general linear model

In statistical modeling of N data observations (N<), two types of variables are usually defined. One is the response variable or variate, usually denoted by Y, and the other is the explanatory variable or covariate X. While there is only one response variable, there may be one or more than one explanatory variables. The response variable is considered random, where as the explanatory variable(s) may or may not be random.

Based on the above setup, a general linear model, or normal linear model, is a statistical model with the following assumptionsPlanetmathPlanetmath:

  1. 1.

    the response variable Y is a continuous random variable

  2. 2.

    the response variable Y can be expressed as a linear combinationMathworldPlanetmath of functions zi(𝐗), of the explanatory variables, plus a random error term ε:


    The portion of Y without the error term is known as the systematic componentMathworldPlanetmathPlanetmathPlanetmath of Y.

  3. 3.

    the error component and the systematic component are independentPlanetmathPlanetmath

  4. 4.

    random error variables εi for the N observations are iid normal with mean 0 and varianceMathworldPlanetmath σ2


  • Conditioning on the explanatory variables, the random variables Yi corresponding to the individual responses are independent, normally distributed, with mean


    and variance σ2.

  • A linear regression model is a special case of the general linear model where all explanatory variables are assumed to be continuousPlanetmathPlanetmath.

  • Analysis of variance model, or ANOVA, is another special case of the general linear model, where all of the explantory variables are categorical in nature (for example, gender, marital status, etc..).

  • Analysis of covariance, or ANCOVA, sits between a linear regression model and the ANOVA, where some of the explanatory variables are continuous and some are categorical.

  • The general linear model is a special case of the generalized linear model, where the assumption that the response variable Y has a normal distributionMathworldPlanetmath is dropped.

Title general linear model
Canonical name GeneralLinearModel
Date of creation 2013-03-22 14:31:23
Last modified on 2013-03-22 14:31:23
Owner CWoo (3771)
Last modified by CWoo (3771)
Numerical id 6
Author CWoo (3771)
Entry type Definition
Classification msc 62J10
Classification msc 62J05
Synonym normal linear model
Defines analysis of variance
Defines ANOVA
Defines analysis of covariance
Defines ANCOVA