ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2020
A Bayesian parametric approach to handle missing longitudinal outcome data in trial-based health economic evaluations.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
7 citing papers in PubMed.
- Bayesian Cost-Effectiveness Analysis Using Individual-Level Data is Sensitive to the Choice of Uniform Priors on the Standard Deviations for Costs in Log-Normal Models.PharmacoEconomics · 2025Review
- The handling of missing data in trial-based economic evaluations: should data be multiply imputed prior to longitudinal linear mixed-model analyses?The European journal of health economics : HEPAC : health economics in prevention and care · 2023Article
- A scoping review of statistical methods for trial-based economic evaluations: The current state of play.Health economics · 2022Article
- Linear mixed models to handle missing at random data in trial-based economic evaluations.Health economics · 2022Article
- Flexible Bayesian longitudinal models for cost-effectiveness analyses with informative missing data.Health economics · 2021Article
- A Bayesian Framework for Patient-Level Partitioned Survival Cost-Utility Analysis.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Article
- Reference-based multiple imputation for missing data sensitivity analyses in trial-based cost-effectiveness analysis.Health economics · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Trial-based economic evaluations are typically performed on cross-sectional variables, derived from the responses for only the completers in the study, using methods that ignore the complexities of utility and cost data (e.g. skewness and spikes). We present an alternative and more efficient Bayesian parametric approach to handle missing longitudinal outcomes in economic evaluations, while accounting for the complexities of the data. We specify a flexible parametric model for the observed data and partially identify the distribution of the missing data with partial identifying restrictions and sensitivity parameters. We explore alternative non-ignorable missingness scenarios through different priors for the sensitivity parameters, calibrated on the observed data. Our approach is motivated by, and applied to, data from a trial assessing the cost-effectiveness of a new treatment for intellectual disability and challenging behaviour.
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Registered trials
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.