Analysis of survival data
نویسندگان
چکیده
منابع مشابه
Bayesian Analysis of Survival Data with Spatial Correlation
Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study. One of the most important issues in the analysis of survival data with spatial dependence, is estimation of the parameters and prediction of the unknown values in known sites based on observations vector. In this paper to analyze this type of survival, Cox...
متن کاملSpatial Modeling of Censored Survival Data
An important issue in survival data analysis is the identification of risk factors. Some of these factors are identifiable and explainable by presence of some covariates in the Cox proportional hazard model, while the others are unidentifiable or even immeasurable. Spatial correlation of censored survival data is one of these sources that are rarely considered in the literatures. In this paper,...
متن کاملAnalysis of Censored Survival Data with Dimension Reduction Methods: Tehran Lipid and Glucose Study
Cardiovascular diseases (CVDs) are the leading cause of death worldwide. To specify an appropriate model to determine the risk of CVD and predict survival rate, users are required to specify a functional form which relates the outcome variables to the input ones. In this paper, we proposed a dimension reduction method using a general model, which includes many widely used survival m...
متن کاملAnalysis of survival data with cross-effects of survival functions.
We present a model and semiparametric estimation procedures for analysis of survival data with cross-effects (CE) of survival functions. Finite sample properties of the estimators are analyzed by simulation. A goodness-of-fit test for the proportional hazards model against the CE model is proposed. The well known data concerning effects of chemotherapy and radiotherapy on the survival times of ...
متن کاملSurvival of Dialysis Patients Using Random Survival Forest Model in Low-Dimensional Data with Few-Events
Background:Dialysis is a process for eliminating extra uremic fluids of patients with chronic renal failure. The present study aimed to determine the variables that influence the survival of dialysis patients using random survival forest model (RSFM) in low-dimensional data with low events per variable (EPV). Methods:In this historical cohort study, infor...
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: Drug Delivery System
سال: 2015
ISSN: 0913-5006,1881-2732
DOI: 10.2745/dds.30.474