# rmaov: Split-plot ANOVA Model In growth: Multivariate Normal and Elliptically-Contoured Repeated Measurements Models

## Description

`rmaov` performs the classical balanced split-plot ANOVA, with `summary` providing the table. This is the so-called repeated measures ANOVA.

## Usage

 `1` ```rmaov(response, tvcov = NULL, ccov = NULL, analysis = TRUE) ```

## Arguments

 `response` A matrix or dataframe of response values with units as rows and repeated measures as columns. `tvcov` A numeric vector or factor variable defining the clusters. If there are several levels of nesting, a matrix or dataframe with columns of such variables defining the nested clusters starting with the highest level (that is, from slowest to fastest varying). If not provided, each response value of a unit is assumed to belong to a different cluster (that is, one factor with `ncol(response)` levels is assumed). `ccov` A vector or factor variable for one inter-subject covariate or a matrix, dataframe, or list of several such variables. `analysis` If FALSE, the design matrix is set up, but the analysis is not performed.

## Details

For unbalanced data, `elliptic` will perform the analysis for one or two levels of nesting.

## Value

The fitted model is returned.

## Author(s)

Ralf Goertz (ralf.goertz@uni-jena.de)

`carma`, `elliptic`, `lm`, `potthoff`.
 ```1 2 3 4 5``` ```# vision data for 7 individuals, with response a 7x8 matrix # two levels of nesting: 4 levels of power for each eye y <- matrix(rnorm(56),ncol=8) tvc <- data.frame(eye=c(rep(1,4),rep(2,4)),power=c(1:4,1:4)) summary(rmaov(y, tvc)) ```