Do individual differences in face recognition ability moderate the other ethnicity effect?

Individuals are better at recognizing faces from their own ethnic group compared with other ethnicity faces-the (OEE). This finding is said to reflect differences in experience and familiarity to faces from other ethnicities relative to faces corresponding with the viewers' ethnicity. However, own-ethnicity face recognition performance ranges considerably within a population, from very poor to extremely good.

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology.

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature.

Learning Through Chain Event Graphs: The Role of Maternal Factors in Childhood Type 1 Diabetes.

Chain event graphs (CEGs) are a graphical representation of a statistical model derived from event trees. They have previously been applied to cohort studies but not to case-control studies. In this paper, we apply the CEG framework to a Yorkshire, United Kingdom, case-control study of childhood type 1 diabetes (1993-1994) in order to examine 4 exposure variables associated with the mother, 3 of which are fully observed (her school-leaving-age, amniocenteses during pregnancy, and delivery type) and 1 with missing values (her rhesus factor), while incorporating previous type 1 diabetes knowledge.