Flexible Bayesian longitudinal models for cost-effectiveness analyses with informative missing data.

ABSTRACT: Cost-effectiveness analyses (CEA) are recommended to include sensitivity analyses which make a range of contextually plausible assumptions about missing data. However, with longitudinal data on, for example, patients' health-related quality of life (HRQoL), the missingness patterns can be complicated because data are often missing both at specific timepoints (interim missingness) and following loss to follow-up. Methods to handle these complex missing data patterns have not been developed for CEA, and must recognize that data may be missing not at random, while accommodating both the correlation between costs and health outcomes and the non-normal distribution of these endpoints. We develop flexible Bayesian longitudinal models that allow the impact of interim missingness and loss to follo

SUBMITTER: Mason AJ 

PROVIDER: S-EPMC7617114 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature