Improving Multilevel Analyses

José Miguel Martinez, Joan Benach, Fernando G. Benavides, Carles Muntaner, Ramon Cleries, Oscar Zurriaga, Miguel Angel Martínez-Beneito, Yutaka Yasui

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Multilevel analysis has been widely used to allow the simultaneous examination of the effects of individual and group-level variables on individual health outcomes. In spite of its utility, multilevel design can have some drawbacks in the estimation of risk factor effects when the within-group variation of variables of interest is small relative to between-group variation. An extreme case of this is a group-level risk factor, which by definition has no within-group variation. To improve the estimation of group-level and individual-level risk factor effects we consider an integrated epide-miologic design using a population-based estimating equation approach that can be considered a further extension of the multilevel design. Although the integrated design uses the same individual-level and group-level data as the multilevel design it includes aggregated health outcome data in each group as additional information. This paper explains differences between the 2 designs, describing advantages and disadvantages of the integrated design over the multilevel design. The 2 designs are applied to a real example of mortality following chronic kidney disease illustrating differences that might be encountered in practice.

Original languageEnglish
Pages (from-to)525-532
Number of pages8
JournalEpidemiology
Volume20
Issue number4
DOIs
Publication statusPublished - 2009 Jul

ASJC Scopus subject areas

  • Epidemiology

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