Response to 'what kind of controls to use in case control studies of malformed infants: recall bias versus "Teratogen nonspecificity" bias'
Explore the source record for details and available documents.
Journal Article↗
SEARCH · Search PubMed
Results for “Bias”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Review of publication bias in studies on publication bias: studies on publication bias are probably susceptible to the bias they study.
Explore the source record for details and available documents.
Periodicals as Topic↗
The potential for social contextual and group biases in team decision-making: biases, conditions and psychological mechanisms.
This paper provides a critical review of social contextual and group biases that are relevant to team decision-making in command and control situations. Motivated by the insufficient level of attention this area has received, the purpose of the paper is to provide an insight into the potential that these types of biases have to affect the decision-making of such teams. The biases considered are: false consensus, groupthink, group polarization and group escalation of commitment. For each bias the following four questions are addressed. What is the descriptive nature of the bias? What factors induce the bias? What psychological mechanisms underlie the bias? What is the relevance of the bias to command and control teams? The analysis suggests that these biases have a strong potential to affect team decisions. Consistent with the nature of team decision-making in command and control situations, all of the biases considered tend to be associated with those decisions that are important or novel and are promoted by time pressure and high levels of uncertainty. A concept unifying these biases is that of the shared mental model, but whereas false consensus emanates from social projection tendencies, the rest emanate from social influence factors. The authors also discuss the 'tricky' distinction between teams and groups and propose a revised definition for command and control team. Finally, the authors emphasize the need for future empirical research in this area to pay additional attention to the social side of cognition and the potential that social biases have to affect team decision-making.
Decision Making, Organizational↗
Review of publication bias in studies on publication bias: meta-research on publication bias does not help transfer research results to patient care.
Explore the source record for details and available documents.
Diffusion of Innovation↗
Review of publication bias in studies on publication bias: here's a proposal for editors that may help reduce publication bias.
Explore the source record for details and available documents.
Periodicals as Topic↗
Is there a universal positivity bias in attributions? A meta-analytic review of individual, developmental, and cultural differences in the self-serving attributional bias.
Researchers have suggested the presence of a self-serving attributional bias, with people making more internal, stable, and global attributions for positive events than for negative events. This study examined the magnitude, ubiquity, and adaptiveness of this bias. The authors conducted a meta-analysis of 266 studies, yielding 503 independent effect sizes. The average d was 0.96, indicating a large bias. The bias was present in nearly all samples. There were significant age differences, with children and older adults displaying the largest biases. Asian samples displayed significantly smaller biases (d = 0.30) than U.S. (d = 1.05) or Western (d = 0.70) samples. Psychopathology was associated with a significantly attenuated bias (d = 0.48) compared with samples without psychopathology (d = 1.28) and community samples (d = 1.08). The bias was smallest for samples with depression (0.21), anxiety (0.46), and attention-deficit/hyperactivity disorder (0.55). Findings confirm that the self-serving attributional bias is pervasive in the general population but demonstrates significant variability across age, culture, and psychopathology.
Affect↗
Detection and normalization of biases present in spotted cDNA microarray data: a composite method addressing dye, intensity-dependent, spatially-dependent, and print-order biases.
Microarrays are often used to identify target genes that trigger specific diseases, to elucidate the mechanisms of drug effects, and to check SNPs. However, data from microarray experiments are well known to contain biases resulting from the experimental protocols. Therefore, in order to elucidate biological knowledge from the data, systematic biases arising from their protocols must be removed prior to any data analysis. To remove these biases, many normalization methods are used by researchers. However, not all biases are eliminated from the microarray data because not all types of errors from experimental protocols are known. In this paper, we report an effective way of removing various types of biases by treating each microarray dataset independently to detect biases present in the dataset. After the biases contained in each dataset were identified, a combination of normalization methods specifically made for each dataset was applied to remove biases one at a time.
Algorithms↗
Belief bias and figural bias in syllogistic reasoning.
