperienced bees are known to have strong innate colour biases we investigated whether bumblebee (Bombus terrestris) colonies with stronger biases for the most rewarding flower colour (violet) foraged more successfully in their local flora. To test the adaptive significance of variation in innate colour bias, we compared the performance of colour-naïve bees, from nine bumblebee colonies raised from local wild-caught queens, in a laboratory colour bias paradigm using violet (bee UV-blue) and blue (bee blue) artificial flowers. The foraging performance of the same colonies was assessed under field conditions. Colonies with a stronger innate bias for violet over blue flowers in the laboratory harvested more nectar per unit time under field conditions. In fact, the colony with the strongest bias for violet (over blue) brought in 41% more nectar than the colony with the least strong bias. As violet flowers in the local area produce more nectar than blue flowers (the next most rewarding flower colour), these data are consistent with the hypothesis that local variation in flower traits could drive selection for innate colour biases. PMID:17579727

Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

PubMed

Cichy, Radoslaw Martin; Pantazis, Dimitrios

2017-09-01

Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

Alcohol cognitive bias modification training for problem drinkers over the web.

PubMed

Wiers, Reinout W; Houben, Katrijn; Fadardi, Javad S; van Beek, Paul; Rhemtulla, Mijke; Cox, W Miles

2015-01-01

Following successful outcomes of cognitive bias modification (CBM) programs for alcoholism in clinical and community samples, the present study investigated whether different varieties of CBM (attention control training and approach-bias re-training) could be delivered successfully in a fully automated web-based way and whether these interventions would help self-selected problem drinkers to reduce their drinking. Participants were recruited through online advertising, which resulted in 697 interested participants, of whom 615 were screened in. Of the 314 who initiated training, 136 completed a pretest, four sessions of computerized training and a posttest. Participants were randomly assigned to one of four experimental conditions (attention control or one of three varieties of approach-bias re-training) or a sham-training control condition. The general pattern of findings was that participants in all conditions (including participants in the control-training condition) reduced their drinking. It is suggested that integrating CBM with online cognitive and motivational interventions could improve results. Copyright © 2014 Elsevier Ltd. All rights reserved.

DigOut: viewing differential expression genes as outliers.

PubMed

Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

2010-12-01

With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

Visuospatial asymmetries and emotional valence influence mental time travel.

PubMed

Thomas, Nicole A; Takarangi, Melanie K T

2018-06-01

Spatial information is tightly intertwined with temporal and valence-based information. Namely, "past" is represented on the left, and "future" on the right, along a horizontal mental timeline. Similarly, right is associated with positive, whereas left is negative. We developed a novel task to examine the effects of emotional valence and temporal distance on mental representations of time. We compared positivity biases, where positive events are positioned closer to now, and right hemisphere emotion biases, where negative events are positioned to the left. When the entire life span was used, a positivity bias emerged; positive events were closer to now. When timeline length was reduced, positivity and right hemisphere emotion biases were consistent for past events. In contrast, positive and negative events were equidistant from now in the future condition, suggesting positivity and right hemisphere emotion biases opposed one another, leading events to be positioned at a similar distance. We then reversed the timeline by moving past to the right and future to the left. Positivity biases in the past condition were eliminated, and negative events were placed slightly closer to now in the future condition. We conclude that an underlying left-to-right mental representation of time is necessary for positivity biases to emerge for past events; however, our mental representations of future events are inconsistent with positivity biases. These findings point to an important difference in the way in which we represent the past and the future on our mental timeline. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

A Question of Control? Examining the Role of Control Conditions in Experimental Psychopathology using the Example of Cognitive Bias Modification Research.

PubMed

Blackwell, Simon E; Woud, Marcella L; MacLeod, Colin

2017-10-26

While control conditions are vitally important in research, selecting the optimal control condition can be challenging. Problems are likely to arise when the choice of control condition is not tightly guided by the specific question that a given study aims to address. Such problems have become increasingly apparent in experimental psychopathology research investigating the experimental modification of cognitive biases, particularly as the focus of this research has shifted from theoretical questions concerning mechanistic aspects of the association between cognitive bias and emotional vulnerability, to questions that instead concern the clinical efficacy of 'cognitive bias modification' (CBM) procedures. We discuss the kinds of control conditions that have typically been employed in CBM research, illustrating how difficulties can arise when changes in the types of research questions asked are not accompanied by changes in the control conditions employed. Crucially, claims made on the basis of comparing active and control conditions within CBM studies should be restricted to those conclusions allowed by the specific control condition employed. CBM studies aiming to establish clinical utility are likely to require quite different control conditions from CBM studies aiming to illuminate mechanisms. Further, conclusions concerning the clinical utility of CBM interventions cannot necessarily be drawn from studies in which the control condition has been chosen to answer questions concerning mechanisms. Appreciating the need to appropriately alter control conditions in the transition from basic mechanisms-focussed investigations to applied clinical research could greatly facilitate the translational process.

Dissociable Effects of Aging and Mild Cognitive Impairment on Bottom-Up Audiovisual Integration.

PubMed

Festa, Elena K; Katz, Andrew P; Ott, Brian R; Tremont, Geoffrey; Heindel, William C

2017-01-01

Effective audiovisual sensory integration involves dynamic changes in functional connectivity between superior temporal sulcus and primary sensory areas. This study examined whether disrupted connectivity in early Alzheimer's disease (AD) produces impaired audiovisual integration under conditions requiring greater corticocortical interactions. Audiovisual speech integration was examined in healthy young adult controls (YC), healthy elderly controls (EC), and patients with amnestic mild cognitive impairment (MCI) using McGurk-type stimuli (providing either congruent or incongruent audiovisual speech information) under conditions differing in the strength of bottom-up support and the degree of top-down lexical asymmetry. All groups accurately identified auditory speech under congruent audiovisual conditions, and displayed high levels of visual bias under strong bottom-up incongruent conditions. Under weak bottom-up incongruent conditions, however, EC and amnestic MCI groups displayed opposite patterns of performance, with enhanced visual bias in the EC group and reduced visual bias in the MCI group relative to the YC group. Moreover, there was no overlap between the EC and MCI groups in individual visual bias scores reflecting the change in audiovisual integration from the strong to the weak stimulus conditions. Top-down lexicality influences on visual biasing were observed only in the MCI patients under weaker bottom-up conditions. Results support a deficit in bottom-up audiovisual integration in early AD attributable to disruptions in corticocortical connectivity. Given that this deficit is not simply an exacerbation of changes associated with healthy aging, tests of audiovisual speech integration may serve as sensitive and specific markers of the earliest cognitive change associated with AD.

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Conditional estimation using prior information in 2-stage group sequential designs assuming asymptotic normality when the trial terminated early.

PubMed

Shimura, Masashi; Maruo, Kazushi; Gosho, Masahiko

2018-04-23

Two-stage designs are widely used to determine whether a clinical trial should be terminated early. In such trials, a maximum likelihood estimate is often adopted to describe the difference in efficacy between the experimental and reference treatments; however, this method is known to display conditional bias. To reduce such bias, a conditional mean-adjusted estimator (CMAE) has been proposed, although the remaining bias may be nonnegligible when a trial is stopped for efficacy at the interim analysis. We propose a new estimator for adjusting the conditional bias of the treatment effect by extending the idea of the CMAE. This estimator is calculated by weighting the maximum likelihood estimate obtained at the interim analysis and the effect size prespecified when calculating the sample size. We evaluate the performance of the proposed estimator through analytical and simulation studies in various settings in which a trial is stopped for efficacy or futility at the interim analysis. We find that the conditional bias of the proposed estimator is smaller than that of the CMAE when the information time at the interim analysis is small. In addition, the mean-squared error of the proposed estimator is also smaller than that of the CMAE. In conclusion, we recommend the use of the proposed estimator for trials that are terminated early for efficacy or futility. Copyright © 2018 John Wiley & Sons, Ltd.

Modifying interpretation biases in body dysmorphic disorder: Evaluation of a brief computerized treatment.

PubMed

Summers, Berta J; Cougle, Jesse R

2016-12-01

Individuals meeting diagnostic criteria for body dysmorphic disorder (BDD; N = 40) were enrolled in a randomized, four-session trial comparing interpretation bias modification (IBM) training designed to target social evaluation- and appearance-related interpretation biases with a placebo control training condition (PC). Sessions took place over the course of two weeks (two sessions per week). Analyses indicated that, relative to the PC condition, IBM led to a significant increase in benign biases and reduction in threat biases at post-treatment. IBM also led to greater reductions in BDD symptoms compared to PC, though this effect was present at high but not low levels of pre-treatment BDD symptoms. Additionally, compared to PC, IBM led to lower urge to check and lower fear in response to an in vivo appearance-related stressor (having their picture taken from different angles), though the latter effect was present only among those reporting elevated fear at pre-treatment. The effects of treatment on interpretation biases and BDD symptoms were largely maintained at a one-month follow-up assessment. Moderated-mediation analyses showed that change in threat bias mediated the effect of condition on post-treatment symptoms for individuals high in pre-treatment BDD symptoms. The current study provides preliminary support for the efficacy of IBM for BDD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Selection bias in population-based cancer case-control studies due to incomplete sampling frame coverage.

PubMed

Walsh, Matthew C; Trentham-Dietz, Amy; Gangnon, Ronald E; Nieto, F Javier; Newcomb, Polly A; Palta, Mari

2012-06-01

Increasing numbers of individuals are choosing to opt out of population-based sampling frames due to privacy concerns. This is especially a problem in the selection of controls for case-control studies, as the cases often arise from relatively complete population-based registries, whereas control selection requires a sampling frame. If opt out is also related to risk factors, bias can arise. We linked breast cancer cases who reported having a valid driver's license from the 2004-2008 Wisconsin women's health study (N = 2,988) with a master list of licensed drivers from the Wisconsin Department of Transportation (WDOT). This master list excludes Wisconsin drivers that requested their information not be sold by the state. Multivariate-adjusted selection probability ratios (SPR) were calculated to estimate potential bias when using this driver's license sampling frame to select controls. A total of 962 cases (32%) had opted out of the WDOT sampling frame. Cases age <40 (SPR = 0.90), income either unreported (SPR = 0.89) or greater than $50,000 (SPR = 0.94), lower parity (SPR = 0.96 per one-child decrease), and hormone use (SPR = 0.93) were significantly less likely to be covered by the WDOT sampling frame (α = 0.05 level). Our results indicate the potential for selection bias due to differential opt out between various demographic and behavioral subgroups of controls. As selection bias may differ by exposure and study base, the assessment of potential bias needs to be ongoing. SPRs can be used to predict the direction of bias when cases and controls stem from different sampling frames in population-based case-control studies.

Accounting for Selection Bias in Studies of Acute Cardiac Events.

PubMed

Banack, Hailey R; Harper, Sam; Kaufman, Jay S

2018-06-01

In cardiovascular research, pre-hospital mortality represents an important potential source of selection bias. Inverse probability of censoring weights are a method to account for this source of bias. The objective of this article is to examine and correct for the influence of selection bias due to pre-hospital mortality on the relationship between cardiovascular risk factors and all-cause mortality after an acute cardiac event. The relationship between the number of cardiovascular disease (CVD) risk factors (0-5; smoking status, diabetes, hypertension, dyslipidemia, and obesity) and all-cause mortality was examined using data from the Atherosclerosis Risk in Communities (ARIC) study. To illustrate the magnitude of selection bias, estimates from an unweighted generalized linear model with a log link and binomial distribution were compared with estimates from an inverse probability of censoring weighted model. In unweighted multivariable analyses the estimated risk ratio for mortality ranged from 1.09 (95% confidence interval [CI], 0.98-1.21) for 1 CVD risk factor to 1.95 (95% CI, 1.41-2.68) for 5 CVD risk factors. In the inverse probability of censoring weights weighted analyses, the risk ratios ranged from 1.14 (95% CI, 0.94-1.39) to 4.23 (95% CI, 2.69-6.66). Estimates from the inverse probability of censoring weighted model were substantially greater than unweighted, adjusted estimates across all risk factor categories. This shows the magnitude of selection bias due to pre-hospital mortality and effect on estimates of the effect of CVD risk factors on mortality. Moreover, the results highlight the utility of using this method to address a common form of bias in cardiovascular research. Copyright © 2018 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

Epilepsy as a systemic condition: Link with somatic comorbidities.

PubMed

Novy, J; Bell, G S; Peacock, J L; Sisodiya, S M; Sander, J W

2017-10-01

People with epilepsy have more concomitant medical conditions than the general population; these comorbidities play an important role in premature mortality. We sought to generate explanatory hypotheses about the co-occurrence of somatic comorbidities and epilepsy, avoiding causal and treatment-resultant biases. We collected clinical, demographic and somatic comorbidity data for 2016 consecutive adults with epilepsy undergoing assessment at a tertiary centre and in 1278 people with epilepsy in the community. Underlying causes of epilepsy were not classed as comorbidities. Somatic comorbidities were more frequent in the referral centre (49%) where people more frequently had active epilepsy than in the community (36%). Consistent risk factors for comorbidities were found in both cohorts. Using multivariable ordinal regression adjusted for age, longer epilepsy duration and an underlying brain lesion were independently associated with a smaller burden of somatic conditions. The treatment burden, measured by the number of drugs to which people were exposed, was not an independent predictor. Shorter epilepsy duration was a predictor for conditions that conceivably harbour significant mortality risks. Somatic comorbidities do not occur randomly in relation to epilepsy; having more severe epilepsy seems to be a risk factor. Independently from age, the early period after epilepsy onset appears to be at particular risk, although it is not clear whether this relates to an early mortality or to a later decrease in the burden of comorbidities. These results suggest that, for some people, epilepsy should be considered a systemic condition not limited to the CNS. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Genetic Essentialism: On the Deceptive Determinism of DNA

ERIC Educational Resources Information Center

Dar-Nimrod, Ilan; Heine, Steven J.

2011-01-01

This article introduces the notion of genetic essentialist biases: cognitive biases associated with essentialist thinking that are elicited when people encounter arguments that genes are relevant for a behavior, condition, or social group. Learning about genetic attributions for various human conditions leads to a particular set of thoughts…

Lies, Damned Lies, and Survey Self-Reports? Identity as a Cause of Measurement Bias.

PubMed

Brenner, Philip S; DeLamater, John

2016-12-01

Explanations of error in survey self-reports have focused on social desirability: that respondents answer questions about normative behavior to appear prosocial to interviewers. However, this paradigm fails to explain why bias occurs even in self-administered modes like mail and web surveys. We offer an alternative explanation rooted in identity theory that focuses on measurement directiveness as a cause of bias. After completing questions about physical exercise on a web survey, respondents completed a text message-based reporting procedure, sending updates on their major activities for five days. Random assignment was then made to one of two conditions: instructions mentioned the focus of the study, physical exercise, or not. Survey responses, text updates, and records from recreation facilities were compared. Direct measures generated bias-overreporting in survey measures and reactivity in the directive text condition-but the nondirective text condition generated unbiased measures. Findings are discussed in terms of identity.

Disambiguation of Necker cube rotation by monocular and binocular depth cues: Relative effectiveness for establishing long-term bias

PubMed Central

Backus, Benjamin T.; Jain, Anshul

2011-01-01

The apparent direction of rotation of perceptually bistable wire-frame (Necker) cubes can be conditioned to depend on retinal location by interleaving their presentation with cubes that are disambiguated by depth cues (Haijiang, Saunders, Stone & Backus, 2006; Harrison & Backus, 2010a). The long-term nature of the learned bias is demonstrated by resistance to counter-conditioning on a consecutive day. In previous work, either binocular disparity and occlusion, or a combination of monocular depth cues that included occlusion, internal occlusion, haze, and depth-from-shading, were used to control the rotation direction of disambiguated cubes. Here, we test the relative effectiveness of these two sets of depth cues in establishing the retinal location bias. Both cue sets were highly effective in establishing a perceptual bias on Day 1 as measured by the perceived rotation direction of ambiguous cubes. The effect of counter-conditioning on Day 2, on perceptual outcome for ambiguous cubes, was independent of whether the cue set was the same or different as Day 1. This invariance suggests that a common neural population instantiates the bias for rotation direction, regardless of the cue-set used. However, in a further experiment where only disambiguated cubes were presented on Day 1, perceptual outcome of ambiguous cubes during Day 2 counter-conditioning showed that the monocular-only cue set was in fact more effective than disparity-plus-occlusion for causing long-term learning of the bias. These results can be reconciled if the conditioning effect of Day 1 ambiguous trials in the first experiment is taken into account (Harrison & Backus, 2010b). We suggest that monocular disambiguation leads to stronger bias either because it more strongly activates a single neural population that is necessary for perceiving rotation, or because ambiguous stimuli engage cortical areas that are also engaged by monocularly disambiguated stimuli but not by disparity-disambiguated stimuli. PMID:21335023

Disambiguation of Necker cube rotation by monocular and binocular depth cues: relative effectiveness for establishing long-term bias.

PubMed

Harrison, Sarah J; Backus, Benjamin T; Jain, Anshul

2011-05-11

The apparent direction of rotation of perceptually bistable wire-frame (Necker) cubes can be conditioned to depend on retinal location by interleaving their presentation with cubes that are disambiguated by depth cues (Haijiang, Saunders, Stone, & Backus, 2006; Harrison & Backus, 2010a). The long-term nature of the learned bias is demonstrated by resistance to counter-conditioning on a consecutive day. In previous work, either binocular disparity and occlusion, or a combination of monocular depth cues that included occlusion, internal occlusion, haze, and depth-from-shading, were used to control the rotation direction of disambiguated cubes. Here, we test the relative effectiveness of these two sets of depth cues in establishing the retinal location bias. Both cue sets were highly effective in establishing a perceptual bias on Day 1 as measured by the perceived rotation direction of ambiguous cubes. The effect of counter-conditioning on Day 2, on perceptual outcome for ambiguous cubes, was independent of whether the cue set was the same or different as Day 1. This invariance suggests that a common neural population instantiates the bias for rotation direction, regardless of the cue set used. However, in a further experiment where only disambiguated cubes were presented on Day 1, perceptual outcome of ambiguous cubes during Day 2 counter-conditioning showed that the monocular-only cue set was in fact more effective than disparity-plus-occlusion for causing long-term learning of the bias. These results can be reconciled if the conditioning effect of Day 1 ambiguous trials in the first experiment is taken into account (Harrison & Backus, 2010b). We suggest that monocular disambiguation leads to stronger bias either because it more strongly activates a single neural population that is necessary for perceiving rotation, or because ambiguous stimuli engage cortical areas that are also engaged by monocularly disambiguated stimuli but not by disparity-disambiguated stimuli. Copyright © 2011 Elsevier Ltd. All rights reserved.

Radial Bias Is Not Necessary For Orientation Decoding

PubMed Central

Pratte, Michael S.; Sy, Jocelyn L.; Swisher, Jascha D.; Tong, Frank

2015-01-01

Multivariate pattern analysis can be used to decode the orientation of a viewed grating from fMRI signals in early visual areas. Although some studies have reported identifying multiple sources of the orientation information that make decoding possible, a recent study argued that orientation decoding is only possible because of a single source: a coarse-scale retinotopically organized preference for radial orientations. Here we aim to resolve these discrepant findings. We show that there were subtle, but critical, experimental design choices that led to the erroneous conclusion that a radial bias is the only source of orientation information in fMRI signals. In particular, we show that the reliance on a fast temporal-encoding paradigm for spatial mapping can be problematic, as effects of space and time become conflated and lead to distorted estimates of a voxel’s orientation or retinotopic preference. When we implement minor changes to the temporal paradigm or to the visual stimulus itself, by slowing the periodic rotation of the stimulus or by smoothing its contrast-energy profile, we find significant evidence of orientation information that does not originate from radial bias. In an additional block-paradigm experiment where space and time were not conflated, we apply a formal model comparison approach and find that many voxels exhibit more complex tuning properties than predicted by radial bias alone or in combination with other known coarse-scale biases. Our findings support the conclusion that radial bias is not necessary for orientation decoding. In addition, our study highlights potential limitations of using temporal phase-encoded fMRI designs for characterizing voxel tuning properties. PMID:26666900

Mapping species distributions with MAXENT using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias.

PubMed

Fourcade, Yoan; Engler, Jan O; Rödder, Dennis; Secondi, Jean

2014-01-01

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one "virtual" derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

PubMed Central

Fourcade, Yoan; Engler, Jan O.; Rödder, Dennis; Secondi, Jean

2014-01-01

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one “virtual” derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases. PMID:24818607

Conditioned associations and economic decision biases.

PubMed

Guitart-Masip, Marc; Talmi, Deborah; Dolan, Ray

2010-10-15

Humans show substantial deviation from rationality during economic decision making under uncertainty. A computational perspective suggests these deviations arise out of an interaction between distinct valuation systems in the brain. Here, we provide behavioural data showing that the incidental presentation of aversive and appetitive conditioned stimuli can alter subjects' preferences in an economic task, involving a choice between a safe or gamble option. These behavioural effects informed a model-based analysis of a functional magnetic resonance imaging (fMRI) experiment, involving an identical paradigm, where we demonstrate that this conditioned behavioral bias engages the amygdala, a brain structure associated with acquisition and expression of conditioned associations. Our findings suggest that a well known bias in human economic choice can arise from an influence of conditioned associations on goal-directed decision making, consistent with an architecture of choice that invokes distinct decision-making systems. Copyright 2010 Elsevier Inc. All rights reserved.

Nonresponse bias in randomized controlled experiments in criminology: Putting the Queensland Community Engagement Trial (QCET) under a microscope.

PubMed

Antrobus, Emma; Elffers, Henk; White, Gentry; Mazerolle, Lorraine

2013-01-01

The goal of this article is to examine whether or not the results of the Queensland Community Engagement Trial (QCET)-a randomized controlled trial that tested the impact of procedural justice policing on citizen attitudes toward police-were affected by different types of nonresponse bias. We use two methods (Cochrane and Elffers methods) to explore nonresponse bias: First, we assess the impact of the low response rate by examining the effects of nonresponse group differences between the experimental and control conditions and pooled variance under different scenarios. Second, we assess the degree to which item response rates are influenced by the control and experimental conditions. Our analysis of the QCET data suggests that our substantive findings are not influenced by the low response rate in the trial. The results are robust even under extreme conditions, and statistical significance of the results would only be compromised in cases where the pooled variance was much larger for the nonresponse group and the difference between experimental and control conditions was greatly diminished. We also find that there were no biases in the item response rates across the experimental and control conditions. RCTs that involve field survey responses-like QCET-are potentially compromised by low response rates and how item response rates might be influenced by the control or experimental conditions. Our results show that the QCET results were not sensitive to the overall low response rate across the experimental and control conditions and the item response rates were not significantly different across the experimental and control groups. Overall, our analysis suggests that the results of QCET are robust and any biases in the survey responses do not significantly influence the main experimental findings.

Visual classification of very fine-grained sediments: Evaluation through univariate and multivariate statistics

USGS Publications Warehouse

Hohn, M. Ed; Nuhfer, E.B.; Vinopal, R.J.; Klanderman, D.S.

1980-01-01

Classifying very fine-grained rocks through fabric elements provides information about depositional environments, but is subject to the biases of visual taxonomy. To evaluate the statistical significance of an empirical classification of very fine-grained rocks, samples from Devonian shales in four cored wells in West Virginia and Virginia were measured for 15 variables: quartz, illite, pyrite and expandable clays determined by X-ray diffraction; total sulfur, organic content, inorganic carbon, matrix density, bulk density, porosity, silt, as well as density, sonic travel time, resistivity, and ??-ray response measured from well logs. The four lithologic types comprised: (1) sharply banded shale, (2) thinly laminated shale, (3) lenticularly laminated shale, and (4) nonbanded shale. Univariate and multivariate analyses of variance showed that the lithologic classification reflects significant differences for the variables measured, difference that can be detected independently of stratigraphic effects. Little-known statistical methods found useful in this work included: the multivariate analysis of variance with more than one effect, simultaneous plotting of samples and variables on canonical variates, and the use of parametric ANOVA and MANOVA on ranked data. ?? 1980 Plenum Publishing Corporation.

"L"-Bivariate and "L"-Multivariate Association Coefficients. Research Report. ETS RR-08-40

ERIC Educational Resources Information Center

Kong, Nan; Lewis, Charles

2008-01-01

Given a system of multiple random variables, a new measure called the "L"-multivariate association coefficient is defined using (conditional) entropy. Unlike traditional correlation measures, the L-multivariate association coefficient measures the multiassociations or multirelations among the multiple variables in the given system; that…

Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

The effects of reality television on weight bias: an examination of The Biggest Loser.

PubMed

Domoff, Sarah E; Hinman, Nova G; Koball, Afton M; Storfer-Isser, Amy; Carhart, Victoria L; Baik, Kyoung D; Carels, Robert A

2012-05-01

Weight-loss reality shows, a popular form of television programming, portray obese individuals and their struggles to lose weight. While the media is believed to reinforce obesity stereotypes and contribute to weight stigma, it is not yet known whether weight-loss reality shows have any effect on weight bias. The goal of this investigation was to examine how exposure to 40-min of The Biggest Loser impacted participants' levels of weight bias. Fifty-nine participants (majority of whom were white females) were randomly assigned to either an experimental (one episode of The Biggest Loser) or control (one episode of a nature reality show) condition. Levels of weight bias were measured by the Implicit Associations Test (IAT), the Obese Person Trait Survey (OPTS), and the Anti-fat Attitudes scale (AFA) at baseline and following the episode viewing (1 week later). Participants in The Biggest Loser condition had significantly higher levels of dislike of overweight individuals and more strongly believed that weight is controllable after the exposure. No significant condition effects were found for implicit bias or traits associated with obese persons. Exploratory analyses examining moderation of the condition effect by BMI and intention to lose weight indicated that participants who had lower BMIs and were not trying to lose weight had significantly higher levels of dislike of overweight individuals following exposure to The Biggest Loser compared to similar participants in the control condition. These results indicate that anti-fat attitudes increase after brief exposure to weight-loss reality television.

Re-training Automatic Action Tendencies to Approach Cigarettes among Adolescent Smokers: A Pilot Study

PubMed Central

Kong, Grace; Larsen, Helle; Cavallo, Dana; Becker, Daniela; Cousijn, Janna; Salemink, Elske; D'Escury-Koenigs, Annemat L. Collot; Morean, Meghan; Wiers, Reinout; Krishnan-Sarin, Suchitra

2015-01-01

Background This pilot study conducted a preliminary examination of whether Cognitive Bias Modification (CBM), a computerized task to retrain cognitive-approach biases towards smoking stimuli, (1) changed approach bias for cigarettes, and (2) improved smoking cessation outcomes in adolescent smokers. Methods Sixty adolescent smokers received four weeks of Cognitive Behavioral Therapy (CBT) for smoking cessation, with CBM (90% avoidance/10% approach for smoking stimuli and 10% avoidance/90% approach for neutral stimuli) or sham (50% avoidance/50% approach for smoking and neutral stimuli) training in the Netherlands (n = 42) and the United States (n = 18). Results While we did not observe changes in action tendencies related to CBM, adolescents with higher smoking approach biases at baseline had greater decreases in approach biases at follow up, compared to adolescents with smoking avoidance biases, regardless of treatment condition (p = 0.01). Intent-to-treat (ITT) analyses showed that CBM, when compared with sham trended toward higher end-of-treatment, biochemically-confirmed, seven-day point prevalence abstinence, (17.2% vs. 3.2%, p = 0.071). ITT analysis also showed that regardless of treatment condition, cotinine level (p = 0.045) and average number of cigarette smoked (p ≤ 0.001) significantly decreased over the course of treatment. Conclusions The findings from this pilot study suggests that re-training approach biases toward cigarettes shows promise for smoking cessation among adolescent smokers. Future research should utilize larger samples and increased distinction between CBM and sham conditions, and examine mechanisms underlying the CBM approach. PMID:26186485

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

PubMed

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

1997-01-01

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

Validating a Local Failure Risk Stratification for Use in Prospective Studies of Adjuvant Radiation Therapy for Bladder Cancer

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

Baumann, Brian C.; He, Jiwei; Hwang, Wei-Ting

Purpose: To inform prospective trials of adjuvant radiation therapy (adj-RT) for bladder cancer after radical cystectomy, a locoregional failure (LF) risk stratification was proposed. This stratification was developed and validated using surgical databases that may not reflect the outcomes expected in prospective trials. Our purpose was to assess sources of bias that may affect the stratification model's validity or alter the LF risk estimates for each subgroup: time bias due to evolving surgical techniques; trial accrual bias due to inclusion of patients who would be ineligible for adj-RT trials because of early disease progression, death, or loss to follow-up shortlymore » after cystectomy; bias due to different statistical methods to estimate LF; and subgrouping bias due to different definitions of the LF subgroups. Methods and Materials: The LF risk stratification was developed using a single-institution cohort (n=442, 1990-2008) and the multi-institutional SWOG 8710 cohort (n=264, 1987-1998) treated with radical cystectomy with or without chemotherapy. We evaluated the sensitivity of the stratification to sources of bias using Fine-Gray regression and Kaplan-Meier analyses. Results: Year of radical cystectomy was not associated with LF risk on univariate or multivariate analysis after controlling for risk group. By use of more stringent inclusion criteria, 26 SWOG patients (10%) and 60 patients from the single-institution cohort (14%) were excluded. Analysis of the remaining patients confirmed 3 subgroups with significantly different LF risks with 3-year rates of 7%, 17%, and 36%, respectively (P<.01), nearly identical to the rates without correcting for trial accrual bias. Kaplan-Meier techniques estimated higher subgroup LF rates than competing risk analysis. The subgroup definitions used in the NRG-GU001 adj-RT trial were validated. Conclusions: These sources of bias did not invalidate the LF risk stratification or substantially change the model's LF estimates.« less

Detecting Bias in Selection for Higher Education: Three Different Methods

ERIC Educational Resources Information Center

Kennet-Cohen, Tamar; Turvall, Elliot; Oren, Carmel

2014-01-01

This study examined selection bias in Israeli university admissions with respect to test language and gender, using three approaches for the detection of such bias: Cleary's model of differential prediction, boundary conditions for differential prediction and difference between "d's" (the Constant Ratio Model). The university admissions…

Meta-Regression Approximations to Reduce Publication Selection Bias

ERIC Educational Resources Information Center

Stanley, T. D.; Doucouliagos, Hristos

2014-01-01

Publication selection bias is a serious challenge to the integrity of all empirical sciences. We derive meta-regression approximations to reduce this bias. Our approach employs Taylor polynomial approximations to the conditional mean of a truncated distribution. A quadratic approximation without a linear term, precision-effect estimate with…

HYPNOTIC TACTILE ANESTHESIA: Psychophysical and Signal-Detection Analyses

PubMed Central

Tataryn, Douglas J.; Kihlstrom, John F.

2017-01-01

Two experiments that studied the effects of hypnotic suggestions on tactile sensitivity are reported. Experiment 1 found that suggestions for anesthesia, as measured by both traditional psychophysical methods and signal detection procedures, were linearly related to hypnotizability. Experiment 2 employed the same methodologies in an application of the real-simulator paradigm to examine the effects of suggestions for both anesthesia and hyperesthesia. Significant effects of hypnotic suggestion on both sensitivity and bias were found in the anesthesia condition but not for the hyperesthesia condition. A new bias parameter, C′, indicated that much of the bias found in the initial analyses was artifactual, a function of changes in sensitivity across conditions. There were no behavioral differences between reals and simulators in any of the conditions, though analyses of postexperimental interviews suggested the 2 groups had very different phenomenal experiences. PMID:28230465

Multivariate Generalizations of Student's t-Distribution. ONR Technical Report. [Biometric Lab Report No. 90-3.

ERIC Educational Resources Information Center

Gibbons, Robert D.; And Others

In the process of developing a conditionally-dependent item response theory (IRT) model, the problem arose of modeling an underlying multivariate normal (MVN) response process with general correlation among the items. Without the assumption of conditional independence, for which the underlying MVN cdf takes on comparatively simple forms and can be…

Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

NASA Astrophysics Data System (ADS)

Mackie, Anna; Palmer, Paul I.; Brindley, Helen

2017-12-01

We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of -12 and 18 W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m-2 for the longwave downwelling (upwelling) radiation flux and -21(-13) W m-2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation-model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model-observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

Backfitting in Smoothing Spline Anova, with Application to Historical Global Temperature Data

NASA Astrophysics Data System (ADS)

Luo, Zhen

In the attempt to estimate the temperature history of the earth using the surface observations, various biases can exist. An important source of bias is the incompleteness of sampling over both time and space. There have been a few methods proposed to deal with this problem. Although they can correct some biases resulting from incomplete sampling, they have ignored some other significant biases. In this dissertation, a smoothing spline ANOVA approach which is a multivariate function estimation method is proposed to deal simultaneously with various biases resulting from incomplete sampling. Besides that, an advantage of this method is that we can get various components of the estimated temperature history with a limited amount of information stored. This method can also be used for detecting erroneous observations in the data base. The method is illustrated through an example of modeling winter surface air temperature as a function of year and location. Extension to more complicated models are discussed. The linear system associated with the smoothing spline ANOVA estimates is too large to be solved by full matrix decomposition methods. A computational procedure combining the backfitting (Gauss-Seidel) algorithm and the iterative imputation algorithm is proposed. This procedure takes advantage of the tensor product structure in the data to make the computation feasible in an environment of limited memory. Various related issues are discussed, e.g., the computation of confidence intervals and the techniques to speed up the convergence of the backfitting algorithm such as collapsing and successive over-relaxation.

The Impact of Cognitive Stressors in the Emergency Department on Physician Implicit Racial Bias.

PubMed

Johnson, Tiffani J; Hickey, Robert W; Switzer, Galen E; Miller, Elizabeth; Winger, Daniel G; Nguyen, Margaret; Saladino, Richard A; Hausmann, Leslie R M

2016-03-01

The emergency department (ED) is characterized by stressors (e.g., fatigue, stress, time pressure, and complex decision-making) that can pose challenges to delivering high-quality, equitable care. Although it has been suggested that characteristics of the ED may exacerbate reliance on cognitive heuristics, no research has directly investigated whether stressors in the ED impact physician racial bias, a common heuristic. We seek to determine if physicians have different levels of implicit racial bias post-ED shift versus preshift and to examine associations between demographics and cognitive stressors with bias. This repeated-measures study of resident physicians in a pediatric ED used electronic pre- and postshift assessments of implicit racial bias, demographics, and cognitive stressors. Implicit bias was measured using the Race Implicit Association Test (IAT). Linear regression models compared differences in IAT scores pre- to postshift and determined associations between participant demographics and cognitive stressors with postshift IAT and pre- to postshift difference scores. Participants (n = 91) displayed moderate prowhite/antiblack bias on preshift (mean ± SD = 0.50 ± 0.34, d = 1.48) and postshift (mean ± SD = 0.55 ± 0.39, d = 1.40) IAT scores. Overall, IAT scores did not differ preshift to postshift (mean increase = 0.05, 95% CI = -0.02 to 0.14, d = 0.13). Subanalyses revealed increased pre- to postshift bias among participants working when the ED was more overcrowded (mean increase = 0.09, 95% CI = 0.01 to 0.17, d = 0.24) and among those caring for >10 patients (mean increase = 0.17, 95% CI = 0.05 to 0.27, d = 0.47). Residents' demographics (including specialty), fatigue, busyness, stressfulness, and number of shifts were not associated with postshift IAT or difference scores. In multivariable models, ED overcrowding was associated with greater postshift bias (coefficient = 0.11 per 1 unit of NEDOCS score, SE = 0.05, 95% CI = 0.00 to 0.21). While resident implicit bias remained stable overall preshift to postshift, cognitive stressors (overcrowding and patient load) were associated with increased implicit bias. Physicians in the ED should be aware of how cognitive stressors may exacerbate implicit racial bias. © 2016 by the Society for Academic Emergency Medicine.

The Impact of Cognitive Stressors in the Emergency Department on Physician Implicit Racial Bias

PubMed Central

Johnson, Tiffani J.; Hickey, Robert W.; Switzer, Galen E.; Miller, Elizabeth; Winger, Daniel G.; Nguyen, Margaret; Saladino, Richard A.; Hausmann, Leslie R. M.

