Bias-corrected estimators for proportion of true null hypotheses: application of adaptive FDR-controlling in segmented failure data.

ABSTRACT: Two recently introduced model-based bias-corrected estimators for proportion of true null hypotheses ( π0 ) under multiple hypotheses testing scenario have been restructured for random observations under a suitable failure model, available for each of the common hypotheses. Based on stochastic ordering, a new motivation behind formulation of some related estimators for π0 is given. The reduction of bias for the model-based estimators are theoretically justified and algorithms for computing the estimators are also presented. The estimators are also used to formulate a popular adaptive multiple testing procedure. Extensive numerical study supports superiority of the bias-corrected estimators. The necessity of the proper distributional assumption for the failure data in the context of the mod

SUBMITTER: Biswas A 

PROVIDER: S-EPMC9562841 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature