We aim for fitting a multinomial regression model with Lasso penalty and doing statistical inference (calculating confidence intervals of coefficients and p-values for individual variables). It implements 1) the coordinate descent algorithm to fit an l1-penalized multinomial regression model (parameterized with a reference level); 2) the debiasing approach to obtain the inference results, which is described in "Tian, Y., Rusinek, H., Masurkar, A. V., & Feng, Y. (2024). L1‐Penalized Multinomial Regression: Estimation, Inference, and Prediction, With an Application to Risk Factor Identification for Different Dementia Subtypes. Statistics in Medicine, 43(30), 5711-5747."
Package details |
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Author | Ye Tian [aut, cre], Henry Rusinek [aut], Arjun V. Masurkar [aut], Yang Feng [aut] |
Maintainer | Ye Tian <ye.t@columbia.edu> |
License | GPL-2 |
Version | 0.1.1 |
Package repository | View on CRAN |
Installation |
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