Hi everyone, this repository is about the method Sparse Common and Distinctive Covariates Logistic Regression (SCD-Cov-logR). It is a classification method that can be used with a mutliblock dataset. It fulfills three research aims:
- Construct a logistic regression model for a binary outcome variable
- Identify common and distinctive predictor processes (explained further below)
- Derive sparse and therefore interpretable coefficients
Two different predictor processes may underlie a multiblock dataset: common and distinctive processes. A common process refers to a predictor process that involves predictor variables from multiple blocks of predictors. On the other hand, a distinctive process is only associated with predictors from a single block.
In this repository, you can find all of the scripts used to generate the results reported in the paper. Feel free to reach me at s.park_1@tilburguniversity.edu when in doubt!