A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose-response data

Qin Liu, Nancy R. Cook, Anna Bergström and Chung-Cheng Hsieh

Computational Statistics & Data Analysis, 2009, vol. 53, issue 12, 4157-4167

Abstract: To estimate a summarized dose-response relation across different exposure levels from epidemiologic data, meta-analysis often needs to take into account heterogeneity across studies beyond the variation associated with fixed effects. We extended a generalized-least-squares method and a multivariate maximum likelihood method to estimate the summarized nonlinear dose-response relation taking into account random effects. These methods are readily suited to fitting and testing models with covariates and curvilinear dose-response relations.

Date: 2009
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/S0167-9473(09)00176-5
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:csdana:v:53:y:2009:i:12:p:4157-4167

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().