Belief bias is the tendency to be influenced by the believability of the conclusion when attempting to solve a syllogistic reasoning problem. Figural bias is the tendency to be influenced by the order in which the information is presented in the premises when attempting to solve a syllogistic reasoning problem. When studied simultaneously they enable an investigation of whether participants' reasoning on the syllogistic reasoning task is guided by the conclusion (backward reasoning) or the premises (forward reasoning). Experiments 1 and 2 found evidence of belief bias but not figural bias on the syllogistic evaluation task paradigm. Experiments 3 and 4 found evidence of figural bias but not belief bias on the syllogistic production task paradigm. The findings highlight that different task characteristics influence performance dependent upon the nature of task presentation. These findings are discussed in the context of current theories of belief bias in syllogistic reasoning.
Cognition↗
Nucleotide bias causes a genomewide bias in the amino acid composition of proteins.
We analyzed the nucleotide contents of several completely sequenced genomes, and we show that nucleotide bias can have a dramatic effect on the amino acid composition of the encoded proteins. By surveying the genes in 21 completely sequenced eubacterial and archaeal genomes, along with the entire Saccharomyces cerevisiae genome and two Plasmodium falciparum chromosomes, we show that biased DNA encodes biased proteins on a genomewide scale. The predicted bias affects virtually all genes within the genome, and it could be clearly seen even when we limited the analysis to sets of homologous gene sequences. Parallel patterns of compositional bias were found within the archaea and the eubacteria. We also found a positive correlation between the degree of amino acid bias and the magnitude of protein sequence divergence. We conclude that mutational bias can have a major effect on the molecular evolution of proteins. These results could have important implications for the interpretation of protein-based molecular phylogenies and for the inference of functional protein adaptation from comparative sequence data.
Amino Acids↗
Effect of variability in assay bias and imprecision on external quality assessment bias and imprecision measures.
BACKGROUND: External quality assessment/proficiency testing programmes that report consensus means and coefficients of variations (CVs) are a potential source of information on assay bias and imprecision. This study examined the effect of variability in assay bias and imprecision on consensus means and CVs, using a computerized spreadsheet model. METHODS: A model with varying assay bias (mean and standard deviation) and assay imprecision (mean and standard deviation) was developed using a MS Excel 2003 spreadsheet with a macro to generate pseudo-random numbers from a Gaussian distribution. The means, standard deviations and CVs of these data points were considered to simulate the consensus measures reported in external quality assessment testing programmes. RESULTS: The simulated consensus CV was very sensitive to increases in assay bias variability, with greater effects at low levels of mean assay imprecision. Changes in assay imprecision variability had a much smaller effect on the simulated consensus CV, while the simulated consensus mean was relatively insensitive to any change in the other variables. CONCLUSION: Consensus imprecision measures from external quality assessment programmes are unreliable measures of assay imprecision. Consensus means are relatively unaffected by variability in assay bias and imprecision, and can be used as reliable measures of assay bias from a statistical standpoint.
Bias↗
Quantifying biases in causal models: classical confounding vs collider-stratification bias.
It has long been known that stratifying on variables affected by the study exposure can create selection bias. More recently it has been shown that stratifying on a variable that precedes exposure and disease can induce confounding, even if there is no confounding in the unstratified (crude) estimate. This paper examines the relative magnitudes of these biases under some simple causal models in which the stratification variable is graphically depicted as a collider (a variable directly affected by two or more other variables in the graph). The results suggest that bias from stratifying on variables affected by exposure and disease may often be comparable in size with bias from classical confounding (bias from failing to stratify on a common cause of exposure and disease), whereas other biases from collider stratification may tend to be much smaller.
Bias↗
The effect of response bias on recall performance, with some observations on processing bias.
