MMRM versus MI in Dealing with Missing Data—A Comparison Based on 25 NDA Data Sets
Abstract
Both multiple imputation (MI) and mixed-effects model repeated measures (MMRM) approaches appear to be better choices than the traditional last-observation-carried-forward (LOCF) approach in analyzing incomplete clinical trial data sets in drug development research. However, relative performances of these two approaches are unknown in controlling type I error rate and statistical power in the hypothesis testing of determining the efficacy of an investigational drug. Little research has been done in comparing robustness of the two approaches in analyzing ignorable missing data of clinical trials. In this research, a comparison between the MI and MMRM approaches is made in analyzing the simulated incomplete data sets and 25 New Drug Application (NDA) data sets of neuropsychiatric drug products. The MMRM approach appears to be a better choice in maintaining statistical properties of a test as compared to the MI approach in dealing with ignorable missing data of clinical trials.
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- Authors
- Siddiqui, O.
- Affiliations
- United States Food and Drug Administration (US)
- Corresponding author
- Siddiqui, Ohidul
- Venue
- Journal of Biopharmaceutical Statistics
- Publisher
- Informa UK Limited
- Published
- 2011-03-24
- Volume
- 21
- Issue
- 3
- Pages
- 423-436
- ISSN
- 1054-3406 (ISSN-L)
- 1520-5711
- OpenAlex
- W2050266605
- Cited by
- 63
- References
- 37
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 7 · 2023: 5 · 2022: 4 · 2021: 2 · 2020: 4 · 2019: 5 · 2018: 4 · 2017: 5 · 2016: 2 · 2015: 3 · 2014: 5 · 2013: 2 · 2012: 1
- FWCI
- 2.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Biopharmaceutical Statistics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- multiple imputation, missing data, last observation carried forward, type I error rate, statistical power, neuropsychiatric drugs, drug efficacy testing
- MeSH terms
- Clinical Trials as Topic, Computer Simulation, Humans, Patient Dropouts, Regression Analysis, Research Design, Models, Statistical, Drugs, Investigational, Randomized Controlled Trials as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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