@article{5a40c4bd70c44aec80c93e95cd83c1fc,
title = "Estimation of Latent Variable Scores with Multiple Group Item Response Models: Implications for Integrative Data Analysis",
abstract = "Integrative data analysis (IDA) involves obtaining multiple datasets, scaling the data to a common metric, and jointly analyzing the data. The first step in IDA is to scale the multisample item-level data to a common metric, which is often done with multiple group item response models (MGM). With invariance constraints tested and imposed, the estimated latent variable scores from the MGM serve as an observed variable in subsequent analyses. This approach was used with empirical multiple group data and different latent variable estimates were obtained for individuals with the same response pattern from different studies. A Monte Carlo simulation study was then conducted to compare the accuracy of latent variable estimates from the MGM, a single-group item response model, and an MGM where group differences were ignored. Results suggest that these alternative approaches led to consistent and equally accurate latent variable estimates. Implications for IDA are discussed.",
keywords = "Data integration, item response model, latent variable estimation, multi-sample, scaling",
author = "Pega Davoudzadeh and Grimm, {Kevin J.} and Widaman, {Keith F.} and Desmarais, {Sarah L.} and Stephen Tueller and Danielle Rodgers and {Van Dorn}, {Richard A.}",
note = "Funding Information: for this study was provided by the National Institute of Mental Health (NIMH), Award Number [R01MH093426] (PI: Van Dorn, Ph.D.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH or the NIH. This paper was based on data from the Facilitated Psychiatric Advance Directive project, supported by NIMH research grant [R01MH063949] and the John D. and Catherine T. MacArthur Foundation Research Network on Mandated Community Treatment (PI: Jeffrey W. Swanson, Ph.D.); data from the MacArthur Mental Disorder and Violence Risk project was supported with funds from the Research Network on Mental Health and the Law of the John D. and Catherine T. MacArthur Foundation, and by NIMH grant [R0149696] (PI: John Monahan, Ph.D.); data from the Schizophrenia Care and Assessment Program project was supported with funds from Eli Lilly, Inc., through a contract with the MedStat Group (PI: Jeffrey W. Swanson, Ph.D.); data from the MacArthur Mandated Community Treatment project was supported with funds from the John D. and Catherine T. MacArthur Foundation Research Network on Mandated Community Treatment (PI: John Monahan, Ph.D.); and data from the Clinical Antipsychotic Trials of Intervention Effectiveness project was supported with funds from NIMH contract [NO1MH90001]. Publisher Copyright: {\textcopyright} 2020 Taylor & Francis Group, LLC.",
year = "2020",
doi = "10.1080/10705511.2020.1724113",
language = "English (US)",
volume = "27",
pages = "931--941",
journal = "Structural Equation Modeling",
issn = "1070-5511",
publisher = "Psychology Press Ltd",
number = "6",
}