joyfulstones
I am interested in the statistical analysis of survival and longitudinal data, and machine learning methods.
Washington University in St. LouisDivision of Biostatistics
Pinned Repositories
Biometrics2008
Code in Liu, L., Huang, X. and O’Quigley, J. (2008). Analysis of longitudinal data in the presence of informative observational times and a dependent terminal event, with application to medical cost data. Biometrics 64, 950-958.
Biometrics2016
Code for paper: Liu, L., Huang, X., Yaroshinsky, A., Cormier, J. (2016). Joint frailty models for zero-inflated recurrent events in the presence of a terminal event. Biometrics. 72, 204-214.
HIMA
High-dimensional Mediation Analysis (HIMA)
HIMA2
HIMA2: High-dimensional Mediation Analysis and its application in epigenome-wide DNA methylation data
joint-model-longitudinal-recurrent-survival
SAS Code in Liu, L. and Huang X. (2009). Joint analysis of correlated repeated measures and recurrent events processes in the presence of a dependent terminal event. Journal of Royal Statistical Society Series C: Applied Statistics 58, 65-81.
marginalized-2PM-with-Beta
This is the SAS code for the paper "A Marginalized Two Part Beta Regression Model for Microbiome Compositional Data"
microbiome-mediation-SIS
This is the R code used in the paper "Testing mediation effects in high-dimensional microbiome compositional data"
two-part-joint-model
Code in Liu, L. (2009). Joint modeling longitudinal semi-continuous data and survival, with application to longitudinal medical cost data. Statistics in Medicine 28, 972-986.
variable-selection-in-joint-frailty-models
Variable selection in joint frailty models of recurrent and terminal events
zero-inflated-continuous
This repository contains SAS programs using in the paper "Analysis of zero-inflated continuous data"
joyfulstones's Repositories
joyfulstones/HIMA2
HIMA2: High-dimensional Mediation Analysis and its application in epigenome-wide DNA methylation data
joyfulstones/joint-model-longitudinal-recurrent-survival
SAS Code in Liu, L. and Huang X. (2009). Joint analysis of correlated repeated measures and recurrent events processes in the presence of a dependent terminal event. Journal of Royal Statistical Society Series C: Applied Statistics 58, 65-81.
joyfulstones/marginalized-2PM-with-Beta
This is the SAS code for the paper "A Marginalized Two Part Beta Regression Model for Microbiome Compositional Data"
joyfulstones/microbiome-mediation-SIS
This is the R code used in the paper "Testing mediation effects in high-dimensional microbiome compositional data"
joyfulstones/variable-selection-in-joint-frailty-models
Variable selection in joint frailty models of recurrent and terminal events
joyfulstones/Biometrics2008
Code in Liu, L., Huang, X. and O’Quigley, J. (2008). Analysis of longitudinal data in the presence of informative observational times and a dependent terminal event, with application to medical cost data. Biometrics 64, 950-958.
joyfulstones/Biometrics2016
Code for paper: Liu, L., Huang, X., Yaroshinsky, A., Cormier, J. (2016). Joint frailty models for zero-inflated recurrent events in the presence of a terminal event. Biometrics. 72, 204-214.
joyfulstones/causality
This is the repository for SAS and R codes for the causality mechanism of the joint analysis of longitudinal and survival data
joyfulstones/HIMA
High-dimensional Mediation Analysis (HIMA)
joyfulstones/two-part-joint-model
Code in Liu, L. (2009). Joint modeling longitudinal semi-continuous data and survival, with application to longitudinal medical cost data. Statistics in Medicine 28, 972-986.
joyfulstones/zero-inflated-continuous
This repository contains SAS programs using in the paper "Analysis of zero-inflated continuous data"
joyfulstones/NLMIXED
The use of Gaussian quadrature in frailty proportional hazards models. Statistics in Medicine 27, 2665-2683
joyfulstones/rticles
LaTeX Journal Article Templates for R Markdown
joyfulstones/THIMA
This is the R code for the targeted mediation analysis for high dimensional mediators
joyfulstones/twopart
Code in Liu, L., Strawderman, R. L., Johnson, B. A., O'Quigley, J.M. (2016). Analyzing repeated measures semi-continuous data, with application to an alcohol dependence study. Statistical Methods in Medical Research. 25, 133-152.
joyfulstones/variable-selection-for-random-effects-two-part-model
This code is for the paper "variable selection for random effects two-part models"