Multiple Testing of Composite Null Hypotheses in Heteroscedastic Models

• Published in: Journal of the American Statistical Association Vol. 107; no. 498; pp. 673 - 687
• Main Authors: Sun, Wenguang, McLain, Alexander C
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis Group 01.06.2012; Taylor & Francis Ltd
• Subjects: Ambivalence; Applied statistics; Compound decision theory; Consistent estimators; data analysis; Deconvoluting kernel density estimator; Density estimation; Deviation; Estimation; Estimators; False important discovery rate; heteroskedasticity; Hypotheses; Hypothesis; Indifference region; Large-scale simultaneous inference; Mathematical procedures; Null hypothesis; Oracles; P values; Regression analysis; Size; Standardization; Statistical methods; Statistical theories; Statistics; Testing; Theory and Methods; Variance analysis

In large-scale studies, the true effect sizes often range continuously from zero to small to large, and are observed with heteroscedastic errors. In practical situations where the failure to reject small deviations from the null is inconsequential, specifying an indifference region (or forming compo...