Optimal two-stage sampling for mean estimation in multilevel populations when cluster size is informative.

ABSTRACT: To estimate the mean of a quantitative variable in a hierarchical population, it is logistically convenient to sample in two stages (two-stage sampling), i.e. selecting first clusters, and then individuals from the sampled clusters. Allowing cluster size to vary in the population and to be related to the mean of the outcome variable of interest (informative cluster size), the following competing sampling designs are considered: sampling clusters with probability proportional to cluster size, and then the same number of individuals per cluster; drawing clusters with equal probability, and then the same percentage of individuals per cluster; and selecting clusters with equal probability, and then the same number of individuals per cluster. For each design, optimal sample sizes are derived un

SUBMITTER: Innocenti F 

PROVIDER: S-EPMC8172256 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature