Discrepant analysis is a widely used technique for estimating the performance parameters of a laboratory test. In discrepant analysis, each specimen is initially tested with the candidate test and a comparison method, and when the results of the two tests disagree, a confirmatory test is used to resolve the discrepancy. Discrepant analysis usually produces biased estimates. This report quantifi...

OBJECTIVE Along with impaired discrimination, patients with Alzheimer's disease (AD) often show an abnormally liberal response bias (greater tendency to respond "old"). Previously we matched discrimination by varying study-test list length and found that participants' usual bias is maintained, such that patients with AD were more liberal than healthy controls. However, this pattern could be a r...

Theoretical frameworks highlight the importance of threat-related information-processing biases for understanding the emergence of anxiety in childhood. The psychometric properties of several tasks measuring these biases and their associations with anxiety were examined in an unselected sample of 9-year-old children (N=155). In each task, threat bias was assessed using bias scores reflecting ta...

Meta-analysis is increasingly utilised in the understanding of consumer behaviour, including in relation to farm animal welfare. However, the issue of publication bias has received little attention. As willingness-to-pay (WTP) is widely used in policy, it is important to explore publication bias. This research aimed to evaluate publication bias in WTP, specifically public WTP for farm animal we...

Supervised learning in machine learning concerns inferring an underlying relation between covariate x and target y based on training covariate-target data. It is traditionally assumed that training data and test data, on which the generalization performance of a learning algorithm is measured, follow the same probability distribution. However, this standard assumption is often violated in many ...

while ignoring income distribution and estimating aggregate demand generally leads to aggregation bias and thus, does not reflect households’ demand properly, yet aggregation bias is rarely considered in empirical demand studies and simply is ignored in most cases. the objective of the present study is to estimate aggregation bias in households’ demand for various types of meats and to evaluate...

Bias in testing has been of interest to psychologists and other test users since the origin of testing. New or revised tests often are subject to analyses that help examine the degree of bias in reference to group membership based on gender, language use, and race/ethnicity. The pervasive use of intelligence test data when making critical and, at times, life-changing decisions warrants the need...

BACKGROUND The tendency towards publication bias is greater for observational studies than for randomized clinical trials. Several statistical methods have been developed to test the publication bias. However, almost all existing methods exhibit rather low power or have inappropriate type I error rates. METHODS We propose a modified regression method, which used a smoothed variance to estimat...