Software for hierarchical modeling of epidemiologic data.
Hierarchical models can provide more reasonable and stable parameter estimates than conventional analytical approaches. This technique also deals with problems of multiple comparisons and allows one to model multilevel data within a hierarchical framework. Hence, one would anticipate a surge in applying hierarchical models to epidemiologic data. Difficulties in fitting hierarchical models, however, seem to have limited their use. To help address this problem, we describe the existing software packages that one can use to fit hierarchical models. Since these packages have limited familiarity and applicability in epidemiology, we also present SAS code for analyzing epidemiologic data with hierarchical models. These results allow epidemiologists to fit hierarchical models with readily available software.
Witte
J S
JS
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44109, USA.
Greenland
S
S
Kim
L L
LL
D001943:Breast Neoplasms / Q000453:epidemiology*; D004032:Diet / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D016017:Odds Ratio; D012306:Risk; D012984:Software