Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors' experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.
|Title of host publication||Alcohol Use Disorders|
|Subtitle of host publication||A Developmental Science Approach to Etiology|
|Number of pages||4|
|State||Published - Jan 18 2018|
Bibliographical notePublisher Copyright:
© Oxford University Press 2018. All rights reserved.
- Alcohol Interventions
- College students
- Individual participant-level data
- Integrative data analysis
ASJC Scopus subject areas
- Psychology (all)