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Tutorials : assumptions of linear regression

The study of the assumptions are based on the standardized residuals (differences between the observed and the predicted values divided by the standard error).

Homoscedasticity

The non-variability of the residuals' variance is evaluated by a plot of the residuals against the predicted values. No particular form should be observed, i.e. the residuals should homogeneous around zero (in-between -2 and 2).

Normality

The residual distribution can be described by an histogram and a quantile-quantile plot (Q-Q plot). This last plot represents the quantiles of the sample against the quantiles of the normal distribution: the point have to be aligned on the first bisector.

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Le laboratoire SPHERE (methodS for Patients-centered outcomes and HEalth REsearch, INSERM UMR 1246, Université de NantesUniversité de Tours) et la société IDBC (groupe A2com) ont décidé de créer ensemble le Laboratoire Commun RISCA (Research in Informatics and Statistics for Cohort-based Analyses)