Repeated Measures and MANOVA
Analysis of variance, repeated measures modeling,
and multiple comparisons for data with multiple responses
Statistics and Machine Learning Toolbox™ provides functions for working with one-way, two-way, and N-way multiple analysis of variance (MANOVA); analysis of variance (ANOVA); repeated measures models; and analysis of covariance (ANCOVA). A repeated measures model is a regression model in which observations have multiple response variables. The responses for each observation typically correspond to measurements at multiple times. MANOVA is a procedure for determining whether variation in multiple response variables occurs within or among different population groups.
Functions
Objects
Topics
Repeated Measures
- Model Specification for Repeated Measures Models
Learn how to specify a repeated measures model infitrm
. - 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
- Perform Multivariate Analysis of Variance (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.