Bayesian pattern-mixture models for dropout and intermittent…
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- DOI 10.3758/s13428-023-02128-y
- PMID https://pubmed.ncbi.nlm.nih.gov/37221346
- PMCID https://www.ncbi.nlm.nih.gov/pmc/articles/10990982
- OpenAlex ID W4377861610
- Type Article
- Language EN
- Published 23 May 2023
- Volume 56 (3)
- Pages 1953–1967
- Source Behavior Research Methods
- Publisher Springer Science+Business Media
- FWCI 1.43
- Countries 1
- Institutions 1
- Added 24 May 2023
- Updated 29 Oct 2026
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Bayesian pattern-mixture models for dropout and intermittently missing data in longitudinal data analysis
Article 2023 EN Hybrid
Valid inference can be drawn from a random-effects model for repeated measures that are incomplete if whether the data are missing or not, known as missingness, is independent of the missing data. Data that are missing completely at random or missing at random are two data types for which missingness is ignorable. Given ignorable missingness, statistical inference can proceed without addressing th…
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1 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Shelley A. Blozis Corresponding | University of California, Davi… (US) |
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