multiple-imputation

stefvanbuuren/fimdbook

Flexible Imputation of Missing Data - bookdown source

Polkas/miceFast

R enviroment - fast imputations :dragon:

alexanderrobitzsch/miceadds

Some Additional Multiple Imputation Functions, Especially for 'mice'.

tom-metherell/Mice.jl

a package for missing data handling via multiple imputation by chained equations in Julia. It is heavily based on the R package {mice} by Stef van Buuren, Karin Groothuis-Oudshoorn and collaborators.

HRDAG/verdata

Una herramienta para el uso y análisis de los datos de Conflicto armado en Colombia resultantes del proyecto conjunto JEP-CEV-HRDAG.

mlpapers/missing-data

Awesome papers on Missing Data

dsalfran/ImputeRobust

Multiple Imputation with GAMLSS

mwheymans/psfmi

psfmi: Predictor Selection Functions for Logistic and Cox regression models in multiply imputed datasets

elliecurnow/midoc

andrewheiss/amelia-tidy-melding

Use tidyverse functions to correctly meld and pool multiply imputed model output

aperezlebel/benchmark_mv_approaches

Code of the experiments ran in our GigaScience article: "Benchmarking missing-values approaches for predictive models on health databases".

alexanderrobitzsch/mdmb

Model Based Treatment of Missing Data

JoshWeiner/ml-impute

A package for synthetic data generation for imputation using single and multiple imputation methods.

zjg540066169/BMIselect

Source Code for Paper "Bayesian MI-LASSO for variable selection on multiply-imputed data" (Arxiv: https://arxiv.org/abs/2211.00114)

survival-lumc/CauseSpecCovarMI

Code and supplementary materials for the manuscript "Multiple imputation for cause-specific Cox models: assessing methods for estimation and prediction" (2022, Statistical Methods in Medical Research)

andrewheiss/amelia-broom-huxtable

Extend broom's tidy() and glance() to work with lists of multiply imputed regression models

bips-hb/micd

Multiple Imputation in Causal Graph Discovery

survival-lumc/ReviewHaemaMissing

Code and supplementary materials for the manuscript "Handling missing covariate data in clinical studies in haematology" (2023, Best Practice & Research Clinical Haematology)

edbonneville/validation-failed-EVT

Code and supplementary materials for the manuscript "Development and validation of a prediction model for failure of the transfemoral approach of endovascular treatment for large vessel occlusion acute ischemic stroke" (2023, Cerebrovascular Diseases))

humburg/miPredict

katharina-brenner/imputation

Machine Learning in Official Statistics

kazilab/XeroGraph

XeroGraph is a Python package developed for researchers and data scientists to analyze, visualize and impute missing data in datasets.

mscsep/SAM_FGT

Analyses of Fear Generalization Task in SAM study

survival-lumc/FineGrayCovarMI

Code repository for the manuscript 'Multiple imputation of missing covariates when using the Fine–Gray model' (submitted)

amices/amices.github.io

Landing page for amices.org

DamonCharlesRoberts/imputation-with-random-forests

Replication code for "Connecting Leaves to the Forest" academic project.

ninagial/mnarinject

Inject Missing Values Not-At-Random to Simulated Likert Data Sets

tessaroes/SpotifyRecommenderSystem

Code for Master's Thesis Data Science & Society

xsswang/remiod

R package for controlled multiple imputation of ordinal or binary responses with missing data in clinical study

phydev/mice

Multiple imputation with chained equation implemented from scratch. This is a low performance implementation meant for pedagogical purposes only.

Zoey1102/Incomplete-Data-Analysis

From missing mechanism of data to data imputation