2016-01-01

Objectives The emergency department (ED) is characterized by stressors (e.g. fatigue, stress, time-pressure, and complex decision-making) that can pose challenges to delivering high quality, equitable care. Although it has been suggested that characteristics of the ED may exacerbate reliance on cognitive heuristics, no research has directly investigated whether stressors in the ED impact physician racial bias, a common heuristic. We seek to determine if physicians have different levels of implicit racial bias post-ED shift versus pre-shift, and to examine associations between demographics and cognitive stressors with bias. Methods This repeated measures study of resident physicians in a pediatric ED used electronic pre- and post-shift assessments of implicit racial bias, demographics, and cognitive stressors. Implicit bias was measured using the Race Implicit Association Test (IAT). Linear regression models compared differences in IAT scores pre- to post-shift, and determined associations between participant demographics and cognitive stressors with post-shift IAT and pre- to post-shift difference scores. Results Participants (n=91) displayed moderate pro-white/anti-black bias on pre-shift (M=0.50, SD=0.34, d=1.48) and post-shift (M=0.55, SD=0.39, d=1.40) IAT scores. Overall, IAT scores did not differ pre-shift to post-shift (mean increase=0.05, 95% CI −0.02,0.14, d=0.13). Sub-analyses revealed increased pre- to post-shift bias among participants working when the ED was more overcrowded (mean increase=0.09, 95% CI 0.01,0.17, d=0.24) and among those caring for >10 patients (mean increase=0.17, 95% CI 0.05,0.27, d=0.47). Residents’ demographics (including specialty), fatigue, busyness, stressfulness, and number of shifts were not associated with post-shift IAT or difference scores. In multivariable models, ED overcrowding was associated with greater post-shift bias (coefficient=0.11 per 1 unit of NEDOCS score, SE=0.05, 95% CI 0.00,0.21). Conclusions While resident implicit bias remained stable overall pre-shift to post-shift, cognitive stressors (overcrowding and patient load) were associated with increased implicit bias. Physicians in the ED should be aware of how cognitive stressors may exacerbate implicit racial bias. PMID:26763939

Evaluation of risk of bias assessment of trials in systematic reviews of oral health interventions, 1991-2014: A methodology study.

PubMed

Saltaji, Humam; Ospina, Maria B; Armijo-Olivo, Susan; Agarwal, Shruti; Cummings, Greta G; Amin, Maryam; Flores-Mir, Carlos

2016-09-01

The authors aimed to describe how often and by what means investigators assessed the risk of bias of clinical trials in systematic reviews of oral health interventions and to identify factors associated with risk of bias assessments. The authors selected therapeutic oral health systematic reviews published from 1991 through 2014. They extracted data related to the tools used for risk of bias assessment of primary studies and data related to other review characteristics. They descriptively analyzed the data and used multivariate logistic regression. The authors identified 1,114 oral health systematic reviews (130 Cochrane reviews and 984 non-Cochrane reviews). The investigators of the primary studies assessed risk of bias in 61.4% of the reviews, and the risk of bias assessments occurred more often in Cochrane reviews than in non-Cochrane reviews (100% versus 56.3%; P < .001) and in reviews published after the dissemination of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (odds ratio [OR], 1.55; 95% confidence interval [CI], 1.17-2.06). Compared with the investigators of reviews of public oral health interventions, investigators of reviews of oral surgery were less likely to assess risk of bias (OR, 0.41; 95% CI, 0.25-0.67). Furthermore, the investigators of systematic reviews published in dental journals were less likely to assess risk of bias of individual trials (OR, 0.28; 95% CI, 0.19-0.41) compared with the investigators of reviews published in nondental journals. The investigators of primary studies did not undertake risk of bias assessment in a considerable portion of non-Cochrane oral health systematic reviews. The investigators of reviews published in dental journals were less likely to assess risk of bias than the investigators of reviews published in nondental journals. The results of this study provide evidence of the need for improving the conduct and reporting of oral health systematic reviews with respect to risk of bias assessment. Clinicians should determine to what extent the findings of a systematic review are valid on the basis of whether the investigators assessed and considered risk of bias during the interpretation of findings. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

Investigating diagnostic bias in autism spectrum conditions: An item response theory analysis of sex bias in the AQ-10.

PubMed

Murray, Aja Louise; Allison, Carrie; Smith, Paula L; Baron-Cohen, Simon; Booth, Tom; Auyeung, Bonnie

2017-05-01

Diagnostic bias is a concern in autism spectrum conditions (ASC) where prevalence and presentation differ by sex. To ensure that females with ASC are not under-identified, it is important that ASC screening tools do not systematically underestimate autistic traits in females relative to males. We evaluated whether the AQ-10, a brief screen for ASC recommended by the National Institute of Clinical Excellence in cases of suspected ASC, exhibits such a bias. Using an item response theory approach, we evaluated differential item functioning and differential test functioning. We found that although individual items showed some sex bias, these biases at times favored males and at other times favored females. Thus, at the level of test scores the item-level biases cancelled out to give an unbiased overall score. Results support the continued use of the AQ-10 sum score in its current form; however, suggest that caution should be exercised when interpreting responses to individual items. The nature of the item level biases could serve as a guide for future research into how ASC affects males and females differently. Autism Res 2017, 10: 790-800. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

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

Attentional bias in older adults: effects of generalized anxiety disorder and cognitive behavior therapy.

PubMed

Mohlman, Jan; Price, Rebecca B; Vietri, Jeff

2013-08-01

Attentional biases are known to play a contributing, and perhaps even causal role in the etiology of anxiety and other negative affective states. The prevalence of anxiety disorders in the older cohort is growing, and there are both theoretical and empirical reasons to suspect that age-related factors could moderate attentional bias effects in the context of late-life anxiety. The current study included one of the most widely-used measures of attentional bias, the dot-probe task (Mathews & MacLeod, 1985). Participants were older adults who were either nonanxious or diagnosed with generalized anxiety disorder. The patient subsample also completed cognitive behavior therapy (CBT) or an equivalent wait list condition, after which the dot probe was administered a second time. Results showed that clinical anxiety had no particular importance for the deployment of attention, casting doubt on the universality of biased attention in older anxiety patients. Although there were no maladaptive biases detected toward either threat or depression words at pretreatment, there was nevertheless a marginally significant differential reduction in bias toward threat words following CBT. This reduction did not occur among those in the wait list condition. Implications are discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2012-12-01

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

Use of Health Care Claims Data to Study Patients with Ophthalmologic Conditions

PubMed Central

Stein, Joshua D.; Lum, Flora; Lee, Paul P.; Rich, William L.; Coleman, Anne L.

2014-01-01

Objective To describe what information is or is not included in health care claims data, provide an overview of the main advantages and limitations of performing analyses using health care claims data, and offer general guidance on how to report and interpret findings of ophthalmology-related claims data analyses. Design Systematic review. Participants Not applicable. Methods A literature review and synthesis of methods for claims-based data analyses. Main Outcome Measures Not applicable. Results Some advantages of using claims data for analyses include large, diverse sample sizes, longitudinal follow-up, lack of selection bias, and potential for complex, multivariable modeling. The disadvantages include (a) the inherent limitations of claims data, such as incomplete, inaccurate, or missing data, or the lack of specific billing codes for some conditions; and (b) the inability, in some circumstances, to adequately evaluate the appropriateness of care. In general, reports of claims data analyses should include clear descriptions of the following methodological elements: the data source, the inclusion and exclusion criteria, the specific billing codes used, and the potential confounding factors incorporated in the multivariable models. Conclusions The use of claims data for research is expected to increase with the enhanced availability of data from Medicare and other sources. The use of claims data to evaluate resource use and efficiency and to determine the basis for supplementary payment methods for physicians is anticipated. Thus, it will be increasingly important for eye care providers to use accurate and descriptive codes for billing. Adherence to general guidance on the reporting of claims data analyses, as outlined in this article, is important to enhance the credibility and applicability of findings. Guidance on optimal ways to conduct and report ophthalmology-related investigations using claims data will likely continue to evolve as health services researchers refine the metrics to analyze large administrative data sets. PMID:24433971

Experimentally induced chocolate craving leads to an attentional bias in increased distraction but not in speeded detection.

PubMed

Smeets, Elke; Roefs, Anne; Jansen, Anita

2009-12-01

In the present study, the causal influence of chocolate craving on attentional bias for chocolate-related information was examined by experimentally inducing chocolate craving in a sample of high trait chocolate cravers vs. low trait chocolate cravers. A sample of 35 high trait chocoholics and 33 low trait chocolate cravers were randomly assigned to either the exposure condition in which craving was manipulated or the non-exposure condition. To measure attentional bias, a pictorial version of the visual search paradigm [Smeets, E., Roefs, A., van Furth, E., & Jansen, A. (2008). Attentional bias for body and food in eating disorders: increased distraction, speeded detection, or both? Behaviour Research and Therapy, 46, 229-238] was used, assessing two components: distraction and detection. It was found that experimentally induced chocolate craving led to increased distraction by chocolate pictures in the high trait chocolate cravers, in comparison to the low trait chocolate cravers. Moreover, this measure of distraction correlated strongly with self-reported craving, but only in the chocoholics and in the exposure condition. In the non-exposure condition, high trait chocolate cravers showed speeded detection of chocolate pictures relative to non-chocoholics, but this component did not correlate with self-reported craving. It is concluded that experimentally induced craving for chocolate causes a bias in, specifically the increased distraction component of attention in high trait chocolate cravers.

A pilot investigation of acute inhibitory control training in cocaine users.

PubMed

Alcorn, Joseph L; Pike, Erika; Stoops, William S; Lile, Joshua A; Rush, Craig R

2017-05-01

Disrupted response inhibition and presence of drug-cue attentional bias in cocaine-using individuals have predicted poor treatment outcomes. Inhibitory control training could help improve treatment outcomes by strengthening cognitive control. This pilot study assessed the effects of acute inhibitory control training to drug- and non-drug-related cues on response inhibition performance and cocaine-cue attentional bias in cocaine-using individuals. Participants who met criteria for a cocaine-use disorder underwent five sessions of inhibitory control training to either non-drug-related cues (i.e., rectangles) or cocaine cues (n=10/condition) in a single day. Response inhibition and attentional bias were assessed prior to and following training using the stop-signal task and visual-probe task with eye tracking, respectively. Training condition groups did not differ on demographics, inhibitory control training performance, response inhibition, or cocaine-cue attentional bias. Response inhibition performance improved as a function of inhibitory control training in both conditions. Cocaine-cue attentional bias was observed, but did not change as a function of inhibitory control training in either condition. Response inhibition in cocaine-using individuals was augmented by acute inhibitory control training, which may improve treatment outcomes through better behavioral inhibition. Future studies should investigate longer-term implementation of inhibitory control training, as well as combining inhibitory control training with other treatment modalities. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Covariation assessment for neutral and emotional verbal stimuli in paranoid delusions.

PubMed

Díez-Alegría, Cristina; Vázquez, Carmelo; Hernández-Lloreda, María J

2008-11-01

Selective processing of emotion-relevant information is considered a central feature in various types of psychopathology, yet the mechanisms underlying these biases are not well understood. One of the first steps in processing information is to gather data to judge the covariation or association of events. The aim of this study was to explore whether patients with persecutory delusions would show a covariation bias when processing stimuli related to social threat. We assessed estimations of covariation in-patients with current persecutory (CP) beliefs (N=40), patients with past persecutory (PP) beliefs (N=25), and a non-clinical control (NC) group (N=36). Covariation estimations were assessed under three different experimental conditions. The first two conditions focused on neutral behaviours (Condition 1) and psychological traits (Condition 2) for two distant cultural groups, while the third condition included self-relevant material by exposing the participant to either protective social (positive) or threatening social (negative) statements about the participant or a third person. Our results showed that all participants were precise in their covariation estimations. However, when judging covariation for self-relevant sentences related to social statements (Condition 3), all groups showed a significant tendency to associate positive social interaction (protection themed) sentences to the self. Yet, when using sentences related to social-threat, the CP group showed a bias consisting of overestimating the number of self-referent sentences. Our results showed that there was no specific covariation assessment bias related to paranoid beliefs. Both NCs and participants with persecutory beliefs showed a similar pattern of results when processing neutral or social threat-related sentences. The implications for understanding of the role of self-referent information processing biases in delusion formation are discussed.

Minimizing Bias When Assessing Student Work

ERIC Educational Resources Information Center

Steinke, Pamela; Fitch, Peggy

2017-01-01

Bias is part of the human condition and becoming aware of how to avoid bias will help to ensure greater accuracy in the work of assessment. In this paper the authors discuss three different theoretical frameworks that can be applied when assessing student work for cognitive skills such as critical thinking and problem solving. Each of the…

Bootstrap Estimation of Sample Statistic Bias in Structural Equation Modeling.

ERIC Educational Resources Information Center

Thompson, Bruce; Fan, Xitao

This study empirically investigated bootstrap bias estimation in the area of structural equation modeling (SEM). Three correctly specified SEM models were used under four different sample size conditions. Monte Carlo experiments were carried out to generate the criteria against which bootstrap bias estimation should be judged. For SEM fit indices,…

Error Biases in Inner and Overt Speech: Evidence from Tongue Twisters

ERIC Educational Resources Information Center

Corley, Martin; Brocklehurst, Paul H.; Moat, H. Susannah

2011-01-01

To compare the properties of inner and overt speech, Oppenheim and Dell (2008) counted participants' self-reported speech errors when reciting tongue twisters either overtly or silently and found a bias toward substituting phonemes that resulted in words in both conditions, but a bias toward substituting similar phonemes only when speech was…

Unconscious Bias: When Good Intentions Aren't Enough

ERIC Educational Resources Information Center

Fiarman, Sarah E.

2016-01-01

"A growing body of research shows that unconscious bias is not only common, but it's also a condition of being human," writes Fiarman. In this article, she argues that implicit biases about race, gender, sexual orientation, and other aspects of identity can overshadow even the best of intentions. Citing examples from her own practice as…

The malleability of emotional perception: Short-term plasticity in retinotopic neurons accompanies the formation of perceptual biases to threat.

PubMed

Thigpen, Nina N; Bartsch, Felix; Keil, Andreas

2017-04-01

Emotional experience changes visual perception, leading to the prioritization of sensory information associated with threats and opportunities. These emotional biases have been extensively studied by basic and clinical scientists, but their underlying mechanism is not known. The present study combined measures of brain-electric activity and autonomic physiology to establish how threat biases emerge in human observers. Participants viewed stimuli designed to differentially challenge known properties of different neuronal populations along the visual pathway: location, eye, and orientation specificity. Biases were induced using aversive conditioning with only 1 combination of eye, orientation, and location predicting a noxious loud noise and replicated in a separate group of participants. Selective heart rate-orienting responses for the conditioned threat stimulus indicated bias formation. Retinotopic visual brain responses were persistently and selectively enhanced after massive aversive learning for only the threat stimulus and dissipated after extinction training. These changes were location-, eye-, and orientation-specific, supporting the hypothesis that short-term plasticity in primary visual neurons mediates the formation of perceptual biases to threat. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Ranking Bias in Association Studies

PubMed Central

Jeffries, Neal O.

2009-01-01

Background It is widely appreciated that genomewide association studies often yield overestimates of the association of a marker with disease when attention focuses upon the marker showing the strongest relationship. For example, in a case-control setting the largest (in absolute value) estimated odds ratio has been found to typically overstate the association as measured in a second, independent set of data. The most common reason given for this observation is that the choice of the most extreme test statistic is often conditional upon first observing a significant p value associated with the marker. A second, less appreciated reason is described here. Under common circumstances it is the multiple testing of many markers and subsequent focus upon those with most extreme test statistics (i.e. highly ranked results) that leads to bias in the estimated effect sizes. Conclusions This bias, termed ranking bias, is separate from that arising from conditioning on a significant p value and may often be a more important factor in generating bias. An analytic description of this bias, simulations demonstrating its extent, and identification of some factors leading to its exacerbation are presented. PMID:19172085

Meta-regression approximations to reduce publication selection bias.

PubMed

Stanley, T D; Doucouliagos, Hristos

2014-03-01

Publication selection bias is a serious challenge to the integrity of all empirical sciences. We derive meta-regression approximations to reduce this bias. Our approach employs Taylor polynomial approximations to the conditional mean of a truncated distribution. A quadratic approximation without a linear term, precision-effect estimate with standard error (PEESE), is shown to have the smallest bias and mean squared error in most cases and to outperform conventional meta-analysis estimators, often by a great deal. Monte Carlo simulations also demonstrate how a new hybrid estimator that conditionally combines PEESE and the Egger regression intercept can provide a practical solution to publication selection bias. PEESE is easily expanded to accommodate systematic heterogeneity along with complex and differential publication selection bias that is related to moderator variables. By providing an intuitive reason for these approximations, we can also explain why the Egger regression works so well and when it does not. These meta-regression methods are applied to several policy-relevant areas of research including antidepressant effectiveness, the value of a statistical life, the minimum wage, and nicotine replacement therapy. Copyright © 2013 John Wiley & Sons, Ltd.

Creation and validation of a novel body condition scoring method for the magellanic penguin (Spheniscus magellanicus) in the zoo setting.

PubMed

Clements, Julie; Sanchez, Jessica N

2015-11-01

This research aims to validate a novel, visual body scoring system created for the Magellanic penguin (Spheniscus magellanicus) suitable for the zoo practitioner. Magellanics go through marked seasonal fluctuations in body mass gains and losses. A standardized multi-variable visual body condition guide may provide a more sensitive and objective assessment tool compared to the previously used single variable method. Accurate body condition scores paired with seasonal weight variation measurements give veterinary and keeper staff a clearer understanding of an individual's nutritional status. San Francisco Zoo staff previously used a nine-point body condition scale based on the classic bird standard of a single point of keel palpation with the bird restrained in hand, with no standard measure of reference assigned to each scoring category. We created a novel, visual body condition scoring system that does not require restraint to assesses subcutaneous fat and muscle at seven body landmarks using illustrations and descriptive terms. The scores range from one, the least robust or under-conditioned, to five, the most robust, or over-conditioned. The ratio of body weight to wing length was used as a "gold standard" index of body condition and compared to both the novel multi-variable and previously used single-variable body condition scores. The novel multi-variable scale showed improved agreement with weight:wing ratio compared to the single-variable scale, demonstrating greater accuracy, and reliability when a trained assessor uses the multi-variable body condition scoring system. Zoo staff may use this tool to manage both the colony and the individual to assist in seasonally appropriate Magellanic penguin nutrition assessment. © 2015 Wiley Periodicals, Inc.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Decreasing self-reported cognitive biases and increasing clinical insight through meta-cognitive training in patients with chronic schizophrenia.

PubMed

Gawęda, Łukasz; Krężołek, Martyna; Olbryś, Joanna; Turska, Agnieszka; Kokoszka, Andrzej

2015-09-01

The aim of this study was to assess the impact of meta-cognitive training (MCT) on cognitive biases, symptoms, clinical insight, and general functioning among low-level functioning persons diagnosed with chronic schizophrenia who were attending a daily Community Social Support Group Program; we compared the treatment-as-usual (TAU) condition with the MCT + TAU condition. Forty-four patients diagnosed with chronic schizophrenia were allocated to either the MCT + treatment-as-usual condition or the treatment-as-usual (TAU) condition. Delusion and hallucination severity, cognitive biases, clinical insight, and global functioning were assessed pre- and post-treatment (clinical trial NCT02187692). No significant changes were found in symptom severity as measured with the PSYRATS. Conversely, a medium to large effect size was observed for delusional ideation changes when assessed by the self-report measure (Paranoia Checklist). MCT was found to ameliorate cognitive biases as measured by the self-report scale at large effect size, however, no changes in jumping to conclusions (the Fish Task) and theory of mind deficits ("Reading the Mind in the Eyes" Test) were found in the behavioral tasks. MCT increased insight at large effect size. No changes in global functioning were found between the two conditions. Low intensity intervention. No follow-up assessment was provided. Only PSYRATS was assessed blind to patient allocation. MCT has a beneficial effect on low-functioning chronic schizophrenic patients in ameliorating cognitive biases and increasing clinical insight. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Effect of exposure to good vs poor medical trainee performance on attending physician ratings of subsequent performances.

PubMed

Yeates, Peter; O'Neill, Paul; Mann, Karen; Eva, Kevin W

2012-12-05

Competency-based models of education require assessments to be based on individuals' capacity to perform, yet the nature of human judgment may fundamentally limit the extent to which such assessment is accurately possible. To determine whether recent observations of the Mini Clinical Evaluation Exercise (Mini-CEX) performance of postgraduate year 1 physicians influence raters' scores of subsequent performances, consistent with either anchoring bias (scores biased similar to previous experience) or contrast bias (scores biased away from previous experience). Internet-based randomized, blinded experiment using videos of Mini-CEX assessments of postgraduate year 1 trainees interviewing new internal medicine patients. Participants were 41 attending physicians from England and Wales experienced with the Mini-CEX, with 20 watching and scoring 3 good trainee performances and 21 watching and scoring 3 poor performances. All then watched and scored the same 3 borderline video performances. The study was completed between July and November 2011. The primary outcome was scores assigned to the borderline videos, using a 6-point Likert scale (anchors included: 1, well below expectations; 3, borderline; 6, well above expectations). Associations were tested in a multivariable analysis that included participants' sex, years of practice, and the stringency index (within-group z score of initial 3 ratings). The mean rating scores assigned by physicians who viewed borderline video performances following exposure to good performances was 2.7 (95% CI, 2.4-3.0) vs 3.4 (95% CI, 3.1-3.7) following exposure to poor performances (difference of 0.67 [95% CI, 0.28-1.07]; P = .001). Borderline videos were categorized as consistent with failing scores in 33 of 60 assessments (55%) in those exposed to good performances and in 15 of 63 assessments (24%) in those exposed to poor performances (P < .001). They were categorized as consistent with passing scores in 5 of 60 assessments (8.3%) in those exposed to good performances compared with 25 of 63 assessments (39.5%) in those exposed to poor performances (P < .001). Sex and years of attending practice were not associated with scores. The priming condition (good vs poor performances) and the stringency index jointly accounted for 45% of the observed variation in raters' scores for the borderline videos (P < .001). In an experimental setting, attending physicians exposed to videos of good medical trainee performances rated subsequent borderline performances lower than those who had been exposed to poor performances, consistent with a contrast bias.

Total Shoulder Arthroplasty: Is Less Time in the Hospital Better?

PubMed

Duchman, Kyle R; Anthony, Chris A; Westermann, Robert W; Pugely, Andrew J; Gao, Yubo; Hettrich, Carolyn M

2017-01-01

The incidence of total shoulder arthroplasty (TSA) has increased significantly over the last decade. Short-stay protocols for other highvolume procedures have been shown to be safe and effective but have yet to be fully explored for TSA. Our purpose in comparing short-stay and inpatient TSA was to determine: (1) patient demographics and comorbidities, (2) 30-day morbidity, mortality, and readmissions using a matched analysis, and (3) independent predictors of 30-day complications. The American College of Surgeons National Surgical Quality Improvement (ACS NSQIP) database was queried and all patients undergoing elective, primary TSA between 2006 and 2013 were identified. Patients were categorized as short-stay or inpatient based on day of discharge. Propensity score matching was used to adjust for selection bias. Univariate and multivariate statistical analysis was used to compare 30-day morbidity and mortality between the two cohorts. Overall, 4,619 cases were available, with inpatient admission occurring in 65.7% of patients. Prior to propensity score matching, short-stay patients were significantly younger, more frequently male, with fewer comorbid conditions. After matching, inpatient admission was associated with increased rates of urinary tract infection (1.1% vs. 0.1%; p = 0.001), blood transfusion (5.3% vs. 0.8%; p < 0.001), and total complications (4.7% vs. 1.8%; p < 0.001). Multivariate analysis identified inpatient admission as an independent risk factor for 30-day complication following TSA. Short-stay TSA is a safe option for the appropriately selected patient. Inpatient admission was an independent risk factor for complication following TSA. Level of Evidence: III.

Diagnostics for Confounding of Time-varying and Other Joint Exposures.

PubMed

Jackson, John W

2016-11-01

The effects of joint exposures (or exposure regimes) include those of adhering to assigned treatment versus placebo in a randomized controlled trial, duration of exposure in a cohort study, interactions between exposures, and direct effects of exposure, among others. Unlike the setting of a single point exposure (e.g., propensity score matching), there are few tools to describe confounding for joint exposures or how well a method resolves it. Investigators need tools that describe confounding in ways that are conceptually grounded and intuitive for those who read, review, and use applied research to guide policy. We revisit the implications of exchangeability conditions that hold in sequentially randomized trials, and the bias structure that motivates the use of g-methods, such as marginal structural models. From these, we develop covariate balance diagnostics for joint exposures that can (1) describe time-varying confounding, (2) assess whether covariates are predicted by prior exposures given their past, the indication for g-methods, and (3) describe residual confounding after inverse probability weighting. For each diagnostic, we present time-specific metrics that encompass a wide class of joint exposures, including regimes of multivariate time-varying exposures in censored data, with multivariate point exposures as a special case. We outline how to estimate these directly or with regression and how to average them over person-time. Using a simulated example, we show how these metrics can be presented graphically. This conceptually grounded framework can potentially aid the transparent design, analysis, and reporting of studies that examine joint exposures. We provide easy-to-use tools to implement it.

Examining Event-Related Potential (ERP) Correlates of Decision Bias in Recognition Memory Judgments

PubMed Central

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500–700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions. PMID:25264982

Examining Event-Related Potential (ERP) correlates of decision bias in recognition memory judgments.

PubMed

Hill, Holger; Windmann, Sabine

2014-01-01

Memory judgments can be based on accurate memory information or on decision bias (the tendency to report that an event is part of episodic memory when one is in fact unsure). Event related potentials (ERP) correlates are important research tools for elucidating the dynamics underlying memory judgments but so far have been established only for investigations of accurate old/new discrimination. To identify the ERP correlates of bias, and observe how these interact with ERP correlates of memory, we conducted three experiments that manipulated decision bias within participants via instructions during recognition memory tests while their ERPs were recorded. In Experiment 1, the bias manipulation was performed between blocks of trials (automatized bias) and compared to trial-by-trial shifts of bias in accord with an external cue (flexibly controlled bias). In Experiment 2, the bias manipulation was performed at two different levels of accurate old/new discrimination as the memory strength of old (studied) items was varied. In Experiment 3, the bias manipulation was added to another, bottom-up driven manipulation of bias induced via familiarity. In the first two Experiments, and in the low familiarity condition of Experiment 3, we found evidence of an early frontocentral ERP component at 320 ms poststimulus (the FN320) that was sensitive to the manipulation of bias via instruction, with more negative amplitudes indexing more liberal bias. By contrast, later during the trial (500-700 ms poststimulus), bias effects interacted with old/new effects across all three experiments. Results suggest that the decision criterion is typically activated early during recognition memory trials, and is integrated with retrieved memory signals and task-specific processing demands later during the trial. More generally, the findings demonstrate how ERPs can help to specify the dynamics of recognition memory processes under top-down and bottom-up controlled retrieval conditions.

Developing interpretation bias modification as a "cognitive vaccine" for depressed mood: imagining positive events makes you feel better than thinking about them verbally.

PubMed

Holmes, Emily A; Lang, Tamara J; Shah, Dhruvi M

2009-02-01

Two interpretation bias modification experiments found that mental imagery vs. verbal processing of positive material have differential emotional effects. In Experiment 1, participants were instructed to imagine positively resolved auditory descriptions or to listen to the same events while thinking about their verbal meaning. Increases in positive mood and bias were greater in the imagery than in the verbal condition, replicating E. A. Holmes, A. Mathews, T. Dalgleish, and B. Mackintosh (2006). An emotional vulnerability test showed that imagery (relative to the verbal condition) protected against a later negative mood induction. Experiment 2 created 2 new verbal conditions aimed to increase or reduce verbal comparisons. Results suggest making unfavorable comparisons with the highly positive material might be partially responsible for the inferiority of the verbal condition in Experiment 1. The findings demonstrate that imagery can play a key role in cognitive bias modification procedures and thus that task instructions are crucial. Imagining a positive event can make you feel better than thinking about the same event verbally. The authors propose that recruiting imagery will be useful in therapeutic innovations to develop a "cognitive vaccine" for depressed mood.

Fear acquisition and liking of out-group and in-group members: Learning bias or attention?

PubMed

Koenig, Stephan; Nauroth, Peter; Lucke, Sara; Lachnit, Harald; Gollwitzer, Mario; Uengoer, Metin

2017-10-01

The present study explores the notion of an out-group fear learning bias that is characterized by facilitated fear acquisition toward harm-doing out-group members. Participants were conditioned with two in-group and two out-group faces as conditioned stimuli. During acquisition, one in-group and one out-group face was paired with an aversive shock whereas the other in-group and out-group face was presented without shock. Psychophysiological measures of fear conditioning (skin conductance and pupil size) and explicit and implicit liking exhibited increased differential responding to out-group faces compared to in-group faces. However, the results did not clearly indicate that harm-doing out-group members were more readily associated with fear than harm-doing in-group members. In contrast, the out-group face not paired with shock decreased conditioned fear and disliking at least to the same extent that the shock-associated out-group face increased these measures. Based on these results, we suggest an account of the out-group fear learning bias that relates to an attentional bias to process in-group information. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling

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

Li Yupeng, E-mail: yupeng@ualberta.ca; Deutsch, Clayton V.

2012-06-15

In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells.more » In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.« less

Cognitive biases toward Internet game-related pictures and executive deficits in individuals with an Internet game addiction.

PubMed

Zhou, Zhenhe; Yuan, Guozhen; Yao, Jianjun

2012-01-01

The cue-related go/no-go switching task provides an experimental approach to study individual's flexibility in changing situations. Because Internet addiction disorder (IAD) belongs to the compulsive-impulsive spectrum of disorders, it should present cognitive bias and executive functioning deficit characteristics of some of these types of disorders. Until now, no studies have been reported on cognitive bias and executive function involving mental flexibility and response inhibition in IAD. A total of 46 subjects who met the criteria of the modified Young's Diagnostic Questionnaire for Internet addiction (YDQ) were recruited as an Internet game addiction (IGA) group, along with 46 healthy control individuals. All participants performed the Internet game-shifting task. Using hit rate, RT, d' and C as the dependent measures, a three-way ANOVA (group × target × condition) was performed. For hit rate, a significant effect of group, type of target and condition were found. The group-target interaction effect was significant. For RT, significant effects were revealed for group and type of target. The group-target interaction effect was significant. Comparisons of the means revealed that the slowing down of IGA relative to NIA was more pronounced when the target stimuli were neutral as opposed to Internet game-related pictures. In addition, the group-condition interaction effect was significant. For d', significant effects of group, type of target and condition were found. The group-target interaction effect was significant. For C, the type of target produced a significant effect. There was a positive correlation between the length of the addiction (number of years) and the severity of the cognitive bias. IGA present cognitive biases towards information related to Internet gaming. These biases, as well as poor executive functioning skills (lower mental flexibility and response inhibition), might be responsible for Internet game addiction. The assessment of cognitive biases in IGA might provide a methodology for evaluation of therapeutic effects.

An Innovative Strategy for Accurate Thermal Compensation of Gyro Bias in Inertial Units by Exploiting a Novel Augmented Kalman Filter

PubMed Central

Angrisani, Leopoldo; Simone, Domenico De

2018-01-01

This paper presents an innovative model for integrating thermal compensation of gyro bias error into an augmented state Kalman filter. The developed model is applied in the Zero Velocity Update filter for inertial units manufactured by exploiting Micro Electro-Mechanical System (MEMS) gyros. It is used to remove residual bias at startup. It is a more effective alternative to traditional approach that is realized by cascading bias thermal correction by calibration and traditional Kalman filtering for bias tracking. This function is very useful when adopted gyros are manufactured using MEMS technology. These systems have significant limitations in terms of sensitivity to environmental conditions. They are characterized by a strong correlation of the systematic error with temperature variations. The traditional process is divided into two separated algorithms, i.e., calibration and filtering, and this aspect reduces system accuracy, reliability, and maintainability. This paper proposes an innovative Zero Velocity Update filter that just requires raw uncalibrated gyro data as input. It unifies in a single algorithm the two steps from the traditional approach. Therefore, it saves time and economic resources, simplifying the management of thermal correction process. In the paper, traditional and innovative Zero Velocity Update filters are described in detail, as well as the experimental data set used to test both methods. The performance of the two filters is compared both in nominal conditions and in the typical case of a residual initial alignment bias. In this last condition, the innovative solution shows significant improvements with respect to the traditional approach. This is the typical case of an aircraft or a car in parking conditions under solar input. PMID:29735956

An Innovative Strategy for Accurate Thermal Compensation of Gyro Bias in Inertial Units by Exploiting a Novel Augmented Kalman Filter.

PubMed

Fontanella, Rita; Accardo, Domenico; Moriello, Rosario Schiano Lo; Angrisani, Leopoldo; Simone, Domenico De

2018-05-07

This paper presents an innovative model for integrating thermal compensation of gyro bias error into an augmented state Kalman filter. The developed model is applied in the Zero Velocity Update filter for inertial units manufactured by exploiting Micro Electro-Mechanical System (MEMS) gyros. It is used to remove residual bias at startup. It is a more effective alternative to traditional approach that is realized by cascading bias thermal correction by calibration and traditional Kalman filtering for bias tracking. This function is very useful when adopted gyros are manufactured using MEMS technology. These systems have significant limitations in terms of sensitivity to environmental conditions. They are characterized by a strong correlation of the systematic error with temperature variations. The traditional process is divided into two separated algorithms, i.e., calibration and filtering, and this aspect reduces system accuracy, reliability, and maintainability. This paper proposes an innovative Zero Velocity Update filter that just requires raw uncalibrated gyro data as input. It unifies in a single algorithm the two steps from the traditional approach. Therefore, it saves time and economic resources, simplifying the management of thermal correction process. In the paper, traditional and innovative Zero Velocity Update filters are described in detail, as well as the experimental data set used to test both methods. The performance of the two filters is compared both in nominal conditions and in the typical case of a residual initial alignment bias. In this last condition, the innovative solution shows significant improvements with respect to the traditional approach. This is the typical case of an aircraft or a car in parking conditions under solar input.

Language dominance shapes non-linguistic rhythmic grouping in bilinguals.

PubMed

Molnar, Monika; Carreiras, Manuel; Gervain, Judit

2016-07-01

To what degree non-linguistic auditory rhythm perception is governed by universal biases (e.g., Iambic-Trochaic Law; Hayes, 1995) or shaped by native language experience is debated. It has been proposed that rhythmic regularities in spoken language, such as phrasal prosody affect the grouping abilities of monolinguals (e.g., Iversen, Patel, & Ohgushi, 2008). Here, we assessed the non-linguistic tone grouping biases of Spanish monolinguals, and three groups of Basque-Spanish bilinguals with different levels of Basque experience. It is usually assumed in the literature that Basque and Spanish have different phrasal prosodies and even linguistic rhythms. To confirm this, first, we quantified Basque and Spanish phrasal prosody (Experiment 1a) and duration patterns used in the classification of languages into rhythm classes (Experiment 1b). The acoustic measurements revealed that regularities in phrasal prosody systematically differ across Basque and Spanish; by contrast, the rhythms of the two languages are only minimally dissimilar. In Experiment 2, participants' non-linguistic rhythm preferences were assessed in response to non-linguistic tones alternating in either intensity (Intensity condition) or in duration (Duration condition). In the Intensity condition, all groups showed a trochaic grouping bias, as predicted by the Iambic-Trochaic Law. In the Duration Condition the Spanish monolingual and the most Basque-dominant bilingual group exhibited opposite grouping preferences in line with the phrasal prosodies of their native/dominant languages, trochaic in Basque, iambic in Spanish. The two other bilingual groups showed no significant biases, however. Overall, results indicate that duration-based grouping mechanisms are biased toward the phrasal prosody of the native and dominant language; also, the presence of an L2 in the environment interacts with the auditory biases. Copyright © 2016 Elsevier B.V. All rights reserved.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian

2018-01-01

Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Large-scale galaxy bias

NASA Astrophysics Data System (ADS)

Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian

2018-02-01

This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.

