Explainable Machine Learning in Survival Analysis
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Updated
Jun 15, 2024 - R
Explainable Machine Learning in Survival Analysis
Group sequential design for clinical trials
A R package and executable for the preprocessing, statistical analysis, and downstream testing and visualization of differentially methylated regions (DMRs) from CpG count matrices (Bismark cytosine reports)
R package for fitting joint models to time-to-event data and multivariate longitudinal data
R package for High dimensional data analysis and integration with O2PLS!
Analysis of simulation studies including Monte Carlo error
Clinical Trial Simulations
R package for fitting joint models to time-to-event and longitudinal data
locus R package - Large-scale variational inference for variable selection in sparse multiple-response regression
Comparative BA-calculation for the EMA's Average Bioequivalence with Expanding Limits (ABEL)
EpiMethEx (Epigenetic Methylation and Expression), a R package to perform a large-scale integrated analysis by cyclic correlation analyses between methylation and gene expression data.
Virtual Experiments to Teach Experimental Design
Incidence Estimation Tools
Something about epi methods, biostats, infectious diseases
R package: Condition-Decomposition Normalization for Biological Applications
R Package Hosted on CRAN to Compute Expected Years of Life Lost (YLL) and Average YLL. See https://CRAN.R-project.org/package=yll
📦 🔬 R/biotmle: Targeted Learning with Moderated Statistics for Biomarker Discovery
Code for sampling from an approximate normalised power posterior using Stan.
Miscellaneous Esoteric Statistical Scripts - an R package
Lesson on statistical distributions in biology
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