Optimal allocation in stratified cluster-based outcome-dependent sampling designs.

ABSTRACT: In public health research, finite resources often require that decisions be made at the study design stage regarding which individuals to sample for detailed data collection. At the same time, when study units are naturally clustered, as patients are in clinics, it may be preferable to sample clusters rather than the study units, especially when the costs associated with travel between clusters are high. In this setting, aggregated data on the outcome and select covariates are sometimes routinely available through, for example, a country's Health Management Information System. If used wisely, this information can be used to guide decisions regarding which clusters to sample, and potentially obtain gains in efficiency over simple random sampling. In this article, we derive a series of formu

SUBMITTER: Sauer S 

PROVIDER: S-EPMC8812629 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature