title: Testing for causality and prognosis: etiological and prognostic models.
abstract: Etiological research aims to investigate the causal relationship between putative risk factors (or determinants) and a given disease or other outcome. In contrast, prognostic research aims to predict the probability of a given clinical outcome and in this perspective the pathophysiology of the disease is not an issue. Multivariate modeling is a fundamental tool both to infer causality and to investigate prognostic factors in epidemiological research. The analytical approaches to etiological and prognostic studies are strictly dependent on the research question and imply knowledge of the main statistical procedures for model building and data interpretation. In this paper we describe the application of multivariate statistical modeling in etiological and prognostic research. We will mainly focus on the differences in model building and data interpretation between these two areas of epidemiologic research.
authors: CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, Reggio Calabria, Italy. gtripepi@ibim.cnr.it
authors: Giovanni
authors: G
authors: Tripepi
authors: Kitty J
authors: KJ
authors: Jager
authors: Friedo W
authors: FW
authors: Dekker
authors: Carmine
authors: C
authors: Zoccali
mesh_terms: D000704:Analysis of Variance; D015984:Causality; D004812:Epidemiologic Methods; D006801:Humans; D011379:Prognosis; D012307:Risk Factors