mauchly.test {stats} R Documentation

## Mauchly's Test of Sphericity

### Description

Tests whether a Wishart-distributed covariance matrix (or transformation thereof) is proportional to a given matrix.

### Usage

```mauchly.test(object, Sigma = diag(nrow = p),
T = Thin.row(proj(M) - proj(X)), M = diag(nrow = p), X = ~0,
idata = data.frame(index = seq(length = p)), ...)
```

### Arguments

 `object` object of class `SSD` or `mlm`. `Sigma` matrix to be proportional to. `T` transformation matrix. By default computed from `M` and `X`. `M` formula or matrix describing the outer projection (see below). `X` formula or matrix describing the inner projection (see below). `idata` data frame describing intra-block design. `...` arguments to be passed to or from other methods.

### Details

Mauchly's test test for whether a covariance matrix can be assumed to be proportional to a given matrix.

It is common to transform the observations prior to testing. This typically involves transformation to intra-block differences, but more complicated within-block designs can be encountered, making more elaborate transformations necessary. A transformation matrix `T` can be given directly or specified as the difference between two projections onto the spaces spanned by `M` and `X`, which in turn can be given as matrices or as model formulas with respect to `idata` (the tests will be invariant to parametrization of the quotient space `M/X`).

The common use of this test is in repeated measurements designs, with `X=~1`. This is almost, but not quite the same as testing for compund symmetry in the untransformed covariance matrix.

This is a generic function with methods for classes `"mlm"` and `"SSD"`.

### Value

An object of class `"htest"`

### Note

The p-value differs slightly from that of SAS because a second order term is included in the asymptotic approximation in R.

### References

T. W. Anderson (1958). An Introduction to Multivariate Statistical Analysis. Wiley.

`SSD`, `anova.mlm`

### Examples

```example(SSD) # Brings in the mlmfit and reacttime objects

### traditional test of intrasubj. contrasts
mauchly.test(mlmfit, X=~1)

### tests using intra-subject 3x2 design
idata <- data.frame(deg=gl(3,1,6, labels=c(0,4,8)),
noise=gl(2,3,6, labels=c("A","P")))
mauchly.test(mlmfit, X = ~ deg + noise, idata = idata)
mauchly.test(mlmfit, M = ~ deg + noise, X = ~ noise, idata=idata)
```

[Package stats version 2.2.1 Index]