Optimal sampling allocation for outcome-dependent designs in cluster-correlated data settings.

ABSTRACT: In clinical and public health studies, it is often the case that some variables relevant to the analysis are too difficult or costly to measure for all individuals in the population of interest. Rather, a subsample of these individuals must be identified for additional data collection. A sampling scheme that incorporates readily-available information for the entire target population at the design stage can increase the statistical efficiency of the intended analysis. While there is no universally optimal sampling design, under certain principles and restrictions, a well-designed and efficient sampling strategy can be implemented. In two-phase designs, efficiency can be gained by stratifying on the outcome and/or auxiliary information that is known at phase I. Additional gains in efficiency

SUBMITTER: Rivera-Rodriguez C 

PROVIDER: S-EPMC10897940 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature