5 papers
Bayesian modelling for binary outcomes in the Regression Discontinuity Design
Sara Geneletti, Federico Ricciardi, Aidan O'Keeffe +1
The Regression Discontinuity (RD) design is a quasi-experimental design which emulates a randomised study by exploiting situations where treatment is assigned according to a contin…
Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: a Review with Future Guidelines
Andrea Gabrio, Alexina Mason, Gianluca Baio
Cost-Effectiveness Analyses (CEAs) alongside randomised controlled trials (RCTs) are increasingly often designed to collect resource use and preference-based health status data for…
A Review of Methods for the Analysis of the Expected Value of Information
Anna Heath, Ioanna Manolopoulou, Gianluca Baio
Over recent years Value of Information analysis has become more widespread in health-economic evaluations, specifically as a tool to perform Probabilistic Sensitivity Analysis. Thi…
Variable Selection in Covariate Dependent Random Partition Models: an Application to Urinary Tract Infection
William Barcella, Maria De Iorio, Gianluca Baio +1
Lower urinary tract symptoms (LUTS) can indicate the presence of urinary tract infection (UTI), a condition that if it becomes chronic requires expensive and time consuming care as…
Bayesian regression discontinuity designs: Incorporating clinical knowledge in the causal analysis of primary care data
Sara Geneletti, Aidan G. O'Keeffe, Linda D. Sharples +2
The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can b…