Harmonizing Depression Measures Across Studies: a Tutorial for Data Harmonization.

ABSTRACT: There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures for an IDA, including item selection, response coding, and modeling decisions. We analyzed caregivers' self-reported data from the ADHD Teen Integrative Data Analysis Longitudinal (ADHD TIDAL) dataset; data from 621 of 854 caregivers were available. We used moderated nonlinear factor analysis (MNLFA) to harmonize items reflecting depressive symptoms. Items were drawn from the Symptom Checklist 90-Revised, the Patient Health Questionnaire-9, and the

SUBMITTER: Zhao X 

PROVIDER: S-EPMC9823146 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature