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A Bayesian Longitudinal Model for Imputing Item-Level Missing Data in Trial-Based Economic Evaluations
Xiaoxiao Ling, Andrea Gabrio, Gianluca Baio
Trial-based economic evaluations are widely used to assess the cost-effectiveness of healthcare interventions and inform decision-making. Cost and effectiveness outcomes are typica…
A Bayesian Approach for Nonignorable Dropout in Bivariate Longitudinal Models
Andrea Gabrio, Michael J. Daniels, Gianluca Baio
Longitudinal data collected in clinical trials are almost always incomplete due to some of the participants dropping out from the study during the planned follow-up. A common strat…
A Bayesian modelling framework for health care resource use and costs in trial-based economic evaluations
Andrea Gabrio
Individual-level effectiveness and healthcare resource use (HRU) data are routinely collected in trial-based economic evaluations. While effectiveness is often expressed in terms o…
A review of heath economic evaluation practice in the Netherlands: are we moving forward?
Andrea Gabrio
In 2016, the Dutch National Health Care Institute issued new guidelines that aggregated and updated previous recommendations on key elements for conducting economic evaluation. How…
Linear mixed models to handle missing at random data in trial-based economic evaluations
Andrea Gabrio, Catrin Plumpton, Sube Banerjee +1
Trial-based cost-effectiveness analyses (CEAs) are an important source of evidence in the assessment of health interventions. In these studies, cost and effectiveness outcomes are…
A Bayesian Parametric Approach to Handle Missing Longitudinal Outcome Data in Trial-Based Health Economic Evaluations
Andrea Gabrio, Michael J. Daniels, Gianluca Baio
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 th…