Mwambi, H., Ramroop, S., White, L., Okiro, E., Nokes, D. James, Shkedy, Z. and Molenberghs, G. (2011) A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort. Statistical Methods in Medical Research , Vol.20 (No.5). pp. 551-570. doi:10.1177/0962280210385749

Research output not available from this repository, contact author.

Request Changes to record.

Abstract

This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach

Item Type:	Journal Article
Divisions:	Faculty of Science > Life Sciences (2010- )
Journal or Publication Title:	Statistical Methods in Medical Research
Publisher:	Sage Publications Ltd.
ISSN:	0962-2802
Official Date:	2011
Dates:	Date Event 2011 Published
Volume:	Vol.20
Number:	No.5
Page Range:	pp. 551-570
DOI:	10.1177/0962280210385749
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Wellcome Trust, IUAP research network of Belgian Government (Belgian Science Policy), NRF of South Africa
Grant number:	061584, P5/24, TTK2005081700004

Data sourced from Thomson Reuters' Web of Knowledge

Request changes or add full text files to a record

Repository staff actions (login required)

View Item