General linear model

Evaluación | Biopsicología | Comparativo | Cognitivo | Del desarrollo | Idioma | Diferencias individuales | Personalidad | Filosofía | Social | Métodos | Estadística | Clínico | Educativo | Industrial | Artículos profesionales | Psicología mundial | Estadística: Método científico · Métodos de búsqueda · Diseño experimental · cursos de pregrado de estadistica · Pruebas estadísticas · Teoría de juego · Decision theory The general linear model (GLM) is a statistical linear model. It may be written as where Y is a matrix with series of multivariate measurements, X is a matrix that might be a design matrix, B is a matrix containing parameters that are usually to be estimated and U is a matrix containing residuals (es decir,, errors or noise). The residual is usually assumed to follow a multivariate normal distribution. If the residual is not a multivariate normal distribution, Generalized linear models may be used to relax assumptions about Y and U. The general linear model incorporates a number of different statistical models: ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, t-test and F-test. If there is only one column in Y (es decir,, one dependent variable) then the model can also be referred to as the multiple regression model (multiple linear regression).  Hypothesis tests with the general linear model can be made in two ways: multivariate and mass-univariate. Applications An application of the general linear model appears in the analysis of neuroimages where Y contains data from brain scanners, X contains experimental design variables and confounds. It is usually tested in a mass-univariate way and is often referred to as statistical parametric mapping. This psychology-related article is a stub. You can help the Psychology Wiki by expanding it. de:Allgemeines Lineares Modell This page uses Creative Commons Licensed content from Wikipedia (ver autores).

Si quieres conocer otros artículos parecidos a General linear model puedes visitar la categoría Psychology stubs.

Deja una respuesta

Tu dirección de correo electrónico no será publicada. Los campos obligatorios están marcados con *


we use own and third party cookies to improve user experience More information