Bayesian Analysis of Multi-Factorial Experimental Designs Using SEM
Bibliographic Data
| ID | 19289903 |
|---|---|
| Authors | Benedikt Langenberg (0000-0002-4757-0698, Maastricht University, corresponding author), Jonathan L Helm (0000-0001-8580-980X, San Diego State University), A Mayer (0000-0001-9716-878X, Bielefeld University) |
| Year | 2024 |
| Volume | 59 |
| Issue | 4 |
| Pages | 716-737 |
| Publication date | 2024-07-03 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Multivariate Behavioral Research (JOURNAL) |
| Journal identifiers | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273171.2024.2315557 |
| PMID | 38984637 |
| OpenAlex | W4400500402 |
| Language | EN |
| Citations received | 1 |
| References cited | 61 |
Latent repeated measures ANOVA (L-RM-ANOVA) has recently been proposed as an alternative to traditional repeated measures ANOVA. L-RM-ANOVA builds upon structural equation modeling and enables researchers to investigate interindividual differences in main/interaction effects, examine custom contrasts, incorporate a measurement model, and account for missing data. However, L-RM-ANOVA uses maximum likelihood and thus cannot incorporate prior information and can have poor statistical properties in small samples. We show how L-RM-ANOVA can be used with Bayesian estimation to resolve the aforementioned issues. We demonstrate how to place informative priors on model parameters that constitute main and interaction effects. We further show how to place weakly informative priors on standardized parameters which can be used when no prior information is available. We conclude that Bayesian estimation can lower Type 1 error and bias, and increase power and efficiency when priors are chosen adequately. We demonstrate the approach using a real empirical example and guide the readers through specification of the model. We argue that ANOVA tables and incomplete descriptive statistics are not sufficient information to specify informative priors, and we identify which parameter estimates should be reported in future research; thereby promoting cumulative research
Analysis of variance · Bayesian probability · Econometrics · Prior information · Prior probability · Repeated measures design · Statistical hypothesis testing · Statistical power · Statistics · Artificial Intelligence · Computer Science · Economic and Environmental Valuation · Mathematics · Optimal Experimental Design Methods · Statistical Methods in Clinical Trials
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |