In

**statistics**, the**generalized linear model**(GLM) is a flexible generalization of ordinary**linear regression**that allows for response variables that have error distribution**models**other than a normal distribution.Simply so, what is the difference between general linear model and generalized linear model?

The

**general linear model**requires that the response variable follows the normal distribution whilst the**generalized linear model**is an extension of the**general linear model**that allows the specification of**models**whose response variable follows**different**distributions.Beside above, what does a general linear model tell you?

The

**General Linear Model**(GLM) is a useful framework for comparing how several variables affect different continuous variables. In it's simplest form, GLM is described as: Data =**Model**+ Error (Rutherford, 2001, p.3) GLM**is the**foundation for several statistical tests, including ANOVA, ANCOVA and**regression**analysis.What is GEE analysis?

In statistics, a generalized estimating equation (

**GEE**) is used to estimate the parameters of a generalized linear model with a possible unknown correlation between outcomes. Parameter estimates from the**GEE**are consistent even when the covariance structure is misspecified, under mild regularity conditions.Is multiple regression A multivariate analysis?

A

**multiple regression**has more than one X in one formula. A**multivariate regression**has more than one Y, but in different formulae. And a**multivariate multiple regression**has**multiple**X's to predict**multiple**Y's with each Y in a different formula, usually based on the same data.