SSD: SSD Matrix and Estimated Variance Matrix in Multivariate...

SSDR Documentation

SSD Matrix and Estimated Variance Matrix in Multivariate Models

Description

Functions to compute matrix of residual sums of squares and products, or the estimated variance matrix for multivariate linear models.

Usage


# S3 method for class 'mlm'
SSD(object, ...)

# S3 methods for class 'SSD' and 'mlm'
estVar(object, ...)

Arguments

object

object of class "mlm", or "SSD" in the case of estVar.

...

Unused

Value

SSD() returns a list of class "SSD" containing the following components

SSD

The residual sums of squares and products matrix

df

Degrees of freedom

call

Copied from object

estVar returns a matrix with the estimated variances and covariances.

See Also

mauchly.test, anova.mlm

Examples

# Lifted from Baron+Li:
# "Notes on the use of R for psychology experiments and questionnaires"
# Maxwell and Delaney, p. 497
reacttime <- matrix(c(
420, 420, 480, 480, 600, 780,
420, 480, 480, 360, 480, 600,
480, 480, 540, 660, 780, 780,
420, 540, 540, 480, 780, 900,
540, 660, 540, 480, 660, 720,
360, 420, 360, 360, 480, 540,
480, 480, 600, 540, 720, 840,
480, 600, 660, 540, 720, 900,
540, 600, 540, 480, 720, 780,
480, 420, 540, 540, 660, 780),
ncol = 6, byrow = TRUE,
dimnames = list(subj = 1:10,
              cond = c("deg0NA", "deg4NA", "deg8NA",
                       "deg0NP", "deg4NP", "deg8NP")))

mlmfit <- lm(reacttime ~ 1)
SSD(mlmfit)
estVar(mlmfit)