There are compelling reasons to expect that cognitively representing any active, powerful deity motivates cooperative behavior. One mechanism underlying this association could be a cognitive bias toward generally attributing moral concern anthropomorphic agents. If humans represent the minds of deities and in same way, if human agents conceptualized as having concern, broad tendency attribute c...

Verification bias arises in diagnostic test evaluation studies when the results from a first test are verified by a reference test only in a non-representative subsample of the original study subjects. This occurs, for example, when inclusion probabilities for the subsample depend on first-stage results and/or on a covariate related to disease status. Reference standard bias arises when the ref...

background several empirical studies have shown the attitude of smokers to formulate judgments based on distortion in the risk perception. this alteration is produced by the activation of the optimistic bias characterized by a set of the unrealistic beliefs compared to the outcomes of their behavior. this bias exposes individuals to adopt lifestyles potentially dangerous for their health, under...

One of the fundamental assumptions behind many supervised machine learning algorithms is that training and test data follow the same probability distribution. However, this important assumption is often violated in practice, for example, because of an unavoidable sample selection bias or non-stationarity of the environment. Due to violation of the assumption, standard machine learning methods s...

The basis assumption that “training and test data drawn from the same distribution” is often violated in reality. In this paper, we propose one common solution to cover various scenarios of learning under “different but related distributions” in a single framework. Explicit examples include (a) sample selection bias between training and testing data, (b) transfer learning or no labeled data in ...

this review provides the basic principle and rational for roc analysis of rating and continuous diagnostic test results versus a gold standard. derived indexes of accuracy, in particular area under the curve (auc) has a meaningful interpretation for disease classification from healthy subjects. the methods of estimate of auc and its testing in single diagnostic test and also comparative studies...