Pinned Repositories
adaptBayes
R package for Boonstra, Philip S. and Barbaro, Ryan P., “Incorporating Historical Models with Adaptive Bayesian Updates” (2020) Biostatistics 21, e47--e64
AEenrich
Gene enrichment tests to perform adverse event (AE) enrichment analysis/ Lili Zhao
iBAG
R/Shiny app for integrative Bayesian analyses of genomics models/ BayesRX Group
ImageOnScalarRegression
Shiny app for viewing brain image data and fitting image on scalar regression/ Jian Kang
MetaIntegration
PPMR
Probabilistic two sample Mendelian Randomization
Rbootcamp
R short course taught at University of Michigan Biostatistics
SEIRfansy
Extended Susceptible-Exposed-Infected-Recovery (SEIR) Model for handling high False Negative Rate and Symptom based administration of diagnostic tests
SynDI
Regression inference for multiple populations by integrating summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and Mukherjee, B.
zGPS.AO
Department of Biostatistics at the University of Michigan's Repositories
umich-biostatistics/iBAG
R/Shiny app for integrative Bayesian analyses of genomics models/ BayesRX Group
umich-biostatistics/adaptBayes
R package for Boonstra, Philip S. and Barbaro, Ryan P., “Incorporating Historical Models with Adaptive Bayesian Updates” (2020) Biostatistics 21, e47--e64
umich-biostatistics/AEenrich
Gene enrichment tests to perform adverse event (AE) enrichment analysis/ Lili Zhao
umich-biostatistics/PPMR
Probabilistic two sample Mendelian Randomization
umich-biostatistics/SEIRfansy
Extended Susceptible-Exposed-Infected-Recovery (SEIR) Model for handling high False Negative Rate and Symptom based administration of diagnostic tests
umich-biostatistics/FEprovideR
A structured profile likelihood algorithm for the logistic fixed effects model with high-dimensional parameters/ Kevin He
umich-biostatistics/healthds
umich-biostatistics/HPC-R-Examples
Example R jobs and scripts for HPC use.
umich-biostatistics/ImageOnScalarRegression
Shiny app for viewing brain image data and fitting image on scalar regression/ Jian Kang
umich-biostatistics/MetaIntegration
umich-biostatistics/Rbootcamp
R short course taught at University of Michigan Biostatistics
umich-biostatistics/SynDI
Regression inference for multiple populations by integrating summary-level data using stacked imputations. Gu, T., Taylor, J.M.G. and Mukherjee, B.
umich-biostatistics/zGPS.AO
umich-biostatistics/ActiSleep
umich-biostatistics/corrsurv
Tests for correlated survival data/ Susan Murray
umich-biostatistics/ECLasso
R package for solving the equality-constrained lasso using inexact ADMM/ Jiang Group
umich-biostatistics/ers
Environmental Risk Score in R/ Sung Kyun Park, Bhramar Mukherjee
umich-biostatistics/hugo_site
Homepage for Biostat. computing.
umich-biostatistics/IMAGE
This package performs high-powered detection of genetic effects on DNA methylation using integrated methylation QTL mapping and allele-specific analysis/ Xiang Zhou
umich-biostatistics/lcra
Joint latent class and regression analysis using MCMC/ Michael Elliot
umich-biostatistics/metaboplot
Shiny interface for exploring metabolite plots based on attributes/ Laura Scott
umich-biostatistics/MiCAPmodels
umich-biostatistics/PRECISE
Proteomic based integrated subject-specific networks in cancer/ BayesRx Group
umich-biostatistics/qif
Estimation and inference in longitudinal data analysis using marginal models/ Peter X.K. Song
umich-biostatistics/rankmodelr
R package for Boonstra and Krauss (2019)
umich-biostatistics/SBLF
Spatial Bayesian Latent Factor Models for Image-on-Image Regression/ Guo, Kang, and Johnson
umich-biostatistics/SIRcorona
Visualize results for state-space SIR models with time-varying quarantine protocols applied to Corona virus/ Peter Song
umich-biostatistics/snSMART
small n Sequential, Multiple Assignment, Randomized Trial (snSMART) two-stage clinical trial design/ Kidwell
umich-biostatistics/TimeVarying
/ Kevin He
umich-biostatistics/umich-biostatistics.github.io