Master Thesis Lab

Statistics & Methods Centre - Multivariate models

Multivariate models, discussed here, consist of analysis-of-variance models and regression models.

Analysis-of-variance (ANOVA) models belong to the family of general linear models with one or more response (dependent) variables and at least one (multi-)categorical predictor or factor. Factorial analysis-of-variance models are models with more than one categorial predictor. Multivariate ANOVA models have several response variables, ANCOVA models have at least one numerical and one categorical predictor. In Repeated measures ANOVA subjects are measured more than once on the same response variable, a situation which typically arises in longitudinal studies. Detailed information on the tests is contained in the books mentioned.

Regression models, presented here, belong to the class of dependence models, in which there is a single response variable (criterion variable, independent variable) and one or more predictor variables (dependent variables). These models are special cases of the general linear model. If the response variable is numerical the models are called multiple regression models, when the response variable is the logarithm of a categorical variable the models are called logistic regression models, and when the response variable is categorical with two or more categories, the models are called discriminant analysis models. When there are only categorical predictors the model is called analysis of variance.

Analysis-of-variance models
Regression models