Documentación

Esta página aún no se ha traducido para esta versión. Puede ver la versión más reciente de esta página en inglés.

# Medidas repetidas y MANOVA

Análisis de varianza, modelado de medidas repetidas y comparaciones múltiples para datos con respuestas múltiples

## Funciones

expandir todo

 `fitrm` Fit repeated measures model `ranova` Repeated measures analysis of variance `mauchly` Mauchly’s test for sphericity `epsilon` Epsilon adjustment for repeated measures anova `multcompare` Multiple comparison of estimated marginal means `anova` Analysis of variance for between-subject effects `manova` Multivariate analysis of variance `coeftest` Linear hypothesis test on coefficients of repeated measures model `grpstats` Compute descriptive statistics of repeated measures data by group `margmean` Estimate marginal means `plot` Plot data with optional grouping `plotprofile` Plot expected marginal means with optional grouping `predict` Compute predicted values given predictor values `random` Generate new random response values given predictor values
 `manova1` One-way multivariate analysis of variance `manovacluster` Dendrogram of group mean clusters following MANOVA

## Clases

 `RepeatedMeasuresModel` Repeated measures model class

## Temas

### Medidas repetidas

Model Specification for Repeated Measures Models

Learn how to specify a repeated measures model in fitrm.

Mauchly’s Test of Sphericity

Learn the test of sphericity used in repeated measures models.

Compound Symmetry Assumption and Epsilon Corrections

Learn the different epsilon corrections used in p-value calculations in the repeated measures ANOVA when the compound symmetry assumption fails.

Multivariate Analysis of Variance for Repeated Measures

Learn the four different methods used in multivariate analysis of variance for repeated measures models.

Wilkinson Notation

Wilkinson notation provides a way to describe regression and repeated measures models without specifying coefficient values.

### Manova

MANOVA

MANOVA is a form of ANOVA with multiple response variables. It determines whether the entire set of means is different from one group to the next.