Identifying Important Risk Factors for Future Mania in
Individuals with Major Depressive Disorder Using Weighted Random Forest
Models and the NESARC Dataset
This is the capstone project for my master’s degree. Here you can
find my presentation
slides and the report.
Understanding
weights options “proportional” and “outer” in EMMeans
In this project, I pioneered research on weights options in Estimated
Marginal Means (EMMs), clarifying application practices through
empirical testing and mathematical analysis. Additionally, I
collaborated with my colleagues at Mental Health Data Science, Columbia
University Department of Psychiatry and New York State Psychiatric
Institute to test and understand the “type” and “regrid” options in
EMMs, and figured out the calculation methods of EMMs from models with
link function for emmeans function in R,
Genmod lsmeans and %margins macro in SAS.
Here you can find the presentation
slides and my code
packet.