XLSTAT MULTIVARIATE COMPARISON HOW TO

If p is the number of factors, the ANOVA model is written as follows: In ANOVA, explanatory variables are often called factors. The exploratory variable is measured at different time or repetition. The main difference comes from the nature of the explanatory variables. Repeated measures Analysis of Variance (ANOVA) uses the same conceptual framework as classical ANOVA. Calculation in Repeated measures Analysis of Variance If the sphericity hypothesis is not rejected, between- and within-subject effects can be tested. For each measure, a classical ANOVA model is estimated, then the sphericity of the covariance matrix between measures is tested using Mauchly’s test, Greenhouse-Geisser epsilon or Huynt-Feldt epsilon. The principle of repeated measures ANOVA is simple. Principles of Repeated measures Analysis of Variance

XLSTAT MULTIVARIATE COMPARISON HOW TO

Not sure which statistical model is the appropriate one for your data? Check out our guide to learn more on how to choose a method according to your question, the type of your variables (i.e., categorical variables, binary, continuous) and the distribution of data. For details on the second method, please read the chapter on mixed models. This chapter is devoted to the first method. The classical way using least squares estimation (LS) that is based on the same model as the classical ANOVA and the alternative way that is based on the maximum likelihood estimation ( REML and ML). XLSTAT proposes two ways for handling repeated measures ANOVA. Multiple comparison tests can be calculated. The advanced options enable you to choose the constraints on the model and to take account of interactions between the factors. Use this tool to carry out Repeated Measures ANOVA (ANalysis Of VAriance).

Xlstat multivariate comparison