We explored Roediger and Payne's proposal that response bias does not affect recall performance and that it is therefore not necessary to control for response productivity in recall studies. Two initial experiments, contrary to expectation, corroborated Roediger and Payne's findings: Forced recall did not produce more correct recalls than free recall, even though forced recall produced substantially more false alarms than did free recall. However, in succeeding experiments involving pictorial and verbal stimuli, reliable response-bias effects on recall were demonstrated. The stimuli yielding response-bias effects were those associated with higher probabilities of being guessed by chance. In addition, some of the data suggest that processing-bias effects (differential retrieval effort) may be unintentionally induced by instructions and may significantly affect recall memory. Consequently, it is necessary to assess or to control response-bias effects and, possibly, processing-bias effects in recall experiments in which level of recall is of interest.
Adult↗
Ego bias, reverse ego bias, and physicians' prognostic.
OBJECTIVE: To evaluate the effects of "ego bias" on physicians' prognostic judgments. Ego bias is defined as systematic overestimation of the prognosis of one's own patients compared with the expected outcome of a population of similar patients. DESIGN: A prospective study of an inception cohort of critically ill patients followed until death or discharge from the hospital. PATIENTS: Consecutive patients admitted to either an ICU or an intermediate ICU at a teaching hospital during January and February 1987, excluding patients admitted after coronary artery bypass grafting, for elective dialysis, or transferred to the intermediate ICU from another critical care unit. MAIN OUTCOME MEASURES AND COMPARISONS: House officers' and critical care attending physicians' assessments of the likelihood of inhospital survival for each patient, and their assessments of the overall survival rate of ICU and intermediate ICU patients were compared with each other and with actual survival rates. RESULTS: The attending physicians' predictions for individual patients were significantly lower than their judgments of the overall survival rate, 79.8% vs. 88.0%, p = .0067, suggesting the presence of a "reverse ego bias." The house officers' predictions for individual patients were significantly higher than their judgments of the overall survival rate, 73.5% vs. 68.9%, p = .018, suggesting the presence of ego bias. The magnitude and directions of these differences varied significantly among the attending physicians (F = 4.3, degrees of freedom = 3, p = .0062 by repeated-measures analysis of variance) and the house officers (F = 6.3, degrees of freedom = 5, p = .0001). CONCLUSIONS: The critical care attending physicians exhibited reverse ego bias that was mainly a function of their optimism about the overall survival rate for critically ill patients. The house officers exhibited ego bias that was mainly a function of their pessimism about the overall survival rate for critically ill patients.
Attitude of Health Personnel↗
Peering into the bias blind spot: people's assessments of bias in themselves and others.
People tend to believe that their own judgments are less prone to bias than those of others, in part because they tend to rely on introspection for evidence of bias in themselves but on their lay theories in assessing bias in others. Two empirical consequences of this asymmetry are explored. Studies 1 and 2 document that people are more inclined to think they are guilty of bias in the abstract than in any specific instance. Studies 3 and 4 demonstrate that people tend to believe that their own personal connection to a given issue is a source of accuracy and enlightenment but that such personal connections in the case of others who hold different views are a source of bias. The implications of this asymmetry in assessing objectivity and bias in the self versus others are discussed.
Attitude↗
Personalizing and externalizing biases in deluded and depressed patients: are attributional biases a stable and specific characteristic of delusions?
OBJECTIVES: The purpose of this study was to explore whether explicit and implicit attributional styles of delusional patients were associated to their clinical state, and whether attributions biases are specific to delusional psychopathology or also appear in other disorders (i.e. depression). DESIGN AND METHODS: A cross-sectional design was used. The sample consisted of 136 participants (40 acute deluded participants, 25 remitted deluded participants, 35 depressed patients and 36 normal controls). The Internal, Personal and Situational Attributions Questionnaire (IPSAQ) and the Pragmatic Inferential Test (PIT) were used to assess explicit and implicit attributional style, respectively. RESULTS: All participants, with the exception of the depressed patients group, showed an externalizing bias (EB) for negative events. Although both acute and remitted deluded patients showed a similar overall pattern of explicit attributions, the personalizing bias (PB) was significantly greater in the acute group. The magnitude of this bias, which was also found in the depressed patients, was significantly related to the patient's degree of severity, as assessed by the total BPRS score (r=.45, p<.001). The results on the implicit attributions were more equivocal, perhaps due the low reliability of the PIT. CONCLUSIONS: Attributional biases seem to be a stable characteristic of delusions. Yet, the PB might be a rather unspecific characteristic that varies with the degree of the severity of psychopathology. The implications of these findings for understanding the role of attributional biases in depression and delusion formation are discussed.
