Impact of communities, health, and emotional-related factors on smoking use: comparison of joint modeling of mean and dispersion and Bayes’ hierarchical models on add health survey

Citation

Pu, Jie; Fang, Di; & Wilson, Jeffrey R. (2017). Impact of communities, health, and emotional-related factors on smoking use: comparison of joint modeling of mean and dispersion and Bayes’ hierarchical models on add health survey. BMC Medical Research Methodology. vol. 17 (1)

Abstract

The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random component. Since the joint distribution of the observations is usually unknown, the conditional distribution is a natural approach. Our objective was to compare the fit of different binary models for correlated data in Tabaco use. We advocate that the joint modeling of the mean and dispersion may be at times just as adequate. We assessed the ability of these models to account for the intraclass correlation. In so doing, we concentrated on fitting logistic regression models to address smoking behaviors.

URL

http://dx.doi.org/10.1186/s12874-017-0303-y

Keyword(s)

Overdispersion

Reference Type

Journal Article

Journal Title

BMC Medical Research Methodology

Author(s)

Pu, Jie
Fang, Di
Wilson, Jeffrey R.

Year Published

2017

Volume Number

17

Issue Number

1

Edition

February 3, 2017

ISSN/ISBN

1471-2288

DOI

10.1186/s12874-017-0303-y

Reference ID

7121