thestatsgeek.com Does a Bernoulli/binomial model really assume everyone has the same probability p? When you estimate a proportion and want to calculate a standard error for the estimate, you would normally do so based on assuming that the number of ‘successes’ in the sample is a draw… thestatsgeek.com Multiple imputation with flexible parametric survival models Following a recent request from someone, I’ve extended the functionality of my R package smcfcs, which performs multiple imputation of missing covariates, compatible with a user-specified sub… 
www.lshtm.ac.uk Covariate adjustment using treatment-blinded covariate selection within When estimating treatment effects in randomized clinical trials, the primary goal of covariate-adjustment is to improve precision (e.g., for linear models) and/or reduce bias (e.g., for non-linear 
jobs.lshtm.ac.uk Jobs at LSHTM www.lshtm.ac.uk Causal Machine Learning for Biomarker Subgroup Discovery in Randomised Trials Decreasing costs of high-throughput ‘omics, as well as new technologies such as the Olink proteomics platform, has driven wider application in clinical trials, for example to inform precision medicine 