missCompare R package - intuitive missing data imputation framework

analysing missing data handling methods with text-mining

A literature review exploring how missing data was handled across the pipeline of commonly used UK clinical prediction models

Este estudio investiga la efectividad de la imputación múltiple en el análisis factorial confirmatorio (AFC) con datos de liderazgo, donde se simularon valores perdidos (MCAR) en un 40% de la muestra.

Supplementary material and reproducible research files for article “A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations” by Emma Skarstein, Sara Martino and Stefanie Muff.