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. 2021 Jun;53(3):1031-1045.
doi: 10.3758/s13428-020-01472-7.

Harmonizing altered measures in integrative data analysis: A methods analogue study

Andrea M Hussong  1 , Daniel J Bauer  2 , Michael L Giordano  2 , Patrick J Curran  2
Affiliations

Harmonizing altered measures in integrative data analysis: A methods analogue study

Andrea M Hussong et al. Behav Res Methods. 2021 Jun.

Abstract

In the current study, we used an analogue integrative data analysis (IDA) design to test optimal scoring strategies for harmonizing alcohol- and drug-use consequence measures with varying degrees of alteration across four study conditions. We evaluated performance of mean, confirmatory factor analysis (CFA), and moderated nonlinear factor analysis (MNLFA) scores based on traditional indices of reliability (test-retest, internal, and score recovery or parallel forms) and validity. Participants in the analogue study included 854 college students (46% male; 21% African American, 5% Hispanic/Latino, 56% European American) who completed two versions of the altered measures at two sessions, separated by 2 weeks. As expected, mean, CFA, and MNLFA scores all resulted in scales with lower reliability given increasing scale alteration (with less fidelity to formerly developed scales) and shorter scale length. MNLFA and CFA scores, however, showed greater validity than mean scores, demonstrating stronger relationships with external correlates. Implications for measurement harmonization in the context of IDA are discussed.

Keywords: Alcohol consequences; Data pooling; Drug consequences; Harmonization; Integrative data analysis.

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