Instrumental variable based SEE variable selection for Poisson regression models with endogenous covariates

被引:0
作者
Jiting Huang
Peixin Zhao
Xingshou Huang
机构
[1] Hechi University,College of Mathematics and Statistics
[2] Chongqing Technology and Business University,College of Mathematics and Statistics
来源
Journal of Applied Mathematics and Computing | 2019年 / 59卷
关键词
Poisson regression model; Smooth-threshold estimating equation; Endogenous covariate; Variable selection; Instrumental variable; 62G05; 62G20; 62G30;
D O I
暂无
中图分类号
学科分类号
摘要
In the case of containing endogenous covariates, we study the variable selection problem for Poisson regression models based on the instrumental variable adjustment technology. By using a modified smooth-threshold estimating equation technology, we propose an instrumental variable based variable selection procedure. The proposed method can attenuate the effect of endogenous covariates, and is easy for application in practice. We also prove that this variable selection procedure is consistent in theory. Some simulations and a real data analysis are given to evaluate the performance of the proposed method, and simulation results show that the proposed variable selection procedure is workable.
引用
收藏
页码:163 / 178
页数:15
相关论文
共 31 条
[1]  
Windmeijer F(1997)Endogeneity in count data models: an application to demand for health care J. Appl. Econom. 12 281-294
[2]  
Santos Silva JMC(2000)An introduction to instrumental variables for epidemiologists Int. J. Epidemiol. 29 722-729
[3]  
Greenland S(2006)Instruments for causal inference-an epidemiologists dream? Epidemiology 17 360-372
[4]  
Hernan MA(1998)Econometrics in outcomes research: the use of instrumental variables Annu. Rev. Public Health 19 17-24
[5]  
Robins JM(1997)Instrumental-variable estimation of count data models: applications to models of cigarette smoking behavior Rev. Econ. Stat. 79 586-593
[6]  
Newhouse JP(2006)Conditional inference methods for incomplete Poisson data with endogenous time-varying covariates: emergency department use among HIV-infected women J. Am. Stat. Assoc. 101 424-434
[7]  
McClellan M(2014)Endogeneity in ultrahigh dimension Ann. Stat. 42 872-917
[8]  
Mullahy J(2013)Adaptive GMM shrinkage estimation with consistent moment selection Econom. Theory 29 857-904
[9]  
Roy J(2013)Modified SEE variable selection for varying coefficient instrumental variable models Stat. Methodol. 12 60-70
[10]  
Alderson D(2009)A note on automatic variable selection using smooth-threshold estimating equations Biometrika 96 1005-1011