![]() ![]() The principle of these tests is the same one as in the case of the linear model. XLSTAT allows computing the type I, II and III tests of the fixed effects. In addition, the interactions to be used in the model can be easily defined in XLSTAT. ![]() XLSTAT propose different covariance matrix between the errors within the framework of mixed models. Parameters are estimated using the maximum likelihood estimator. ![]() Where y is the dependent variable, X gathers all fixed effects (these factors are the classical OLS regression variables or the ANOVA factors), β is a vector of parameters associated with the fixed factors, Z is a matrix gathering all the random effects (factors that cannot be set as fixed), γ is a vector of parameters associated with the random effects and ε is an error vector. Mixed models can be used to carry out repeated measures ANOVA. The explanatory variables could be as well quantitative as qualitative. They make it possible to take into account, on the one hand, the concept of repeated measurement and, on the other hand, that of random factor. Mixed models are complex models based on the same principle as general linear models, such as the linear regression. ![]()
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