Simulation Study on Measurement Bias in Intensive Longitudinal Data for ML-SEM

A simulation study evaluating model fit in multilevel structural equation models (ML-SEM) under conditions of within-person nonuniform measurement bias. The study simulated intensive longitudinal data (ILD) across 450 conditions varying sample sizes, retesting frequencies, and intraclass correlations. It was authored by Georg Krammer and last updated on April 23, 2026.

Use Cases

• Evaluating the performance of fit indices (χ², CFI, RMSEA, SRMR) in ML-SEM based on the described simulation conditions.
• Designing studies using ecological momentary assessment or daily diary methods based on the provided guidelines for sample sizes and retesting frequencies.
• Investigating the impact of within-person nonuniform measurement bias on the comparability of measurements across time.

Strengths

• Simulation covers 450 distinct conditions, allowing for a detailed analysis of effects.
• Results provide specific practical recommendations on sample sizes and retesting frequencies.
• The dataset is openly licensed under CC-BY-4.0.

Limitations

• The dataset is a 107.4 KB DOCX file, indicating a very limited scope focused on documentation rather than raw simulation data.
• Row count and column-level documentation are unknown, which may limit suitability assessment.
• The description does not specify the exact variables or parameters used in the simulations.

Provenance

Source

figshare

Collection Method

Data was generated via simulation for a methodological study.

Freshness

Last updated 2026-04-23 05:34:48; freshness should be verified.