5 citations · 8 across the 7 of their papers we have counts for
4 papers · 1 filter
Bayesian additive regression trees for evaluating treatment benefit predictors using observational data
Yuan Xia, Mohsen Sadatsafavi, Jeenat Mehareen +1
A treatment benefit predictor (TBP) is an algorithm that maps a patient's characteristics to their putative benefit from a given treatment, which can be used to inform treatment de…
Methods for adjusting for covariate measurement error in flexible modelling of functional form: results of a blinded, controlled neutral comparison simulation study
Mohammed Sedki, Aris Perperoglou, Anne C. M. Thiébaut +6
Covariate measurement error is pervasive in epidemiological research and distorts estimated exposure-outcome associations, yet correction methods have been studied almost exclusive…
Methods for adjusting for covariate measurement error in flexible modelling of functional form: designing a blinded, controlled neutral comparison simulation study
Anne C M Thiébaut, Aris Perperouglou, Mohammed Sedki +6
This article describes the design of a neutral comparison study in the context of empirical studies where the interest is in learning the functional relationship between a continuo…
Don't Disregard the Data for Lack of a Likelihood: Bayesian Synthetic Likelihood for Enhanced Multilevel Network Meta-Regression
Harlan Campbell, Charles C. Margossian, Jeroen P. Jansen +1
Multilevel network meta-regression (ML-NMR) enables population-adjusted indirect treatment comparisons by combining individual patient data (IPD) with aggregate data. When individu…