Acute Disease↗
Are covariation biases attributable to a priori expectancy biases?
Illusory correlation experiments indicate that people overestimate the association between random presentations of snake slides and shock, but do not overestimate the association between random presentations of slides of damaged and exposed electric outlets (DEEOs) and shock. To investigate whether reports of covariation biases might be attributable to expectancy biases, we had Ss rate the a priori probabilities with which they would expect slides of snakes (or DEEOs), flowers, and mushrooms to be paired with shock, a tone, or nothing. In Study 1, Ss reported a pattern of a priori slide/outcome probability estimates that is nearly identical to that reported by Ss who have just undergone an illusory correlation procedure involving phylogenetic fear-relevant stimuli (e.g. snakes). Therefore, postexperimental estimates of covariation involving such stimuli appear at least partly attributable to pre-experimental expectancy biases rather than solely attributable to on-line processing biases. Study 2 revealed that Ss also display inflated a priori probability estimates for DEEO slides and shock, unlike Ss who have just undergone an illusory correlation procedure involving such stimuli. Taken together, these studies suggest that random slide/outcome pairings easily abolish pre-experimental expectancy biases for ontogenetic, but not phylogenetic, fear-relevant stimuli.
Adult↗
Bias in estimates of quantitative-trait-locus effect in genome scans: demonstration of the phenomenon and a method-of-moments procedure for reducing bias.
An attractive feature of variance-components methods (including the Haseman-Elston tests) for the detection of quantitative-trait loci (QTL) is that these methods provide estimates of the QTL effect. However, estimates that are obtained by commonly used methods can be biased for several reasons. Perhaps the largest source of bias is the selection process. Generally, QTL effects are reported only at locations where statistically significant results are obtained. This conditional reporting can lead to a marked upward bias. In this article, we demonstrate this bias and show that its magnitude can be large. We then present a simple method-of-moments (MOM)-based procedure to obtain more-accurate estimates, and we demonstrate its validity via Monte Carlo simulation. Finally, limitations of the MOM approach are noted, and we discuss some alternative procedures that may also reduce bias.
Bias↗
Impact of severity of illness bias and control group misclassification bias in case-control studies of antimicrobial-resistant organisms.
BACKGROUND: Case-control studies often analyze risk factors for antibiotic resistance. Recently published articles have illustrated that randomly selected control-patients may be preferable to those with the susceptible phenotype of the organism. A possible methodologic problem with randomly selected control-patients is potential bias due to control group misclassification. This occurs if some control-patients did not have clinical cultures performed and thus might have been unidentified case-patients. If this bias exists, these studies might be expected to report lower odds ratios (ORs) because control-patients would be more like case-patients. OBJECTIVE: To analyze potential biases that might arise due to control group misclassification and potentially larger selection biases that may be introduced if control-patients are required to have at least one clinical culture. PATIENTS: One hundred twenty case-patients, 770 control-patients in group 1, and 510 control-patients in group 2. METHODS: Two case-control studies. Case-patients had clinical cultures positive for imipenem-resistant Pseudomonas aeruginosa. The first group of control-patients were random. The second group of control-patients were identical to those in group 1 except being required to have at least one clinical culture. RESULTS: Univariate analyses showed higher ORs for case-patients versus control-patients in group 1 (imipenem [OR, 12.5], piperacillin-tazobactam [OR, 3.7], and vancomycin [OR, 4.7]) as compared with case-patients versus control-patients in group 2 (imipenem [OR, 8.0], piperacillin-tazobactam [OR, 2.5], and vancomycin [OR, 3.0]). CONCLUSION: Requiring control-patients to have at least one clinical culture introduces a selection bias likely because it eliminates patients with less severe illness.
Anti-Bacterial Agents↗