collapse: Advanced and Fast Statistical Computing and Data Transformation in R. Krantz, S. Journal of Statistical Software 2026, 116(1), 1–38. doi.org/10.18637/jss...
Selective randomization inference for adaptive experiments. Tobias Freidling, Qingyuan Zhao, Zijun Gao. Journal of the Royal Statistical Society Series B: Statistical Methodology. doi.org/10.1093/jrss...
bayesNMF: Fast Bayesian Poisson NMF with Automatically Learned Rank Applied to Mutational Signatures. Jenna M. Landy, Nishanth Basava & Giovanni Parmigiani. Journal of Computational and Graphical Statistics. www.tandfonline.com/doi/full/10....
Causal Inference: A Tale of Three Frameworks. Linbo Wang, Thomas S. Richardson, James M. Robins. Journal of Data Science. jds-online.org/journal/JDS/...
Automatic debiased machine learning for covariate shifts. V Chernozhukov, M Newey, W K Newey, R Singh, V Syrgkanis. Biometrika. doi.org/10.1093/biom...
Global Sensitivity Analysis for Studies Extending Inferences From a Randomized Trial to a Target Population. Issa J. Dahabreh, James M. Robins, Sebastien J-P. A. Haneuse, Sarah E. Robertson, Jon A. Steingrimsson, Miguel A. Hernán. Statistics in Medicine. onlinelibrary.wiley.com/doi/10.1002/...
Bayesian and Frequentist Stratified Analysis of Treatment Effects with Survival Data in Comparative Trials. Bayesian and Frequentist Stratified Analysis of Treatment Effects with Survival Data in Comparative Trials. Paydarfar D et al. Stat Biopharm Res. www.tandfonline.com/doi/full/10....
Simulating Complex Cross-Sectional and Longitudinal Data Using the simDAG R Package. Denz, R., & Timmesfeld, N. Journal of Statistical Software 2026, 116(2), 1–40. doi.org/10.18637/jss...
Pseudo-death: a new measure to evaluate composite outcomes in survival analysis. Jialu Fang, Yu Gu, Guosheng Yin. Journal of the Royal Statistical Society Series C: Applied Statistics. doi.org/10.1093/jrss...
Revisiting Bessel’s Correction and the Bias-Variance Tradeoff in Variance Estimation. Parzival Borlinghaus, Maximilian Coblenz, Oliver Grothe, Fabian Kächele. The American Statistician. www.tandfonline.com/doi/full/10....
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<p>collapse is a large C/C++-based infrastructure package facilitating complex statistical computing, data transformation, and exploration tasks in R - at outstanding levels of performance and memory ...
Bayesian Poisson Non-Negative Matrix Factorization (NMF) is widely used to model count data, including in cancer mutational signature analysis. However, standard Gibbs samplers rely on computationa...
When estimating the variance from a sample, usually the so-called Bessel’s correction is used, that is, unintuitively each term is weighted by the sample size n minus one. Although this is an unbia...
When individuals participating in a randomized trial differ with respect to the distribution of effect modifiers compared with the target population where the trial results will be used, treatment ef....
In comparative studies with time-to-event outcomes, stratified analyses are routinely used to adjust for imbalances in baseline characteristics between treatment groups, with the stratified Cox pro...
<p>Generating artificial data is a crucial step when performing Monte Carlo simulation studies. Depending on the planned study, complex data generation processes (DGPs) containing multiple, possibly t...
SUMMARY. We present machine learning estimators for causal and predictive parameters under covariate shift, where covariate distributions differ between tr
jds-online.org
Causal inference is a central goal across many scientific disciplines. Over the past several decades, three major frameworks have emerged to formalize causal questions and guide their analysis: the po...
Abstract. Traditional methods for analysing composite survival endpoints, such as the proportional hazards model, proportional mean, proportional win-fract
