title: [Statistical models and multivariable analysis].
abstract: Most clinical research can be simplified as an investigation of an input/output relationship. The inputs are called explanatory (independent) variables or predictors and are thought to be related to the outcome, or response (independent) variable. This relationship is usually complicated by other factors related to both the input and the output (presence of confounding) and can vary according to the levels of the other variables (presence of interaction). This input/output relationship is usually described by statistical models that include a fit part and a residual component or difference between the data and the fit. The most popular models are the general linear models, which can be considered the paradigm of all models used in multi-variable analyzes.
authors.affiliation: Divisione di Nefrologia e Dialisi, Azienda Ospedaliera, Cremona. p.ravani@libero.it
authors.forename: P
authors.initials: P
authors.lastname: Ravani
authors.forename: F
authors.initials: F
authors.lastname: Malberti
mesh_terms: D035843:Biomedical Research / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis