Journal of Statistical Theory and Applications

Volume 18, Issue 3, September 2019, Pages 182 - 197

Gaussian Copula–based Regression Models for the Analysis of Mixed Outcomes: An Application on Household's Utilization of Health Services Data

Authors
Z. Rezaei Ghahroodi1, 2, *, R. Aliakbari Saba1, T. Baghfalaki2
1School of Mathematics, Statistics and Computer Science, University of Tehran, Tehran, Iran
2Statistical Research and Training Center, Tehran, Iran
*Corresponding author. Email: zrezaeighahroodi@gmail.com
Corresponding Author
Z. Rezaei Ghahroodi
Received 24 June 2017, Accepted 16 April 2018, Available Online 11 July 2019.
DOI
10.2991/jsta.d.190306.009How to use a DOI?
Keywords
Copula models; mixed outcomes; sampling weights; marginal model
Abstract

In analyzing most correlated outcomes, the popular multivariate Gaussian distribution is very restrictive and therefore dependence modeling using copulas is nowadays very common to take into account the association among mixed outcomes. In this paper, we use Gaussian copula to construct a joint distribution for three mixed discrete and continuous responses. Our approach entails specifying marginal regression models for the outcomes, and combining them via a copula to form a joint model. Closed form for likelihood function is obtained by considering sampling weights. We also obtain the likelihood function for mixed responses where one of the responses, time to event outcome, may have censored values. Some simulation studies are performed to illustrate the performance of the model. Finally, the model is applied on data involving trivariate mixed outcomes on hospitalization of individuals, based on the survey of household's utilization of health services.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
18 - 3
Pages
182 - 197
Publication Date
2019/07/11
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
10.2991/jsta.d.190306.009How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Z. Rezaei Ghahroodi
AU  - R. Aliakbari Saba
AU  - T. Baghfalaki
PY  - 2019
DA  - 2019/07/11
TI  - Gaussian Copula–based Regression Models for the Analysis of Mixed Outcomes: An Application on Household's Utilization of Health Services Data
JO  - Journal of Statistical Theory and Applications
SP  - 182
EP  - 197
VL  - 18
IS  - 3
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.190306.009
DO  - 10.2991/jsta.d.190306.009
ID  - Ghahroodi2019
ER  -