Influence of growth conditions on exchange bias of NiMn-based spin valves

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

Wienecke, Anja; Kruppe, Rahel; Rissing, Lutz

2015-05-07

As shown in previous investigations, a correlation between a NiMn-based spin valve's thermal stability and its inherent exchange bias exists, even if the blocking temperature of the antiferromagnet is clearly above the heating temperature and the reason for thermal degradation is mainly diffusion and not the loss of exchange bias. Samples with high exchange bias are thermally more stable than samples with low exchange bias. Those structures promoting a high exchange bias are seemingly the same suppressing thermally induced diffusion processes (A. Wienecke and L. Rissing, “Relationship between thermal stability and layer-stack/structure of NiMn-based GMR systems,” in IEEE Transaction onmore » Magnetic Conference (EMSA 2014)). Many investigations were carried out on the influence of the sputtering parameters as well as the layer thickness on the magnetoresistive effect. The influence of these parameters on the exchange bias and the sample's thermal stability, respectively, was hardly taken into account. The investigation described here concentrates on the last named issue. The focus lies on the influence of the sputtering parameters and layer thickness of the “starting layers” in the stack and the layers forming the (synthetic) antiferromagnet. This paper includes a guideline for the evaluated sputtering conditions and layer thicknesses to realize a high exchange bias and presumably good thermal stability for NiMn-based spin valves with a synthetic antiferromagnet.« less

The grouping benefit in extinction: overcoming the temporal order bias.

PubMed

Rappaport, Sarah J; Riddoch, M Jane; Humphreys, Glyn W

2011-01-01

Grouping between contra- and ipsilesional stimuli can alleviate the lateralised bias in spatial extinction (Gilchrist, Humphreys, & Riddoch, 1996; Ward, Goodrich, & Driver, 1994). In the current study we demonstrate for the first time that perceptual grouping can also modulate the spatio/temporal biases in temporal order judgements affecting the temporal as well as the spatial coding of stimuli. Perceived temporal order was assessed by presenting two coloured letter stimuli in either hemi-field temporally segregated by a range of onset-intervals. Items were either identical (grouping condition) or differed in both shape and colour (non-grouping condition). Observers were required to indicate which item appeared second. Patients with visual extinction had a bias against the contralesional item appearing first, but this was modulated by perceptual grouping. When both items were identical in shape and colour the temporal bias against reporting the contralesional item was reduced. The results suggest that grouping can alter the coding of temporal relations between stimuli. Copyright © 2010 Elsevier Ltd. All rights reserved.

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…

Fast computation of the multivariable stability margin for real interrelated uncertain parameters

NASA Technical Reports Server (NTRS)

Sideris, Athanasios; Sanchez Pena, Ricardo S.

1988-01-01

A novel algorithm for computing the multivariable stability margin for checking the robust stability of feedback systems with real parametric uncertainty is proposed. This method eliminates the need for the frequency search involved in another given algorithm by reducing it to checking a finite number of conditions. These conditions have a special structure, which allows a significant improvement on the speed of computations.

Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS)

NASA Astrophysics Data System (ADS)

Durmaz, Murat; Karslioglu, Mahmut Onur

2015-04-01

There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.

Bias correction of risk estimates in vaccine safety studies with rare adverse events using a self-controlled case series design.

PubMed

Zeng, Chan; Newcomer, Sophia R; Glanz, Jason M; Shoup, Jo Ann; Daley, Matthew F; Hambidge, Simon J; Xu, Stanley

2013-12-15

The self-controlled case series (SCCS) method is often used to examine the temporal association between vaccination and adverse events using only data from patients who experienced such events. Conditional Poisson regression models are used to estimate incidence rate ratios, and these models perform well with large or medium-sized case samples. However, in some vaccine safety studies, the adverse events studied are rare and the maximum likelihood estimates may be biased. Several bias correction methods have been examined in case-control studies using conditional logistic regression, but none of these methods have been evaluated in studies using the SCCS design. In this study, we used simulations to evaluate 2 bias correction approaches-the Firth penalized maximum likelihood method and Cordeiro and McCullagh's bias reduction after maximum likelihood estimation-with small sample sizes in studies using the SCCS design. The simulations showed that the bias under the SCCS design with a small number of cases can be large and is also sensitive to a short risk period. The Firth correction method provides finite and less biased estimates than the maximum likelihood method and Cordeiro and McCullagh's method. However, limitations still exist when the risk period in the SCCS design is short relative to the entire observation period.

Selective processing of smoking-related cues in smokers: manipulation of deprivation level and comparison of three measures of processing bias.

PubMed

Mogg, Karin; Bradley, Brendan P

2002-12-01

Recent theories of addiction suggest that an attentional bias for drug-related cues plays an important role in maintaining drug-taking behaviours. A key feature of the present study is that it used three different measures of processing bias for linguistic and pictorial smoking-related cues: masked and unmasked conditions of the modified Stroop task, and a pictorial version of the visual probe task. Participants were smokers (n = 27), who were tested twice, with deprivation level manipulated as a within-subjects variable. They were asked to abstain from smoking for 12 h before one session, and to smoke normally before the other. Results were consistent with an attentional bias for smoking-related pictures on the visual probe task, and for smoking-related words in the unmasked condition of the modified Stroop task. The latter bias was most strongly predicted by self-reported urge to smoke, rather than by the deprivation manipulation. There was no evidence of a preconscious bias for smoking cues. The three measures of cognitive bias (from masked and unmasked Stroop and visual probe tasks) were not significantly correlated with each other, which suggests they may tap different underlying mechanisms. We discuss the results with respect to conceptualizations of selective attention, addiction and motivational states in general.

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.

Majority of systematic reviews published in high-impact journals neglected to register the protocols: a meta-epidemiological study.

PubMed

Tsujimoto, Yasushi; Tsujimoto, Hiraku; Kataoka, Yuki; Kimachi, Miho; Shimizu, Sayaka; Ikenoue, Tatsuyoshi; Fukuma, Shingo; Yamamoto, Yosuke; Fukuhara, Shunichi

2017-04-01

To describe the registration of systematic review (SR) protocols and examine whether or not registration reduced the outcome reporting bias in high-impact journals. We searched MEDLINE via PubMed to identify SRs of randomized controlled trials of interventions. We included SRs published between August 2009 and June 2015 in the 10 general and internal medicinal journals with the highest impact factors in 2013. We examined the proportion of SR protocol registration and investigated the relationship between registration and outcome reporting bias using multivariable logistic regression. Among the 284 included reviews, 60 (21%) protocols were registered. The proportion of registration increased from 5.6% in 2009 to 27% in 2015 (P for trend <0.001). Protocol registration was not associated with outcome reporting bias (adjusted odds ratio [OR] 0.85, 95% confidence interval [CI] 0.39-1.86). The association between Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) adherence and protocol registration was not statistically significant (OR 1.09, 95% CI 0.59-2.01). Six years after the launch of the PRISMA statement, the proportion of protocol registration in high-impact journals has increased some but remains low. The present study found no evidence suggesting that protocol registration reduced outcome reporting bias. Copyright © 2017 Elsevier Inc. All rights reserved.

Ageism among social work faculty: impact of personal factors and other "isms".

PubMed

Chonody, Jill M; Wang, Donna

2014-01-01

The purpose of this article was (a) to determine the extent to which ageist attitudes are evident among social work faculty and how educational factors may contribute to ageism, (b) to determine if terror management theory (in terms of aging anxiety) offers a further explanation for ageist attitudes beyond known correlates, and (c) to understand how intersecting prejudices (attitudes toward women, gay men, and lesbians) may be associated with ageist attitudes. Results indicated a low bias toward older adults, with two variables, psychological anxiety about aging and paid experience with older adults, accounting for 29.7% of the variance. Further, no association was found between ageism and sexism and sexual prejudice in the multivariate analyses. These results indicate promising advances for terror management theory in explaining ageism. Social work faculty's low bias and perceived need for gerontological content in curricula is an encouraging finding for gerontological social work education.

Rapid neural discrimination of communicative gestures

PubMed Central

Carlson, Thomas A.

2015-01-01

Humans are biased toward social interaction. Behaviorally, this bias is evident in the rapid effects that self-relevant communicative signals have on attention and perceptual systems. The processing of communicative cues recruits a wide network of brain regions, including mentalizing systems. Relatively less work, however, has examined the timing of the processing of self-relevant communicative cues. In the present study, we used multivariate pattern analysis (decoding) approach to the analysis of magnetoencephalography (MEG) to study the processing dynamics of social-communicative actions. Twenty-four participants viewed images of a woman performing actions that varied on a continuum of communicative factors including self-relevance (to the participant) and emotional valence, while their brain activity was recorded using MEG. Controlling for low-level visual factors, we found early discrimination of emotional valence (70 ms) and self-relevant communicative signals (100 ms). These data offer neural support for the robust and rapid effects of self-relevant communicative cues on behavior. PMID:24958087

Medical School Experiences Associated with Change in Implicit Racial Bias Among 3547 Students: A Medical Student CHANGES Study Report.

PubMed

van Ryn, Michelle; Hardeman, Rachel; Phelan, Sean M; Burgess, Diana J; Dovidio, John F; Herrin, Jeph; Burke, Sara E; Nelson, David B; Perry, Sylvia; Yeazel, Mark; Przedworski, Julia M

2015-12-01

Physician implicit (unconscious, automatic) bias has been shown to contribute to racial disparities in medical care. The impact of medical education on implicit racial bias is unknown. To examine the association between change in student implicit racial bias towards African Americans and student reports on their experiences with 1) formal curricula related to disparities in health and health care, cultural competence, and/or minority health; 2) informal curricula including racial climate and role model behavior; and 3) the amount and favorability of interracial contact during school. Prospective observational study involving Web-based questionnaires administered during first (2010) and last (2014) semesters of medical school. A total of 3547 students from a stratified random sample of 49 U.S. medical schools. Change in implicit racial attitudes as assessed by the Black-White Implicit Association Test administered during the first semester and again during the last semester of medical school. In multivariable modeling, having completed the Black-White Implicit Association Test during medical school remained a statistically significant predictor of decreased implicit racial bias (-5.34, p ≤ 0.001: mixed effects regression with random intercept across schools). Students' self-assessed skills regarding providing care to African American patients had a borderline association with decreased implicit racial bias (-2.18, p = 0.056). Having heard negative comments from attending physicians or residents about African American patients (3.17, p = 0.026) and having had unfavorable vs. very favorable contact with African American physicians (18.79, p = 0.003) were statistically significant predictors of increased implicit racial bias. Medical school experiences in all three domains were independently associated with change in student implicit racial attitudes. These findings are notable given that even small differences in implicit racial attitudes have been shown to affect behavior and that implicit attitudes are developed over a long period of repeated exposure and are difficult to change.

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.

High-resolution near real-time drought monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

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

PubMed

Lam, King-Yeung; Lou, Yuan

2014-02-01

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

Effect of altered sensory conditions on multivariate descriptors of human postural sway

NASA Technical Reports Server (NTRS)

Kuo, A. D.; Speers, R. A.; Peterka, R. J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

1998-01-01

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

Sampling bias in an internet treatment trial for depression.

PubMed

Donkin, L; Hickie, I B; Christensen, H; Naismith, S L; Neal, B; Cockayne, N L; Glozier, N

2012-10-23

Internet psychological interventions are efficacious and may reduce traditional access barriers. No studies have evaluated whether any sampling bias exists in these trials that may limit the translation of the results of these trials into real-world application. We identified 7999 potentially eligible trial participants from a community-based health cohort study and invited them to participate in a randomized controlled trial of an online cognitive behavioural therapy programme for people with depression. We compared those who consented to being assessed for trial inclusion with nonconsenters on demographic, clinical and behavioural indicators captured in the health study. Any potentially biasing factors were then assessed for their association with depression outcome among trial participants to evaluate the existence of sampling bias. Of the 35 health survey variables explored, only 4 were independently associated with higher likelihood of consenting-female sex (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.05-1.19), speaking English at home (OR 1.48, 95% CI 1.15-1.90) higher education (OR 1.67, 95% CI 1.46-1.92) and a prior diagnosis of depression (OR 1.37, 95% CI 1.22-1.55). The multivariate model accounted for limited variance (C-statistic 0.6) in explaining participation. These four factors were not significantly associated with either the primary trial outcome measure or any differential impact by intervention arm. This demonstrates that, among eligible trial participants, few factors were associated with the consent to participate. There was no indication that such self-selection biased the trial results or would limit the generalizability and translation into a public or clinical setting.

Sex-biased investment in yolk androgens depends on female quality and laying order in zebra finches (Taeniopygia guttata)

NASA Astrophysics Data System (ADS)

Gilbert, Lucy; Rutstein, Alison N.; Hazon, Neil; Graves, Jefferson A.

2005-04-01

The Trivers-Willard hypothesis predicts sex biases in parental investment according to parental condition. In addition, parents may need to sex bias their investment if there is an asymmetry between the sexes in offspring fitness under different conditions. For studying maternal differential investment, egg resources are ideal subjects because they are self contained and allocated unequivocally by the female. Recent studies show that yolk androgens can be beneficial to offspring, so here we test for sex-biased investment with maternal investment of yolk testosterone (T) in zebra finch (Taeniopygia guttata) eggs. From the Trivers-Willard hypothesis, we predicted females to invest more in male eggs in optimum circumstances (e.g. good-condition mother, early-laid egg), and more in female eggs under suboptimal conditions (e.g. poor-condition mother, late-laid egg). This latter prediction is also because in this species there is a female nestling disadvantage in poor conditions and we expected mothers to help compensate for this in female eggs. Indeed, we found more yolk T in female than male eggs. Moreover, in accordance with our predictions, yolk T in male eggs increased with maternal quality relative to female eggs, and decreased with laying order relative to female eggs. This supports our predictions for the different needs and value of male and female offspring in zebra finches. Our results support the idea that females may use yolk androgens as a tool to adaptively manipulate the inequalities between different nestlings.

Insights on the impact of systematic model errors on data assimilation performance in changing catchments

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.

2018-03-01

The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.

Causal role for inverse reasoning on obsessive-compulsive symptoms: Preliminary evidence from a cognitive bias modification for interpretation bias study.

PubMed

Wong, Shiu F; Grisham, Jessica R

2017-12-01

The inference-based approach (IBA) is a cognitive account of the genesis and maintenance of obsessive-compulsive disorder (OCD). According to the IBA, individuals with OCD are prone to using inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Several studies have provided preliminary support for an association between features of the IBA and OCD symptoms. However, there are currently no studies that have investigated the proposed causal relationship of inverse reasoning in OCD. In a non-clinical sample (N = 187), we used an interpretive cognitive bias procedure to train a bias towards using inverse reasoning (n = 64), healthy sensory-based reasoning (n = 65), or a control condition (n = 58). Participants were randomly allocated to these training conditions. This manipulation allowed us to assess whether, consistent with the IBA, inverse reasoning training increased compulsive-like behaviours and self-reported OCD symptoms. Results indicated that compared to a control condition, participants trained in inverse reasoning reported more OCD symptoms and were more avoidant of potentially contaminated objects. Moreover, change in inverse reasoning bias was a small but significant mediator of the relationship between training condition and behavioural avoidance. Conversely, training in a healthy (non-inverse) reasoning style did not have any effect on symptoms or behaviour relative to the control condition. As this study was conducted in a non-clinical sample, we were unable to generalise our findings to a clinical population. Findings generally support the IBA model by providing preliminary evidence of a causal role for inverse reasoning in OCD. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-06-01

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

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions. PMID:29795827

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations.

PubMed

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-06-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions.

Testing day: The effects of processing bias induced by Navon stimuli on the strength of the Müller-Lyer illusion.

PubMed

Mundy, Matthew E

2014-01-01

Explanations for the cognitive basis of the Müller-Lyer illusion are still frustratingly mixed. To date, Day's (1989) theory of perceptual compromise has received little empirical attention. In this study, we examine the merit of Day's hypothesis for the Müller-Lyer illusion by biasing participants toward global or local visual processing through exposure to Navon (1977) stimuli, which are known to alter processing level preference for a short time. Participants (N = 306) were randomly allocated to global, local, or control conditions. Those in global or local conditions were exposed to Navon stimuli for 5 min and participants were required to report on the global or local stimulus features, respectively. Subsequently, participants completed a computerized Müller-Lyer experiment where they adjusted the length of a line to match an illusory-figure. The illusion was significantly stronger for participants with a global bias, and significantly weaker for those with a local bias, compared with the control condition. These findings provide empirical support for Day's "conflicting cues" theory of perceptual compromise in the Müller-Lyer illusion.

An alternative derivation of the stationary distribution of the multivariate neutral Wright-Fisher model for low mutation rates with a view to mutation rate estimation from site frequency data.

PubMed

Schrempf, Dominik; Hobolth, Asger

2017-04-01

Recently, Burden and Tang (2016) provided an analytical expression for the stationary distribution of the multivariate neutral Wright-Fisher model with low mutation rates. In this paper we present a simple, alternative derivation that illustrates the approximation. Our proof is based on the discrete multivariate boundary mutation model which has three key ingredients. First, the decoupled Moran model is used to describe genetic drift. Second, low mutation rates are assumed by limiting mutations to monomorphic states. Third, the mutation rate matrix is separated into a time-reversible part and a flux part, as suggested by Burden and Tang (2016). An application of our result to data from several great apes reveals that the assumption of stationarity may be inadequate or that other evolutionary forces like selection or biased gene conversion are acting. Furthermore we find that the model with a reversible mutation rate matrix provides a reasonably good fit to the data compared to the one with a non-reversible mutation rate matrix. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Impulsivity moderates the effect of approach bias modification on healthy food consumption.

PubMed

Kakoschke, Naomi; Kemps, Eva; Tiggemann, Marika

2017-10-01

The study aimed to modify approach bias for healthy and unhealthy food and to determine its effect on subsequent food consumption. In addition, we investigated the potential moderating role of impulsivity in the effect of approach bias re-training on food consumption. Participants were 200 undergraduate women (17-26 years) who were randomly allocated to one of five conditions of an approach-avoidance task varying in the training of an approach bias for healthy food, unhealthy food, and non-food cues in a single session of 10 min. Outcome variables were approach bias for healthy and unhealthy food and the proportion of healthy relative to unhealthy snack food consumed. As predicted, approach bias for healthy food significantly increased in the 'avoid unhealthy food/approach healthy food' condition. Importantly, the effect of training on snack consumption was moderated by trait impulsivity. Participants high in impulsivity consumed a greater proportion of healthy snack food following the 'avoid unhealthy food/approach healthy food' training. This finding supports the suggestion that automatic processing of appetitive cues has a greater influence on consumption behaviour in individuals with poor self-regulatory control. Copyright © 2017 Elsevier Ltd. All rights reserved.

Abstract analysis method facilitates filtering low-methodological quality and high-bias risk systematic reviews on psoriasis interventions.

PubMed

Gómez-García, Francisco; Ruano, Juan; Aguilar-Luque, Macarena; Alcalde-Mellado, Patricia; Gay-Mimbrera, Jesús; Hernández-Romero, José Luis; Sanz-Cabanillas, Juan Luis; Maestre-López, Beatriz; González-Padilla, Marcelino; Carmona-Fernández, Pedro J; García-Nieto, Antonio Vélez; Isla-Tejera, Beatriz

2017-12-29

Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone. Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company. This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score < 6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ≥ 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk. The methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.

Eye Movements while Reading Biased Homographs: Effects of Prior Encounter and Biasing Context on Reducing the Subordinate Bias Effect

PubMed Central

Leinenger, Mallorie; Rayner, Keith

2013-01-01

Readers experience processing difficulties when reading biased homographs preceded by subordinate-biasing contexts. Attempts to overcome this processing deficit have often failed to reduce the subordinate bias effect (SBE). In the present studies, we examined the processing of biased homographs preceded by single-sentence, subordinate-biasing contexts, and varied whether this preceding context contained a prior instance of the homograph or a control word/phrase. Having previously encountered the homograph earlier in the sentence reduced the SBE for the subsequent encounter, while simply instantiating the subordinate meaning produced processing difficulty. We compared these reductions in reading times to differences in processing time between dominant-biased repeated and non-repeated conditions in order to verify that the reductions observed in the subordinate cases did not simply reflect a general repetition benefit. Our results indicate that a strong, subordinate-biasing context can interact during lexical access to overcome the activation from meaning frequency and reduce the SBE during reading. PMID:24073328

A leftward bias however you look at it: Revisiting the emotional chimeric face task as a tool for measuring emotion lateralization.

PubMed

R Innes, Bobby; Burt, D Michael; Birch, Yan K; Hausmann, Markus

2015-12-28

Left hemiface biases observed within the Emotional Chimeric Face Task (ECFT) support emotional face perception models whereby all expressions are preferentially processed by the right hemisphere. However, previous research using this task has not considered that the visible midline between hemifaces might engage atypical facial emotion processing strategies in upright or inverted conditions, nor controlled for left visual field (thus right hemispheric) visuospatial attention biases. This study used novel emotional chimeric faces (blended at the midline) to examine laterality biases for all basic emotions. Left hemiface biases were demonstrated across all emotional expressions and were reduced, but not reversed, for inverted faces. The ECFT bias in upright faces was significantly increased in participants with a large attention bias. These results support the theory that left hemiface biases reflect a genuine bias in emotional face processing, and this bias can interact with attention processes similarly localized in the right hemisphere.

Effects of Bias Modification Training in Binge Eating Disorder.

PubMed

Schmitz, Florian; Svaldi, Jennifer

2017-09-01

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

A reply to Zigler and Seitz.

PubMed

Neman, R

1975-03-01

The Zigler and Seitz (1975) critique was carefully examined with respect to the conclusions of the Neman et al. (1975) study. Particular attention was given to the following questions: (a) did experimenter bias or commitment account for the results, (b) were unreliable and invalid psychometric instruments used, (c) were the statistical analyses insufficient or incorrect, (d) did the results reflect no more than the operation of chance, and (e) were the results biased by artifactually inflated profile scores. Experimenter bias and commitment were shown to be insufficient to account for the results; a further review of Buros (1972) showed that there was no need for apprehension about the testing instruments; the statistical analyses were shown to exceed prevailing standards for research reporting; the results were shown to reflect valid findings at the .05 probability level; and the Neman et al. (1975) results for the profile measure were equally significant using either "raw" neurological scores or "scales" neurological age scores. Zigler, Seitz, and I agreed on the needs for (a) using multivariate analyses, where applicable, in studies having more than one dependent variable; (b) defining the population for which sensorimotor training procedures may be appropriately prescribed; and (c) validating the profile measure as a tool to assess neurological disorganization.

Stimulus- and state-dependence of systematic bias in spatial attention: additive effects of stimulus-size and time-on-task.

PubMed

Benwell, Christopher S Y; Harvey, Monika; Gardner, Stephanie; Thut, Gregor

2013-03-01

Systematic biases in spatial attention are a common finding. In the general population, a systematic leftward bias is typically observed (pseudoneglect), possibly as a consequence of right hemisphere dominance for visuospatial attention. However, this leftward bias can cross-over to a systematic rightward bias with changes in stimulus and state factors (such as line length and arousal). The processes governing these changes are still unknown. Here we tested models of spatial attention as to their ability to account for these effects. To this end, we experimentally manipulated both stimulus and state factors, while healthy participants performed a computerized version of a landmark task. State was manipulated by time-on-task (>1 h) leading to increased fatigue and a reliable left- to rightward shift in spatial bias. Stimulus was manipulated by presenting either long or short lines which was associated with a shift of subjective midpoint from a reliable leftward bias for long to a more rightward bias for short lines. Importantly, we found time-on-task and line length effects to be additive suggesting a common denominator for line bisection across all conditions, which is in disagreement with models that assume that bisection decisions in long and short lines are governed by distinct processes (Magnitude estimation vs Global/local distinction). Our findings emphasize the dynamic rather than static nature of spatial biases in midline judgement. They are best captured by theories of spatial attention positing that spatial bias is flexibly modulated, and subject to inter-hemispheric balance which can change over time or conditions to accommodate task demands or reflect fatigue. Copyright © 2012 Elsevier Ltd. All rights reserved.

Don't look now! Oculomotor avoidance as a conditioned disgust response.

PubMed

Armstrong, Thomas; McClenahan, Laura; Kittle, Jody; Olatunji, Bunmi O

2014-02-01

Pavlovian conditioning paradigms have revealed fear learning tendencies that may be implicated in the etiology and maintenance of anxiety disorders. Given the prominence of disgust in certain anxiety disorders, it may be fruitful to study disgust learning in addition to fear learning. The present study utilized eye tracking to examine the effects of disgust conditioning on attentional bias, a phenomenon that characterizes anxiety disorders. Participants completed either a disgust condition, in which a face (conditioned stimulus; CS+) was paired with videos of individuals vomiting (unconditioned stimulus; US), or a negative condition in which a face was paired with videos of individuals being harmed in motor-vehicle accidents. Eye movements were used to measure attentional biases related to the USs and the CSs. In line with prior research, attentional avoidance was observed for the disgust CS+. However, this effect did not reach significance until after extinction and was linked to self-reported disgust postacquisition, yet decoupled from self-reported disgust postextinction. Attentional avoidance of the CS+ was not found in the negative condition, and postextinction differences in attentional bias for the CS+ between conditions were found to be mediated by differences in attentional bias for the US, as only the disgust US elicited attentional avoidance. Also, individual differences in disgust sensitivity were found to be associated with attentional avoidance of the disgust US, and this effect was mediated by self-reported disgust in response to the US. Further, disgust sensitivity was associated with attentional avoidance of the disgust CS+, and this effect was mediated by attentional avoidance of the disgust US. These findings provide new insight into a complex pattern of relations between disgust, evaluative learning, and attention that may have implications for the etiology and maintenance of certain anxiety disorders. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

NASA Astrophysics Data System (ADS)

Wilson, Brian Christopher David

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

The role of vision, speed, and attention in overcoming directional biases during arm movements.

PubMed

Dounskaia, Natalia; Goble, Jacob A

2011-03-01

Previous research has revealed directional biases (preferences to select movements in specific directions) during horizontal arm movements with the use of a free-stroke drawing task. The biases were interpreted as a result of a tendency to generate motion at either the shoulder or elbow (leading joint) and move the other (subordinate) joint predominantly passively to avoid neural effort for control of interaction torque. Here, we examined influence of vision, movement speed, and attention on the directional biases. Participants performed the free-stroke drawing task, producing center-out strokes in randomly selected directions. Movements were performed with and without vision and at comfortable and fast pace. A secondary, cognitive task was used to distract attention. Preferred directions remained the same in all conditions. Bias strength mildly increased without vision, especially during fast movements. Striking increases in bias strength were caused by the secondary task, pointing to additional cognitive load associated with selection of movements in the non-preferred directions. Further analyses demonstrated that the tendency to minimize active interference with interaction torque at the subordinate joint matched directional biases in all conditions. This match supports the explanation of directional biases as a result of a tendency to minimize neural effort for interaction torque control. The cognitive load may enhance this tendency in two ways, directly, by reducing neural capacity for interaction torque control, and indirectly, by decreasing capacity of working memory that stores visited directions. The obtained results suggest strong directional biases during daily activities because natural arm movements usually subserve cognitive tasks.

Conditional equivalence testing: An alternative remedy for publication bias

PubMed Central

Gustafson, Paul

2018-01-01

We introduce a publication policy that incorporates “conditional equivalence testing” (CET), a two-stage testing scheme in which standard NHST is followed conditionally by testing for equivalence. The idea of CET is carefully considered as it has the potential to address recent concerns about reproducibility and the limited publication of null results. In this paper we detail the implementation of CET, investigate similarities with a Bayesian testing scheme, and outline the basis for how a scientific journal could proceed to reduce publication bias while remaining relevant. PMID:29652891

A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

Immune to Situation: The Self-Serving Bias in Unambiguous Contexts

PubMed Central

Wang, Xiaoyan; Zheng, Li; Li, Lin; Zheng, Yijie; Sun, Peng; Zhou, Fanzhi A.; Guo, Xiuyan

2017-01-01

Traditionally, the self-serving bias has been investigated in ambiguous contexts in which participants work on tasks that measure novel abilities before making attributions without clear criteria for success or failure feedback. Prior studies have confirmed that the self-serving bias is pervasive in the general population, yet it varies significantly across situations involving ambiguous contexts. The present study features an unambiguous context encompassing interpersonal events that involved implicit causality (with the “self” as an actor or recipient), the inherent logic of which indicated attribution criteria. The aim of this study was to explore whether there is a self-serving bias in unambiguous contexts and to examine whether it is as sensitive to situation as it has been shown to be in ambiguous contexts. The results showed that, in an unambiguous context, participants exhibited self-serving bias in relation to attribution associated with negative interpersonal events. Additionally, the self-serving bias was greater in the actor condition relative to the recipient condition (Study 1), and this effect was not affected by the level of self-awareness, which was manipulated by the use or otherwise of a camera during the experiment (Study 2). Our findings provide evidence for the existence of the self-serving bias in unambiguous contexts. Moreover, the self-serving bias was shown to be immune to situation in unambiguous contexts, but it did depend on factors associated with the events per se, such as the actor versus recipient role that the self played in interpersonal events. PMID:28588532

Additive genetic variation and evolvability of a multivariate trait can be increased by epistatic gene action.

PubMed

Griswold, Cortland K

2015-12-21

Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

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.

Experimenter bias and subliminal perception

ERIC Educational Resources Information Center

Barber, Paul J.; Rushton, J. Philippe

1975-01-01

It has been suggested that subliminal perception phenomena may be in part due to experimenter bias effects. Two studies that obtained positive evidence of subliminal perception were therefore replicated with experimenters tested under blind and not blind conditions. (Editor)

Role of AlGaN/GaN interface traps on negative threshold voltage shift in AlGaN/GaN HEMT

NASA Astrophysics Data System (ADS)

Malik, Amit; Sharma, Chandan; Laishram, Robert; Bag, Rajesh Kumar; Rawal, Dipendra Singh; Vinayak, Seema; Sharma, Rajesh Kumar

2018-04-01

This article reports negative shift in the threshold-voltage in AlGaN/GaN high electron mobility transistor (HEMT) with application of reverse gate bias stress. The device is biased in strong pinch-off and low drain to source voltage condition for a fixed time duration (reverse gate bias stress), followed by measurement of transfer characteristics. Negative threshold voltage shift after application of reverse gate bias stress indicates the presence of more carriers in channel as compared to the unstressed condition. We propose the presence of AlGaN/GaN interface states to be the reason of negative threshold voltage shift, and developed a process to electrically characterize AlGaN/GaN interface states. We verified the results with Technology Computer Aided Design (TCAD) ATLAS simulation and got a good match with experimental measurements.

An experimental verification of laser-velocimeter sampling bias and its correction

NASA Technical Reports Server (NTRS)

Johnson, D. A.; Modarress, D.; Owen, F. K.

1982-01-01

The existence of 'sampling bias' in individual-realization laser velocimeter measurements is experimentally verified and shown to be independent of sample rate. The experiments were performed in a simple two-stream mixing shear flow with the standard for comparison being laser-velocimeter results obtained under continuous-wave conditions. It is also demonstrated that the errors resulting from sampling bias can be removed by a proper interpretation of the sampling statistics. In addition, data obtained in a shock-induced separated flow and in the near-wake of airfoils are presented, both bias-corrected and uncorrected, to illustrate the effects of sampling bias in the extreme.

Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks

PubMed Central

Besada, Juan A.

2017-01-01

In this paper, a complete and rigorous mathematical model for secondary surveillance radar systematic errors (biases) is developed. The model takes into account the physical effects systematically affecting the measurement processes. The azimuth biases are calculated from the physical error of the antenna calibration and the errors of the angle determination dispositive. Distance bias is calculated from the delay of the signal produced by the refractivity index of the atmosphere, and from clock errors, while the altitude bias is calculated taking into account the atmosphere conditions (pressure and temperature). It will be shown, using simulated and real data, that adapting a classical bias estimation process to use the complete parametrized model results in improved accuracy in the bias estimation. PMID:28934157

Adaptive Variable Bias Magnetic Bearing Control

NASA Technical Reports Server (NTRS)

Johnson, Dexter; Brown, Gerald V.; Inman, Daniel J.

1998-01-01

Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.

Analysis of TID process, geometry, and bias condition dependence in 14-nm FinFETs and implications for RF and SRAM performance

DOE PAGES

King, M. P.; Wu, X.; Eller, Manfred; ...

2016-12-07

Here, total ionizing dose results are provided, showing the effects of different threshold adjust implant processes and irradiation bias conditions of 14-nm FinFETs. Minimal radiation-induced threshold voltage shift across a variety of transistor types is observed. Off-state leakage current of nMOSFET transistors exhibits a strong gate bias dependence, indicating electrostatic gate control of the sub-fin region and the corresponding parasitic conduction path are the largest concern for radiation hardness in FinFET technology. The high-Vth transistors exhibit the best irradiation performance across all bias conditions, showing a reasonably small change in off-state leakage current and Vth, while the low-Vth transistors exhibitmore » a larger change in off-state leakage current. The “worst-case” bias condition during irradiation for both pull-down and pass-gate nMOSFETs in static random access memory is determined to be the on-state (Vgs = Vdd). We find the nMOSFET pull-down and pass-gate transistors of the SRAM bit-cell show less radiation-induced degradation due to transistor geometry and channel doping differences than the low-Vth transistor. Near-threshold operation is presented as a methodology for reducing radiation-induced increases in off-state device leakage current. In a 14-nm FinFET technology, the modeling indicates devices with high channel stop doping show the most robust response to TID allowing stable operation of ring oscillators and the SRAM bit-cell with minimal shift in critical operating characteristics.« less

Analysis of TID process, geometry, and bias condition dependence in 14-nm FinFETs and implications for RF and SRAM performance

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

King, M. P.; Wu, X.; Eller, Manfred

Here, total ionizing dose results are provided, showing the effects of different threshold adjust implant processes and irradiation bias conditions of 14-nm FinFETs. Minimal radiation-induced threshold voltage shift across a variety of transistor types is observed. Off-state leakage current of nMOSFET transistors exhibits a strong gate bias dependence, indicating electrostatic gate control of the sub-fin region and the corresponding parasitic conduction path are the largest concern for radiation hardness in FinFET technology. The high-Vth transistors exhibit the best irradiation performance across all bias conditions, showing a reasonably small change in off-state leakage current and Vth, while the low-Vth transistors exhibitmore » a larger change in off-state leakage current. The “worst-case” bias condition during irradiation for both pull-down and pass-gate nMOSFETs in static random access memory is determined to be the on-state (Vgs = Vdd). We find the nMOSFET pull-down and pass-gate transistors of the SRAM bit-cell show less radiation-induced degradation due to transistor geometry and channel doping differences than the low-Vth transistor. Near-threshold operation is presented as a methodology for reducing radiation-induced increases in off-state device leakage current. In a 14-nm FinFET technology, the modeling indicates devices with high channel stop doping show the most robust response to TID allowing stable operation of ring oscillators and the SRAM bit-cell with minimal shift in critical operating characteristics.« less

Attentional bias to threat in the general population is contingent on target competition, not on attentional control settings.

PubMed

Wirth, Benedikt Emanuel; Wentura, Dirk

2018-04-01

Dot-probe studies usually find an attentional bias towards threatening stimuli only in anxious participants. Here, we investigated under what conditions such a bias occurs in unselected samples. According to contingent-capture theory, an irrelevant cue only captures attention if it matches an attentional control setting. Therefore, we first tested the hypothesis that an attentional control setting tuned to threat must be activated in (non-anxious) individuals. In Experiment 1, we used a dot-probe task with a manipulation of attentional control settings ('threat' - set vs. control set). Surprisingly, we found an (anxiety-independent) attentional bias to angry faces that was not moderated by attentional control settings. Since we presented two stimuli (i.e., a target and a distractor) on the target screen in Experiment 1 (a necessity to realise the test of contingent capture), but most dot-probe studies only employ a single target, we conducted Experiment 2 to test the hypothesis that attentional bias in the general population is contingent on target competition. Participants performed a dot-probe task, involving presentation of a stand-alone target or a target competing with a distractor. We found an (anxiety-independent) attentional bias towards angry faces in the latter but not the former condition. This suggests that attentional bias towards angry faces in unselected samples is not contingent on attentional control settings but on target competition.

