Variable Selection in the Cox Regression Model with Covariates Missing at Random
نویسندگان
چکیده
منابع مشابه
Multi-index regression models with missing covariates at random
AMS subject classifications: 62H12 62G20 Keywords: Covariates missing at random Inverse selection probability Multi-index model Single-index model a b s t r a c t This paper considers estimation of the semiparametric multi-index model with missing covariates at random. A weighted estimating equation is suggested by invoking the inverse selection probability approach, and estimators of the indic...
متن کاملModel selection for zero-inflated regression with missing covariates
Count data are widely existed in the fields of medical trials, public health, surveys and environmental studies. In analyzing count data, it is important to find outwhether the zeroinflation exists or not and how to select the most suitable model. However, the classic AIC criterion formodel selection is invalid when the observations aremissing. In this paper, we develop a new model selection cr...
متن کاملCox Regression for Current Status Data with Missing Covariates
Statistical inference based on the right-censored data for proportional hazard (PH) model with missing covariates has received considerable attention, but interval-censored or current status data with missing covariates are not yet investigated. Our study is partly motivated by analysis of fracture data from a cross-sectional study, where the ocurrence time of fracture was interval-censored and...
متن کاملBayesian Single Index Model with Covariates Missing at Random
Bayesian single index model is a highly promising dimension reduction tool for an interpretable modeling of the non linear relationship between the response and its predictors. However, existing Bayesian tools in this area suffer from slow mixing of the Markov Chain Monte Carlo (MCMC) computational tool and also lack the ability to deal with missing covariates. To circumvent these practical pro...
متن کاملPosterior Propriety and Computation for the Cox Regression Model with Applications to Missing Covariates
In this paper, we carry out an in-depth theoretical investigation for Bayesian inference for the Cox regression model (Cox, 1972, 1975). Specifically, we establish establish necessary and sufficient conditions for posterior propriety of the regression coefficients, β, in Cox’s partial likelihood, which can be obtained as the limiting marginal posterior distribution of β through the specificatio...
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: Biometrics
سال: 2009
ISSN: 0006-341X
DOI: 10.1111/j.1541-0420.2009.01274.x