Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

ABSTRACT: Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the n

SUBMITTER: Huang FL 

PROVIDER: S-EPMC5965657 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature