Over the years, I have written a lot of code: simulations, analyses, functions and packages. Below are three project sites that contain information on the packages I have written, as well as a lot of useful materials related to these packages. In addition, I have listed all publications for which I can make code publically available. This will be useful for those who seek to reproduce results of simulation studies from my research papers. You can find the respective files and instructions under the code and project tags.

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MAMI

Model Averaging after Multiple Imputation

CICI

Causal Inference for Continuous Interventions

SAE

Shrinkage Averaging Estimation

Publications

Publications, and accompanying materials

Selected Projects

Featured Research

Software

Software & Code

Internal Project

An example of using the in-built project page.

Publications with Available Code

L. Bothmann, S. Dandl, M. Schomaker (2023). Causal Fair Machine Learning via Rank-Preserving Interventional Distributions. arXiv e-prints, https://arxiv.org/abs/2307.12797.

Preprint Code Slides

M. Schomaker, P. Baumann (2023). Doubly Robust Estimation of Average Treatment Effects on the Treated through Marginal Structural Models. Observational Studies, 9(3): pp.43-57.

PDF Code Dataset Project

C. Heumann, M. Schomaker, Shalabh (2023). Introduction to Statistics and Data Analysis - With Exercises, Solutions and Applications in R (Second updated and extended edition). Springer, Cham.

PDF Code Dataset

R. Zepeda-Tello, M. Schomaker, C. Maringe, M. Smith, A. Belot, B. Rachet, M. Schnitzer, M. Luque-Fernandez (2022). The Delta-Method and Influence Function in Medical Statistics: a Reproducible Tutorial. arXiv e-prints, https://arxiv.org/abs/2206.15310.

Preprint Code Project

P. Baumann, M. Schomaker, E. Rossi (2021). Estimating the Effect of Central Bank Independence on Inflation Using Longitudinal Targeted Maximum Likelihood Estimation. Journal of Causal Inference, 9(1): pp.109-146.

Preprint PDF Code Dataset Project Slides Column Column (2)

M. Schomaker (2021). Regression and Causality. arXiv e-prints, https://arxiv.org/abs/2006.11754.

Preprint Code

M. Schomaker, C. Heumann (2020). When and when not to use optimal model averaging. Statistical Papers, 61: pp.2221-2240.

Preprint PDF Code Project

M. Schomaker, M. A. Luque Fernandez, V. Leroy, M. A. Davies (2019). Using Longitudinal Targeted Maximum Likelihood Estimation in Complex Settings with Dynamic Interventions. Statistics in Medicine, 38: pp.4888-4911.

Preprint PDF Code Poster Slides

M. A. Luque Fernandez, M. Schomaker, D. Redondo-Sanchez, M.J. Sanchez Perez, A. Vaidya, M. E. Schnitzer (2019). Paradoxical Collider Effect in the Analysis of Non-Communicable Disease Epidemiological Data: a reproducible illustration and web application. International Journal of Epidemiology, 48(2): pp.640-653.

Preprint PDF Code Project

M. A. Luque-Fernandez, D. Redondo-Sanchez, M. Schomaker (2019). Effect Modification and Collapsibility in Evaluations of Public Health Interventions. American Journal of Public Health, 109(3): pp.e12-e13.

PDF Code Project

M. A. Luque-Fernandez, M. Schomaker, B. Rachet, M. E. Schnitzer (2018). Targeted maximum likelihood estimation for a binary treatment: A tutorial. Statistics in Medicine, 37(16): pp.2530-2546.

PDF Code

M. Schomaker, C. Heumann (2018). Bootstrap inference when using multiple imputation. Statistics in Medicine, 37(14): pp.2252-2266.

Preprint PDF Code Project

M. Schomaker, M. A. Davies, M. Cornell, N. Ford (2018). Assessing the risk of dolutegravir for women of childbearing potential. Lancet Global Health, 6(9): pp.e958-e959.

PDF Code

C. Heumann, M. Schomaker, Shalabh (2016). Introduction to Statistics and Data Analysis - With Exercises, Solutions and Applications in R. Springer, Heidelberg.

PDF Code Dataset

M. Schomaker, S. Hogger, L. F. Johnson, C. J. Hoffmann, T. Barnighausen, C. Heumann (2015). Simultaneous Treatment of Missing Data and Measurement Error in HIV Research Using Multiple Overimputation. Epidemiology, 26(5): pp.628-636.

PDF Code Slides

M. Schomaker, C. Heumann (2014). Model selection and model averaging after multiple imputation. Computational Statistics & Data Analysis, 71: pp.758-770.

PDF Code Project

M. Schomaker, T. Gsponer, J. Estill, M. Fox, A. Boulle (2014). Non-ignorable loss to follow-up: correcting mortality estimates based on additional outcome ascertainment. Statistics in Medicine, 33(1): pp.129-42.

PDF Code

M. Schomaker (2012). Shrinkage averaging estimation. Statistical Papers, 53(4): pp.1015-1034.

PDF Code Project