COMT Val(108/158)Met polymorphism effects on emotional brain function and negativity bias.

PubMed

Williams, Leanne M; Gatt, Justine M; Grieve, Stuart M; Dobson-Stone, Carol; Paul, Robert H; Gordon, Evian; Schofield, Peter R

2010-11-15

Biases toward processing negative versus positive information vary as a function of level of awareness, and are modulated by monoamines. Excessive biases are associated with individual differences in mood and emotional stability, and emotional disorder. Here, we examined the impact of the catechol-O-methyltransferase (COMT) Val(108/158)Met polymorphism, involved in dopamine and norepinephrine catabolism, on both emotional brain function and self-reported negativity bias. COMT genotyping and self-reported level of negativity bias were completed for 46 healthy participants taking part in the Brain Resource International Database. Functional MRI was undertaken during perception of facial expressions of fear and happiness presented under unmasked (consciously identified) and masked (to prevent conscious detection) conditions. Structural MR images were also acquired. A greater number of COMT Met alleles predicted increased activation in brainstem, amygdala, basal ganglia and medial prefrontal regions for conscious fear, but decreased activation for conscious happiness. This pattern was also apparent for brainstem activation for the masked condition. Effects were most apparent for females. These differences could not be explained by gray matter variations. The Met-related profile of activation, particularly prefrontally, predicted greater negativity bias associated with risk for emotional disorder. The findings suggest that the COMT Met allele modulates neural substrates of negative versus positive emotion processing. This effect may contribute to negativity biases, which confer susceptibility for emotional disorders. Copyright 2010 Elsevier Inc. All rights reserved.

Mindfulness reduces the correspondence bias.

PubMed

Hopthrow, Tim; Hooper, Nic; Mahmood, Lynsey; Meier, Brian P; Weger, Ulrich

2017-03-01

The correspondence bias (CB) refers to the idea that people sometimes give undue weight to dispositional rather than situational factors when explaining behaviours and attitudes. Three experiments examined whether mindfulness, a non-judgmental focus on the present moment, could reduce the CB. Participants engaged in a brief mindfulness exercise (the raisin task), a control task, or an attention to detail task before completing a typical CB measure involving an attitude-attribution paradigm. The results indicated that participants in the mindfulness condition experienced a significant reduction in the CB compared to participants in the control or attention to detail conditions. These results suggest that mindfulness training can play a unique role in reducing social biases related to person perception.

Flat-roof phenomenon of dynamic equilibrium phase in the negative bias temperature instability effect on a power MOSFET

NASA Astrophysics Data System (ADS)

Zhang, Yue; Zhuo, Qing-Qing; Liu, Hong-Xia; Ma, Xiao-Hua; Hao, Yue

2014-05-01

The effect of the static negative bias temperature (NBT) stress on a p-channel power metal—oxide—semiconductor field-effect transistor (MOSFET) is investigated by experiment and simulation. The time evolution of the negative bias temperature instability (NBTI) degradation has the trend predicted by the reaction—diffusion (R—D) model but with an exaggerated time scale. The phenomena of the flat-roof section are observed under various stress conditions, which can be considered as the dynamic equilibrium phase in the R—D process. Based on the simulated results, the variation of the flat-roof section with the stress condition can be explained.

Bias polarization study of steam electrolysis by composite oxygen electrode Ba0.5Sr0.5Co0.8Fe0.2O3-δ/BaCe0.4Zr0.4Y0.2O3-δ

NASA Astrophysics Data System (ADS)

Yang, Tao; Shaula, Aliaksandr; Pukazhselvan, D.; Ramasamy, Devaraj; Deng, Jiguang; da Silva, E. L.; Duarte, Ricardo; Saraiva, Jorge A.

2017-12-01

The polarization behavior of Ba0.5Sr0.5Co0.8Fe0.2O3-δ-BaCe0.4Zr0.4Y0.2O3-δ (BSCF-BCZY) electrode under steam electrolysis conditions was studied in detail. The composite oxygen electrode supported by BCZY electrolyzer has been assessed as a function of temperature (T), water vapor partial pressures (pH2O), and bias polarization voltage for electrodes of comparable microstructure. The Electrochemical impedance spectra show two depressed arcs in general without bias polarization. And the electrode resistance became smaller with the increase of the bias polarization under the same water vapor partial pressures. The total resistance of the electrode was shown to be significantly affected by temperature, with the same level of pH2O and bias polarization voltage. This result highlights BSCF-BCZY as an effective oxygen electrode under moderate polarization and pH2O conditions.

Do two and three year old children use an incremental first-NP-as-agent bias to process active transitive and passive sentences?: A permutation analysis

PubMed Central

Chang, Franklin; Rowland, Caroline; Ferguson, Heather; Pine, Julian

2017-01-01

We used eye-tracking to investigate if and when children show an incremental bias to assume that the first noun phrase in a sentence is the agent (first-NP-as-agent bias) while processing the meaning of English active and passive transitive sentences. We also investigated whether children can override this bias to successfully distinguish active from passive sentences, after processing the remainder of the sentence frame. For this second question we used eye-tracking (Study 1) and forced-choice pointing (Study 2). For both studies, we used a paradigm in which participants simultaneously saw two novel actions with reversed agent-patient relations while listening to active and passive sentences. We compared English-speaking 25-month-olds and 41-month-olds in between-subjects sentence structure conditions (Active Transitive Condition vs. Passive Condition). A permutation analysis found that both age groups showed a bias to incrementally map the first noun in a sentence onto an agent role. Regarding the second question, 25-month-olds showed some evidence of distinguishing the two structures in the eye-tracking study. However, the 25-month-olds did not distinguish active from passive sentences in the forced choice pointing task. In contrast, the 41-month-old children did reanalyse their initial first-NP-as-agent bias to the extent that they clearly distinguished between active and passive sentences both in the eye-tracking data and in the pointing task. The results are discussed in relation to the development of syntactic (re)parsing. PMID:29049390

Working memory and the memory distortion component of hindsight bias.

PubMed

Calvillo, Dustin P

2012-01-01

One component of hindsight bias is memory distortion: Individuals' recollections of their predictions are biased towards known outcomes. The present study examined the role of working memory in the memory distortion component of hindsight bias. Participants answered almanac-like questions, completed a measure of working memory capacity, were provided with the correct answers, and attempted to recollect their original judgements in two conditions: with and without a concurrent working memory load. Participants' recalled judgements were more biased by feedback when they recalled these judgements with a concurrent memory load and working memory capacity was negatively correlated with memory distortion. These findings are consistent with reconstruction accounts of the memory distortion component of hindsight bias and, more generally, with dual process theories of cognition. These results also relate the memory distortion component of hindsight bias with other cognitive errors, such as source monitoring errors, the belief bias in syllogistic reasoning and anchoring effects. Implications for the separate components view of hindsight bias are discussed.

High-Resolution Near Real-Time Drought Monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

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

NASA Astrophysics Data System (ADS)

Esguerra, Jose Perico; Reyes, Jelian

2017-08-01

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

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

PubMed

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

2018-06-03

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

Selection bias in rheumatic disease research.

PubMed

Choi, Hyon K; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing

2014-07-01

The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias--a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic--in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the 'risk factor paradox'--a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research.

Gender differences in leadership amongst first-year medical students in the small-group setting.

PubMed

Wayne, Nancy L; Vermillion, Michelle; Uijtdehaage, Sebastian

2010-08-01

To investigate the extent of gender bias in the volunteerism of small-group leaders amongst first-year medical students, and whether bias could be eliminated with special instructions to the students. The gender of leaders in small-group sessions in a real academic setting was monitored under two conditions: control conditions, in which basic instructions were provided to participants, and intervention conditions, in which the same basic instructions were provided plus a brief "pep talk" on the importance of experiencing a leadership role in a safe environment. During the small-group sessions, an observer noted the gender and names of group leaders for later analysis. After a class debriefing, a subset of leaders and nonleaders from both the control and intervention groups were invited to be interviewed about their perceptions of the small-group experience. Interviews were tape recorded and transcribed for analysis. In 2007-2008 and 2008-2009, disproportionately fewer women than men volunteered to become small-group leaders under control conditions. This gender bias was eliminated under intervention conditions. The interviews illustrated how a subtle change in instructions helped some female students take on a leadership role. Gender bias in leadership in the small-group setting amongst medical students-even when women make up half of the class-may persist without targeted intervention. The authors suggest that frequent and consistent intervention during medical school could be an important factor in encouraging women to identify themselves as leaders, promoting confidence to consider leadership roles in medicine.

Inter-Annual Variability of Fledgling Sex Ratio in King Penguins.

PubMed

Bordier, Célia; Saraux, Claire; Viblanc, Vincent A; Gachot-Neveu, Hélène; Beaugey, Magali; Le Maho, Yvon; Le Bohec, Céline

2014-01-01

As the number of breeding pairs depends on the adult sex ratio in a monogamous species with biparental care, investigating sex-ratio variability in natural populations is essential to understand population dynamics. Using 10 years of data (2000-2009) in a seasonally monogamous seabird, the king penguin (Aptenodytes patagonicus), we investigated the annual sex ratio at fledging, and the potential environmental causes for its variation. Over more than 4000 birds, the annual sex ratio at fledging was highly variable (ranging from 44.4% to 58.3% of males), and on average slightly biased towards males (51.6%). Yearly variation in sex-ratio bias was neither related to density within the colony, nor to global or local oceanographic conditions known to affect both the productivity and accessibility of penguin foraging areas. However, rising sea surface temperature coincided with an increase in fledging sex-ratio variability. Fledging sex ratio was also correlated with difference in body condition between male and female fledglings. When more males were produced in a given year, their body condition was higher (and reciprocally), suggesting that parents might adopt a sex-biased allocation strategy depending on yearly environmental conditions and/or that the effect of environmental parameters on chick condition and survival may be sex-dependent. The initial bias in sex ratio observed at the juvenile stage tended to return to 1∶1 equilibrium upon first breeding attempts, as would be expected from Fisher's classic theory of offspring sex-ratio variation.

Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

PubMed

Lie, Octavian V; van Mierlo, Pieter

2017-01-01

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (<60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling

NASA Astrophysics Data System (ADS)

Yu, Liuqian; Fennel, Katja; Bertino, Laurent; Gharamti, Mohamad El; Thompson, Keith R.

2018-06-01

Effective data assimilation methods for incorporating observations into marine biogeochemical models are required to improve hindcasts, nowcasts and forecasts of the ocean's biogeochemical state. Recent assimilation efforts have shown that updating model physics alone can degrade biogeochemical fields while only updating biogeochemical variables may not improve a model's predictive skill when the physical fields are inaccurate. Here we systematically investigate whether multivariate updates of physical and biogeochemical model states are superior to only updating either physical or biogeochemical variables. We conducted a series of twin experiments in an idealized ocean channel that experiences wind-driven upwelling. The forecast model was forced with biased wind stress and perturbed biogeochemical model parameters compared to the model run representing the "truth". Taking advantage of the multivariate nature of the deterministic Ensemble Kalman Filter (DEnKF), we assimilated different combinations of synthetic physical (sea surface height, sea surface temperature and temperature profiles) and biogeochemical (surface chlorophyll and nitrate profiles) observations. We show that when biogeochemical and physical properties are highly correlated (e.g., thermocline and nutricline), multivariate updates of both are essential for improving model skill and can be accomplished by assimilating either physical (e.g., temperature profiles) or biogeochemical (e.g., nutrient profiles) observations. In our idealized domain, the improvement is largely due to a better representation of nutrient upwelling, which results in a more accurate nutrient input into the euphotic zone. In contrast, assimilating surface chlorophyll improves the model state only slightly, because surface chlorophyll contains little information about the vertical density structure. We also show that a degradation of the correlation between observed subsurface temperature and nutrient fields, which has been an issue in several previous assimilation studies, can be reduced by multivariate updates of physical and biogeochemical fields.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-01-20

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-02-01

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement.

PubMed

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-02-01

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. A complete checklist is available at http://www.tripod-statement.org. © 2015 American College of Physicians.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-06

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD)

PubMed Central

Reitsma, Johannes B.; Altman, Douglas G.; Moons, Karel G.M.

2015-01-01

Background— Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. Methods— The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. Results— The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. Conclusions— To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). PMID:25561516

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement

PubMed Central

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-01-01

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). PMID:25562432

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, G S; Reitsma, J B; Altman, D G; Moons, K G M

2015-02-01

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 Royal College of Obstetricians and Gynaecologists.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-13

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). © 2015 The Authors.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-01-06

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-02-01

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). Copyright © 2015 Elsevier Inc. All rights reserved.

Estimators for longitudinal latent exposure models: examining measurement model assumptions.

PubMed

Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D

2017-06-15

Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Second-order standard addition for deconvolution and quantification of fatty acids of fish oil using GC-MS.

PubMed

Vosough, Maryam; Salemi, Amir

2007-08-15

In the present work two second-order calibration methods, generalized rank annihilation method (GRAM) and multivariate curve resolution-alternating least square (MCR-ALS) have been applied on standard addition data matrices obtained by gas chromatography-mass spectrometry (GC-MS) to characterize and quantify four unsaturated fatty acids cis-9-hexadecenoic acid (C16:1omega7c), cis-9-octadecenoic acid (C18:1omega9c), cis-11-eicosenoic acid (C20:1omega9) and cis-13-docosenoic acid (C22:1omega9) in fish oil considering matrix interferences. With these methods, the area does not need to be directly measured and predictions are more accurate. Because of non-trilinear conditions of GC-MS data matrices, at first MCR-ALS and GRAM have been used on uncorrected data matrices. In comparison to MCR-ALS, biased and imprecise concentrations (%R.S.D.=27.3) were obtained using GRAM without correcting the retention time-shift. As trilinearity is the essential requirement for implementing GRAM, the data need to be corrected. Multivariate rank alignment objectively corrects the run-to-run retention time variations between sample GC-MS data matrix and a standard addition GC-MS data matrix. Then, two second-order algorithms have been compared with each other. The above algorithms provided similar mean predictions, pure concentrations and spectral profiles. The results validated using standard mass spectra of target compounds. In addition, some of the quantification results were compared with the concentration values obtained using the selected mass chromatograms. As in the case of strong peak-overlap and the matrix effect, the classical univariate method of determination of the area of the peaks of the analytes will fail, the "second-order advantage" has solved this problem successfully.

Depression in primary TKA and higher medical comorbidities in revision TKA are associated with suboptimal subjective improvement in knee function.

PubMed

Singh, Jasvinder A; Lewallen, David G

2014-04-11

To characterize whether medical comorbidities, depression and anxiety predict patient-reported functional improvement after total knee arthroplasty (TKA). We analyzed the prospectively collected data from the Mayo Clinic Total Joint Registry for patients who underwent primary or revision TKA between 1993-2005. Using multivariable-adjusted logistic regression analyses, we examined whether medical comorbidities, depression and anxiety were associated with patient-reported subjective improvement in knee function 2- or 5-years after primary or revision TKA. Odds ratios (OR), along with 95% confidence intervals (CI) and p-value are presented. We studied 7,139 primary TKAs at 2- and 4,234 at 5-years; and, 1,533 revision TKAs at 2-years and 881 at 5-years. In multivariable-adjusted analyses, we found that depression was associated with significantly lower odds of 0.5 (95% confidence interval [CI]: 0.3 to 0.9; p = 0.02) of 'much better' knee functional status (relative to same or worse status) 2 years after primary TKA. Higher Deyo-Charlson index was significantly associated with lower odds of 0.5 (95% CI: 0.2 to 1.0; p = 0.05) of 'much better' knee functional status after revision TKA for every 5-point increase in score. Depression in primary TKA and higher medical comorbidity in revision TKA cohorts were associated with suboptimal improvement in index knee function. It remains to be seen whether strategies focused at optimization of medical comorbidities and depression pre- and peri-operatively may help to improve TKA outcomes. Study limitations include non-response bias and the use of diagnostic codes, which may be associated with under-diagnosis of conditions.

2D Vertical Heterostructures for Novel Tunneling Device Applications

DTIC Science & Technology

2017-03-01

controlled by a combination of the drain-source voltage bias (VDS) and the top and bottom gate biases (VTG and VBG, respectively). The drain-source...properties that can potentially overcome some of the limitations of epitaxial 3D semiconductor heterostructures. Simulations of 2D...interlayer barrier, such as h-BN, a high-k dielectric material, or a van der Waal gap. Under appropriate bias conditions, charge carriers can tunnel

Mood & alcohol-related attentional biases: New considerations for gender differences and reliability of the visual-probe task.

PubMed

Emery, Noah N; Simons, Jeffrey S

2015-11-01

Alcohol-related attentional biases are positively associated with drinking history and may represent a mechanism by which alcohol use behavior is maintained over time. This study was designed to address two unresolved issues regarding alcohol-related attention biases. Specifically, this study tested whether acute changes in positive and negative mood increase attentional biases toward alcohol cues and whether coping and enhancement drinking motives moderate these effects. Participants were 100 college students aged 18-25, who drank alcohol at least once in the last 90 days. In a 2 × 3 mixed design, participants were randomized to one of three mood conditions (neutral, negative, or positive) and completed visual-probe tasks pre- and post-mood-induction. Attentional biases toward alcohol cues were significantly associated with alcohol consumption among men, but not women. Although the mood manipulation was highly successful, attentional biases did not vary as a function of mood condition and hypothesized moderating effects of drinking motives were not significant. The largely null findings of the experiment are discussed in light of the fact that the visual probe task had poor reliability. Issues related to the reliability of visual-probe task are discussed, as more research is needed to evaluate and improve the psychometrics of this method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biases in comparative analyses of extinction risk: mind the gap.

PubMed

González-Suárez, Manuela; Lucas, Pablo M; Revilla, Eloy

2012-11-01

1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species' traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species' traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14-99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.

Surveying the hidden attitudes of hospital nurses' towards poverty.

PubMed

Wittenauer, James; Ludwick, Ruth; Baughman, Kristin; Fishbein, Rebecca

2015-08-01

To explore the attitudes held by registered nurses about persons living in poverty. As a profession, nursing has strong commitment to advocating for the socioeconomically disadvantaged. The links among poverty and health disparities are well established and research demonstrates that attitudes of providers can influence how those in poverty use health services. Although nurses are the largest sector of healthcare providers globally, little research has been published on their attitudes towards patients they care for who live in poverty. Cross-sectional survey. Used a convenience sample of 117 registered nurses who completed the Attitudes Towards Poverty Short Form that contained three subscales. Regression analysis was used to examine the associations between the nurses' age, education, and years of experience, political views and financial security with their total score and subscale scores. Nurses were more likely to agree with stigmatising statements than statements that attributed poverty to personal deficiency or structural factors. In the multivariate analysis, years of experience were associated with more positive attitudes towards those living in poverty. Nurses with the most experience had less stigmatising beliefs about poverty and were more likely to endorse structural explanations. Those with a baccalaureate education were also more likely to endorse structural explanations for poverty. Gaining knowledge about attitudes towards and the factors influencing those attitudes, for example, education, are important in helping combat the disparities associated with poverty. Nurses have a duty to evaluate their individual attitudes and biases towards those living in poverty and how those attitudes and biases may influence daily practice. Assessing nurses' attitudes towards poverty may aid in better means of empowering nurses to seek solutions that will improve health conditions for those living in poverty. © 2015 John Wiley & Sons Ltd.

Potential bias in the bank: what distinguishes refusers, nonresponders and participants in a clinic-based biobank?

PubMed

Ridgeway, J L; Han, L C; Olson, J E; Lackore, K A; Koenig, B A; Beebe, T J; Ziegenfuss, J Y

2013-01-01

Biobanks are an important resource for genetic and epidemiologic research, but bias may be introduced if those who accept the recruitment invitation differ systematically from those who do not in terms of attributes important to health-related investigations. To understand potential bias in a clinic-based biobank of biological samples, including genetic data linked to electronic health record information, we compared patient characteristics and self-reported information among participants, nonresponders and refusers. We also compared reasons for nonparticipation between refusers and nonresponders to elucidate potential pathways to reduce nonparticipation and any uncovered bias. We mailed recruitment packets to 1,600 adult patients with upcoming appointments at Mayo Clinic (Rochester, Minn., USA) and recorded their participation status. Administrative data were used to compare characteristics across groups. We used phone interviews with 26 nonresponders and 26 refusers to collect self-reported information, including reasons for nonparticipation. Participants were asked to complete a mailed questionnaire. We achieved 26.2% participation (n=419) with 12.1% refusing (n=193) and 61.8% nonresponse (n=988). In multivariate analyses, sex, age, region of residence, and race/ethnicity were significantly associated with participation. The groups differed in information-seeking behaviors and research experience. Refusers more often cited privacy concerns, while nonresponders more often identified time constraints as the reason for nonparticipation. For genomic medicine to advance, large, representative biobanks are required. Significant associations between patient characteristics and nonresponse, as well as systematic differences between refusers and nonresponders, could introduce bias. Oversampling or recruitment changes, including heightened attention to privacy protection and participation burden, may be necessary to increase participation among less-represented groups. Copyright © 2013 S. Karger AG, Basel.

Potential Bias in the Bank: What Distinguishes Refusers, Non-responders and Participants in a Clinic-based Biobank?

PubMed Central

Ridgeway, Jennifer L; Han, Leona C; Olson, Janet E; Lackore, Kandace A; Koenig, Barbara A; Beebe, Timothy J; Ziegenfuss, Jeanette Y

2013-01-01

Background Biobanks are an important resource for genetic and epidemiologic research, but bias may be introduced if those who accept the recruitment invitation differ systematically from those who do not in attributes important to health-related investigations. To understand potential bias in a clinic-based biobank of biological samples, including genetic data linked to Electronic Medical Record information, we compared patient characteristics and self-reported information among participants, non-responders, and refusers. We also compared reasons for non-participation between refusers and non-responders to elucidate potential pathways to reduce non-participation and any uncovered bias. Methods We mailed recruitment packets to 1600 adult patients with upcoming appointments at Mayo Clinic (Rochester, MN) and recorded their participation status. Administrative data were used to compare characteristics across groups. We used phone interviews with 26 non-responders and 26 refusers to collect self-reported information, including reasons for non-participation. Participants were asked to complete a mailed questionnaire. Results We achieved 26.2% participation (n=419) with 12.1% refusing (n=193) and 61.8% non-response (n=988). In multivariate analyses, sex, age, region of residence, and race/ethnicity were significantly associated with participation. The groups differed in information-seeking behaviors and research experience. Refusers more often cited privacy concerns while non-responders more often identified time constraints as the reason for non-participation. Conclusion For genomic medicine to advance, large, representative biobanks are required. Significant associations between patient characteristics and nonresponse, as well as systematic differences between refusers and nonresponders, could introduce bias. Oversampling or recruitment changes, including heightened attention to privacy protection and participation burden, may be necessary to increase participation among less-represented groups. PMID:23595106

Impact of bias-corrected reanalysis-derived lateral boundary conditions on WRF simulations

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro Benson; Sharma, Ashish; Evans, Jason Peter; Mehrotra, Rajeshwar; Rocheta, Eytan

2017-08-01

Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis data sets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational data sets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias-corrected WRF simulations are, however, found to be marginally better than mean only bias-corrected WRF simulations and raw ERA-I reanalysis-driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.

Affective Biases in Humans and Animals.

PubMed

Robinson, E S J; Roiser, J P

Depression is one of the most common but poorly understood psychiatric conditions. Although drug treatments and psychological therapies are effective in some patients, many do not achieve full remission and some patients receive no apparent benefit. Developing new improved treatments requires a better understanding of the aetiology of symptoms and evaluation of novel therapeutic targets in pre-clinical studies. Recent developments in our understanding of the basic cognitive processes that may contribute to the development of depression and its treatment offer new opportunities for both clinical and pre-clinical research. This chapter discusses the clinical evidence supporting a cognitive neuropsychological model of depression and antidepressant efficacy, and how this information may be usefully translated to pre-clinical investigation. Studies using neuropsychological tests in depressed patients and at risk populations have revealed basic negative emotional biases and disrupted reward and punishment processing, which may also impact on non-affective cognition. These affective biases are sensitive to antidepressant treatments with early onset effects observed, suggesting an important role in recovery. This clinical work into affective biases has also facilitated back-translation to animals and the development of assays to study affective biases in rodents. These animal studies suggest that, similar to humans, rodents in putative negative affective states exhibit negative affective biases on decision-making and memory tasks. Antidepressant treatments also induce positive biases in these rodent tasks, supporting the translational validity of this approach. Although still in the early stages of development and validation, affective biases in depression have the potential to offer new insights into the clinical condition, as well as facilitating the development of more translational approaches for pre-clinical studies.

Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement.

PubMed

Collins, Gary S; Reitsma, Johannes B; Altman, Douglas G; Moons, Karel G M

2015-06-01

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org). The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

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

PubMed

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

2011-01-01

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

Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

NASA Astrophysics Data System (ADS)

Eum, H. I.; Cannon, A. J.

2015-12-01

Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the ranking of this study may be changed when various GCMs are downscaled and evaluated. Nevertheless, it may be informative for end-users (i.e. modelers or water resources managers) to understand and select more suitable downscaling methods corresponding to priorities on regional applications.

The unique contribution of manual chest compression-vibrations to airflow during physiotherapy in sedated, fully ventilated children.

PubMed

Gregson, Rachael K; Shannon, Harriet; Stocks, Janet; Cole, Tim J; Peters, Mark J; Main, Eleanor

2012-03-01

This study aimed to quantify the specific effects of manual lung inflations with chest compression-vibrations, commonly used to assist airway clearance in ventilated patients. The hypothesis was that force applied during the compressions made a significant additional contribution to increases in peak expiratory flow and expiratory to inspiratory flow ratio over and above that resulting from accompanying increases in inflation volume. Prospective observational study. Cardiac and general pediatric intensive care. Sedated, fully ventilated children. Customized force-sensing mats and a commercial respiratory monitor recorded force and respiration during physiotherapy. Percentage changes in peak expiratory flow, peak expiratory to inspiratory flow ratios, inflation volume, and peak inflation pressure between baseline and manual inflations with and without compression-vibrations were calculated. Analysis of covariance determined the relative contribution of changes in pressure, volume, and force to influence changes in peak expiratory flow and peak expiratory to inspiratory flow ratio. Data from 105 children were analyzed (median age, 1.3 yrs; range, 1 wk to 15.9 yrs). Force during compressions ranged from 15 to 179 N (median, 46 N). Peak expiratory flow increased on average by 76% during compressions compared with baseline ventilation. Increases in peak expiratory flow were significantly related to increases in inflation volume, peak inflation pressure, and force with peak expiratory flow increasing by, on average, 4% for every 10% increase in inflation volume (p < .001), 5% for every 10% increase in peak inflation pressure (p = .005), and 3% for each 10 N of applied force (p < .001). By contrast, increase in peak expiratory to inspiratory flow ratio was only related to applied force with a 4% increase for each 10 N of force (p < .001). These results provide evidence of the unique contribution of compression forces in increasing peak expiratory flow and peak expiratory to inspiratory flow ratio bias over and above that related to accompanying changes from manual hyperinflations. Force generated during compression-vibrations was the single significant factor in multivariable analysis to explain the increases in expiratory flow bias. Such increases in the expiratory bias provide theoretically optimal physiological conditions for cephalad mucus movement in fully ventilated children.

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

PubMed

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

2013-09-01

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

Selection bias in rheumatic disease research

PubMed Central

Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing

2014-01-01

The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic—in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the ‘risk factor paradox’—a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research. PMID:24686510

Biases in Long-term NO2 Averages Inferred from Satellite Observations Due to Cloud Selection Criteria

NASA Technical Reports Server (NTRS)

Geddes, Jeffrey A.; Murphy, Jennifer G.; O'Brien, Jason M.; Celarier, Edward A.

2012-01-01

Retrievals of atmospheric trace gas column densities from space are compromised by the presence of clouds, requiring most studies to exclude observations with significant cloud fractions in the instrument's field of view. Using NO2 observations at three ground stations representing urban, suburban, and rural environments, and tropospheric vertical column densities measured by the Ozone Monitoring Instrument (OMI) over each site, we show that the observations from space represent monthly averaged ground-level pollutant conditions well (R=0.86) under relatively cloud-free conditions. However, by analyzing the ground-level data and applying the OMI cloud fraction as a filter, we show there is a significant bias in long-term averaged NO2 as a result of removing the data during cloudy conditions. For the ground-based sites considered in this study, excluding observations on days when OMI-derived cloud fractions were greater than 0.2 causes 12:00-14:00 mean summer mixing ratios to be underestimated by 12%+/-6%, 20%+/-7%, and 40%+/-10% on average (+/-1 standard deviation) at the urban, suburban, and rural sites respectively. This bias was investigated in particular at the rural site, a region where pollutant transport is the main source of NO2, and where longterm observations of NOy were also available. Evidence of changing photochemical conditions and a correlation between clear skies and the transport of cleaner air masses play key roles in explaining the bias. The magnitude of a bias is expected to vary from site to site depending on meteorology and proximity to NOx sources, and decreases when longer averaging times of ground station data (e.g. 24-h) are used for the comparison.

Look for good and never give up: A novel attention training treatment for childhood anxiety disorders.

PubMed

Waters, Allison M; Zimmer-Gembeck, Melanie J; Craske, Michelle G; Pine, Daniel S; Bradley, Brendan P; Mogg, Karin

2015-10-01

Attention bias modification training (ABMT) is a promising treatment for anxiety disorders. Recent evidence suggests that attention training towards positive stimuli, using visual-search based ABMT, has beneficial effects on anxiety and attention biases in children. The present study extends this prior research using distinctive techniques designed to increase participant learning, memory consolidation, and treatment engagement. Fifty-nine clinically anxious children were randomly assigned to the active treatment condition (ATC) (N = 31) or waitlist control condition (WLC) (N = 28). In the ATC, children completed 12 treatment sessions at home on computer in which they searched matrices for a pleasant or calm target amongst unpleasant background pictures, while also engaging in techniques designed to consolidate learning and memory for these search strategies. No contact was made with children in the WLC during the wait period. Diagnostic, parent- and child-reports of anxiety and depressive symptoms, externalising behaviour problems and attention biases were assessed pre- and post-condition and six-months after treatment. Children in the ATC showed greater improvements on multiple clinical measures compared to children in the WLC. Post-treatment gains improved six-months after treatment. Attention biases for angry and happy faces did not change significantly from pre-to post-condition. However, larger pre-treatment attention bias towards threat was associated with greater reduction in anxiety at post-treatment. Also, children who showed greater consolidation of learning and memory strategies during treatment achieved greater improvement in global functioning at post-treatment. Attention training towards positive stimuli using enhanced visual-search procedures appears to be a promising treatment for childhood anxiety disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measurement of the Errors of Service Altimeter Installations During Landing-Approach and Take-Off Operations

NASA Technical Reports Server (NTRS)

Gracey, William; Jewel, Joseph W., Jr.; Carpenter, Gene T.

1960-01-01

The overall errors of the service altimeter installations of a variety of civil transport, military, and general-aviation airplanes have been experimentally determined during normal landing-approach and take-off operations. The average height above the runway at which the data were obtained was about 280 feet for the landings and about 440 feet for the take-offs. An analysis of the data obtained from 196 airplanes during 415 landing approaches and from 70 airplanes during 152 take-offs showed that: 1. The overall error of the altimeter installations in the landing- approach condition had a probable value (50 percent probability) of +/- 36 feet and a maximum probable value (99.7 percent probability) of +/- 159 feet with a bias of +10 feet. 2. The overall error in the take-off condition had a probable value of +/- 47 feet and a maximum probable value of +/- 207 feet with a bias of -33 feet. 3. The overall errors of the military airplanes were generally larger than those of the civil transports in both the landing-approach and take-off conditions. In the landing-approach condition the probable error and the maximum probable error of the military airplanes were +/- 43 and +/- 189 feet, respectively, with a bias of +15 feet, whereas those for the civil transports were +/- 22 and +/- 96 feet, respectively, with a bias of +1 foot. 4. The bias values of the error distributions (+10 feet for the landings and -33 feet for the take-offs) appear to represent a measure of the hysteresis characteristics (after effect and recovery) and friction of the instrument and the pressure lag of the tubing-instrument system.

Overweight in adult cats: a cross-sectional study.

PubMed

Öhlund, Malin; Palmgren, Malin; Holst, Bodil Ström

2018-01-19

Overweight in cats is a major risk factor for diabetes mellitus and has also been associated with other disorders. Overweight and obesity are believed to be increasing problems in cats, as is currently seen in people, with important health consequences. The objectives of the present study were to determine the prevalence of overweight in cats from two different cohorts in a cross-sectional study design and to assess associations between overweight and diagnoses, and between overweight and demographic and environmental factors. Data were obtained from medical records for cats (n = 1072) visiting an academic medical center during 2013-2015, and from a questionnaire on insured cats (n = 1665). From the medical records, information on body condition score, breed, age, sex, neutering status, and diagnosis was obtained. The questionnaire included questions relating to the cat's body condition, breed, age, sex, neutering status, outdoor access, activity level, and diet. Data were analyzed by multivariable logistic regression. The prevalence of overweight was 45% in the medical records cohort and 22% in the questionnaire cohort, where owners judged their pet's body condition. Overweight cats in the medical records cohort were more likely to be diagnosed with lower urinary tract disease, diabetes mellitus, respiratory disease, skin disorders, locomotor disease, and trauma. Eating predominantly dry food, being a greedy eater, and inactivity were factors associated with an increased risk of overweight in the final model in the questionnaire cohort. In both cohorts, the Birman and Persian breeds, and geriatric cats, were less likely to be overweight, and male cats were more likely to be overweight. The prevalence of overweight cats (45%) as assessed by trained personnel was high and in the same range as previously reported. Birman and Persian cats had a lower risk of overweight. The association with dry food found in adult, neutered cats is potentially important because this type of food is commonly fed to cats worldwide, and warrants further attention. Drawbacks related to the study design need to be acknowledged when interpreting the results, such as a potential for selection bias for cats visiting an animal hospital, and an information bias for questionnaire data. The high occurrence of overweight in cats needs to be addressed because it negatively affects their health.

Multivariate EMD and full spectrum based condition monitoring for rotating machinery

NASA Astrophysics Data System (ADS)

Zhao, Xiaomin; Patel, Tejas H.; Zuo, Ming J.

2012-02-01

Early assessment of machinery health condition is of paramount importance today. A sensor network with sensors in multiple directions and locations is usually employed for monitoring the condition of rotating machinery. Extraction of health condition information from these sensors for effective fault detection and fault tracking is always challenging. Empirical mode decomposition (EMD) is an advanced signal processing technology that has been widely used for this purpose. Standard EMD has the limitation in that it works only for a single real-valued signal. When dealing with data from multiple sensors and multiple health conditions, standard EMD faces two problems. First, because of the local and self-adaptive nature of standard EMD, the decomposition of signals from different sources may not match in either number or frequency content. Second, it may not be possible to express the joint information between different sensors. The present study proposes a method of extracting fault information by employing multivariate EMD and full spectrum. Multivariate EMD can overcome the limitations of standard EMD when dealing with data from multiple sources. It is used to extract the intrinsic mode functions (IMFs) embedded in raw multivariate signals. A criterion based on mutual information is proposed for selecting a sensitive IMF. A full spectral feature is then extracted from the selected fault-sensitive IMF to capture the joint information between signals measured from two orthogonal directions. The proposed method is first explained using simple simulated data, and then is tested for the condition monitoring of rotating machinery applications. The effectiveness of the proposed method is demonstrated through monitoring damage on the vane trailing edge of an impeller and rotor-stator rub in an experimental rotor rig.

A normality bias in legal decision making.

