Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival
نویسندگان
چکیده
منابع مشابه
Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival.
As data-rich medical datasets are becoming routinely collected, there is a growing demand for regression methodology that facilitates variable selection over a large number of predictors. Bayesian variable selection algorithms offer an attractive solution, whereby a sparsity inducing prior allows inclusion of sets of predictors simultaneously, leading to adjusted effect estimates and inference ...
متن کاملPrognostic factors of survival of patients with oesophageal cancer under radiotherapy using cox regression model
oesophageal cancer is one of the most fatal cancer in human in spite of high incidence in the north of Iran and poor prognosis,there is not information regarding prognostic factors in this area.this study was conducted to determine prognodtic factors of the survival of patients with oesophageal cancer under radiotherapy.We conducted a descriptive-analytical study using historical cohort that ha...
متن کاملBayesian Approximate Kernel Regression with Variable Selection
Nonlinear kernel regression models are often used in statistics and machine learning due to greater accuracy than linear models. Variable selection for kernel regression models is a challenge partly because, unlike the linear regression setting, there is no clear concept of an effect size for regression coefficients. In this paper, we propose a novel framework that provides an analog of the eff...
متن کاملJointness in Bayesian Variable Selection With Applications to Growth Regression
We present a measure of jointness to explore dependence among regressors, in the context of Bayesian model selection. The jointness measure proposed here equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. We illustrate its application in cross-country growth regressions using two datasets from Fernández et al. (2...
متن کاملNonparametric Regression using Bayesian Variable Selection
This paper estimates an additive model semiparametrically, while automatically selecting the significant independent variables and the app~opriatc power transformation of the dependent variable. The nonlinear variables arc modeled as regression splincs, with significant knots selected fiom a large number of candidate knots. The estimation is made robust by modeling the errors as a mixture of no...
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: Statistical Methods in Medical Research
سال: 2016
ISSN: 0962-2802,1477-0334
DOI: 10.1177/0962280214548748