ALassoSurvIC
Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data
Penalized variable selection tools for the Cox proportional hazards model with interval censored and possibly left truncated data. It performs variable selection via penalized nonparametric maximum likelihood estimation with an adaptive lasso penalty. The optimal thresholding parameter can be searched by the package based on the profile Bayesian information criterion (BIC). The asymptotic validity of the methodology is established in Li et al. (2019 doi:10.1177/0962280219856238). The unpenalized nonparametric maximum likelihood estimation for interval censored and possibly left truncated data is also available.
- Version0.1.1
- R version≥ 3.5.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release12/01/2022
Documentation
Team
Daewoo Pak
Chenxi Li
David Todem
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