ArticleStatistical methods in medical research2024
Weight calibration in the joint modelling of medical cost and mortality.
Article in Statistical methods in medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Joint Modeling of Longitudinal and Survival Data in Public Health and Biomedical Research: A Systematic Review.International journal of environmental research and public health · 2026Pooled it
- Verbal Fluency Selectively Predicts Survival in Old and Very Old Age.Psychological science · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Joint modelling of longitudinal and time-to-event data is a method that recognizes the dependency between the two data types, and combines the two outcomes into a single model, which leads to more precise estimates. These models are applicable when individuals are followed over a period of time, generally to monitor the progression of a disease or a medical condition, and also when longitudinal covariates are available. Medical cost datasets are often also available in longitudinal scenarios, but these datasets usually arise from a complex sampling design rather than simple random sampling and such complex sampling design needs to be accounted for in the statistical analysis. Ignoring the sampling mechanism can lead to misleading conclusions. This article proposes a novel approach to the joint modelling of complex data by combining survey calibration with standard joint modelling. This is achieved by incorporating a new set of equations to calibrate the sampling weights for the survival model in a joint model setting. The proposed method is applied to data on anti-dementia medication costs and mortality in people with diagnosed dementia in New Zealand.
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