TY - JOUR
T1 - Improving Multilevel Analyses
AU - Martinez, José Miguel
AU - Benach, Joan
AU - Benavides, Fernando G.
AU - Muntaner, Carles
AU - Cleries, Ramon
AU - Zurriaga, Oscar
AU - Martínez-Beneito, Miguel Angel
AU - Yasui, Yutaka
PY - 2009/7
Y1 - 2009/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=67651030486&partnerID=8YFLogxK
U2 - 10.1097/EDE.0b013e3181a48c33
DO - 10.1097/EDE.0b013e3181a48c33
M3 - Article
C2 - 19436212
AN - SCOPUS:67651030486
SN - 1044-3983
VL - 20
SP - 525
EP - 532
JO - Epidemiology
JF - Epidemiology
IS - 4
ER -