Variable selection in Cox regression models with varying coefficients
نویسندگان
چکیده
منابع مشابه
Variable selection in Cox regression models with varying coefficients
We deal with two kinds of Cox regression models with varying coefficients. The coefficients vary with time in one model. In the other model, there is an important random variable called an index variable and the coefficients vary with the variable. In both models, we have p-dimensional covariates and p increases moderately. However, it is the case that only a small part of the covariates are re...
متن کاملModel selection for Cox models with time-varying coefficients.
Summary Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right-censored failure times. Because not all covariate coefficients are time varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time-varying coefficient from those with time-independent coefficient. ...
متن کاملVariable Selection for Regression Models
A simple method for subset selection of independent variables in regression models is proposed. We expand the usual regression equation to an equation that incorporates all possible subsets of predictors by adding indicator variables as parameters. The vector of indicator variables dictates which predictors to include. Several choices of priors can be employed for the unknown regression coeecie...
متن کاملVariable selection in quantile varying coefficient models with longitudinal data
In this paper, we develop a new variable selection procedure for quantile varying coefficient models with longitudinal data. The proposed method is based on basis function approximation and a class of group versions of the adaptive LASSOpenalty,which penalizes the Lγ norm of the within-group coefficients with γ ≥ 1. We show that with properly chosen adaptive group weights in the penalization, t...
متن کاملCensored Quantile Regression with Varying Coefficients
We propose a varying-coefficient quantile regression model for survival data subject to random censoring. Motivated by the work of Yang (1999), quantilebased moments are constructed using covariate-weighted empirical cumulative hazard functions. We estimate regression parameters based on the generalized method of moments. The proposed estimators are shown to be consistent and asymptotically nor...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Planning and Inference
سال: 2014
ISSN: 0378-3758
DOI: 10.1016/j.jspi.2013.12.002