Density ratio model for multivariate outcomes

Scott Marchese and Guoqing Diao

Journal of Multivariate Analysis, 2017, vol. 154, issue C, 249-261

Abstract: The Density Ratio Model is a semi-parametric regression model which allows analysis of data from any exponential family without making a parametric distribution assumption. For univariate outcomes several authors have shown desirable properties of this model including robustness to mis-specification and efficiency of the estimators within a suitable class. In this paper we consider analysis of multivariate outcomes with this model, where each marginal distribution is from an exponential family. We show that the model successfully analyzes data from mixed outcome types (continuous, integer, binary), providing valid tests of the joint effects of covariates. Furthermore, for continuous outcomes we provide a bootstrap technique which correctly estimates the underlying marginal regression parameters and provides appropriate coverage probabilities without specifying the covariance structure. The methods are demonstrated via simulation studies and analysis of healthcare data.

Keywords: Density ratio model; Empirical likelihood; Semiparametric regression (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X16301622
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:154:y:2017:i:c:p:249-261

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2016.11.008

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().