| summary.manova {stats} | R Documentation |
A summary method for class "manova".
## S3 method for class 'manova':
summary(object,
test = c("Pillai", "Wilks", "Hotelling-Lawley", "Roy"),
intercept = FALSE, ...)
object |
An object of class "manova" or an aov
object with multiple responses. |
test |
The name of the test statistic to be used. Partial matching is used so the name can be abbreviated. |
intercept |
logical. If TRUE, the intercept term is
included in the table. |
... |
further arguments passed to or from other methods. |
The summary.manova method uses a multivariate test statistic
for the summary table. Wilks' statistic is most popular in the
literature, but the default Pillai-Bartlett statistic is recommended
by Hand and Taylor (1987).
A list with components
SS |
A named list of sums of squares and product matrices. |
Eigenvalues |
A matrix of eigenvalues. |
stats |
A matrix of the statistics, approximate F value, degrees of freedom and P value. |
Krzanowski, W. J. (1988) Principles of Multivariate Analysis. A User's Perspective. Oxford.
Hand, D. J. and Taylor, C. C. (1987) Multivariate Analysis of Variance and Repeated Measures. Chapman and Hall.
## Example on producing plastic film from Krzanowski (1998, p. 381)
tear <- c(6.5, 6.2, 5.8, 6.5, 6.5, 6.9, 7.2, 6.9, 6.1, 6.3,
6.7, 6.6, 7.2, 7.1, 6.8, 7.1, 7.0, 7.2, 7.5, 7.6)
gloss <- c(9.5, 9.9, 9.6, 9.6, 9.2, 9.1, 10.0, 9.9, 9.5, 9.4,
9.1, 9.3, 8.3, 8.4, 8.5, 9.2, 8.8, 9.7, 10.1, 9.2)
opacity <- c(4.4, 6.4, 3.0, 4.1, 0.8, 5.7, 2.0, 3.9, 1.9, 5.7,
2.8, 4.1, 3.8, 1.6, 3.4, 8.4, 5.2, 6.9, 2.7, 1.9)
Y <- cbind(tear, gloss, opacity)
rate <- factor(gl(2,10), labels=c("Low", "High"))
additive <- factor(gl(2, 5, len=20), labels=c("Low", "High"))
fit <- manova(Y ~ rate * additive)
summary.aov(fit) # univariate ANOVA tables
summary(fit, test="Wilks") # ANOVA table of Wilks' lambda