ArticleStructural equation modeling : a multidisciplinary journal2020
Estimation of Latent Variable Scores with Multiple Group Item Response Models: Implications for Integrative Data Analysis.
Article in Structural equation modeling : a multidisciplinary journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Methodological challenges and opportunities when studying the course of autism.Autism : the international journal of research and practice · 2025Article
- A data integration method for new advances in development cognitive neuroscience.Developmental cognitive neuroscience · 2024Article
- The bidirectional relationship between physical health and memory.Psychology and aging · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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 are ignored. Results suggest that these alternative approaches led to consistent and equally accurate latent variable estimates. Implications for IDA are discussed.
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Registered trials
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