16 citations · 18 across the 5 of their papers we have counts for
6 papers
Optimal risk-assessment scheduling for primary prevention of cardiovascular disease
Francesca Gasperoni, Christopher H. Jackson, Angela M. Wood +4
In this work, we introduce a personalised and age-specific Net Benefit function, composed of benefits and costs, to recommend optimal timing of risk assessments for cardiovascular…
Tailored Bayes: a risk modelling framework under unequal misclassification costs
Solon Karapanagiotis, Umberto Benedetto, Sach Mukherjee +2
Risk prediction models are a crucial tool in healthcare. Risk prediction models with a binary outcome (i.e., binary classification models) are often constructed using methodology w…
Statistical Methods for cis-Mendelian Randomization with Two-sample Summary-level Data
Apostolos Gkatzionis, Stephen Burgess, Paul J. Newcombe
Mendelian randomization is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two-samp…
A Bayesian framework for case-cohort Cox regression: application to dietary epidemiology
Andrew Yiu, Robert J. B. Goudie, Stephen J. Sharp +2
The case-cohort study design bypasses resource constraints by collecting certain expensive covariates for only a small subset of the full cohort. Weighted Cox regression is the mos…
Conditional inference in cis-Mendelian randomization using weak genetic factors
Ashish Patel, Dipender Gill, Paul J. Newcombe +1
Mendelian randomization is a widely-used method to estimate the unconfounded effect of an exposure on an outcome by using genetic variants as instrumental variables. Mendelian rand…
Two-Stage Penalized Regression Screening to Detect Biomarker-Treatment Interactions in Randomized Clinical Trials
Jixiong Wang, Ashish Patel, James M. S. Wason +1
High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that imp…