Learn More
Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Each copy of any part of a JSTOR transmission must contain the same copyright notice that(More)
We analyze a semiparametric model for data that suffer from the problems of incidental truncation, where some of the data are observed for only part of the sample with a probability that depends on a selection equation, and of endogeneity, where a covariate is correlated with the disturbance term. The introduction of nonparametric functions in the model(More)
INTRODUCTION The aim of this study is to evaluate computed tomography perfusion (CTP) during admission baseline period (days 0-3) in aneurysmal subarachnoid hemorrhage (A-SAH) for development of vasospasm. METHODS Retrospective analysis was performed on A-SAH patients from Dec 2004 to Feb 2007 with CTP on days 0-3. Cerebral blood flow (CBF), cerebral(More)
This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the random effects and fixed effects is proposed and compared with a(More)
Bcl-2 inhibits apoptosis by two distinct mechanisms but only one is targeted to treat Bcl-2-positive malignancies. In this mechanism, the BH1-3 domains of Bcl-2 form a hydrophobic pocket, binding and inhibiting pro-apoptotic proteins, including Bim. In the other mechanism, the BH4 domain mediates interaction of Bcl-2 with inositol 1,4, 5-trisphosphate(More)
This paper considers a puzzle in growth theory from a Keynesian perspective. If neither wage and price adjustment nor monetary policy are effective at stimulating demand, no endogenous dynamic process exists to assure that demand grows fast enough to employ a growing labor force. Yet output grows persistently over long periods, occasionally reaching(More)
In this paper we consider a nonparametric regression model in which the conditional variance function is assumed to vary smoothly with the predictor. We offer an easily implemented and fully Bayesian approach that involves the Markov chain Monte Carlo sampling of standard distributions. This method is based on a technique utilized by Kim, Shephard, and Chib(More)