A Simple GMM Estimator for the Semi-parametric Mixed Proportional Hazard Model
نویسندگان
چکیده
A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear Rank Estimator (LRE) of Tsiatis (1990) and Robins and Tsiatis (1991) to this class of models. The optimal LRE is a two-step estimator. We propose a simple first-step estimator that is close to optimal if there is no unobserved heterogeneity. The efficiency gain associated with the optimal LRE increases with the degree of unobserved heterogeneity. JEL Classification: C41, C14
منابع مشابه
Testing a parametric transformation model versus a nonparametric alternative
Despite an abundance of semiparametric estimators of the transformation model, no procedure has been proposed yet to test the hypothesis that the transformation function belongs to a finite-dimensional parametric family against a nonparametric alternative. In this paper we introduce a bootstrap test based on integrated squared distance between a nonparametric estimator and a parametric null. As...
متن کاملSurvival analysis of thalassemia major patients using Cox, Gompertz proportional hazard and Weibull accelerated failure time models
Background: Thalassemia major (TM) is a severe disease and the most common anemia worldwide. The survival time of the disease and its risk factors are of importance for physicians. The present study was conducted to apply the semi-parametric Cox PH model and use parametric proportional hazards (PH) and accelerated failure time (AFT) models to identify the risk factors related to survival of TM ...
متن کاملOuter and Inner Confidence Intervals Based on Extreme Order Statistics in a Proportional Hazard Model
Let Mi and Mi be the maximum and minimum of the ith sample from k independent sample with different sample sizes, respectively. Suppose that the survival distribution function of the ith sample is F ̄i = F ̄αi, where αi is known and positive constant. It is shown that how various exact non-parametric inferential proce- ′ dures can be developed on the basis of Mi’s and Mi ’s for distribution ...
متن کامل0.1 coxph: Cox Proportional Hazards Regression for Duration Dependent Variables
Choose the Cox proportional hazards regression model if the values in your dependent variable are duration observations. The advantage of the semi-parametric Cox proportional hazards model over fully parametric models such as the exponential or Weibull models is that it makes no assumptions about the shape of the baseline hazard. The model only requires the proportional hazards assumption that ...
متن کامل0.1 coxph: Cox Proportional Hazards Regression for Duration Dependent Variables
Choose the Cox proportional hazards regression model if the values in your dependent variable are duration observations. The advantage of the semi-parametric Cox proportional hazards model over fully parametric models such as the exponential or Weibull models is that it makes no assumptions about the shape of the baseline hazard. The model only requires the proportional hazards assumption that ...
متن کامل