The first component develops and compares parametric and non-parametric tests to assess the assumption of homogeneity of effects in data from a series of trials. This component considers data from Gaussian, binomial, and Poisson sampling distributions. The second considers meta-analytic methods for combining the evidence from a series of HIV seroprevalence studies to estimate HIV prevalence in a target population. Sentinel studies are typically investigations of incompletely defined cohorts which are convenient to survey but are often based on non-probability samples. Self-selection and similar issues inherent in sentinel studies makes generalizing results from a single study to a target population problematic. This research assesses the use of formal meta-analytic methods for HIV prevalence estimation in a target population by incorporating information from several HIV sentinel seroprevalence studies. The third component addresses issues that pertain to the use of meta-analysis in the design and monitoring of clinical trials. This research evaluates the role of formal incorporation of external evidence summarized from a meta-analysis of previous or concurrent results into sample size considerations and stopping rules during the conduct of a clinical trial.