PubMed

Prentice, Robert A; Koehler, Jonathan J

2003-03-01

It is important to understand how legal fact finders determine causation and assign blame. However, this process is poorly understood. Among the psychological factors that affect decision makers are an omission bias (a tendency to blame actions more than inactions [omissions] for bad results), and a normality bias (a tendency to react more strongly to bad outcomes that spring from abnormal rather than normal circumstances). The omission and normality biases often reinforce one another when inaction preserves the normal state and when action creates an abnormal state. But what happens when these biases push in opposite directions as they would when inaction promotes an abnormal state or when action promotes a normal state? Which bias exerts the stronger influence on the judgments and behaviors of legal decision makers? The authors address this issue in two controlled experiments. One experiment involves medical malpractice and the other involves stockbroker negligence. They find that jurors pay much more attention to the normality of conditions than to whether those conditions arose through acts or omissions. Defendants who followed a nontraditional medical treatment regime or who chose a nontraditional stock portfolio received more blame and more punishment for bad outcomes than did defendants who obtained equally poor results after recommending a traditional medical regime or a traditional stock portfolio. Whether these recommendations entailed an action or an omission was essentially irrelevant. The Article concludes with a discussion of the implications of a robust normality bias for American jurisprudence.

Robot-assisted laparoscopic prostatectomy is not associated with early postoperative radiation therapy.

PubMed

Chino, Junzo; Schroeck, Florian R; Sun, Leon; Lee, W Robert; Albala, David M; Moul, Judd W; Koontz, Bridget F

2009-11-01

To compare open radical prostatectomy (RP) and robot-assisted laparoscopic prostatectomy (RALP), and to determine whether RALP is associated with a higher risk of features that determine recommendations for postoperative radiation therapy (RT). Patients undergoing RP from 2003 to 2007 were stratified into two groups: open RP and RALP. Preoperative (PSA level, T stage and Gleason score), pathological factors (T stage, Gleason score, extracapsular extension [ECE] and the status of surgical margins and seminal vesicle invasion [SVI]) and early treatment with RT or referral for RT within 6 months were compared between the groups. Multivariate analysis was used to control for selection bias in the RALP group. In all, 904 patients were identified; 368 underwent RALP and 536 underwent open RP (retropubic or perineal). Patients undergoing open RP had a higher pathological stage with ECE present in 24.8% vs 19.3% in RALP (P = 0.05) and SVI in 10.3% vs 3.8% (P < 0.001). In the RALP vs open RP group, there were positive surgical margins in 31.5% vs 31.9% (P = 0.9) and there were postoperative PSA levels of (3) 0.2 ng/mL in 5.7% vs 6.3% (P = 0.7), respectively. On multivariate analysis to control for selection bias, RALP was not associated with indication for RT (odds ratio (OR) 1.10, P = 0.55), or referral for RT (OR 1.04, P = 0.86). RALP was not associated with an increase in either indication or referral for early postoperative RT.

Transmission of sporadic Creutzfeldt-Jakob disease by blood transfusion: risk factor or possible biases.

PubMed

Puopolo, Maria; Ladogana, Anna; Vetrugno, Vito; Pocchiari, Maurizio

2011-07-01

The occurrence of transfusion transmissions of variant Creutzfeldt-Jakob disease (CJD) cases has reawakened attention to the possible similar risk posed by other forms of CJD. CJD with a definite or probable diagnosis (sporadic CJD, n = 741; genetic CJD, n = 175) and no-CJD patients with definite alternative diagnosis (n = 482) with available blood transfusion history were included in the study. The risk of exposure to blood transfusion occurring more than 10 years before disease onset and for some possible confounding factors was evaluated by calculating crude odds ratios (ORs). Variables with significant ORs in univariate analyses were included in multivariate logistic regression analyses. In the univariate model, blood transfusion occurring more than 10 years before clinical onset is 4.1-fold more frequent in sporadic CJD than in other neurologic disorders. This significance is lost when the 10-year lag time was not considered. Multivariate analyses show that the risk of developing sporadic CJD after transfusion increases (OR, 5.05) after adjusting for possible confounding factors. Analysis conducted on patients with genetic CJD did not reveal any significant risk factor associated with transfusion. This is the first case-control study showing a significant risk of transfusion occurring more than 10 years before clinical onset in sporadic CJD patients. It remains questionable whether the significance of these data is biologically plausible or the consequence of biases in the design of the study, but they counterbalance previous epidemiologic negative reports that might have overestimated the assessment of blood safety in sporadic CJD. © 2010 American Association of Blood Banks.

Personality and its Relation to Mental and Psychosocial Health in Emerging Adult Sexual Minority Men: The P18 Cohort Study.

PubMed

D'Avanzo, Paul A; Barton, Staci C; Kapadia, Farzana; Halkitis, Perry N

2017-01-01

Personality disorder and personality pathology encompass a dimension of psychological dysfunction known to severely impact multiple domains of functioning. However, there is a notable dearth of research regarding both the pervasiveness and correlates of personality pathology among young sexual minority males who themselves experience heightened mental health burdens. Using the self-report version of the Standardized Assessment of Personality-Abbreviated Scale we tested associations between distinct personality characteristics with sociodemographic and psychosocial factors as well as mental health states in a sample of 528 young (aged 21-25 years) sexual minority men. In multivariate analysis, personality traits varied significantly by race/ethnicity. Personality traits were also positively associated with psychosocial states, specifically, internalized anti-homosexual bias, level of connection with the gay community, and male body dissatisfaction, as well as mental health in the form of recent depressive and anxious symptomatology. These findings support the complex synergy which exists between personality characteristics, psychosocial conditions, and mental health burdens present among sexual minority men and support the need for an all-encompassing approach to both the study and care of this population that addresses the influences of both internal and external factors on well-being.

Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

PubMed Central

Koenig, Stephan; Uengoer, Metin; Lachnit, Harald

2017-01-01

We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L < P < H) and the uncertainty of their prediction (L < P > H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention. PMID:28588466

Sex-biased severity of sarcoptic mange at the same biological cost in a sexually dimorphic ungulate.

PubMed

López-Olvera, Jorge R; Serrano, Emmanuel; Armenteros, Anna; Pérez, Jesús M; Fandos, Paulino; Carvalho, João; Velarde, Roser; Cano-Manuel, Francisco J; Ráez, Arián; Espinosa, José; Soriguer, Ramón C; Granados, José E

2015-11-10

In sexually dimorphic species, male susceptibility to parasite infection and mortality is frequently higher than in females. The Iberian ibex (Capra pyrenaica) is a sexually dimorphic mountain ungulate endemic to the Iberian Peninsula commonly affected by sarcoptic mange, a chronic catabolic skin disease caused by Sarcoptes scabiei. Since 1992, sarcoptic mange affects the Iberian ibex population of the Sierra Nevada Natural Space (SNNS). This study aims at exploring whether mange severity, in terms of prevalence and its effects on body condition, is male-biased in Iberian ibex. One thousand and seventy-one adult Iberian ibexes (439 females and 632 males) were randomly shot-harvested in the SNNS from May 1995 to February 2008. Sarcoptic mange stage was classified as healthy, mildly infected or severely infected. Sex-biased prevalence of severe mange was evaluated by a Chi-square test whereas the interaction between mange severity and sex on body condition was assessed by additive models. Among scabietic individuals, the prevalence of severely affected males was 1.29 times higher than in females. On the other hand, both sexes were not able to take profit of a higher availability of seasonal food resources when sarcoptic, particularly in the severe stages. Sarcoptic mange severity is male-biased in Iberian ibex, though not mange effects on body condition. Behavioural, immunological and physiological characteristics of males may contribute to this partial sex-biased susceptibility to sarcoptic mange.

The effects of acute exercise on attentional bias towards smoking-related stimuli during temporary abstinence from smoking.

PubMed

Van Rensburg, Kate Janse; Taylor, Adrian; Hodgson, Tim

2009-11-01

Attentional bias towards smoking-related cues is increased during abstinence and can predict relapse after quitting. Exercise has been found to reduce cigarette cravings and desire to smoke during temporary abstinence and attenuate increased cravings in response to smoking cues. To assess the acute effects of exercise on attentional bias to smoking-related cues during temporary abstinence from smoking. In a randomized cross-over design, on separate days regular smokers (n = 20) undertook 15 minutes of exercise (moderate intensity stationary cycling) or passive seating following 15 hours of nicotine abstinence. Attentional bias was measured at baseline and post-treatment. The percentage of dwell time and direction of initial fixation was assessed during the passive viewing of a series of paired smoking and neutral images using an Eyelink II eye-tracking system. Self-reported desire to smoke was recorded at baseline, mid- and post-treatment and post-eye-tracking task. There was a significant condition x time interaction for desire to smoke, F((1,18)) = 10.67, P = 0.004, eta(2) = 0.36, with significantly lower desire to smoke at mid- and post-treatment following the exercise condition. The percentage of dwell time and direction of initial fixations towards smoking images were also reduced significantly following the exercise condition compared with the passive control. Findings support previous research that acute exercise reduces desire to smoke. This is the first study to show that exercise appears to also influence the salience and attentional biases towards cigarettes.

Temperament differentially influences early information processing in men and women: Preliminary electrophysiological evidence of attentional biases in healthy individuals.

PubMed

Pintzinger, Nina M; Pfabigan, Daniela M; Pfau, Lorenz; Kryspin-Exner, Ilse; Lamm, Claus

2017-01-01

Preferential processing of threat-related information is a robust finding in anxiety disorders. The observation that attentional biases are also present in healthy individuals suggests factors other than clinical symptoms to play a role. Using a dot-probe paradigm while event-related potentials were recorded in 59 healthy adults, we investigated whether temperament and gender, both related to individual variation in anxiety levels, influence attentional processing. All participants showed protective attentional biases in terms of enhanced attention engagement with positive information, indexed by larger N1 amplitudes in positive compared to negative conditions. Taking gender differences into account, we observed that women showed enhanced attention engagement with negative compared to neutral information, indicated by larger P2 amplitudes in congruent than in incongruent negative conditions. Attentional processing was influenced by the temperament traits negative affect and effortful control. Our results emphasize that gender and temperament modulate attentional biases in healthy adults. Copyright © 2016 Elsevier B.V. All rights reserved.

Sensitivity and bias under conditions of equal and unequal academic task difficulty.

PubMed

Reed, Derek D; Martens, Brian K

2008-01-01

We conducted an experimental analysis of children's relative problem-completion rates across two workstations under conditions of equal (Experiment 1) and unequal (Experiment 2) problem difficulty. Results were described using the generalized matching equation and were evaluated for degree of schedule versus stimulus control. Experiment 1 involved a symmetrical choice arrangement in which the children could earn points exchangeable for rewards contingent on correct math problem completion. Points were delivered according to signaled variable-interval schedules at each workstation. For 2 children, relative rates of problem completion appeared to have been controlled by the schedule requirements in effect and matched relative rates of reinforcement, with sensitivity values near 1 and bias values near 0. Experiment 2 involved increasing the difficulty of math problems at one of the workstations. Sensitivity values for all 3 participants were near 1, but a substantial increase in bias toward the easier math problems was observed. This bias was possibly associated with responding at the more difficult workstation coming under stimulus control rather than schedule control.

Strong mechanically induced effects in DC current-biased suspended Josephson junctions

NASA Astrophysics Data System (ADS)

McDermott, Thomas; Deng, Hai-Yao; Isacsson, Andreas; Mariani, Eros

2018-01-01

Superconductivity is a result of quantum coherence at macroscopic scales. Two superconductors separated by a metallic or insulating weak link exhibit the AC Josephson effect: the conversion of a DC voltage bias into an AC supercurrent. This current may be used to activate mechanical oscillations in a suspended weak link. As the DC-voltage bias condition is remarkably difficult to achieve in experiments, here we analyze theoretically how the Josephson effect can be exploited to activate and detect mechanical oscillations in the experimentally relevant condition with purely DC current bias. We unveil how changing the strength of the electromechanical coupling results in two qualitatively different regimes showing dramatic effects of the oscillations on the DC-voltage characteristic of the device. These include the appearance of Shapiro-type plateaus for weak coupling and a sudden mechanically induced retrapping for strong coupling. Our predictions, measurable in state-of-the-art experimental setups, allow the determination of the frequency and quality factor of the resonator using DC only techniques.

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.

Assessing the validity of subjective reports in the auditory streaming paradigm.

PubMed

Farkas, Dávid; Denham, Susan L; Bendixen, Alexandra; Winkler, István

2016-04-01

While subjective reports provide a direct measure of perception, their validity is not self-evident. Here, the authors tested three possible biasing effects on perceptual reports in the auditory streaming paradigm: errors due to imperfect understanding of the instructions, voluntary perceptual biasing, and susceptibility to implicit expectations. (1) Analysis of the responses to catch trials separately promoting each of the possible percepts allowed the authors to exclude participants who likely have not fully understood the instructions. (2) Explicit biasing instructions led to markedly different behavior than the conventional neutral-instruction condition, suggesting that listeners did not voluntarily bias their perception in a systematic way under the neutral instructions. Comparison with a random response condition further supported this conclusion. (3) No significant relationship was found between social desirability, a scale-based measure of susceptibility to implicit social expectations, and any of the perceptual measures extracted from the subjective reports. This suggests that listeners did not significantly bias their perceptual reports due to possible implicit expectations present in the experimental context. In sum, these results suggest that valid perceptual data can be obtained from subjective reports in the auditory streaming paradigm.

Sensitivity of the Antarctic surface mass balance to oceanic perturbations

NASA Astrophysics Data System (ADS)

Kittel, C.; Amory, C.; Agosta, C.; Fettweis, X.

2017-12-01

Regional climate models (RCMs) are suitable numerical tools to study the surface mass balance (SMB) of the wide polar ice sheets due to their high spatial resolution and polar-adapted physics. Nonetheless, RCMs are driven at their boundaries and over the ocean by reanalysis or global climate model (GCM) products and are thus influenced by potential biases in these large-scale fields. These biases can be significant for both the atmosphere and the sea surface conditions (i.e. sea ice concentration and sea surface temperature). With the RCM MAR, a set of sensitivity experiments has been realized to assess the direct response of the SMB of the Antarctic ice sheet to oceanic perturbations. MAR is forced by ERA-Interim and anomalies based on mean GCM biases are introduced in sea surface conditions. Results show significant increases (decreases) of liquid and solid precipitation due to biases related to warm (cold) oceans. As precipitation is mainly caused by low-pressure systems that intrude into the continent and do not penetrate far inland, coastal areas are more sensitive than inland regions. Furthermore, warm ocean representative biases lead to anomalies as large as anomalies simulated by other RCMs or GCMs for the end of the 21st century.

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

Racial bias in sport medical staff's perceptions of others' pain.

PubMed

Druckman, James N; Trawalter, Sophie; Montes, Ivonne; Fredendall, Alexandria; Kanter, Noah; Rubenstein, Allison Paige

2017-11-27

Unequal treatment based on race is well documented in higher education and healthcare settings. In the present work, we examine racial bias at the intersection of these domains: racial bias in pain-related perceptions among National Collegiate Athletic Association (NCAA) Division 1 sport medical staff. Using experimental vignettes about a student-athlete who injured his/her anterior cruciate ligament (ACL), we find, like prior work, that respondents perceived Black (vs. White) targets as having higher initial pain tolerance. Moreover, this bias was mediated by perceptions of social class. We extend prior work by showing racial bias was not evident on other outcome measures, including perception of recovery process pain, likelihood of over-reporting pain, and over-use of drugs to combat pain. This suggests stricter boundary conditions on bias in pain perceptions than had been previously recognized.

Classifier performance prediction for computer-aided diagnosis using a limited dataset.

PubMed

Sahiner, Berkman; Chan, Heang-Ping; Hadjiiski, Lubomir

2008-04-01

In a practical classifier design problem, the true population is generally unknown and the available sample is finite-sized. A common approach is to use a resampling technique to estimate the performance of the classifier that will be trained with the available sample. We conducted a Monte Carlo simulation study to compare the ability of the different resampling techniques in training the classifier and predicting its performance under the constraint of a finite-sized sample. The true population for the two classes was assumed to be multivariate normal distributions with known covariance matrices. Finite sets of sample vectors were drawn from the population. The true performance of the classifier is defined as the area under the receiver operating characteristic curve (AUC) when the classifier designed with the specific sample is applied to the true population. We investigated methods based on the Fukunaga-Hayes and the leave-one-out techniques, as well as three different types of bootstrap methods, namely, the ordinary, 0.632, and 0.632+ bootstrap. The Fisher's linear discriminant analysis was used as the classifier. The dimensionality of the feature space was varied from 3 to 15. The sample size n2 from the positive class was varied between 25 and 60, while the number of cases from the negative class was either equal to n2 or 3n2. Each experiment was performed with an independent dataset randomly drawn from the true population. Using a total of 1000 experiments for each simulation condition, we compared the bias, the variance, and the root-mean-squared error (RMSE) of the AUC estimated using the different resampling techniques relative to the true AUC (obtained from training on a finite dataset and testing on the population). Our results indicated that, under the study conditions, there can be a large difference in the RMSE obtained using different resampling methods, especially when the feature space dimensionality is relatively large and the sample size is small. Under this type of conditions, the 0.632 and 0.632+ bootstrap methods have the lowest RMSE, indicating that the difference between the estimated and the true performances obtained using the 0.632 and 0.632+ bootstrap will be statistically smaller than those obtained using the other three resampling methods. Of the three bootstrap methods, the 0.632+ bootstrap provides the lowest bias. Although this investigation is performed under some specific conditions, it reveals important trends for the problem of classifier performance prediction under the constraint of a limited dataset.

`Been There Done That': Disentangling Option Value Effects from User Heterogeneity When Valuing Natural Resources with a Use Component

NASA Astrophysics Data System (ADS)

Lyssenko, Nikita; Martínez-Espiñeira, Roberto

2012-11-01

Endogeneity bias arises in contingent valuation studies when the error term in the willingness to pay (WTP) equation is correlated with explanatory variables because observable and unobservable characteristics of the respondents affect both their WTP and the value of those variables. We correct for the endogeneity of variables that capture previous experience with the resource valued, humpback whales, and with the geographic area of study. We consider several endogenous behavioral variables. Therefore, we apply a multivariate Probit approach to jointly model them with WTP. In this case, correcting for endogeneity increases econometric efficiency and substantially corrects the bias affecting the estimated coefficients of the experience variables, by isolating the decreasing effect on option value caused by having already experienced the resource. Stark differences are unveiled between the marginal effects on WTP of previous experience of the resource in an alternative location versus experience in the location studied, Newfoundland and Labrador (Canada).

Rapid neural discrimination of communicative gestures.

PubMed

Redcay, Elizabeth; Carlson, Thomas A

2015-04-01

Humans are biased toward social interaction. Behaviorally, this bias is evident in the rapid effects that self-relevant communicative signals have on attention and perceptual systems. The processing of communicative cues recruits a wide network of brain regions, including mentalizing systems. Relatively less work, however, has examined the timing of the processing of self-relevant communicative cues. In the present study, we used multivariate pattern analysis (decoding) approach to the analysis of magnetoencephalography (MEG) to study the processing dynamics of social-communicative actions. Twenty-four participants viewed images of a woman performing actions that varied on a continuum of communicative factors including self-relevance (to the participant) and emotional valence, while their brain activity was recorded using MEG. Controlling for low-level visual factors, we found early discrimination of emotional valence (70 ms) and self-relevant communicative signals (100 ms). These data offer neural support for the robust and rapid effects of self-relevant communicative cues on behavior. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

'Been there done that': disentangling option value effects from user heterogeneity when valuing natural resources with a use component.

PubMed

Lyssenko, Nikita; Martínez-Espiñeira, Roberto

2012-11-01

Endogeneity bias arises in contingent valuation studies when the error term in the willingness to pay (WTP) equation is correlated with explanatory variables because observable and unobservable characteristics of the respondents affect both their WTP and the value of those variables. We correct for the endogeneity of variables that capture previous experience with the resource valued, humpback whales, and with the geographic area of study. We consider several endogenous behavioral variables. Therefore, we apply a multivariate Probit approach to jointly model them with WTP. In this case, correcting for endogeneity increases econometric efficiency and substantially corrects the bias affecting the estimated coefficients of the experience variables, by isolating the decreasing effect on option value caused by having already experienced the resource. Stark differences are unveiled between the marginal effects on WTP of previous experience of the resource in an alternative location versus experience in the location studied, Newfoundland and Labrador (Canada).

Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments.

PubMed

Leong, Yuan Chang; Radulescu, Angela; Daniel, Reka; DeWoskin, Vivian; Niv, Yael

2017-01-18

Little is known about the relationship between attention and learning during decision making. Using eye tracking and multivariate pattern analysis of fMRI data, we measured participants' dimensional attention as they performed a trial-and-error learning task in which only one of three stimulus dimensions was relevant for reward at any given time. Analysis of participants' choices revealed that attention biased both value computation during choice and value update during learning. Value signals in the ventromedial prefrontal cortex and prediction errors in the striatum were similarly biased by attention. In turn, participants' focus of attention was dynamically modulated by ongoing learning. Attentional switches across dimensions correlated with activity in a frontoparietal attention network, which showed enhanced connectivity with the ventromedial prefrontal cortex between switches. Our results suggest a bidirectional interaction between attention and learning: attention constrains learning to relevant dimensions of the environment, while we learn what to attend to via trial and error. Copyright © 2017 Elsevier Inc. All rights reserved.

Host influence in the genomic composition of flaviviruses: A multivariate approach.

PubMed

Simón, Diego; Fajardo, Alvaro; Sóñora, Martín; Delfraro, Adriana; Musto, Héctor

2017-10-28

Flaviviruses present substantial differences in their host range and transmissibility. We studied the evolution of base composition, dinucleotide biases, codon usage and amino acid frequencies in the genus Flavivirus within a phylogenetic framework by principal components analysis. There is a mutual interplay between the evolutionary history of flaviviruses and their respective vectors and/or hosts. Hosts associated to distinct phylogenetic groups may be driving flaviviruses at different pace and through various sequence landscapes, as can be seen for viruses associated with Aedes or Culex spp., although phylogenetic inertia cannot be ruled out. In some cases, viruses face even opposite forces. For instance, in tick-borne flaviviruses, while vertebrate hosts exert pressure to deplete their CpG, tick vectors drive them to exhibit GC-rich codons. Within a vertebrate environment, natural selection appears to be acting on the viral genome to overcome the immune system. On the other side, within an arthropod environment, mutational biases seem to be the dominant forces. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitation of active pharmaceutical ingredients and excipients in powder blends using designed multivariate calibration models by near-infrared spectroscopy.

PubMed

Li, Weiyong; Worosila, Gregory D

2005-05-13

This research note demonstrates the simultaneous quantitation of a pharmaceutical active ingredient and three excipients in a simulated powder blend containing acetaminophen, Prosolv and Crospovidone. An experimental design approach was used in generating a 5-level (%, w/w) calibration sample set that included 125 samples. The samples were prepared by weighing suitable amount of powders into separate 20-mL scintillation vials and were mixed manually. Partial least squares (PLS) regression was used in calibration model development. The models generated accurate results for quantitation of Crospovidone (at 5%, w/w) and magnesium stearate (at 0.5%, w/w). Further testing of the models demonstrated that the 2-level models were as effective as the 5-level ones, which reduced the calibration sample number to 50. The models had a small bias for quantitation of acetaminophen (at 30%, w/w) and Prosolv (at 64.5%, w/w) in the blend. The implication of the bias is discussed.

Adaptable history biases in human perceptual decisions.

PubMed

Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L

2016-06-21

When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.

The Case for Intervention Bias in the Practice of Medicine

PubMed Central

Foy, Andrew J.; Filippone, Edward J.

2013-01-01

Bias is an inclination to present or hold a partial perspective at the expense of possibly equal or more valid alternatives. In this paper, we present a series of conditional arguments to prove that intervention bias exists in the practice of medicine. We then explore its potential causes, consequences, and criticisms. We use the term to describe the bias on the part of physicians and the medical community to intervene, whether it is with drugs, diagnostic tests, non-invasive procedures, or surgeries, when not intervening would be a reasonable alternative. The recognition of intervention bias in medicine is critically important given today’s emphasis on providing high-value care and reducing unnecessary and potentially harmful interventions. PMID:23766747

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

PubMed Central

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

2003-01-01

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

A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.

PubMed

De Silva, Anurika Priyanjali; Moreno-Betancur, Margarita; De Livera, Alysha Madhu; Lee, Katherine Jane; Simpson, Julie Anne

2017-07-25

Missing data is a common problem in epidemiological studies, and is particularly prominent in longitudinal data, which involve multiple waves of data collection. Traditional multiple imputation (MI) methods (fully conditional specification (FCS) and multivariate normal imputation (MVNI)) treat repeated measurements of the same time-dependent variable as just another 'distinct' variable for imputation and therefore do not make the most of the longitudinal structure of the data. Only a few studies have explored extensions to the standard approaches to account for the temporal structure of longitudinal data. One suggestion is the two-fold fully conditional specification (two-fold FCS) algorithm, which restricts the imputation of a time-dependent variable to time blocks where the imputation model includes measurements taken at the specified and adjacent times. To date, no study has investigated the performance of two-fold FCS and standard MI methods for handling missing data in a time-varying covariate with a non-linear trajectory over time - a commonly encountered scenario in epidemiological studies. We simulated 1000 datasets of 5000 individuals based on the Longitudinal Study of Australian Children (LSAC). Three missing data mechanisms: missing completely at random (MCAR), and a weak and a strong missing at random (MAR) scenarios were used to impose missingness on body mass index (BMI) for age z-scores; a continuous time-varying exposure variable with a non-linear trajectory over time. We evaluated the performance of FCS, MVNI, and two-fold FCS for handling up to 50% of missing data when assessing the association between childhood obesity and sleep problems. The standard two-fold FCS produced slightly more biased and less precise estimates than FCS and MVNI. We observed slight improvements in bias and precision when using a time window width of two for the two-fold FCS algorithm compared to the standard width of one. We recommend the use of FCS or MVNI in a similar longitudinal setting, and when encountering convergence issues due to a large number of time points or variables with missing values, the two-fold FCS with exploration of a suitable time window.

Biases in the production and reception of collective knowledge: the case of hindsight bias in Wikipedia.

PubMed

Oeberst, Aileen; von der Beck, Ina; D Back, Mitja; Cress, Ulrike; Nestler, Steffen

2017-04-17

The Web 2.0 enabled collaboration at an unprecedented level. In one of the flagships of mass collaboration-Wikipedia-a large number of authors socially negotiate the world's largest compendium of knowledge. Several guidelines in Wikipedia restrict contributions to verifiable information from reliable sources to ensure recognized knowledge. Much psychological research demonstrates, however, that individual information processing is biased. This poses the question whether individual biases translate to Wikipedia articles or whether they are prevented by its guidelines. The present research makes use of hindsight bias to examine this question. To this end, we analyzed foresight and hindsight versions of Wikipedia articles regarding a broad variety of events (Study 1). We found the majority of articles not to contain traces of hindsight bias-contrary to prior individual research. However, for a particular category of events-disasters-we found robust evidence for hindsight bias. In a lab experiment (Study 2), we then examined whether individuals' hindsight bias is translated into articles under controlled conditions and tested whether collaborative writing-as present in Wikipedia-affects the resultant bias (vs. individual writing). Finally, we investigated the impact of biased Wikipedia articles on readers (Study 3). As predicted, biased articles elicited a hindsight bias in readers, who had not known of the event previously. Moreover, biased articles also affected individuals who knew about the event already, and who had already developed a hindsight bias: biased articles further increased their hindsight.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Sequencing on the SOLiD 5500xl System - in-depth characterization of the GC bias.

PubMed

Roeh, Simone; Weber, Peter; Rex-Haffner, Monika; Deussing, Jan M; Binder, Elisabeth B; Jakovcevski, Mira

2017-07-04

Different types of sequencing biases have been described and subsequently improved for a variety of sequencing systems, mostly focusing on the widely used Illumina systems. Similar studies are missing for the SOLiD 5500xl system, a sequencer which produced many data sets available to researchers today. Describing and understanding the bias is important to accurately interpret and integrate these published data in various ongoing research projects. We report a particularly strong GC bias for this sequencing system when analyzing a defined gDNA mix of 5 microbes with a wide range of different GC contents (20-72%) when comparing to the expected distribution and Illumina MiSeq data from the same DNA pool. Since we observed this bias already under PCR-free conditions, changing the PCR conditions during library preparation - a common strategy to handle bias in the Illumina system - was not relevant. Source of the bias appeared to be an uneven heat distribution during the SOLiD emulsion PCR (ePCR) - for enrichment of libraries prior loading - since ePCR in either small pouches or in 96-well plates improved the GC bias. Sequencing of chromatin immunoprecipitated DNA (ChIP-seq) is a common approach in epigenetics. ChIP-seq of the mixed source histone mark H3K9ac (acetyl Histone H3 lysine 9), typically found on promoter regions and on gene bodies, including CpG islands, performed on a SOLiD 5500xl machine, resulted in major loss of reads at GC rich loci (GC content ≥ 62%), not explained by low sequencing depth. This was improved with adaptations of the ePCR.

Vasopressin eliminates the expression of familiar odor bias in neonatal female mice through V1aR

PubMed Central

Hammock, Elizabeth A.D.; Law, Caitlin S.; Levitt, Pat

2014-01-01

Summary V1aR has a well established role in the neural regulation of adult mammalian social behavior. The role of V1aR in developmentally emerging social behavior is less well understood. We mapped V1aR at post-natal day 8 (P8) and demonstrate developmentally-specific expression in the neocortex and hippocampus. We tested the ability of male and female C57BL/6J mice to show orienting bias to a familiar odor at this age. We demonstrate that females, but not males, show an orienting bias for odors previously paired with the mother, which is eliminated by V1aR signaling. Arginine-vasopressin (AVP) and the vasopressin V1a receptor (V1aR) acting within the forebrain are involved in social behavior in adult animals. Much less is known about the function of V1aR in neurobehavioral development. In the present study, at post-natal day 8 (P8) in neonatal C57BL/6J mice, we map V1aR and use an olfactory exposure paradigm to assess a role for V1aR on olfactory preferences. In addition to V1aR in the lateral septum and ventral tegmental area, we observe V1aR in the neocortex and hippocampus, not typically observed in adult mice, implicating a developmental sensitive period for V1aR to modulate these brain areas in an experience-dependent manner. Males and females were tested on P8 for orienting preferences after exposure to a non-social odor, presented either when the mother was in the home cage (contingent) or when the mother had been removed from the home cage (not contingent). Wild-type female mice show a selective orienting bias toward the exposed odor, but only in the contingent condition. Males did not show orienting bias after either training condition. Female Avpr1a-/- mice showed strong familiar odor bias, regardless of the training condition. This finding led us to test the ability of AVP to diminish odor bias in females. Central application of AVP eliminated odor bias in Avpr1a+/+, but not Avpr1a-/- female mice. Together, these data indicate that AVP acting at V1aR eliminates the expression of familiar odor bias in neonatal mice. This suggests a developmental role for AVP on familiarity bias, which has implications for species-typical life history trajectories of social learning and natal dispersal. PMID:23261858

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Temporal processing deficit leads to impaired multisensory binding in schizophrenia.

PubMed

Zvyagintsev, Mikhail; Parisi, Carmen; Mathiak, Klaus

2017-09-01

Schizophrenia has been characterised by neurodevelopmental dysconnectivity resulting in cognitive and perceptual dysmetria. Hence patients with schizophrenia may be impaired to detect the temporal relationship between stimuli in different sensory modalities. However, only a few studies described deficit in perception of temporally asynchronous multisensory stimuli in schizophrenia. We examined the perceptual bias and the processing time of synchronous and delayed sounds in the streaming-bouncing illusion in 16 patients with schizophrenia and a matched control group of 18 participants. Equal for patients and controls, the synchronous sound biased the percept of two moving squares towards bouncing as opposed to the more frequent streaming percept in the condition without sound. In healthy controls, a delay of the sound presentation significantly reduced the bias and led to prolonged processing time whereas patients with schizophrenia did not differentiate between this condition and the condition with synchronous sound. Schizophrenia leads to a prolonged window of simultaneity for audiovisual stimuli. Therefore, temporal processing deficit in schizophrenia can lead to hyperintegration of temporally unmatched multisensory stimuli.

Evidence for arousal-biased competition in perceptual learning.

PubMed

Lee, Tae-Ho; Itti, Laurent; Mather, Mara

2012-01-01

Arousal-biased competition theory predicts that arousal biases competition in favor of perceptually salient stimuli and against non-salient stimuli (Mather and Sutherland, 2011). The current study tested this hypothesis by having observers complete many trials in a visual search task in which the target either always was salient (a 55° tilted line among 80° distractors) or non-salient (a 55° tilted line among 50° distractors). Each participant completed one session in an emotional condition, in which visual search trials were preceded by negative arousing images, and one session in a non-emotional condition, in which the arousing images were replaced with neutral images (with session order counterbalanced). Test trials in which the target line had to be selected from among a set of lines with different tilts revealed that the emotional condition enhanced identification of the salient target line tilt but impaired identification of the non-salient target line tilt. Thus, arousal enhanced perceptual learning of salient stimuli but impaired perceptual learning of non-salient stimuli.

Evidence for Arousal-Biased Competition in Perceptual Learning

PubMed Central

Lee, Tae-Ho; Itti, Laurent; Mather, Mara

2012-01-01

Arousal-biased competition theory predicts that arousal biases competition in favor of perceptually salient stimuli and against non-salient stimuli (Mather and Sutherland, 2011). The current study tested this hypothesis by having observers complete many trials in a visual search task in which the target either always was salient (a 55° tilted line among 80° distractors) or non-salient (a 55° tilted line among 50° distractors). Each participant completed one session in an emotional condition, in which visual search trials were preceded by negative arousing images, and one session in a non-emotional condition, in which the arousing images were replaced with neutral images (with session order counterbalanced). Test trials in which the target line had to be selected from among a set of lines with different tilts revealed that the emotional condition enhanced identification of the salient target line tilt but impaired identification of the non-salient target line tilt. Thus, arousal enhanced perceptual learning of salient stimuli but impaired perceptual learning of non-salient stimuli. PMID:22833729

Error Covariance Penalized Regression: A novel multivariate model combining penalized regression with multivariate error structure.

PubMed

Allegrini, Franco; Braga, Jez W B; Moreira, Alessandro C O; Olivieri, Alejandro C

2018-06-29

A new multivariate regression model, named Error Covariance Penalized Regression (ECPR) is presented. Following a penalized regression strategy, the proposed model incorporates information about the measurement error structure of the system, using the error covariance matrix (ECM) as a penalization term. Results are reported from both simulations and experimental data based on replicate mid and near infrared (MIR and NIR) spectral measurements. The results for ECPR are better under non-iid conditions when compared with traditional first-order multivariate methods such as ridge regression (RR), principal component regression (PCR) and partial least-squares regression (PLS). Copyright © 2018 Elsevier B.V. All rights reserved.

Identifiability of Additive Actuator and Sensor Faults by State Augmentation

NASA Technical Reports Server (NTRS)

Joshi, Suresh; Gonzalez, Oscar R.; Upchurch, Jason M.

2014-01-01

A class of fault detection and identification (FDI) methods for bias-type actuator and sensor faults is explored in detail from the point of view of fault identifiability. The methods use state augmentation along with banks of Kalman-Bucy filters for fault detection, fault pattern determination, and fault value estimation. A complete characterization of conditions for identifiability of bias-type actuator faults, sensor faults, and simultaneous actuator and sensor faults is presented. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have unknown biases. The fault identifiability conditions are demonstrated via numerical examples. The analytical and numerical results indicate that caution must be exercised to ensure fault identifiability for different fault patterns when using such methods.

"Are cognitive interventions effective in Alzheimer's disease? A controlled meta- analysis of the effects of bias": Correction to Oltra-Cucarella et al. (2016).

PubMed

2016-07-01

Reports an error in "Are Cognitive Interventions Effective in Alzheimer's Disease? A Controlled Meta-Analysis of the Effects of Bias" by Javier Oltra-Cucarella, Rubén Pérez-Elvira, Raul Espert and Anita Sohn McCormick (Neuropsychology, Advanced Online Publication, Apr 7, 2016, np). In the article the first sentence of the third paragraph of the Source of bias subsection in the Statistical Analysis subsection of the Correlational Meta-Analysis section should read "For the control condition bias, three comparison groups were differentiated: (a) a structured cognitive intervention, (b) a placebo control condition, and (c) a pharma control condition without cognitive intervention or no treatment at all." (The following abstract of the original article appeared in record 2016-16656-001.) There is limited evidence about the efficacy of cognitive interventions for Alzheimer's disease (AD). However, aside from the methodological quality of the studies analyzed, the methodology used in previous meta-analyses is itself a risk of bias as different types of effect sizes (ESs) were calculated and combined. This study aimed at examining the results of nonpharmacological interventions for AD with an adequate control of statistical methods and to demonstrate a different approach to meta-analysis. ESs were calculated with the independent groups pre/post design. Average ESs for separate outcomes were calculated and moderator analyses were performed so as to offer an overview of the effects of bias. Eighty-seven outcomes from 19 studies (n = 812) were meta-analyzed. ESs were small on average for cognitive and functional outcomes after intervention. Moderator analyses showed no effect of control of bias, although ESs were different from zero only in some circumstances (e.g., memory outcomes in randomized studies). Cognitive interventions showed no more efficacy than placebo interventions, and functional ESs were consistently low across conditions. cognitive interventions delivered may not be effective in AD probably due to the fact that the assumptions behind the cognitive interventions might be inadequate. Future directions include a change in the type of intervention as well as the use of outcomes other than standardized tests. Additional studies with larger sample sizes and different designs are needed to increase the power of both primary studies and meta-analyses. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

NASA Astrophysics Data System (ADS)

Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

2018-01-01

A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

Modifying interpretation biases: Effects on symptomatology, behavior, and physiological reactivity in social anxiety.

PubMed

Nowakowski, Matilda E; Antony, Martin M; Koerner, Naomi

2015-12-01

The present study investigated the effects of computerized interpretation training and cognitive restructuring on symptomatology, behavior, and physiological reactivity in an analogue social anxiety sample. Seventy-two participants with elevated social anxiety scores were randomized to one session of computerized interpretation training (n = 24), cognitive restructuring (n = 24), or an active placebo control condition (n = 24). Participants completed self-report questionnaires focused on interpretation biases and social anxiety symptomatology at pre and posttraining and a speech task at posttraining during which subjective, behavioral, and physiological measures of anxiety were assessed. Only participants in the interpretation training condition endorsed significantly more positive than negative interpretations of ambiguous social situations at posttraining. There was no evidence of generalizability of interpretation training effects to self-report measures of interpretation biases and symptomatology or the anxiety response during the posttraining speech task. Participants in the cognitive restructuring condition were rated as having higher quality speeches and showing fewer signs of anxiety during the posttraining speech task compared to participants in the interpretation training condition. The present study did not include baseline measures of speech performance or computer assessed interpretation biases. The results of the present study bring into question the generalizability of computerized interpretation training as well as the effectiveness of a single session of cognitive restructuring in modifying the full anxiety response. Clinical and theoretical implications are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measuring watershed runoff capability with ERTS data. [Washita River Basin, Oklahoma

NASA Technical Reports Server (NTRS)

Blanchard, B. J.

1974-01-01

Parameters of most equations used to predict runoff from an ungaged area are based on characteristics of the watershed and subject to the biases of a hydrologist. Digital multispectral scanner, MSS, data from ERTS was reduced with the aid of computer programs and a Dicomed display. Multivariate analyses of the MSS data indicate that discrimination between watersheds with different runoff capabilities is possible using ERTS data. Differences between two visible bands of MSS data can be used to more accurately evaluate the parameters than present subjective methods, thus reducing construction cost due to overdesign of flood detention structures.

Cognitive and behavioral predictors of MMPI scores in pretrial psychological evaluations of murderers.

PubMed

Holcomb, W R; Adams, N A; Ponder, H M; Anderson, W P

1984-03-01

Tested by multivariate regression the validity of the MMPI with accused murderers (N = 96) who were undergoing pre-trial evaluations. Four significant behavioral and cognitive predictors of MMPI elevated scores were identified. These include low intelligence, history of drug abuse, suspiciousness observed on the ward, and the fact that the accused was a stranger to the victim. These results support the validity of the MMPI with this population and also suggest that high F scale scores on the MMPI are more a measure of psychopathology than invalidity due to test-taking response bias.

Hypothesis-Driven Story Building: Counteracting Human Cognitive Biases to Improve Medical Diagnosis Support

ERIC Educational Resources Information Center

Zhu, Shizhuo

2010-01-01

Clinical decision-making is challenging mainly because of two factors: (1) patient conditions are often complicated with partial and changing information; (2) people have cognitive biases in their decision-making and information-seeking. Consequentially, misdiagnoses and ineffective use of resources may happen. To better support clinical…

Categorical Biases in Spatial Memory: The Role of Certainty

ERIC Educational Resources Information Center

Holden, Mark P.; Newcombe, Nora S.; Shipley, Thomas F.

2015-01-01

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan,…

Role of quantum-confined stark effect on bias dependent photoluminescence of N-polar GaN/InGaN multi-quantum disk amber light emitting diodes

NASA Astrophysics Data System (ADS)

Tangi, Malleswararao; Mishra, Pawan; Janjua, Bilal; Prabaswara, Aditya; Zhao, Chao; Priante, Davide; Min, Jung-Wook; Ng, Tien Khee; Ooi, Boon S.

2018-03-01

We study the impact of quantum-confined stark effect (QCSE) on bias dependent micro-photoluminescence emission of the quantum disk (Q-disk) based nanowires light emitting diodes (NWs-LED) exhibiting the amber colored emission. The NWs are found to be nitrogen polar (N-polar) verified using KOH wet chemical etching and valence band spectrum analysis of high-resolution X-ray photoelectron spectroscopy. The crystal structure and quality of the NWs were investigated by high-angle annular dark field - scanning transmission electron microscopy. The LEDs were fabricated to acquire the bias dependent micro-photoluminescence spectra. We observe a redshift and a blueshift of the μPL peak in the forward and reverse bias conditions, respectively, with reference to zero bias, which is in contrast to the metal-polar InGaN well-based LEDs in the literature. Such opposite shifts of μPL peak emission observed for N-polar NWs-LEDs, in our study, are due to the change in the direction of the internal piezoelectric field. The quenching of PL intensity, under the reverse bias conditions, is ascribed to the reduction of electron-hole overlap. Furthermore, the blueshift of μPL emission with increasing excitation power reveals the suppression of QCSE resulting from the photo-generated carriers. Thereby, our study confirms the presence of QCSE for NWs-LEDs from both bias and power dependent μPL measurements. Thus, this study serves to understand the QCSE in N-polar InGaN Q-disk NWs-LEDs and other related wide-bandgap nitride nanowires, in general.

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

PubMed

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

Mechanisms of attentional selection bias for threatening emotions of anger and disgust in individuals with high-trait anxiety.

PubMed

Xia, Luyao; Cui, Lixia; Zhang, Qin; Dong, Xiaofei; Shi, Guangyuan

2018-03-07

There are still some controversies that attentional bias to negative emotions in individuals with high-trait anxiety (HTA), as compare with those with low-trait anxiety (LTA), occurs in the engagement or disengagement facet of attentional selectivity and whether this attentional bias is affected by negative emotional types. In this study, we explored the different attentional selectivity mechanisms for threatening emotions of anger and disgust between individuals with HTA and LTA using the variant attentional-probe paradigm. The results showed that under the engagement condition, the HTA group's attentional bias index of the anger mood was negative and was significantly less than the disgusting mood (positive) and that the P1 was smaller with angry faces as compared with neutral faces, which was separate from the results of the disgusted faces, having a significant difference with neutral faces on P1 component. In the LTA group, under the disengagement condition, the attentional bias index of the disgusting mood was significantly bigger than the attentional bias index of the anger mood. Moreover, the P1 of the disgusted faces was significantly bigger than the P1 of the angry faces. The topographical maps were also made to reveal the different neural underpinnings. The results suggested that there were different mechanisms of selective attentional bias for threatening emotions of anger and disgust in individuals with HTA. HTA individuals were characterized by facilitated attentional engagement with angry faces and impaired attentional engagement with disgusted faces. LTA individuals had different neural underpinnings and had impaired attentional disengagement with disgusted faces.

Individuals Who Believe in the Paranormal Expose Themselves to Biased Information and Develop More Causal Illusions than Nonbelievers in the Laboratory.

PubMed

Blanco, Fernando; Barberia, Itxaso; Matute, Helena

2015-01-01

In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena.

Individuals Who Believe in the Paranormal Expose Themselves to Biased Information and Develop More Causal Illusions than Nonbelievers in the Laboratory

PubMed Central

Blanco, Fernando; Barberia, Itxaso; Matute, Helena

2015-01-01

In the reasoning literature, paranormal beliefs have been proposed to be linked to two related phenomena: a biased perception of causality and a biased information-sampling strategy (believers tend to test fewer hypotheses and prefer confirmatory information). In parallel, recent contingency learning studies showed that, when two unrelated events coincide frequently, individuals interpret this ambiguous pattern as evidence of a causal relationship. Moreover, the latter studies indicate that sampling more cause-present cases than cause-absent cases strengthens the illusion. If paranormal believers actually exhibit a biased exposure to the available information, they should also show this bias in the contingency learning task: they would in fact expose themselves to more cause-present cases than cause-absent trials. Thus, by combining the two traditions, we predicted that believers in the paranormal would be more vulnerable to developing causal illusions in the laboratory than nonbelievers because there is a bias in the information they experience. In this study, we found that paranormal beliefs (measured using a questionnaire) correlated with causal illusions (assessed by using contingency judgments). As expected, this correlation was mediated entirely by the believers' tendency to expose themselves to more cause-present cases. The association between paranormal beliefs, biased exposure to information, and causal illusions was only observed for ambiguous materials (i.e., the noncontingent condition). In contrast, the participants' ability to detect causal relationships which did exist (i.e., the contingent condition) was unaffected by their susceptibility to believe in paranormal phenomena. PMID:26177025

[Gender perspective in socio-health care needs].

PubMed

Vázquez-Santiago, Soledad; Garrido Peña, Francisco

2016-01-01

Social conditions are the first environment that modulate external factors which impact on health. In turn gender is a decisive factor in these social determinants of health. This paper analyzes gender bias in the health system as a relevant part in social determinants. We can distinguish three types of bias: cognitive, social, and institutional. In the institutional biases, we analyze the risks of gender and costs originated from the coordination between the health system and the system of social protection. Finally, we suggest a series of measures to minimize these biases and risks. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

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.

The Lateral Habenula and Its Input to the Rostromedial Tegmental Nucleus Mediates Outcome-Specific Conditioned Inhibition.

PubMed

Laurent, Vincent; Wong, Felix L; Balleine, Bernard W

2017-11-08

Animals can readily learn that stimuli predict the absence of specific appetitive outcomes; however, the neural substrates underlying such outcome-specific conditioned inhibition remain largely unexplored. Here, using female and male rats as subjects, we examined the involvement of the lateral habenula (LHb) and of its inputs onto the rostromedial tegmental nucleus (RMTg) in inhibitory learning. In these experiments, we used backward conditioning and contingency reversal to establish outcome-specific conditioned inhibitors for two distinct appetitive outcomes. Then, using the Pavlovian-instrumental transfer paradigm, we assessed the effects of manipulations of the LHb and the LHb-RMTg pathway on that inhibitory encoding. In control animals, we found that an outcome-specific conditioned inhibitor biased choice away from actions delivering that outcome and toward actions earning other outcomes. Importantly, this bias was abolished by both electrolytic lesions of the LHb and selective ablation of LHb neurons using Cre-dependent Caspase3 expression in Cre-expressing neurons projecting to the RMTg. This deficit was specific to conditioned inhibition; an excitatory predictor of a specific outcome-biased choice toward actions delivering the same outcome to a similar degree whether the LHb or the LHb-RMTg network was intact or not. LHb lesions also disrupted the ability of animals to inhibit previously encoded stimulus-outcome contingencies after their reversal, pointing to a critical role of the LHb and of its inputs onto the RMTg in outcome-specific conditioned inhibition in appetitive settings. These findings are consistent with the developing view that the LHb promotes a negative reward prediction error in Pavlovian conditioning. SIGNIFICANCE STATEMENT Stimuli that positively or negatively predict rewarding outcomes influence choice between actions that deliver those outcomes. Previous studies have found that a positive predictor of a specific outcome biases choice toward actions delivering that outcome. In contrast, a negative predictor of an outcome biases choice away from actions earning that outcome and toward other actions. Here we reveal that the lateral habenula is critical for negative predictors, but not positive predictors, to affect choice. Furthermore, these effects were found to require activation of lateral habenula inputs to the rostromedial tegmental nucleus. These results are consistent with the view that the lateral habenula establishes inhibitory relationships between stimuli and food outcomes and computes a negative prediction error in Pavlovian conditioning. Copyright © 2017 the authors 0270-6474/17/3710932-11$15.00/0.

Solar array/spacecraft biasing

NASA Technical Reports Server (NTRS)

Fitzgerald, D. J.

1981-01-01

Biasing techniques and their application to the control of spacecraft potential is discussed. Normally when a spacecraft is operated with ion thrusters, the spacecraft will be 10-20 volts negative of the surrounding plasma. This will affect scientific measurements and will allow ions from the charge-exchange plasma to bombard the spacecraft surfaces with a few tens of volts of energy. This condition may not be tolerable. A proper bias system is described that can bring the spacecraft to or near the potential of the surrounding plasma.

Revelation of Influencing Factors in Overall Codon Usage Bias of Equine Influenza Viruses

PubMed Central

Bhatia, Sandeep; Sood, Richa; Selvaraj, Pavulraj

2016-01-01

Equine influenza viruses (EIVs) of H3N8 subtype are culprits of severe acute respiratory infections in horses, and are still responsible for significant outbreaks worldwide. Adaptability of influenza viruses to a particular host is significantly influenced by their codon usage preference, due to an absolute dependence on the host cellular machinery for their replication. In the present study, we analyzed genome-wide codon usage patterns in 92 EIV strains, including both H3N8 and H7N7 subtypes by computing several codon usage indices and applying multivariate statistical methods. Relative synonymous codon usage (RSCU) analysis disclosed bias of preferred synonymous codons towards A/U-ended codons. The overall codon usage bias in EIVs was slightly lower, and mainly affected by the nucleotide compositional constraints as inferred from the RSCU and effective number of codon (ENc) analysis. Our data suggested that codon usage pattern in EIVs is governed by the interplay of mutation pressure, natural selection from its hosts and undefined factors. The H7N7 subtype was found less fit to its host (horse) in comparison to H3N8, by possessing higher codon bias, lower mutation pressure and much less adaptation to tRNA pool of equine cells. To the best of our knowledge, this is the first report describing the codon usage analysis of the complete genomes of EIVs. The outcome of our study is likely to enhance our understanding of factors involved in viral adaptation, evolution, and fitness towards their hosts. PMID:27119730

A sampling bias in identifying children in foster care using Medicaid data.

PubMed

Rubin, David M; Pati, Susmita; Luan, Xianqun; Alessandrini, Evaline A

2005-01-01

Prior research identified foster care children using Medicaid eligibility codes specific to foster care, but it is unknown whether these codes capture all foster care children. To describe the sampling bias in relying on Medicaid eligibility codes to identify foster care children. Using foster care administrative files linked to Medicaid data, we describe the proportion of children whose Medicaid eligibility was correctly encoded as foster child during a 1-year follow-up period following a new episode of foster care. Sampling bias is described by comparing claims in mental health, emergency department (ED), and other ambulatory settings among correctly and incorrectly classified foster care children. Twenty-eight percent of the 5683 sampled children were incorrectly classified in Medicaid eligibility files. In a multivariate logistic regression model, correct classification was associated with duration of foster care (>9 vs <2 months, odds ratio [OR] 7.67, 95% confidence interval [CI] 7.17-7.97), number of placements (>3 vs 1 placement, OR 4.20, 95% CI 3.14-5.64), and placement in a group home among adjudicated dependent children (OR 1.87, 95% CI 1.33-2.63). Compared with incorrectly classified children, correctly classified foster care children were 3 times more likely to use any services, 2 times more likely to visit the ED, 3 times more likely to make ambulatory visits, and 4 times more likely to use mental health care services (P < .001 for all comparisons). Identifying children in foster care using Medicaid eligibility files is prone to sampling bias that over-represents children in foster care who use more services.

Galaxy bias and primordial non-Gaussianity

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

Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian, E-mail: assassi@ias.edu, E-mail: D.D.Baumann@uva.nl, E-mail: fabians@MPA-Garching.MPG.DE

2015-12-01

We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin ofmore » any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.« less

Exchange bias and perpendicular anisotropy study of ultrathin Pt-Co-Pt-IrMn multilayers sputtered on float glass

NASA Astrophysics Data System (ADS)

Laval, M.; Lüders, U.; Bobo, J. F.

2007-09-01

We have prepared ultrathin Pt-Co-Pt-IrMn polycrystalline multilayers on float-glass substrates by DC magnetron sputtering. We have determined the optimal set of thickness for both Pt layers, the Co layer and the IrMn biasing layer so that these samples exhibit at the same time out-of-plane magnetic anisotropy and exchange bias. Kerr microscopy domain structure imaging evidences an increase of nucleation rate accompanied with inhomogeneous magnetic behavior in the case of exchange-biased films compared to Pt-Co-Pt trilayers. Polar hysteresis loops are measured in obliquely applied magnetic field conditions, allowing us to determine both perpendicular anisotropy effective constant Keff and exchange-bias coupling JE, which are significantly different from the ones determined by standard switching field measurements.

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass.

PubMed

Dabros, Michal; Dennewald, Danielle; Currie, David J; Lee, Mark H; Todd, Robert W; Marison, Ian W; von Stockar, Urs

2009-02-01

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory results.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

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

Evans, Stuart; Marchand, Roger; Ackerman, Thomas

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

NASA Astrophysics Data System (ADS)

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; Donner, Leo; Golaz, Jean-Christophe; Seman, Charles

2017-12-01

We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

DOE PAGES

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; ...

2017-11-16

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Dark channels in resonant tunneling transport through artificial atoms.

PubMed

Vaz, Eduardo; Kyriakidis, Jordan

2008-07-14

We investigate sequential tunneling through a multilevel quantum dot confining multiple electrons in the regime where several channels are available for transport within the bias window. By analyzing solutions to the master equations of the reduced density matrix, we give general conditions on when the presence of a second transport channel in the bias window quenches transport through the quantum dot. These conditions are in terms of distinct tunneling anisotropies which may aid in explaining the occurrence of negative differential conductance in quantum dots in the nonlinear regime.

Instrumental variables as bias amplifiers with general outcome and confounding.

PubMed

Ding, P; VanderWeele, T J; Robins, J M

2017-06-01

Drawing causal inference with observational studies is the central pillar of many disciplines. One sufficient condition for identifying the causal effect is that the treatment-outcome relationship is unconfounded conditional on the observed covariates. It is often believed that the more covariates we condition on, the more plausible this unconfoundedness assumption is. This belief has had a huge impact on practical causal inference, suggesting that we should adjust for all pretreatment covariates. However, when there is unmeasured confounding between the treatment and outcome, estimators adjusting for some pretreatment covariate might have greater bias than estimators without adjusting for this covariate. This kind of covariate is called a bias amplifier, and includes instrumental variables that are independent of the confounder, and affect the outcome only through the treatment. Previously, theoretical results for this phenomenon have been established only for linear models. We fill in this gap in the literature by providing a general theory, showing that this phenomenon happens under a wide class of models satisfying certain monotonicity assumptions. We further show that when the treatment follows an additive or multiplicative model conditional on the instrumental variable and the confounder, these monotonicity assumptions can be interpreted as the signs of the arrows of the causal diagrams.

Attention Training to Reduce Attention Bias and Social Stressor Reactivity: An Attempt to Replicate and Extend Previous Findings

PubMed Central

Julian, Kristin; Beard, Courtney; Schmidt, Norman B.; Powers, Mark B.; Smits, Jasper A. J.

2012-01-01

Cognitive theories suggest that social anxiety is maintained, in part, by an attentional bias toward threat. Recent research shows that a single session of attention modification training (AMP) reduces attention bias and vulnerability to a social stressor (Amir, Weber, Beard, Bomyea, & Taylor, 2008). In addition, exercise may augment the effects of attention training by its direct effects on attentional control and inhibition, thereby allowing participants receiving the AMP to more effectively disengage attention from the threatening cues and shift attention to the neutral cues. We attempted to replicate and extend previous findings by randomizing participants (N = 112) to a single session of: a) Exercise + attention training (EX + AMP); b) Rest + attention training (REST + AMP); c) Exercise + attention control condition (EX + ACC); or d) Rest + attention control condition (REST + ACC) prior to completing a public speaking challenge. We used identical assessment and training procedures to those employed by Amir et al. (2008). Results showed there was no effect of attention training on attention bias or anxiety reactivity to the speech challenge and no interactive effects of attention training and exercise on attention bias or anxiety reactivity to the speech challenge. The failure to replicate previous findings is discussed. PMID:22466022

A study of electromigration behaviors of Ge2Sb2Te5 chalcogenide nano-strips subjected to pulse bias

NASA Astrophysics Data System (ADS)

Huang, Yin-Hsien; Hsieh, Tsung-Eong

2017-07-01

Electromigration (EM) behaviors of pristine Ge2Sb2Te5 (GST) and cerium-doped GST (Ce-GST) nano-strips were investigated by the mean-time-to-failure (MTTF) tests under the pulse bias at the conditions of pulse frequency (f) ranging from 1 to 25 MHz and duty cycle ranging from 50% to 80%. Analytical results indicated that, at f greater than 10 MHz, the EM failure of GST nano-strips in pulse bias environment could be depicted by the ‘average current model’. With the aid of Black’s theory, the activation energies (E a) of EM process under pulse bias were found to be 0.63 and 0.56 eV for GST and Ce-GST nano-strips, respectively. The E a values were comparatively smaller than those observed in direct-current MTTF test of GST thin-film samples, implying the enhancement of surface diffusion and skin effect in GST nano-strips. The morphology and composition analyses indicated that the electrostatic and the electron-wind forces might simultaneously involve in the mass transport in GST nano-strips under the test conditions of this study. The composition analysis also revealed that doping could not effectively alleviate the element segregation in GST subjected to electrical bias.

A Judgement Bias Test to Assess Affective State and Potential Therapeutics in a Rat Model of Chemotherapy-Induced Mucositis.

PubMed

George, Rebecca P; Barker, Timothy H; Lymn, Kerry A; Bigatton, Dylan A; Howarth, Gordon S; Whittaker, Alexandra L

2018-05-29

Chemotherapy-induced mucositis is an extremely painful condition that occurs in 40-60% of patients undergoing chemotherapy. As mucositis currently has no effective treatment, and due to the self-limiting nature of the condition, the major treatment aims are to manage symptoms and limit pain with significance placed on improving patient quality of life. Rodent models are frequently used in mucositis research. These investigations typically assess pathological outcomes, yet fail to include a measure of affective state; the key therapeutic goal. Assessment of cognitive biases is a novel approach to determining the affective state of animals. Consequently, this study aimed to validate a cognitive bias test through a judgement bias paradigm to measure affective state in a rat model of chemotherapy-induced intestinal mucositis. Rats with intestinal mucositis demonstrated a negative affective state, which was partially ameliorated by analgesic administration, whilst healthy rats showed an optimistic response. This study concluded that the judgement bias test was able to evaluate the emotional state of rats with chemotherapy-induced mucositis. These findings provide a foundation for future refinement to the experimental design associated with the animal model that will expedite successful transitioning of novel therapeutics to clinical practice, and also improve humane endpoint implementation.

Real time optical edge enhancement using a Hughes liquid crystal light valve

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1989-01-01

The discovery of an edge enhancement effect in using a Hughes CdS liquid crystal light valve (LCLV) is reported. An edge-enhanced version of the input writing image can be directly obtained by operating the LCLV at a lower bias frequency and bias voltage. Experimental conditions in which this edge enhancement effect can be optimized are described. Experimental results show that the SNR of the readout image using this technique is superior to that obtained using high-pass filtering. The repeatability of this effect is confirmed by obtaining an edge enhancement result using two different Hughes LCLVs. The applicability of this effect to improve discrimination capability in optical pattern recognition is addressed. The results show that the Hughes LCLV can be used in both continuous tone and edge-enhancing modes by simply adjusting its bias conditions.

Fluid simulation of the bias effect in inductive/capacitive discharges

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

Zhang, Yu-Ru; Research Group PLASMANT, Department of Chemistry, University of Antwerp, Universiteitsplein 1, Wilrijk, BE-2610 Antwerp; Gao, Fei

Computer simulations are performed for an argon inductively coupled plasma (ICP) with a capacitive radio-frequency bias power, to investigate the bias effect on the discharge mode transition and on the plasma characteristics at various ICP currents, bias voltages, and bias frequencies. When the bias frequency is fixed at 13.56 MHz and the ICP current is low, e.g., 6 A, the spatiotemporal averaged plasma density increases monotonically with bias voltage, and the bias effect is already prominent at a bias voltage of 90 V. The maximum of the ionization rate moves toward the bottom electrode, which indicates clearly the discharge mode transition in inductive/capacitivemore » discharges. At higher ICP currents, i.e., 11 and 13 A, the plasma density decreases first and then increases with bias voltage, due to the competing mechanisms between the ion acceleration power dissipation and the capacitive power deposition. At 11 A, the bias effect is still important, but it is noticeable only at higher bias voltages. At 13 A, the ionization rate is characterized by a maximum at the reactor center near the dielectric window at all selected bias voltages, which indicates that the ICP power, instead of the bias power, plays a dominant role under this condition, and no mode transition is observed. Indeed, the ratio of the bias power to the total power is lower than 0.4 over a wide range of bias voltages, i.e., 0–300 V. Besides the effect of ICP current, also the effect of various bias frequencies is investigated. It is found that the modulation of the bias power to the spatiotemporal distributions of the ionization rate at 2 MHz is strikingly different from the behavior observed at higher bias frequencies. Furthermore, the minimum of the plasma density appears at different bias voltages, i.e., 120 V at 2 MHz and 90 V at 27.12 MHz.« less

Sex-ratio biasing towards daughters among lower-ranking co-wives in Rwanda.

PubMed

Pollet, Thomas V; Fawcett, Tim W; Buunk, Abraham P; Nettle, Daniel

2009-12-23

There is considerable debate as to whether human females bias the sex ratio of their offspring as a function of their own condition. We apply the Trivers-Willard prediction-that mothers in poor condition will overproduce daughters-to a novel measure of condition, namely wife rank within a polygynous marriage. Using a large-scale sample of over 95 000 Rwandan mothers, we show that lower-ranking polygynous wives do indeed have significantly more daughters than higher-ranking polygynous wives and monogamously married women. This effect remains when controlling for potential confounds such as maternal age. We discuss these results in reference to previous work on sex-ratio adjustment in humans.

Biased Feedback in Spatial Recall Yields a Violation of Delta Rule Learning

PubMed Central

Lipinski, John; Spencer, John P.; Samuelson, Larissa K.

2010-01-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4° towards the vertical axis (Towards condition) or 4° further away from the vertical axis (Away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) in the Away condition produced a stronger experience-dependent change over blocks than in the Towards condition. This violates delta rule learning. Subsequent simulations of the Dynamic Field Theory of spatial cognition provide a theoretically unified account of these results. PMID:20702881

Biased feedback in spatial recall yields a violation of delta rule learning.

PubMed

Lipinski, John; Spencer, John P; Samuelson, Larissa K

2010-08-01

This study investigates whether inductive processes influencing spatial memory performance generalize to supervised learning scenarios with differential feedback. After providing a location memory response in a spatial recall task, participants received visual feedback showing the target location. In critical blocks, feedback was systematically biased either 4 degrees toward the vertical axis (toward condition) or 4 degrees farther away from the vertical axis (away condition). Results showed that the weaker teaching signal (i.e., a smaller difference between the remembered location and the feedback location) produced a stronger experience-dependent change over blocks in the away condition than in the toward condition. This violates delta rule learning. Subsequent simulations of the dynamic field theory of spatial cognition provide a theoretically unified account of these results.

The Existence of Implicit Racial Bias in Nursing Faculty

ERIC Educational Resources Information Center

Fitzsimmons, Kathleen A.

2009-01-01

This study examined the existence of implicit racial bias in nursing faculty using the Implicit Association Test (IAT). It was conducted within a critical race theory framework where race was seen as a permanent, pervasive, and systemic condition, not an individual process. The study was fueled by data showing continued disparate academic and…

Biasing Influences on Test Level Assignments for Hearing Impaired Students.

ERIC Educational Resources Information Center

Wolk, Steve

1985-01-01

Possible biasing influences of student characteristics were considered for teachers' judgments of appropriate test level assignments for about 1,300 hearing impaired special education students. Analyses indicated the presence of strong influences of race and severity of handicapping condition, as well as of sex, upon change in level assignments,…

Arguing to Agree: Mitigating My-Side Bias Through Consensus-Seeking Dialogue

ERIC Educational Resources Information Center

Felton, Mark; Crowell, Amanda; Liu, Tina

2015-01-01

Research has shown that novice writers tend to ignore opposing viewpoints when framing and developing arguments in writing, a phenomenon commonly referred to as my-side bias. In the present article, we contrast two forms of argumentative discourse conditions (arguing to persuade and arguing to reach consensus) and examine their differential…

How to Explain Receptivity to Conjunction-Fallacy Inhibition Training: Evidence from the Iowa Gambling Task

ERIC Educational Resources Information Center

Cassotti, Mathieu; Moutier, Sylvain

2010-01-01

Intuitive predictions and judgments under conditions of uncertainty are often mediated by judgment heuristics that sometimes lead to biases. Using the classical conjunction bias example, the present study examines the relationship between receptivity to metacognitive executive training and emotion-based learning ability indexed by Iowa Gambling…

Quantile regression reveals hidden bias and uncertainty in habitat models

Treesearch

Brian S. Cade; Barry R. Noon; Curtis H. Flather

2005-01-01

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias...

Selective attention to emotional pictures as a function of gambling motives in problem and nonproblem gamblers.

PubMed

Hudson, Amanda; Jacques, Sophie; Stewart, Sherry H

2013-12-01

Problem gambling may reflect a maladaptive means of fulfilling specific affect-regulation motives, such as enhancing positive affect or coping with negative affect. Research with clinical populations indicates that disorders with prominent affective symptoms are characterized by attentional biases for symptom-congruent information. Thus, we assessed whether problem gamblers with enhancement motives for gambling would demonstrate attentional biases for positive emotional information, relative to other types of emotional information, and problem gamblers with coping motives for gambling would demonstrate attentional biases for negative emotional information, compared with other types of emotional information. In addition, we expected motive-congruent biases to be stronger in problem gamblers than nonproblem gamblers. To test these hypotheses, problem and nonproblem gamblers received an emotional orienting task in which neutral, negative, and positive pictorial cues appeared to one side of the computer screen, followed by target words in cued or uncued locations. In a look-away condition, participants had to shift attention away from pictures to respond to predominantly uncued targets, whereas in a look-toward condition, they had to orient to pictures to categorize predominantly cued targets. The results revealed motive-congruent orienting biases and disengagement lags for emotional pictures in problem gamblers. The link between motives and affective biases was less apparent in nonproblem gamblers. Results suggest that attentional measures may provide a useful complement to the subjective methodologies that are typically employed in studying problem gamblers. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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

NASA Astrophysics Data System (ADS)

Arya, Gaurav; Schlick, Tamar

2007-01-01

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

Silicon Photomultiplier charaterization

NASA Astrophysics Data System (ADS)

Munoz, Leonel; Osornio, Leo; Para, Adam

2014-03-01

Silicon Photo Multiples (SiPM's) are relatively new photon detectors. They offer many advantages compared to photo multiplier tubes (PMT's) such as insensitivity to magnetic field, robustness at varying lighting levels, and low cost. The SiPM output wave forms are poorly understood. The experiment conducted collected waveforms of responses of Hamamatsu SiPM to incident laser pulse at varying temperatures and bias voltages. Ambient noise was characterized at all temperatures and bias voltages by averaging the waveforms. Pulse shape of the SiPM response was determined under different operating conditions: the pulse shape is nearly independent of the bias voltage but exhibits strong variation with temperature, consistent with the temperature variation of the quenching resistor. Amplitude of responses of the SiPM to low intensity laser light shows many peaks corresponding to the detection of 1,2,3 etc. photons. Amplitude of these pulses depends linearly on the bias voltage, enabling determination of the breakdown voltage at each temperature. Poisson statistics has been used to determine the average number of detected photons at each operating conditions. Department of Education Grant No. P0315090007 and the Department of Energy/ Fermi National Accelerator Laboratory.

Calculation of the radial electric field with RF sheath boundary conditions in divertor geometry

NASA Astrophysics Data System (ADS)

Gui, B.; Xia, T. Y.; Xu, X. Q.; Myra, J. R.; Xiao, X. T.

2018-02-01

The equilibrium electric field that results from an imposed DC bias potential, such as that driven by a radio frequency (RF) sheath, is calculated using a new minimal two-field model in the BOUT++ framework. Biasing, using an RF-modified sheath boundary condition, is applied to an axisymmetric limiter, and a thermal sheath boundary is applied to the divertor plates. The penetration of the bias potential into the plasma is studied with a minimal self-consistent model that includes the physics of vorticity (charge balance), ion polarization currents, force balance with E× B , ion diamagnetic flow (ion pressure gradient) and parallel electron charge loss to the thermal and biased sheaths. It is found that a positive radial electric field forms in the scrape-off layer and it smoothly connects across the separatrix to the force-balanced radial electric field in the closed flux surface region. The results are in qualitative agreement with the experiments. Plasma convection related to the E× B net flow in front of the limiter is also obtained from the calculation.

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

Cosmic shear bias and calibration in dark energy studies

NASA Astrophysics Data System (ADS)

Taylor, A. N.; Kitching, T. D.

2018-07-01

With the advent of large-scale weak lensing surveys there is a need to understand how realistic, scale-dependent systematics bias cosmic shear and dark energy measurements, and how they can be removed. Here, we show how spatially varying image distortions are convolved with the shear field, mixing convergence E and B modes, and bias the observed shear power spectrum. In practise, many of these biases can be removed by calibration to data or simulations. The uncertainty in this calibration is marginalized over, and we calculate how this propagates into parameter estimation and degrades the dark energy Figure-of-Merit. We find that noise-like biases affect dark energy measurements the most, while spikes in the bias power have the least impact. We argue that, in order to remove systematic biases in cosmic shear surveys and maintain statistical power, effort should be put into improving the accuracy of the bias calibration rather than minimizing the size of the bias. In general, this appears to be a weaker condition for bias removal. We also investigate how to minimize the size of the calibration set for a fixed reduction in the Figure-of-Merit. Our results can be used to correctly model the effect of biases and calibration on a cosmic shear survey, assess their impact on the measurement of modified gravity and dark energy models, and to optimize survey and calibration requirements.

Validation of a weather forecast model at radiance level against satellite observations allowing quantification of temperature, humidity, and cloud-related biases

NASA Astrophysics Data System (ADS)

Bani Shahabadi, Maziar; Huang, Yi; Garand, Louis; Heilliette, Sylvain; Yang, Ping

2016-09-01

An established radiative transfer model (RTM) is adapted for simulating all-sky infrared radiance spectra from the Canadian Global Environmental Multiscale (GEM) model in order to validate its forecasts at the radiance level against Atmospheric InfraRed Sounder (AIRS) observations. Synthetic spectra are generated for 2 months from short-term (3-9 h) GEM forecasts. The RTM uses a monthly climatological land surface emissivity/reflectivity atlas. An updated ice particle optical property library was introduced for cloudy radiance calculations. Forward model brightness temperature (BT) biases are assessed to be of the order of ˜1 K for both clear-sky and overcast conditions. To quantify GEM forecast meteorological variables biases, spectral sensitivity kernels are generated and used to attribute radiance biases to surface and atmospheric temperatures, atmospheric humidity, and clouds biases. The kernel method, supplemented with retrieved profiles based on AIRS observations in collocation with a microwave sounder, achieves good closure in explaining clear-sky radiance biases, which are attributed mostly to surface temperature and upper tropospheric water vapor biases. Cloudy-sky radiance biases are dominated by cloud-induced radiance biases. Prominent GEM biases are identified as: (1) too low surface temperature over land, causing about -5 K bias in the atmospheric window region; (2) too high upper tropospheric water vapor, inducing about -3 K bias in the water vapor absorption band; (3) too few high clouds in the convective regions, generating about +10 K bias in window band and about +6 K bias in the water vapor band.

