說明 
86 p 
附註 
Source: Dissertation Abstracts International, Volume: 7107, Section: A, page: 2567 

Adviser: John Geweke 

Thesis (Ph.D.)The University of Iowa, 2010 

In this dissertation I examine the effects of sample selection on the probability of stroke among older adults. If study subjects are selected into the sample based on some nonexperimental selection process, then statistical analysis may produce inconsistent estimates 

Chapter 1 develops a model of nonignorable selection for a discrete outcome variable, such as whether stroke occurred or not. I start by noticing that in the literature there are relatively few applications of the Heckman model to the case of a discrete outcome variable and they are limited to a bivariate case. After that I extend the Bayesian multivariate probit model of Chib and Greenberg (1998) broadly following the logic of Heckman's original (1979) work. The model in the first chapter of my dissertation is set in a way general enough to handle multiple selection and discretecontinuous outcome equations 

The first extension of the multivariate probit model in Chib and Greenberg (1998) allows some of the outcomes to be missing. In particular, stroke occurrence is missing whenever the person is not selected into the sample. In terms of latent variable representation this implies that multivariate normal distribution is not truncated in the direction of missing outcome. I also use Cholesky factorization of the variance matrix to avoid the MetropolisHastings algorithm in the Gibbs sampler 

Chapter 2 evaluates how severe the problem of sample selection is in Assets and HEAlth Dynamics among the Oldest Old (AHEAD) data set. I start with a more restrictive assumption of ignorable selection. In particular, I apply the propensity score method as in a recent paper by Wolinsky et al. (2009) and find no selection effects in the study of stroke. Then I consider the model developed in Chapter 1, which is based on a less restrictive assumption of nonignorable selection, and also find no evidence of selection. Thus, the main substantive contribution of this chapter is the absence of selection effects based on either ignorable or nonignorable sample selection model 

School code: 0096 
Host Item 
Dissertation Abstracts International 7107A

主題 
Economics, General


Health Sciences, General


0501


0566

Alt Author 
The University of Iowa. Economics

