The Effects of Confirmation Bias Instructions and Strength of Evidence on Convictions

2012 ◽  
Author(s):  
Shannon Johnson ◽  
Lisa D. Topp
Keyword(s):  
Confirmation Bias ◽  
Strength Of Evidence

745: Confirmation Bias in Prostate Cancer Grading

2007 ◽  
Vol 177 (4S) ◽  
pp. 250-250
Author(s):  
Thomas M. Fandel ◽  
Maria Pfnuer ◽  
Claudia Corinth ◽  
Michael Ansorge ◽  
Sebastian W. Melchior ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Confirmation Bias ◽  
Cancer Grading

Confirmation bias in decision making for fingerprints, DNA and eyewitness evidence cannot be explained by cognitive style or thinking dispositions.

2019 ◽  
Author(s):  
Daniel Edgcumbe
Keyword(s):  
Decision Making ◽  
Cognitive Style ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Criminal Case ◽  
Court Cases ◽  
Legal Proceedings ◽  
Thinking Dispositions ◽  
Evaluation Of Evidence ◽  
Facial Composite

Pre-existing beliefs about the background or guilt of a suspect can bias the subsequent evaluation of evidence for forensic examiners and lay people alike. This biasing effect, called the confirmation bias, has influenced legal proceedings in prominent court cases such as that of Brandon Mayfield. Today many forensic providers attempt to train their examiners against these cognitive biases. Nine hundred and forty-two participants read a fictional criminal case and received either neutral, incriminating or exonerating evidence (fingerprint, eyewitness, or DNA) before providing an initial rating of guilt. Participants then viewed ambiguous evidence (alibi, facial composite, handwriting sample or informant statement) before providing a final rating of guilt. Final guilt ratings were higher for all evidence conditions (neutral, incriminating or exonerating) following exposure to the ambiguous evidence. This provides evidence that the confirmation bias influences the evaluation of evidence.

The Argument from (A) to (Y)

2018 ◽  
Author(s):  
Ted Poston
Keyword(s):  
Bayesian Model ◽  
Independent Evidence ◽  
Strength Of Evidence ◽  
Wide Range ◽  
Simple Summation

This chapter provides a Bayesian model of strength of evidence in cases in which there are multiple items of independent evidence. The author uses this Bayesian model to evaluate the strength of evidence for theism if, as Plantinga claims, there are two dozen or so arguments for theism. The model turns questions of the overall strength of multiple arguments into a simple summation problem. Moreover, it provides a clear framework for advancing questions about how relationships between the arguments bear on the overall strength of evidence for theism. The Bayesian model developed in this chapter has a wide-range of applications for modeling strength of evidence in cumulative case arguments.

scholarly journals Do we need to improve the reporting of evidence in tendinopathy management? A critical appraisal of systematic reviews with recommendations on strength of evidence assessment

2021 ◽  
Vol 7 (1) ◽  
pp. e000920
Author(s):  
Dimitris Challoumas ◽  
Neal L Millar
Keyword(s):  
Systematic Reviews ◽  
Assessment Tool ◽  
Data Extraction ◽  
Cochrane Collaboration ◽  
Mean Difference ◽  
Strength Of Evidence ◽  
The Mean ◽  
Randomised Controlled ◽  
Meta Analyses ◽  
The Cochrane Collaboration

ObjectiveTo critically appraise the quality of published systematic reviews (SRs) of randomised controlled trials (RCTs) in tendinopathy with regard to handling and reporting of results with special emphasis on strength of evidence assessment.Data sourcesMedline from inception to June 2020.Study eligibilityAll SRs of RCTs assessing the effectiveness of any intervention(s) on any location of tendinopathy.Data extraction and synthesisIncluded SRs were appraised with the use of a 12-item tool devised by the authors arising from the Preferred Reporting Items in Systematic Reviews and Meta-Analyses statement and other relevant guidance. Subgroup analyses were performed based on impact factor (IF) of publishing journals and date of publication.ResultsA total of 57 SRs were included published in 38 journals between 2006 and 2020. The most commonly used risk-of-bias (RoB) assessment tool and strength of evidence assessment tool were the Cochrane Collaboration RoB tool and the Cochrane Collaboration Back Review Group tool, respectively. The mean score on the appraisal tool was 46.5% (range 0%–100%). SRs published in higher IF journals (>4.7) were associated with a higher mean score than those in lower IF journals (mean difference 26.4%±8.8%, p=0.004). The mean score of the 10 most recently published SRs was similar to that of the first 10 published SRs (mean difference 8.3%±13.7%, p=0.54). Only 23 SRs (40%) used the results of their RoB assessment in data synthesis and more than half (n=30; 50%) did not assess the strength of evidence of their results. Only 12 SRs (21%) assessed their strength of evidence appropriately.ConclusionsIn light of the poor presentation of evidence identified by our review, we provide recommendations to increase transparency and reproducibility in future SRs.

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