Attrition analysed in five waves of a longitudinal yearly survey of smokers: findings from the ITC Netherlands survey.

PubMed

Zethof, Dennis; Nagelhout, Gera E; de Rooij, Mark; Driezen, Pete; Fong, Geoffrey T; van den Putte, Bas; Hummel, Karin; de Vries, Hein; Thompson, Mary E; Willemsen, Marc C

2016-08-01

Attrition bias can affect the external validity of findings. This article analyses attrition bias and assesses the effectiveness of replenishment samples on demographic and smoking-related characteristics for the International Tobacco Control Netherlands Survey, a longitudinal survey among smokers. Attrition analyses were conducted for the first five survey waves (2008-12). We assessed, including and excluding replenishment samples, whether the demographic composition of the samples changed between the first and fifth waves. Replenishment samples were tailored to ensure the sample remained representative of the smoking population. We also constructed a multivariable survival model of attrition that included all five waves with replenishment samples. Of the original 1820 respondents recruited in 2008, 46% participated again in 2012. Demographic differences between waves due to attrition were generally small and replenishment samples tended to minimize them further. The multivariable survival analysis revealed that only two of the 10 variables analysed were significant predictors of attrition: a weak effect for gender (men dropped out more often) and weak to moderate effects for age (respondents aged 15-24 years dropped out more than aged 25-39 years, who dropped out more than those aged 40+ years). Weak to moderate attrition effects were found for men and younger age groups. This information could be used to minimize respondent attrition. Our findings suggest that sampling weights and tailored replenishment samples can effectively compensate for attrition effects. This is already being done for the International Tobacco Control Netherlands Survey, including the categories that significantly predicted attrition in this study. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

Fractional Brownian motion and multivariate-t models for longitudinal biomedical data, with application to CD4 counts in HIV-positive patients.

PubMed

Stirrup, Oliver T; Babiker, Abdel G; Carpenter, James R; Copas, Andrew J

2016-04-30

Longitudinal data are widely analysed using linear mixed models, with 'random slopes' models particularly common. However, when modelling, for example, longitudinal pre-treatment CD4 cell counts in HIV-positive patients, the incorporation of non-stationary stochastic processes such as Brownian motion has been shown to lead to a more biologically plausible model and a substantial improvement in model fit. In this article, we propose two further extensions. Firstly, we propose the addition of a fractional Brownian motion component, and secondly, we generalise the model to follow a multivariate-t distribution. These extensions are biologically plausible, and each demonstrated substantially improved fit on application to example data from the Concerted Action on SeroConversion to AIDS and Death in Europe study. We also propose novel procedures for residual diagnostic plots that allow such models to be assessed. Cohorts of patients were simulated from the previously reported and newly developed models in order to evaluate differences in predictions made for the timing of treatment initiation under different clinical management strategies. A further simulation study was performed to demonstrate the substantial biases in parameter estimates of the mean slope of CD4 decline with time that can occur when random slopes models are applied in the presence of censoring because of treatment initiation, with the degree of bias found to depend strongly on the treatment initiation rule applied. Our findings indicate that researchers should consider more complex and flexible models for the analysis of longitudinal biomarker data, particularly when there are substantial missing data, and that the parameter estimates from random slopes models must be interpreted with caution. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Empirical performance of the self-controlled case series design: lessons for developing a risk identification and analysis system.

PubMed

Suchard, Marc A; Zorych, Ivan; Simpson, Shawn E; Schuemie, Martijn J; Ryan, Patrick B; Madigan, David

2013-10-01

The self-controlled case series (SCCS) offers potential as an statistical method for risk identification involving medical products from large-scale observational healthcare data. However, analytic design choices remain in encoding the longitudinal health records into the SCCS framework and its risk identification performance across real-world databases is unknown. To evaluate the performance of SCCS and its design choices as a tool for risk identification in observational healthcare data. We examined the risk identification performance of SCCS across five design choices using 399 drug-health outcome pairs in five real observational databases (four administrative claims and one electronic health records). In these databases, the pairs involve 165 positive controls and 234 negative controls. We also consider several synthetic databases with known relative risks between drug-outcome pairs. We evaluate risk identification performance through estimating the area under the receiver-operator characteristics curve (AUC) and bias and coverage probability in the synthetic examples. The SCCS achieves strong predictive performance. Twelve of the twenty health outcome-database scenarios return AUCs >0.75 across all drugs. Including all adverse events instead of just the first per patient and applying a multivariate adjustment for concomitant drug use are the most important design choices. However, the SCCS as applied here returns relative risk point-estimates biased towards the null value of 1 with low coverage probability. The SCCS recently extended to apply a multivariate adjustment for concomitant drug use offers promise as a statistical tool for risk identification in large-scale observational healthcare databases. Poor estimator calibration dampens enthusiasm, but on-going work should correct this short-coming.

Measurement issues in research on social support and health.

PubMed Central

Dean, K; Holst, E; Kreiner, S; Schoenborn, C; Wilson, R

1994-01-01

STUDY OBJECTIVE--The aims were: (1) to identify methodological problems that may explain the inconsistencies and contradictions in the research evidence on social support and health, and (2) to validate a frequently used measure of social support in order to determine whether or not it could be used in multivariate analyses of population data in research on social support and health. DESIGN AND METHODS--Secondary analysis of data collected in a cross sectional survey of a multistage cluster sample of the population of the United States, designed to study relationships in behavioural, social support and health variables. Statistical models based on item response theory and graph theory were used to validate the measure of social support to be used in subsequent analyses. PARTICIPANTS--Data on 1755 men and women aged 20 to 64 years were available for the scale validation. RESULTS--Massive evidence of item bias was found for all items of a group membership subscale. The most serious problems were found in relationship to an item measuring membership in work related groups. Using that item in the social network scale in multivariate analyses would distort findings on the statistical effects of education, employment status, and household income. Evidence of item bias was also found for a sociability subscale. When marital status was included to create what is called an intimate contacts subscale, the confounding grew worse. CONCLUSIONS--The composite measure of social network is not valid and would seriously distort the findings of analyses attempting to study relationships between the index and other variables. The findings show that valid measurement is a methodological issue that must be addressed in scientific research on population health. PMID:8189179

Bias Toward Psychodynamic Therapy: Framing the Problem and Working Toward a Solution.

PubMed

Plakun, Eric M

2017-09-01

Although psychodynamic therapy (PDT) is an evidence-based intervention for a broad spectrum of psychiatric conditions, there is often notable bias in the way PDT is depicted both in the popular media and in the scientific literature. This has contributed to a negative view of PDT, which hampers both patient access to this treatment and researcher access to funding for further research on PDT. The adverse effects of these distortions and biases are detrimental not only to PDT but also to the overall field of psychotherapy, raising questions about its credibility. Here we summarize current evidence for PDT, describe existing biases, and formulate a set of recommendations to foster a more balanced perspective on PDT.

Forms of attrition in a longitudinal study of religion and health in older adults and implications for sample bias

PubMed Central

Hayward, R. David; Krause, Neal

2014-01-01

The use of longitudinal designs in the field of religion and health makes it important to understand how attrition bias may affect findings in this area. This study examines attrition in a 4-wave, 8-year study of older adults. Attrition resulted in a sample biased towards more educated and more religiously-involved individuals. Conditional linear growth curve models found that trajectories of change for some variables differed among attrition categories. Ineligibles had worsening depression, declining control, and declining attendance. Mortality was associated with worsening religious coping styles. Refusers experienced worsening depression. Nevertheless, there was no evidence of bias in the key religion and health results. PMID:25257794

Forms of Attrition in a Longitudinal Study of Religion and Health in Older Adults and Implications for Sample Bias.

PubMed

Hayward, R David; Krause, Neal

2016-02-01

The use of longitudinal designs in the field of religion and health makes it important to understand how attrition bias may affect findings in this area. This study examines attrition in a 4-wave, 8-year study of older adults. Attrition resulted in a sample biased toward more educated and more religiously involved individuals. Conditional linear growth curve models found that trajectories of change for some variables differed among attrition categories. Ineligibles had worsening depression, declining control, and declining attendance. Mortality was associated with worsening religious coping styles. Refusers experienced worsening depression. Nevertheless, there was no evidence of bias in the key religion and health results.

Bias temperature instability in tunnel field-effect transistors

NASA Astrophysics Data System (ADS)

Mizubayashi, Wataru; Mori, Takahiro; Fukuda, Koichi; Ishikawa, Yuki; Morita, Yukinori; Migita, Shinji; Ota, Hiroyuki; Liu, Yongxun; O'uchi, Shinichi; Tsukada, Junichi; Yamauchi, Hiromi; Matsukawa, Takashi; Masahara, Meishoku; Endo, Kazuhiko

2017-04-01

We systematically investigated the bias temperature instability (BTI) of tunnel field-effect transistors (TFETs). The positive BTI and negative BTI mechanisms in TFETs are the same as those in metal-oxide-semiconductor FETs (MOSFETs). In TFETs, although traps are generated in high-k gate dielectrics by the bias stress and/or the interface state is degraded at the interfacial layer/channel interface, the threshold voltage (V th) shift due to BTI degradation is caused by the traps and/or the degradation of the interface state locating the band-to-band tunneling (BTBT) region near the source/gate edge. The BTI lifetime in n- and p-type TFETs is improved by applying a drain bias corresponding to the operation conditions.

Affect, affective disorder and schizophrenia. A neuropsychological investigation of right hemisphere function.

PubMed

David, A S; Cutting, J C

1990-04-01

Performance on a happy-sad chimeric face test was used to examine the role of right hemisphere activation in positive and negative affect, both normal and abnormal, as well as in schizophrenia. This test is known to elicit a left-sided perceptual bias in right-handed normal subjects. Happy and sad mood in normals did not influence the perceptual bias. Depression and mania were associated with reduced and increased biases respectively, while schizophrenics showed no bias to either side. Possible explanations are right hemisphere hyperfunction in mania, moderate relative hypofunction in depression, and severe relative hypofunction in schizophrenia. The marked difference between mania and schizophrenia supports distinct pathophysiologies underlying the two conditions.

Fear learning circuitry is biased toward generalization of fear associations in posttraumatic stress disorder

PubMed Central

Morey, R A; Dunsmoor, J E; Haswell, C C; Brown, V M; Vora, A; Weiner, J; Stjepanovic, D; Wagner, H R; Brancu, Mira; Marx, Christine E; Naylor, Jennifer C; Van Voorhees, Elizabeth; Taber, Katherine H; Beckham, Jean C; Calhoun, Patrick S; Fairbank, John A; Szabo, Steven T; LaBar, K S

2015-01-01

Fear conditioning is an established model for investigating posttraumatic stress disorder (PTSD). However, symptom triggers may vaguely resemble the initial traumatic event, differing on a variety of sensory and affective dimensions. We extended the fear-conditioning model to assess generalization of conditioned fear on fear processing neurocircuitry in PTSD. Military veterans (n=67) consisting of PTSD (n=32) and trauma-exposed comparison (n=35) groups underwent functional magnetic resonance imaging during fear conditioning to a low fear-expressing face while a neutral face was explicitly unreinforced. Stimuli that varied along a neutral-to-fearful continuum were presented before conditioning to assess baseline responses, and after conditioning to assess experience-dependent changes in neural activity. Compared with trauma-exposed controls, PTSD patients exhibited greater post-study memory distortion of the fear-conditioned stimulus toward the stimulus expressing the highest fear intensity. PTSD patients exhibited biased neural activation toward high-intensity stimuli in fusiform gyrus (P<0.02), insula (P<0.001), primary visual cortex (P<0.05), locus coeruleus (P<0.04), thalamus (P<0.01), and at the trend level in inferior frontal gyrus (P=0.07). All regions except fusiform were moderated by childhood trauma. Amygdala–calcarine (P=0.01) and amygdala–thalamus (P=0.06) functional connectivity selectively increased in PTSD patients for high-intensity stimuli after conditioning. In contrast, amygdala–ventromedial prefrontal cortex (P=0.04) connectivity selectively increased in trauma-exposed controls compared with PTSD patients for low-intensity stimuli after conditioning, representing safety learning. In summary, fear generalization in PTSD is biased toward stimuli with higher emotional intensity than the original conditioned-fear stimulus. Functional brain differences provide a putative neurobiological model for fear generalization whereby PTSD symptoms are triggered by threat cues that merely resemble the index trauma. PMID:26670285

A device adaptive inflow boundary condition for Wigner equations of quantum transport

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

Jiang, Haiyan; Lu, Tiao; Cai, Wei, E-mail: wcai@uncc.edu

2014-02-01

In this paper, an improved inflow boundary condition is proposed for Wigner equations in simulating a resonant tunneling diode (RTD), which takes into consideration the band structure of the device. The original Frensley inflow boundary condition prescribes the Wigner distribution function at the device boundary to be the semi-classical Fermi–Dirac distribution for free electrons in the device contacts without considering the effect of the quantum interaction inside the quantum device. The proposed device adaptive inflow boundary condition includes this effect by assigning the Wigner distribution to the value obtained from the Wigner transform of wave functions inside the device atmore » zero external bias voltage, thus including the dominant effect on the electron distribution in the contacts due to the device internal band energy profile. Numerical results on computing the electron density inside the RTD under various incident waves and non-zero bias conditions show much improvement by the new boundary condition over the traditional Frensley inflow boundary condition.« less

Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities

USGS Publications Warehouse

McNew, Lance B.; Handel, Colleen M.

2015-01-01

Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results indicate that neglecting the effects of site covariates on species detection probabilities may lead to significant bias in estimation of species richness, as well as the inferred relationships between community size and environmental covariates.

Ambient condition bias stress stability of vanadium (IV) oxide phthalocyanine based p-channel organic field-effect transistors

NASA Astrophysics Data System (ADS)

Obaidulla, Sk Md; Singh, Subhash; Mohapatra, Y. N.; Giri, P. K.

2018-01-01

High bias-stress stability and low threshold voltage (V th) shift under ambient conditions are highly desirable for practical applications of organic field-effect transistors (OFETs). We demonstrate here a 20-fold enhancement in the bias-stress stability for hexamethyledisilazane (HMDS) treated vanadium (IV) oxide phthalocyanine (VOPc) based OFETs as compared to the bare VOPc case under ambient conditions. VOPc based OFETs were fabricated on bare (non treated) SiO2 and a HMDS monolayer passivated SiO2 layer, with an operating voltage of 40 V. The devices with top contact gold (Au) electrodes exhibit excellent p-channel behavior with a moderate hole mobility for the HMDS-treated device. It is demonstrated that the time dependent ON-current decay and V th shift can be effectively controlled by using self-assembled monolayers of HMDS on the VOPc layer. For the HMDS-treated case, the bias stress stability study shows the stretched exponential decay of drain current by only ~15% during the long-term operation with constant bias voltage under ambient conditions, while it shows a large decay of  >70% for the nontreated devices operated for 1000 s. The corresponding characteric decay time constant (τ) is 104 s for the HMDS treated case, while that of the the non-treated SiO2 case is only ~480 s under ambient conditions. The inferior performance of the device with bare SiO2 is traced to the charge trapping at the voids in the inter-grain region of the films, while it is almost negligible for the HMDS-treated case, as confirmed from the AFM and XRD analyses. It is believed that HMDS treatment provides an excellent interface with a low density of traps and passivates the dangling bonds, which improve the charge transport characteristics. Also, the surface morphology of the VOPc film clearly influences the device performance. Thus, the HMDS treatment provides a very attractive approach for attaining long-term air stability and a low V th shift for the VOPc based OFET devices.

Intermittent regime of brain activity at the early, bias-guided stage of perceptual learning.

PubMed

Nikolaev, Andrey R; Gepshtein, Sergei; van Leeuwen, Cees

2016-11-01

Perceptual learning improves visual performance. Among the plausible mechanisms of learning, reduction of perceptual bias has been studied the least. Perceptual bias may compensate for lack of stimulus information, but excessive reliance on bias diminishes visual discriminability. We investigated the time course of bias in a perceptual grouping task and studied the associated cortical dynamics in spontaneous and evoked EEG. Participants reported the perceived orientation of dot groupings in ambiguous dot lattices. Performance improved over a 1-hr period as indicated by the proportion of trials in which participants preferred dot groupings favored by dot proximity. The proximity-based responses were compromised by perceptual bias: Vertical groupings were sometimes preferred to horizontal ones, independent of dot proximity. In the evoked EEG activity, greater amplitude of the N1 component for horizontal than vertical responses indicated that the bias was most prominent in conditions of reduced visual discriminability. The prominence of bias decreased in the course of the experiment. Although the bias was still prominent, prestimulus activity was characterized by an intermittent regime of alternating modes of low and high alpha power. Responses were more biased in the former mode, indicating that perceptual bias was deployed actively to compensate for stimulus uncertainty. Thus, early stages of perceptual learning were characterized by episodes of greater reliance on prior visual preferences, alternating with episodes of receptivity to stimulus information. In the course of learning, the former episodes disappeared, and biases reappeared only infrequently.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant.

PubMed

Lender, Anja; Meule, Adrian; Rinck, Mike; Brockmeyer, Timo; Blechert, Jens

2018-06-01

Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them "near" with a joystick that controls a corresponding image zoom. One version of the task couples movement direction with image content-independent features, for example, pulling blue-framed images and pushing green-framed images regardless of content ('irrelevant feature version'). However, participants might selectively attend to this feature and ignore image content and, thus, such a task setup might underestimate existing biases. The present study tested this attention account by comparing two irrelevant feature versions of the task with either a more peripheral (image frame color: green vs. blue) or central (small circle vs. cross overlaid over the image content) image feature as response instruction to a 'relevant feature version', in which participants responded to the image content, thus making it impossible to ignore that content. Images of chocolate-containing foods and of objects were used, and several trait and state measures were acquired to validate the obtained biases. Results revealed a robust approach bias towards food only in the relevant feature condition. Interestingly, a positive correlation with state chocolate craving during the task was found when all three conditions were combined, indicative of criterion validity of all three versions. However, no correlations were found with trait chocolate craving. Results provide a strong case for the relevant feature version of the AAT for bias measurement. They also point to several methodological avenues for future research around selective attention in the irrelevant versions and task validity regarding trait vs. state variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

Recursive estimators of mean-areal and local bias in precipitation products that account for conditional bias

NASA Astrophysics Data System (ADS)

Zhang, Yu; Seo, Dong-Jun

2017-03-01

This paper presents novel formulations of Mean field bias (MFB) and local bias (LB) correction schemes that incorporate conditional bias (CB) penalty. These schemes are based on the operational MFB and LB algorithms in the National Weather Service (NWS) Multisensor Precipitation Estimator (MPE). By incorporating CB penalty in the cost function of exponential smoothers, we are able to derive augmented versions of recursive estimators of MFB and LB. Two extended versions of MFB algorithms are presented, one incorporating spatial variation of gauge locations only (MFB-L), and the second integrating both gauge locations and CB penalty (MFB-X). These two MFB schemes and the extended LB scheme (LB-X) are assessed relative to the original MFB and LB algorithms (referred to as MFB-O and LB-O, respectively) through a retrospective experiment over a radar domain in north-central Texas, and through a synthetic experiment over the Mid-Atlantic region. The outcome of the former experiment indicates that introducing the CB penalty to the MFB formulation leads to small, but consistent improvements in bias and CB, while its impacts on hourly correlation and Root Mean Square Error (RMSE) are mixed. Incorporating CB penalty in LB formulation tends to improve the RMSE at high rainfall thresholds, but its impacts on bias are also mixed. The synthetic experiment suggests that beneficial impacts are more conspicuous at low gauge density (9 per 58,000 km2), and tend to diminish at higher gauge density. The improvement at high rainfall intensity is partly an outcome of the conservativeness of the extended LB scheme. This conservativeness arises in part from the more frequent presence of negative eigenvalues in the extended covariance matrix which leads to no, or smaller incremental changes to the smoothed rainfall amounts.

Cognitive bias modification as an add-on treatment in clinical depression: Results from a placebo-controlled, single-blinded randomized control trial.

PubMed

Vrijsen, Janna N; Fischer, Verena S; Müller, Bernhard W; Scherbaum, Norbert; Becker, Eni S; Rinck, Mike; Tendolkar, Indira

2018-06-06

Only 60% of depressed patients respond sufficiently to treatment, so there is a dire need for novel approaches to improve treatment effects. Cognitive Bias Modification (CBM) may be an effective and easily implemented computerized add-on to treatment-as-usual. Therefore, we investigated the effects of a positivity-attention training and a positivity-approach training compared to control trainings. In a blinded randomized-controlled design, 139 depressed inpatients received either the CBM Attention Dot-Probe Training (DPT) or the CBM Approach-Avoidance Training (AAT), next to treatment as usual. N = 121 finished all four training sessions. Both trainings had an active and a control condition. In both active conditions, patients were trained to preferentially process generally positive pictures over neutral pictures. Depressive symptom severity was assessed before and after CBM, and positivity bias was measured at the start and end of each session. Clinician-rated depressive symptom severity decreased more in patients who received the active condition of the DPT or the AAT compared to patients in the control conditions. Significant change in positivity bias was found for the DPT (not the AAT), but did not mediate the effect of the training on depressive symptoms. The results suggest that both types of CBM (i.e., DPT and AAT) may provide a fitting add-on treatment option for clinical depression. The working mechanisms and optimal dose of CBM trainings, plus their possible combination, should be examined in more detail. Copyright © 2018. Published by Elsevier B.V.

Breastfeeding structure as a test of parental investment theory in Papua New Guinea.

PubMed

Tracer, David P

2009-01-01

Evolutionary parental investment theory predicts that parents invest preferentially in offspring best able to translate investments into fitness payoffs. It has also been proposed that where the reproductive prospects of offspring are directly correlated with parental investment and variance in fertility is higher for males than females, parents in better condition should bias investment toward males while those in poorer condition should bias investment toward females. Lactation is arguably among the costliest forms of investment expended by mothers and is thus expected to be allocated in ways consistent with fitness payoffs. Quantitative data collected among 110 Papua New Guinean mother-infant pairs during 470 h of focal follows on nursing frequency and duration and responses to infant demands by maternal and offspring characteristics are presented to provide empirically-based descriptions of infant care and tests of evolutionary parental investment theory. Results indicate that mothers show very high levels of investment in offspring. However, although breastfeeding in developing countries is often characterized as on-demand, fussing and crying by infants were only attended to with breastfeeding about 30% of the time. Contrary to expectations of parental investment theory that parents should invest less in poorer quality offspring, mothers increased investment in offspring in poorer condition. The expectation that mothers in better condition would bias investment toward male offspring was also not supported; better nourished mothers biased investment toward female offspring. This study illustrates how infant feeding data may be used for testing larger evolutionary questions such as those derived from parental investment theory.

Bias of cylinder diameter estimation from ground-based laser scanners with different beam widths: A simulation study

NASA Astrophysics Data System (ADS)

Forsman, Mona; Börlin, Niclas; Olofsson, Kenneth; Reese, Heather; Holmgren, Johan

2018-01-01

In this study we have investigated why diameters of tree stems, which are approximately cylindrical, are often overestimated by mobile laser scanning. This paper analyzes the physical processes when using ground-based laser scanning that may contribute to a bias when estimating cylinder diameters using circle-fit methods. A laser scanner simulator was implemented and used to evaluate various properties, such as distance, cylinder diameter, and beam width of a laser scanner-cylinder system to find critical conditions. The simulation results suggest that a positive bias of the diameter estimation is expected. Furthermore, the bias follows a quadratic function of one parameter - the relative footprint, i.e., the fraction of the cylinder width illuminated by the laser beam. The quadratic signature opens up a possibility to construct a compensation model for the bias.

The role of observer bias in the North American Breeding Bird Survey

USGS Publications Warehouse

Faanes, C.A.; Bystrak, D.

1981-01-01

Ornithologists sampling breeding bird populations are subject to a number of biases in bird recognition and identification. Using Breeding Bird Survey data, these biases are examined qualitatively and quantitatively, and their effects on counts are evaluated. Differences in hearing ability and degree of expertise are the major observer biases considered. Other, more subtle influences are also discussed, including unfamiliar species, resolution, imagination, similar songs and attitude and condition of observers. In most cases, welltrained observers are comparable in ability and their differences contribute little beyond sampling error. However, just as hearing loss can affect results, so can an unprepared observer. These biases are important because they can reduce the credibility of any bird population sampling effort. Care is advised in choosing observers and in interpreting and using results when observers of variable competence are involved.

Fore and aft elastic response characteristics of size 34x9.9, type 7, 14 ply-rated aircraft tires of bias ply, bias belted, and radial belted design. M.S. Thesis - George Washington Univ., Washington, D. C.

NASA Technical Reports Server (NTRS)

Tanner, J. A.

1973-01-01

An investigation was conducted to determine the fore-and-aft elastic response characteristics of aircraft tires of bias ply, bias-belted, and radial-belted design. The investigation consisted of: (1)static and rolling tests, (2)a statistical analysis which related the measured tire elastic characteristics to variations in the vertical load, inflation pressure, braking force and/or tire vertical deflection, and (3) a semi-empirical analysis which related the tire elastic behavior to measured wheel slippage during a steady-state braking. The results of this investigation indicate that the bias-belted tire has the largest spring constant value for most loading conditions and the radial-belted tire has the smallest spring constant value.

Hemispheric asymmetry: Looking for a novel signature of the modulation of spatial attention in multisensory processing.

PubMed

Chen, Yi-Chuan; Spence, Charles

2017-06-01

The extent to which attention modulates multisensory processing in a top-down fashion is still a subject of debate among researchers. Typically, cognitive psychologists interested in this question have manipulated the participants' attention in terms of single/dual tasking or focal/divided attention between sensory modalities. We suggest an alternative approach, one that builds on the extensive older literature highlighting hemispheric asymmetries in the distribution of spatial attention. Specifically, spatial attention in vision, audition, and touch is typically biased preferentially toward the right hemispace, especially under conditions of high perceptual load. We review the evidence demonstrating such an attentional bias toward the right in extinction patients and healthy adults, along with the evidence of such rightward-biased attention in multisensory experimental settings. We then evaluate those studies that have demonstrated either a more pronounced multisensory effect in right than in left hemispace, or else similar effects in the two hemispaces. The results suggest that the influence of rightward-biased attention is more likely to be observed when the crossmodal signals interact at later stages of information processing and under conditions of higher perceptual load-that is, conditions under which attention is perhaps a compulsory enhancer of information processing. We therefore suggest that the spatial asymmetry in attention may provide a useful signature of top-down attentional modulation in multisensory processing.

Estimating multivariate response surface model with data outliers, case study in enhancing surface layer properties of an aircraft aluminium alloy

NASA Astrophysics Data System (ADS)

Widodo, Edy; Kariyam

2017-03-01

To determine the input variable settings that create the optimal compromise in response variable used Response Surface Methodology (RSM). There are three primary steps in the RSM problem, namely data collection, modelling, and optimization. In this study focused on the establishment of response surface models, using the assumption that the data produced is correct. Usually the response surface model parameters are estimated by OLS. However, this method is highly sensitive to outliers. Outliers can generate substantial residual and often affect the estimator models. Estimator models produced can be biased and could lead to errors in the determination of the optimal point of fact, that the main purpose of RSM is not reached. Meanwhile, in real life, the collected data often contain some response variable and a set of independent variables. Treat each response separately and apply a single response procedures can result in the wrong interpretation. So we need a development model for the multi-response case. Therefore, it takes a multivariate model of the response surface that is resistant to outliers. As an alternative, in this study discussed on M-estimation as a parameter estimator in multivariate response surface models containing outliers. As an illustration presented a case study on the experimental results to the enhancement of the surface layer of aluminium alloy air by shot peening.

Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

PubMed

Liu, Ya-Juan; André, Silvère; Saint Cristau, Lydia; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Devos, Olivier; Duponchel, Ludovic

2017-02-01

Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T 2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry. Copyright © 2016 Elsevier B.V. All rights reserved.

Multivariable regression analysis of list experiment data on abortion: results from a large, randomly-selected population based study in Liberia.

PubMed

Moseson, Heidi; Gerdts, Caitlin; Dehlendorf, Christine; Hiatt, Robert A; Vittinghoff, Eric

2017-12-21

The list experiment is a promising measurement tool for eliciting truthful responses to stigmatized or sensitive health behaviors. However, investigators may be hesitant to adopt the method due to previously untestable assumptions and the perceived inability to conduct multivariable analysis. With a recently developed statistical test that can detect the presence of a design effect - the absence of which is a central assumption of the list experiment method - we sought to test the validity of a list experiment conducted on self-reported abortion in Liberia. We also aim to introduce recently developed multivariable regression estimators for the analysis of list experiment data, to explore relationships between respondent characteristics and having had an abortion - an important component of understanding the experiences of women who have abortions. To test the null hypothesis of no design effect in the Liberian list experiment data, we calculated the percentage of each respondent "type," characterized by response to the control items, and compared these percentages across treatment and control groups with a Bonferroni-adjusted alpha criterion. We then implemented two least squares and two maximum likelihood models (four total), each representing different bias-variance trade-offs, to estimate the association between respondent characteristics and abortion. We find no clear evidence of a design effect in list experiment data from Liberia (p = 0.18), affirming the first key assumption of the method. Multivariable analyses suggest a negative association between education and history of abortion. The retrospective nature of measuring lifetime experience of abortion, however, complicates interpretation of results, as the timing and safety of a respondent's abortion may have influenced her ability to pursue an education. Our work demonstrates that multivariable analyses, as well as statistical testing of a key design assumption, are possible with list experiment data, although with important limitations when considering lifetime measures. We outline how to implement this methodology with list experiment data in future research.

Effects of past and recent blood pressure and cholesterol level on coronary heart disease and stroke mortality, accounting for measurement error.

PubMed

Boshuizen, Hendriek C; Lanti, Mariapaola; Menotti, Alessandro; Moschandreas, Joanna; Tolonen, Hanna; Nissinen, Aulikki; Nedeljkovic, Srecko; Kafatos, Anthony; Kromhout, Daan

2007-02-15

The authors aimed to quantify the effects of current systolic blood pressure (SBP) and serum total cholesterol on the risk of mortality in comparison with SBP or serum cholesterol 25 years previously, taking measurement error into account. The authors reanalyzed 35-year follow-up data on mortality due to coronary heart disease and stroke among subjects aged 65 years or more from nine cohorts of the Seven Countries Study. The two-step method of Tsiatis et al. (J Am Stat Assoc 1995;90:27-37) was used to adjust for regression dilution bias, and results were compared with those obtained using more commonly applied methods of adjustment for regression dilution bias. It was found that the commonly used univariate adjustment for regression dilution bias overestimates the effects of both SBP and cholesterol compared with multivariate methods. Also, the two-step method makes better use of the information available, resulting in smaller confidence intervals. Results comparing recent and past exposure indicated that past SBP is more important than recent SBP in terms of its effect on coronary heart disease mortality, while both recent and past values seem to be important for effects of cholesterol on coronary heart disease mortality and effects of SBP on stroke mortality. Associations between serum cholesterol concentration and risk of stroke mortality are weak.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

PubMed

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Total Ionizing Dose Effects on Ge Channel $p$FETs with Raised $${\\rm Si}_{0.55}{\\rm Ge}_{0.45}$$ Source/Drain

DOE PAGES

Wang, Liang; Zhang, En Xia; Schrimpf, Ronald D.; ...

2015-12-17

Here, the total ionizing dose response of Ge channel pFETs with raised Si 0.55Ge 0.45 source/drain is investigated under different radiation bias conditions. Threshold-voltage shifts and transconductance degradation are noticeable only for negative-bias (on state) irradiation, and are mainly due to negative bias-temperature instability (NBTI). Nonmonotonic leakage changes during irradiation are observed, which are attributed to the competition of radiation-induced field transistor leakage and S/D junction leakage.

Introduction to CAUSES: Description of Weather and Climate Models and Their Near-Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

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

Morcrette, C. J.; Van Weverberg, K.; Ma, H. -Y.

The Clouds Above the United States and Errors at the Surface (CAUSES) project is aimed at gaining a better understanding of the physical processes that are leading to the creation of warm screen-temperature biases over the American Midwest, which are seen in many numerical models. Here in Part 1, a series of 5-day hindcasts, each initialised from re-analyses and performed by 11 different models, are evaluated against screen-temperature observations. All the models have a warm bias over parts of the Midwest. Several ways of quantifying the impact of the initial conditions on the evolution of the simulations are presented, showingmore » that within a day or so all models have produced a warm bias that is representative of their bias after 5 days, and not closely tied to the conditions at the initial time. Although the surface temperature biases sometimes coincide with locations where the re-analyses themselves have a bias, there are many regions in each of the models where biases grow over the course of 5 days or are larger than the biases present in the reanalyses. At the Southern Great Plains site, the model biases are shown to not be confined to the surface, but extend several kilometres into the atmosphere. In most of the models, there is a strong diurnal cycle in the screen-temperature bias and in some models the biases are largest around midday, while in the others it is largest during the night. While the different physical processes that are contributing to a given model having a screen-temperature error will be discussed in more detail in the companion papers (Parts 2 and 3) the fact that there is a spatial coherence in the phase of the diurnal cycle of the error across wide regions and that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP suggest that the detailed evaluations of the role of different processes in contributing to errors at SGP will be representative of errors that are prevalent over a much larger spatial scale.« less

Introduction to CAUSES: Description of weather and climate models and their near-surface temperature errors in 5-day hindcasts near the Southern Great Plains

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

Morcrette, Cyril J.; Van Weverberg, Kwinten; Ma, H

2018-02-16

The Clouds Above the United States and Errors at the Surface (CAUSES) project is aimed at gaining a better understanding of the physical processes that are leading to the creation of warm screen-temperature biases over the American Midwest, which are seen in many numerical models. Here in Part 1, a series of 5-day hindcasts, each initialised from re-analyses and performed by 11 different models, are evaluated against screen-temperature observations. All the models have a warm bias over parts of the Midwest. Several ways of quantifying the impact of the initial conditions on the evolution of the simulations are presented, showingmore » that within a day or so all models have produced a warm bias that is representative of their bias after 5 days, and not closely tied to the conditions at the initial time. Although the surface temperature biases sometimes coincide with locations where the re-analyses themselves have a bias, there are many regions in each of the models where biases grow over the course of 5 days or are larger than the biases present in the reanalyses. At the Southern Great Plains site, the model biases are shown to not be confined to the surface, but extend several kilometres into the atmosphere. In most of the models, there is a strong diurnal cycle in the screen-temperature bias and in some models the biases are largest around midday, while in the others it is largest during the night. While the different physical processes that are contributing to a given model having a screen-temperature error will be discussed in more detail in the companion papers (Parts 2 and 3) the fact that there is a spatial coherence in the phase of the diurnal cycle of the error across wide regions and that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP suggest that the detailed evaluations of the role of different processes in contributing to errors at SGP will be representative of errors that are prevalent over a much larger spatial scale.« less

Hot-spot heating susceptibility due to reverse bias operating conditions

NASA Technical Reports Server (NTRS)

Gonzalez, C. C.

1985-01-01

Because of field experience (indicating that cell and module degradation could occur as a result of hot spot heating), a laboratory test was developed at JPL to determine hot spot susceptibility of modules. The initial hot spot testing work at JPL formed a foundation for the test development. Test parameters are selected as follows. For high shunt resistance cells, the applied back bias test current is set equal to the test cell current at maximum power. For low shunt resistance cells, the test current is set equal to the cell short circuit current. The shadow level is selected to conform to that which would lead to maximum back bias voltage under the appropriate test current level. The test voltage is determined by the bypass diode frequency. The test conditions are meant to simulate the thermal boundary conditions for 100 mW/sq cm, 40C ambient environment. The test lasts 100 hours. A key assumption made during the development of the test is that no current imbalance results from the connecting of multiparallel cell strings. Therefore, the test as originally developed was applicable for single string case only.

