ArticleStatistics in medicine2017
A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.
Article in Statistics in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Home-based extended rehabilitation for older people with frailty (HERO): a multicentre randomised controlled trial with health economic analysis and process evaluation.Health technology assessment (Winchester, England) · 2026Trial
- Meta Salud Diabetes study protocol: a cluster-randomised trial to reduce cardiovascular risk among a diabetic population of Mexico.BMJ open · 2018Trial
- Association Between Behavioral Phenotypes and Paid Subscription and Renewal Among New mHealth App Users: Six-Month Prospective Cohort Study.Journal of medical Internet research · 2026Article
- Change ofFrontiers in psychology · 2026Article
- Article
- Clustering-Informed Shared-Structure Variational Autoencoder for Missing Data Imputation in Large-Scale Healthcare Data.Statistics in medicine · 2025Article
- Handling Missing Outcome Data in Cluster Randomized Trials With Both Individual- and Cluster-Level Dropout.Statistics in medicine · 2025Article
- Analysis of Cohort Stepped Wedge Cluster-Randomized Trials With Nonignorable Dropout via Joint Modeling.Statistics in medicine · 2025Article
- Randomized controlled study of a digital data driven intervention for depressive and generalized anxiety symptoms.NPJ digital medicine · 2025Article
- The effect of social care nurses on health related quality of life in patients with advanced cancer: A non-randomized, multicenter, controlled trial.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- Reducing Information and Selection Bias in EHR-Linked Biobanks via Genetics-Informed Multiple Imputation and Sample Weighting.medRxiv : the preprint server for health sciences · 2024Article
- A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.BMC medical research methodology · 2023Article
- Article
- Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Intention-to-treat analysis when only a baseline value is available.Contemporary clinical trials communications · 2020Article
- Article
- Advancing successful implementation of task-shifted mental health care in low-resource settings (BASIC): protocol for a stepped wedge cluster randomized trial.BMC psychiatry · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.