Integrative Data Analysis and the Study of Global Health

Abstract

In this chapter, we introduce Integrative Data Analysis (IDA) for use in the field of Global Health. IDA is a novel framework for simultaneous analysis of individual-level data pooled from multiple studies. This framework has been applied to address questions about substance use, cancer, HIV, and rare diseases from studies around the world. Advantages of this approach include efficiency (i.e., reuse of extant data), statistical power (i.e., large combined sample sizes), the potential to address questions not answerable by a single contributing study (e.g., combining studies with overlapping ethnicities to examine cross-cultural differences or age periods to examine longer periods of development), and the opportunity to test replicability of effects across studies in the pooled analysis. We describe the IDA methodological framework, emphasizing unique issues in measurement harmonization and hypothesis testing. We illustrate the application of the method using examples. We also describe emerging tools to handle specific harmonization challenges. Finally, we consider the potential utility of IDA in Global Health and epidemiological research.