A meta-analysis of sex differences in human brain structure☆

PubMed Central

Ruigrok, Amber N.V.; Salimi-Khorshidi, Gholamreza; Lai, Meng-Chuan; Baron-Cohen, Simon; Lombardo, Michael V.; Tait, Roger J.; Suckling, John

2014-01-01

The prevalence, age of onset, and symptomatology of many neuropsychiatric conditions differ between males and females. To understand the causes and consequences of sex differences it is important to establish where they occur in the human brain. We report the first meta-analysis of typical sex differences on global brain volume, a descriptive account of the breakdown of studies of each compartmental volume by six age categories, and whole-brain voxel-wise meta-analyses on brain volume and density. Gaussian-process regression coordinate-based meta-analysis was used to examine sex differences in voxel-based regional volume and density. On average, males have larger total brain volumes than females. Examination of the breakdown of studies providing total volumes by age categories indicated a bias towards the 18–59 year-old category. Regional sex differences in volume and tissue density include the amygdala, hippocampus and insula, areas known to be implicated in sex-biased neuropsychiatric conditions. Together, these results suggest candidate regions for investigating the asymmetric effect that sex has on the developing brain, and for understanding sex-biased neurological and psychiatric conditions. PMID:24374381

Structure-Activity Analysis of Biased Agonism at the Human Adenosine A3 Receptor

PubMed Central

Baltos, Jo-Anne; Paoletta, Silvia; Nguyen, Anh T. N.; Gregory, Karen J.; Tosh, Dilip K.; Christopoulos, Arthur; Jacobson, Kenneth A.

2016-01-01

Biased agonism at G protein–coupled receptors (GPCRs) has significant implications for current drug discovery, but molecular determinants that govern ligand bias remain largely unknown. The adenosine A3 GPCR (A3AR) is a potential therapeutic target for various conditions, including cancer, inflammation, and ischemia, but for which biased agonism remains largely unexplored. We now report the generation of bias “fingerprints” for prototypical ribose containing A3AR agonists and rigidified (N)-methanocarba 5′-N-methyluronamide nucleoside derivatives with regard to their ability to mediate different signaling pathways. Relative to the reference prototypical agonist IB-MECA, (N)-methanocarba 5′-N-methyluronamide nucleoside derivatives with significant N6 or C2 modifications, including elongated aryl-ethynyl groups, exhibited biased agonism. Significant positive correlation was observed between the C2 substituent length (in Å) and bias toward cell survival. Molecular modeling suggests that extended C2 substituents on (N)-methanocarba 5′-N-methyluronamide nucleosides promote a progressive outward shift of the A3AR transmembrane domain 2, which may contribute to the subset of A3AR conformations stabilized on biased agonist binding. PMID:27136943

Perceptual-Attentional and Motor-Intentional Bias in Near and Far Space

PubMed Central

Garza, John P.; Eslinger, Paul J.; Barrett, Anna M.

2008-01-01

Spatial bias demonstrated in tasks such as line-bisection may stem from perceptual-attentional (PA) “where” and motor-intentional (MI) “aiming” influences. We tested normal participants’ line bisection performance in the presence of an asymmetric visual distracter with a video apparatus designed to dissociate PA from MI bias. An experimenter stood as a distractor to the left or right of a video monitor positioned in either near or far space, where participants viewed lines and a laser point they directed under 1) natural and 2) mirror-reversed conditions. Each trial started with the pointer positioned at either the top left or top right corner of the screen, and alternated thereafter. Data analysis indicated that participants made primarily PA leftward errors in near space, but not in far space. Furthermore, PA, but not MI, bias increased bilaterally in the direction of distraction. In contrast, MI, but not PA, bias was shifted bilaterally in the direction of startside. Results support the conclusion that a primarily PA left sided bias in near space is consistent with right hemisphere spatial attentional dominance. A bottom-up visual distractor specifically affected PA “where” spatial bias while top-down motor cuing influenced MI “aiming” bias. PMID:18381226

The role of metadata and strategies to detect and control temporal data bias in environmental monitoring of soil contamination.

PubMed

Desaules, André

2012-11-01

It is crucial for environmental monitoring to fully control temporal bias, which is the distortion of real data evolution by varying bias through time. Temporal bias cannot be fully controlled by statistics alone but requires appropriate and sufficient metadata, which should be under rigorous and continuous quality assurance and control (QA/QC) to reliably document the degree of consistency of the monitoring system. All presented strategies to detect and control temporal data bias (QA/QC, harmonisation/homogenisation/standardisation, mass balance approach, use of tracers and analogues and control of changing boundary conditions) rely on metadata. The Will Rogers phenomenon, due to subsequent reclassification, is a particular source of temporal data bias introduced to environmental monitoring here. Sources and effects of temporal data bias are illustrated by examples from the Swiss soil monitoring network. The attempt to make a comprehensive compilation and assessment of required metadata for soil contamination monitoring reveals that most metadata are still far from being reliable. This leads to the conclusion that progress in environmental monitoring means further development of the concept of environmental metadata for the sake of temporal data bias control as a prerequisite for reliable interpretations and decisions.

The left inferior frontal gyrus is involved in adjusting response bias during a perceptual decision-making task.

PubMed

Reckless, Greg E; Ousdal, Olga T; Server, Andres; Walter, Henrik; Andreassen, Ole A; Jensen, Jimmy

2014-05-01

Changing the way we make decisions from one environment to another allows us to maintain optimal decision-making. One way decision-making may change is how biased one is toward one option or another. Identifying the regions of the brain that underlie the change in bias will allow for a better understanding of flexible decision-making. An event-related, perceptual decision-making task where participants had to detect a picture of an animal amongst distractors was used during functional magnetic resonance imaging. Positive and negative financial motivation were used to affect a change in response bias, and changes in decision-making behavior were quantified using signal detection theory. Response bias became relatively more liberal during both positive and negative motivated trials compared to neutral trials. For both motivational conditions, the larger the liberal shift in bias, the greater the left inferior frontal gyrus (IFG) activity. There was no relationship between individuals' belief that they used a different strategy and their actual change in response bias. The present findings suggest that the left IFG plays a role in adjusting response bias across different decision environments. This suggests a potential role for the left IFG in flexible decision-making.

Rapid social perception is flexible: approach and avoidance motivational states shape P100 responses to other-race faces

PubMed Central

Cunningham, William A.; Van Bavel, Jay J.; Arbuckle, Nathan L.; Packer, Dominic J.; Waggoner, Ashley S.

2012-01-01

Research on person categorization suggests that people automatically and inflexibly categorize others according to group memberships, such as race. Consistent with this view, research using electroencephalography (EEG) has found that White participants tend to show an early difference in processing Black versus White faces. Yet, new research has shown that these ostensibly automatic biases may not be as inevitable as once thought and that motivational influences may be able to eliminate these biases. It is unclear, however, whether motivational influences shape the initial biases or whether these biases can only be modulated by later, controlled processes. Using EEG to examine the time course of biased processing, we manipulated approach and avoidance motivational states by having participants pull or push a joystick, respectively, while viewing White or Black faces. Consistent with previous work on own-race bias, we observed a greater P100 response to White than Black faces; however, this racial bias was attenuated in the approach condition. These data suggest that rapid social perception may be flexible and can be modulated by motivational states. PMID:22661937

A Diffusion Model Analysis of Decision Biases Affecting Delayed Recognition of Emotional Stimuli.

PubMed

Bowen, Holly J; Spaniol, Julia; Patel, Ronak; Voss, Andreas

2016-01-01

Previous empirical work suggests that emotion can influence accuracy and cognitive biases underlying recognition memory, depending on the experimental conditions. The current study examines the effects of arousal and valence on delayed recognition memory using the diffusion model, which allows the separation of two decision biases thought to underlie memory: response bias and memory bias. Memory bias has not been given much attention in the literature but can provide insight into the retrieval dynamics of emotion modulated memory. Participants viewed emotional pictorial stimuli; half were given a recognition test 1-day later and the other half 7-days later. Analyses revealed that emotional valence generally evokes liberal responding, whereas high arousal evokes liberal responding only at a short retention interval. The memory bias analyses indicated that participants experienced greater familiarity with high-arousal compared to low-arousal items and this pattern became more pronounced as study-test lag increased; positive items evoke greater familiarity compared to negative and this pattern remained stable across retention interval. The findings provide insight into the separate contributions of valence and arousal to the cognitive mechanisms underlying delayed emotion modulated memory.

Genetic and codon usage bias analyses of polymerase genes of equine influenza virus and its relation to evolution.

PubMed

Bera, Bidhan Ch; Virmani, Nitin; Kumar, Naveen; Anand, Taruna; Pavulraj, S; Rash, Adam; Elton, Debra; Rash, Nicola; Bhatia, Sandeep; Sood, Richa; Singh, Raj Kumar; Tripathi, Bhupendra Nath

2017-08-23

Equine influenza is a major health problem of equines worldwide. The polymerase genes of influenza virus have key roles in virus replication, transcription, transmission between hosts and pathogenesis. Hence, the comprehensive genetic and codon usage bias of polymerase genes of equine influenza virus (EIV) were analyzed to elucidate the genetic and evolutionary relationships in a novel perspective. The group - specific consensus amino acid substitutions were identified in all polymerase genes of EIVs that led to divergence of EIVs into various clades. The consistent amino acid changes were also detected in the Florida clade 2 EIVs circulating in Europe and Asia since 2007. To study the codon usage patterns, a total of 281,324 codons of polymerase genes of EIV H3N8 isolates from 1963 to 2015 were systemically analyzed. The polymerase genes of EIVs exhibit a weak codon usage bias. The ENc-GC3s and Neutrality plots indicated that natural selection is the major influencing factor of codon usage bias, and that the impact of mutation pressure is comparatively minor. The methods for estimating host imposed translation pressure suggested that the polymerase acidic (PA) gene seems to be under less translational pressure compared to polymerase basic 1 (PB1) and polymerase basic 2 (PB2) genes. The multivariate statistical analysis of polymerase genes divided EIVs into four evolutionary diverged clusters - Pre-divergent, Eurasian, Florida sub-lineage 1 and 2. Various lineage specific amino acid substitutions observed in all polymerase genes of EIVs and especially, clade 2 EIVs underwent major variations which led to the emergence of a phylogenetically distinct group of EIVs originating from Richmond/1/07. The codon usage bias was low in all the polymerase genes of EIVs that was influenced by the multiple factors such as the nucleotide compositions, mutation pressure, aromaticity and hydropathicity. However, natural selection was the major influencing factor in defining the codon usage patterns and evolution of polymerase genes of EIVs.

Reward sensitivity predicts ice cream-related attentional bias assessed by inattentional blindness.

PubMed

Li, Xiaoming; Tao, Qian; Fang, Ya; Cheng, Chen; Hao, Yangyang; Qi, Jianjun; Li, Yu; Zhang, Wei; Wang, Ying; Zhang, Xiaochu

2015-06-01

The cognitive mechanism underlying the association between individual differences in reward sensitivity and food craving is unknown. The present study explored the mechanism by examining the role of reward sensitivity in attentional bias toward ice cream cues. Forty-nine college students who displayed high level of ice cream craving (HICs) and 46 who displayed low level of ice cream craving (LICs) performed an inattentional blindness (IB) task which was used to assess attentional bias for ice cream. In addition, reward sensitivity and coping style were assessed by the Behavior Inhibition System/Behavior Activation System Scales and Simplified Coping Style Questionnaire. Results showed significant higher identification rate of the critical stimulus in the HICs than LICs, suggesting greater attentional bias for ice cream in the HICs. It was indicated that attentional bias for food cues persisted even under inattentional condition. Furthermore, a significant correlation was found between the attentional bias and reward sensitivity after controlling for coping style, and reward sensitivity predicted attentional bias for food cues. The mediation analyses showed that attentional bias mediated the relationship between reward sensitivity and food craving. Those findings suggest that the association between individual differences in reward sensitivity and food craving may be attributed to attentional bias for food-related cues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Linking multimetric and multivariate approaches to assess the ecological condition of streams.

PubMed

Collier, Kevin J

2009-10-01

Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.

Bayesian transformation cure frailty models with multivariate failure time data.

PubMed

Yin, Guosheng

2008-12-10

We propose a class of transformation cure frailty models to accommodate a survival fraction in multivariate failure time data. Established through a general power transformation, this family of cure frailty models includes the proportional hazards and the proportional odds modeling structures as two special cases. Within the Bayesian paradigm, we obtain the joint posterior distribution and the corresponding full conditional distributions of the model parameters for the implementation of Gibbs sampling. Model selection is based on the conditional predictive ordinate statistic and deviance information criterion. As an illustration, we apply the proposed method to a real data set from dentistry.

Behavioral biases when viewing multiplexed scenes: scene structure and frames of reference for inspection

PubMed Central

Stainer, Matthew J.; Scott-Brown, Kenneth C.; Tatler, Benjamin W.

2013-01-01

Where people look when viewing a scene has been a much explored avenue of vision research (e.g., see Tatler, 2009). Current understanding of eye guidance suggests that a combination of high and low-level factors influence fixation selection (e.g., Torralba et al., 2006), but that there are also strong biases toward the center of an image (Tatler, 2007). However, situations where we view multiplexed scenes are becoming increasingly common, and it is unclear how visual inspection might be arranged when content lacks normal semantic or spatial structure. Here we use the central bias to examine how gaze behavior is organized in scenes that are presented in their normal format, or disrupted by scrambling the quadrants and separating them by space. In Experiment 1, scrambling scenes had the strongest influence on gaze allocation. Observers were highly biased by the quadrant center, although physical space did not enhance this bias. However, the center of the display still contributed to fixation selection above chance, and was most influential early in scene viewing. When the top left quadrant was held constant across all conditions in Experiment 2, fixation behavior was significantly influenced by the overall arrangement of the display, with fixations being biased toward the quadrant center when the other three quadrants were scrambled (despite the visual information in this quadrant being identical in all conditions). When scenes are scrambled into four quadrants and semantic contiguity is disrupted, observers no longer appear to view the content as a single scene (despite it consisting of the same visual information overall), but rather anchor visual inspection around the four separate “sub-scenes.” Moreover, the frame of reference that observers use when viewing the multiplex seems to change across viewing time: from an early bias toward the display center to a later bias toward quadrant centers. PMID:24069008

Stroop interference and food intake.

PubMed

Overduin, J; Jansen, A; Louwerse, E

1995-11-01

The Stroop task is aimed at assessing attentional bias. Words are displayed one by one on a computer screen and subjects are instructed to name the color in which every word is printed. The attentional bias is supposed to be reflected in the extent to which the word meanings interfere with the speed of color naming: The longer the color naming latency, the larger the attentional bias. Experiments using this task have demonstrated attentional bias for eating and body shape-related words in bulimic, anorexic, and restrained subjects. Explanations of these results have generally been formulated in terms of restricted food intake or emotional concerns about food and body shape-related themes. In contrast, in the present article it was proposed that Stroop interference might reflect a tendency either to withdraw or approach food or body shape-related stimuli. Fifty-one subjects (25 unrestrained, 26 restrained) were administered a Stroop task containing neutral, food, and body shape-related words. There were two conditions to which subjects were randomly allocated: the "appetizer" and "no-appetizer" condition. The appetizer was a bit of pudding to be ingested by the subject just before the Stroop task. Following the Stroop task an ice cream taste test was presented in which the subjects were allowed to eat as much as they liked. The amount of ice cream eaten was registered secretly. The results show that in unrestrained subjects Stroop interference for food words was found only in the appetizer condition. Restrained subjects, however, showed a permanent interference for food words. A significant correlation of .58 between Stroop food-word interference and ice cream intake was found only in unrestrained subjects. In restrained eaters the correlation was near 0. No effect of condition or restraint was found on Stroop body shape-word interference. The findings indicate that (1) ingestion of an appetizer seems to have evoked an attentional bias for food words in nonrestraints that correlated with food intake; (2) restrained eaters showed continuous attentional bias. This appears to support the urge-to-act explanation of Stroop interference. The lack of correlation between restraints' attentional bias and ad lib food intake could have been caused by inhibition of approach which is one of the characteristics of restrained eating: The present procedure seems not to have triggered disinhibited eating in these subjects. Among other things it is concluded that Stroop interference, as a measure of "craving" triggered by food cue, might be a useful aid in assessing the risk of relapse in treated binge eating patients.

Probing bias reduction to improve comparability of lint cotton water and moisture contents at moisture equilibrium

USDA-ARS?s Scientific Manuscript database

The Karl Fischer Titration (KFT) reference method is specific for water in lint cotton and was designed for samples conditioned to moisture equilibrium, thus limiting its biases. There is a standard method for moisture content – weight loss – by oven drying (OD), just not for equilibrium moisture c...

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

ERIC Educational Resources Information Center

Bishara, Anthony J.; Hittner, James B.

2015-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…

Electronic Health Records to Evaluate and Account for Non-response Bias: A Survey of Patients Using Chronic Opioid Therapy.

PubMed

Shortreed, Susan M; Von Korff, Michael; Thielke, Stephen; LeResche, Linda; Saunders, Kathleen; Rosenberg, Dori; Turner, Judith A

2016-01-01

In observational studies concerning drug use and misuse, persons misusing drugs may be less likely to respond to surveys. However, little is known about differences in drug use and drug misuse risk factors between survey respondents and nonrespondents. Using electronic health record (EHR) data, we compared respondents and non-respondents in a telephone survey of middle-aged and older chronic opioid therapy patients to assess predictors of interview nonresponse. We compared general patient characteristics, specific opioid misuse risk factors, and patterns of opioid use associated with increased risk of opioid misuse. Inverse probability weights were calculated to account for nonresponse bias by EHR-measured covariates. EHR-measured covariate distributions for the full sample (nonrespondents and respondents), the unweighted respondent sample, and the inverse probability weighted respondent sample are reported. We present weighted and unweighted prevalence of self-reported opioid misuse risk factors. Among 2489 potentially eligible patients, 1477 (59.3%) completed interviews. Response rates differed with age (45-54 years, 51.8%; 55-64 years, 58.7%; 65-74 years, 67.9%; and 75 years or older, 59.9%). Tobacco users had lower response rates than did nonusers (53.5% versus 60.9%). Charlson comorbidity score was also related to response rates. Individuals with a Charlson score of 2 had the highest response rate at 65.6%; response rates were lower amoung patients with the lowest (the patients with the fewest health conditions had response rates of 56.7-60.0%) and the highest Charlson scores (patients with the most health conditions had response rates of 52.2-56.0%). These bivariate relationships persisted in adjusted multivariable logistic regression models predicting survey response. Response rates of persons with and without specific opioid misuse risk factors were similar (e.g., 58.7% for persons with substance abuse diagnoses, 59.4% for those without). Opioid use patterns associated with opioid misuse did not predict response rates (e.g., 60.6% versus 59.2% for those receiving versus not receiving opioids from 3 or more physicians outside their primary care clinic). Very few patient characteristics predicted non-response; thus, inverse probability weights accounting for nonresponse had little impact on the distributions of EHR-measured covariates or self-reported measures related to opioid use and misuse. Response rates differed by characteristics that predict nonresponse in general health surveys (age, tobacco use), but did not appear to differ by specific patient or drug use risk factors for prescription opioid misuse among middle- and older-aged chronic opioid therapy patients. When observational studies are conducted in health plan populations, electronic health records may be used to evaluate nonresponse bias and to adjust for variables predicting interview nonresponse, complementing other research uses of EHR data in observational studies.

Early group bias in the Faroe Islands: Cultural variation in children's group-based reasoning.

PubMed

Schug, Mariah G; Shusterman, Anna; Barth, Hilary; Patalano, Andrea L

2016-01-01

Recent developmental research demonstrates that group bias emerges early in childhood. However, little is known about the extent to which bias in minimal (i.e., arbitrarily assigned) groups varies with children's environment and experience, and whether such bias is universal across cultures. In this study, the development of group bias was investigated using a minimal groups paradigm with 46 four- to six-year-olds from the Faroe Islands. Children observed in-group and out-group members exhibiting varying degrees of prosocial behaviour (egalitarian or stingy sharing). Children did not prefer their in-group in the pretest, but a pro-in-group and anti-out-group sentiment emerged in both conditions in the posttest. Faroese children's response patterns differ from those of American children [Schug, M. G., Shusterman, A., Barth, H., & Patalano, A. L. (2013). Minimal-group membership influences children's responses to novel experience with group members. Developmental Science, 16(1), 47-55], suggesting that intergroup bias shows cultural variation even in a minimal groups context.

Retarding field analyzer for ion energy distribution measurements at a radio-frequency biased electrode

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

Gahan, D.; Hopkins, M. B.; Dolinaj, B.

2008-03-15

A retarding field energy analyzer designed to measure ion energy distributions impacting a radio-frequency biased electrode in a plasma discharge is examined. The analyzer is compact so that the need for differential pumping is avoided. The analyzer is designed to sit on the electrode surface, in place of the substrate, and the signal cables are fed out through the reactor side port. This prevents the need for modifications to the rf electrode--as is normally the case for analyzers built into such electrodes. The capabilities of the analyzer are demonstrated through experiments with various electrode bias conditions in an inductively coupledmore » plasma reactor. The electrode is initially grounded and the measured distributions are validated with the Langmuir probe measurements of the plasma potential. Ion energy distributions are then given for various rf bias voltage levels, discharge pressures, rf bias frequencies - 500 kHz to 30 MHz, and rf bias waveforms - sinusoidal, square, and dual frequency.« less

A CMOS matrix for extracting MOSFET parameters before and after irradiation

NASA Technical Reports Server (NTRS)

Blaes, B. R.; Buehler, M. G.; Lin, Y.-S.; Hicks, K. A.

1988-01-01

An addressable matrix of 16 n- and 16 p-MOSFETs was designed to extract the dc MOSFET parameters for all dc gate bias conditions before and after irradiation. The matrix contains four sets of MOSFETs, each with four different geometries that can be biased independently. Thus the worst-case bias scenarios can be determined. The MOSFET matrix was fabricated at a silicon foundry using a radiation-soft CMOS p-well LOCOS process. Co-60 irradiation results for the n-MOSFETs showed a threshold-voltage shift of -3 mV/krad(Si), whereas the p-MOSFETs showed a shift of 21 mV/krad(Si). The worst-case threshold-voltage shift occurred for the n-MOSFETs, with a gate bias of 5 V during the anneal. For the p-MOSFETs, biasing did not affect the shift in the threshold voltage. A parasitic MOSFET dominated the leakage of the n-MOSFET biased with 5 V on the gate during irradiation. Co-60 test results for other parameters are also presented.

Lies, Damned Lies, and Survey Self-Reports? Identity as a Cause of Measurement Bias

PubMed Central

Brenner, Philip S.; DeLamater, John

2017-01-01

Explanations of error in survey self-reports have focused on social desirability: that respondents answer questions about normative behavior to appear prosocial to interviewers. However, this paradigm fails to explain why bias occurs even in self-administered modes like mail and web surveys. We offer an alternative explanation rooted in identity theory that focuses on measurement directiveness as a cause of bias. After completing questions about physical exercise on a web survey, respondents completed a text message–based reporting procedure, sending updates on their major activities for five days. Random assignment was then made to one of two conditions: instructions mentioned the focus of the study, physical exercise, or not. Survey responses, text updates, and records from recreation facilities were compared. Direct measures generated bias—overreporting in survey measures and reactivity in the directive text condition—but the nondirective text condition generated unbiased measures. Findings are discussed in terms of identity. PMID:29038609

Probability judgments of agency: rational or irrational?

PubMed

Schmidt, Thomas; Heumüller, Vera C

2010-03-01

We studied how people attribute action outcomes to their own actions under conditions of uncertainty. Participants chose between left and right keypresses to produce an action effect (a corresponding left or right light), while a computer player made a simultaneous keypress decision. In each trial, a random generator determined which of the players controlled the action effect at varying probabilities, and participants then judged which player had produced it. Participants' effect control ranged from 20% to 80%, varied blockwise, and they could use trial-by-trial feedback to optimize the accuracy of their agency judgments. Participants tended to attribute action effects to themselves (agency bias), probably reflecting a rational guessing strategy of always naming the more likely player. However, participants systematically neglected information favoring the computer player as the agent, even under conditions where this bias could only harm judgment accuracy. We conclude that agency biases have both rational and irrational components.

Multiphoton laser ionization for energy conversion in barium vapor

NASA Astrophysics Data System (ADS)

Makdisi, Y.; Kokaj, J.; Afrousheh, K.; Mathew, J.; Nair, R.; Pichler, G.

2013-03-01

We have studied the ion detection of barium atoms in special heated ovens with a tungsten rod in the middle of the stainless steel tube. The tungsten rod was heated indirectly by the oven body heaters. A bias voltage between the cell body and the tungsten rod of 9 V was used to collect electrons, after the barium ions had been created. However, we could collect the electrons even without the bias voltage, although with ten times less efficiency. We studied the conditions for the successful bias-less thermionic signal detection using excimer/dye laser two-photon excitation of Rydberg states below and above the first ionization limit (two-photon wavelength at 475.79 nm). We employed a hot-pipe oven and heat-pipe oven (with inserted mesh) in order to generate different barium vapor distributions inside the oven. The thermionic signal increased by a factor of two under heat-pipe oven conditions.

Decision Processes in Discrimination: Fundamental Misrepresentations of Signal Detection Theory

NASA Technical Reports Server (NTRS)

Balakrishnan, J. D.

1998-01-01

In the first part of this article, I describe a new approach to studying decision making in discrimination tasks that does not depend on the technical assumptions of signal detection theory (e.g., normality of the encoding distributions). Applying these new distribution-free tests to data from three experiments, I show that base rate and payoff manipulations had substantial effects on the participants' encoding distributions but no effect on their decision rules, which were uniformly unbiased in equal and unequal base rate conditions and in symmetric and asymmetric payoff conditions. In the second part of the article, I show that this seemingly paradoxical result is readily explained by the sequential sampling models of discrimination. I then propose a new, "model-free" test for response bias that seems to more properly identify both the nature and direction of the biases induced by the classical bias manipulations.

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

NASA Astrophysics Data System (ADS)

Greenwald, Thomas J.; Bennartz, Ralf; Lebsock, Matthew; Teixeira, João.

2018-04-01

The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9-year record of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E): clear-sky bias, cloud-rain partition (CRP) bias, cloud-fraction-dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR-E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud-Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud-fraction-dependent bias was found to be a combination of the CRP bias, an in-cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in-cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias-corrected AMSR-E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible-infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations.

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.

Multivariate Statistical Modelling of Drought and Heat Wave Events

NASA Astrophysics Data System (ADS)

Manning, Colin; Widmann, Martin; Vrac, Mathieu; Maraun, Douglas; Bevaqua, Emanuele

2016-04-01

Multivariate Statistical Modelling of Drought and Heat Wave Events C. Manning1,2, M. Widmann1, M. Vrac2, D. Maraun3, E. Bevaqua2,3 1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK 2. Laboratoire des Sciences du Climat et de l'Environnement, (LSCE-IPSL), Centre d'Etudes de Saclay, Gif-sur-Yvette, France 3. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria Compound extreme events are a combination of two or more contributing events which in themselves may not be extreme but through their joint occurrence produce an extreme impact. Compound events are noted in the latest IPCC report as an important type of extreme event that have been given little attention so far. As part of the CE:LLO project (Compound Events: muLtivariate statisticaL mOdelling) we are developing a multivariate statistical model to gain an understanding of the dependence structure of certain compound events. One focus of this project is on the interaction between drought and heat wave events. Soil moisture has both a local and non-local effect on the occurrence of heat waves where it strongly controls the latent heat flux affecting the transfer of sensible heat to the atmosphere. These processes can create a feedback whereby a heat wave maybe amplified or suppressed by the soil moisture preconditioning, and vice versa, the heat wave may in turn have an effect on soil conditions. An aim of this project is to capture this dependence in order to correctly describe the joint probabilities of these conditions and the resulting probability of their compound impact. We will show an application of Pair Copula Constructions (PCCs) to study the aforementioned compound event. PCCs allow in theory for the formulation of multivariate dependence structures in any dimension where the PCC is a decomposition of a multivariate distribution into a product of bivariate components modelled using copulas. A copula is a multivariate distribution function which allows one to model the dependence structure of given variables separately from the marginal behaviour. We firstly look at the structure of soil moisture drought over the entire of France using the SAFRAN dataset between 1959 and 2009. Soil moisture is represented using the Standardised Precipitation Evapotranspiration Index (SPEI). Drought characteristics are computed at grid point scale where drought conditions are identified as those with an SPEI value below -1.0. We model the multivariate dependence structure of drought events defined by certain characteristics and compute return levels of these events. We initially find that drought characteristics such as duration, mean SPEI and the maximum contiguous area to a grid point all have positive correlations, though the degree to which they are correlated can vary considerably spatially. A spatial representation of return levels then may provide insight into the areas most prone to drought conditions. As a next step, we analyse the dependence structure between soil moisture conditions preceding the onset of a heat wave and the heat wave itself.

An Attempt to Target Anxiety Sensitivity via Cognitive Bias Modification

PubMed Central

Clerkin, Elise M.; Beard, Courtney; Fisher, Christopher R.; Schofield, Casey A

2015-01-01

Our goals in the present study were to test an adaptation of a Cognitive Bias Modification program to reduce anxiety sensitivity, and to evaluate the causal relationships between interpretation bias of physiological cues, anxiety sensitivity, and anxiety and avoidance associated with interoceptive exposures. Participants with elevated anxiety sensitivity who endorsed having a panic attack or limited symptom attack were randomly assigned to either an Interpretation Modification Program (IMP; n = 33) or a Control (n = 32) condition. During interpretation modification training (via the Word Sentence Association Paradigm), participants read short sentences describing ambiguous panic-relevant physiological and cognitive symptoms and were trained to endorse benign interpretations and reject threatening interpretations associated with these cues. Compared to the Control condition, IMP training successfully increased endorsements of benign interpretations and decreased endorsements of threatening interpretations at visit 2. Although self-reported anxiety sensitivity decreased from pre-selection to visit 1 and from visit 1 to visit 2, the reduction was not larger for the experimental versus control condition. Further, participants in IMP (vs. Control) training did not experience less anxiety and avoidance associated with interoceptive exposures. In fact, there was some evidence that those in the Control condition experienced less avoidance following training. Potential explanations for the null findings, including problems with the benign panic-relevant stimuli and limitations with the control condition, are discussed. PMID:25692491

An attempt to target anxiety sensitivity via cognitive bias modification.

PubMed

Clerkin, Elise M; Beard, Courtney; Fisher, Christopher R; Schofield, Casey A

2015-01-01

Our goals in the present study were to test an adaptation of a Cognitive Bias Modification program to reduce anxiety sensitivity, and to evaluate the causal relationships between interpretation bias of physiological cues, anxiety sensitivity, and anxiety and avoidance associated with interoceptive exposures. Participants with elevated anxiety sensitivity who endorsed having a panic attack or limited symptom attack were randomly assigned to either an Interpretation Modification Program (IMP; n = 33) or a Control (n = 32) condition. During interpretation modification training (via the Word Sentence Association Paradigm), participants read short sentences describing ambiguous panic-relevant physiological and cognitive symptoms and were trained to endorse benign interpretations and reject threatening interpretations associated with these cues. Compared to the Control condition, IMP training successfully increased endorsements of benign interpretations and decreased endorsements of threatening interpretations at visit 2. Although self-reported anxiety sensitivity decreased from pre-selection to visit 1 and from visit 1 to visit 2, the reduction was not larger for the experimental versus control condition. Further, participants in IMP (vs. Control) training did not experience less anxiety and avoidance associated with interoceptive exposures. In fact, there was some evidence that those in the Control condition experienced less avoidance following training. Potential explanations for the null findings, including problems with the benign panic-relevant stimuli and limitations with the control condition, are discussed.

Reward expectation regulates brain responses to task-relevant and task-irrelevant emotional words: ERP evidence.

PubMed

Wei, Ping; Wang, Di; Ji, Liyan

2016-02-01

We investigated the effect of reward expectation on the processing of emotional words in two experiments using event-related potentials (ERPs). A cue indicating the reward condition of each trial (incentive vs non-incentive) was followed by the presentation of a negative or neutral word, the target. Participants were asked to discriminate the emotional content of the target word in Experiment 1 and to discriminate the color of the target word in Experiment 2, rendering the emotionality of the target word task-relevant in Experiment 1, but task-irrelevant in Experiment 2. The negative bias effect, in terms of the amplitude difference between ERPs for negative and neutral targets, was modulated by the task-set. In Experiment 1, P31 and early posterior negativity revealed a larger negative bias effect in the incentive condition than that in the non-incentive condition. However, in Experiment 2, P31 revealed a diminished negative bias effect in the incentive condition compared with that in the non-incentive condition. These results indicate that reward expectation improves top-down attentional concentration to task-relevant information, with enhanced sensitivity to the emotional content of target words when emotionality is task-relevant, but with reduced differential brain responses to emotional words when their content is task-irrelevant. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

"Model age-based" and "copy when uncertain" biases in children's social learning of a novel task.

PubMed

Wood, Lara A; Harrison, Rachel A; Lucas, Amanda J; McGuigan, Nicola; Burdett, Emily R R; Whiten, Andrew

2016-10-01

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N=140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children's continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Investigating possible ethnicity and sex bias in clinical examiners: an analysis of data from the MRCP(UK) PACES and nPACES examinations.

PubMed

McManus, I C; Elder, Andrew T; Dacre, Jane

2013-07-30

Bias of clinical examiners against some types of candidate, based on characteristics such as sex or ethnicity, would represent a threat to the validity of an examination, since sex or ethnicity are 'construct-irrelevant' characteristics. In this paper we report a novel method for assessing sex and ethnic bias in over 2000 examiners who had taken part in the PACES and nPACES (new PACES) examinations of the MRCP(UK). PACES and nPACES are clinical skills examinations that have two examiners at each station who mark candidates independently. Differences between examiners cannot be due to differences in performance of a candidate because that is the same for the two examiners, and hence may result from bias or unreliability on the part of the examiners. By comparing each examiner against a 'basket' of all of their co-examiners, it is possible to identify examiners whose behaviour is anomalous. The method assessed hawkishness-doveishness, sex bias, ethnic bias and, as a control condition to assess the statistical method, 'even-number bias' (i.e. treating candidates with odd and even exam numbers differently). Significance levels were Bonferroni corrected because of the large number of examiners being considered. The results of 26 diets of PACES and six diets of nPACES were examined statistically to assess the extent of hawkishness, as well as sex bias and ethnicity bias in individual examiners. The control (odd-number) condition suggested that about 5% of examiners were significant at an (uncorrected) 5% level, and that the method therefore worked as expected. As in a previous study (BMC Medical Education, 2006, 6:42), some examiners were hawkish or doveish relative to their peers. No examiners showed significant sex bias, and only a single examiner showed evidence consistent with ethnic bias. A re-analysis of the data considering only one examiner per station, as would be the case for many clinical examinations, showed that analysis with a single examiner runs a serious risk of false positive identifications probably due to differences in case-mix and content-specificity. In examinations where there are two independent examiners at a station, our method can assess the extent of bias against candidates with particular characteristics. The method would be far less sensitive in examinations with only a single examiner per station as examiner variance would be confounded with candidate performance variance. The method however works well when there is more than one examiner at a station and in the case of the current MRCP(UK) clinical examination, nPACES, found possible sex bias in no examiners and possible ethnic bias in only one.

Why do providers contribute to disparities and what can be done about it?

PubMed

Burgess, Diana J; Fu, Steven S; van Ryn, Michelle

2004-11-01

This paper applies social cognition research to understanding and ameliorating the provider contribution to racial/ethnic disparities in health care. We discuss how fundamental cognitive mechanisms such as automatic, unconscious processes (e.g., stereotyping) can help explain provider bias. Even well-intentioned providers who are motivated to be nonprejudiced may stereotype racial/ethnic minority members, particularly under conditions of that diminish cognitive capacity. These conditions-time pressure, fatigue, and information overload-are frequently found in health care settings. We conclude with implications of the social-cognitive perspective for developing interventions to reduce provider bias.