RESEARCH ARTICLE


Binary Regression Models with Log-Link in the Cohort Studies



Katri Jalava*, 1, Sirpa Räsänen2, Kaija Ala-Kojola2, Saara Nironen3, Jyrki Möttönen4, Jukka Ollgren1
1 Department of Infectious Disease Surveillance and Control, National Institute for Health and Welfare, Helsinki, Finland
2 Health Services, City of Tampere, Tampere, Finland
3 Health Services, Rauma Town, Rauma, Finland
4 Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland

Article Information


Identifiers and Pagination:

Year: 2013
Volume: 6
First Page: 18
Last Page: 20
Publisher Id: TOEPIJ-6-18
DOI: 10.2174/1874297101306010018

Article History:

Received Date: 14/06/2013
Revision Received Date: 04/09/2013
Acceptance Date: 04/09/2013
Electronic publication date: 4/10/2013
Collection year: 2013

© 2013Jalava et al..

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Infectious Disease Surveillance and Control, National Institute for Health and Welfare, Helsinki, Finland; Tel: 00-358-29-524 8914; Fax: 00-358-29-524 8468; E-mail: katri.jalava@thl.fi


Abstract

Regression models have been used to control confounding in food borne cohort studies, logistic regression has been commonly used due to easy converge. However, logistic regression provide estimates for OR only when RR estimate is lower than 10%, an unlikely situation in food borne outbreaks. Recent developments have resolved the binary model convergence problems applying log link. Food items significant in the univariable analysis were included for the multivariable analysis of two recent Finnish norovirus outbreaks. We used both log and logistic regression models in R and Bayesian model in Winbugs by SPSS and R. The log-link model could be used to identify the vehicle in the two norovirus outbreak datasets. Convergence problems were solved using Bayesian modelling. Binary model applying log link provided accurate and useful estimates of RR estimating the true risk, a suitable method of choice for multivariable analysis of outbreak cohort studies.

Keywords: Cohort studies, linear models, regression analysis, risk, outbreak, foodborne illnesses, norovirus.