Integrative data analysis from a unifying research synthesis perspective

Eun Young Mun, Anne E. Ray

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

7 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationAlcohol Use Disorders
Subtitle of host publicationA Developmental Science Approach to Etiology
Pages351-354
Number of pages4
ISBN (Electronic)9780190676025
DOIs
StatePublished - Jan 18 2018

Bibliographical note

Publisher Copyright:
© Oxford University Press 2018. All rights reserved.

Keywords

  • Alcohol Interventions
  • College students
  • Individual participant-level data
  • Integrative data analysis
  • Meta-analysis

ASJC Scopus subject areas

  • General Psychology

Fingerprint

Dive into the research topics of 'Integrative data analysis from a unifying research synthesis perspective'. Together they form a unique fingerprint.

Cite this