manova
that contains the
fit for the multivariate analysis of variance of the specified model.
manova(formula, data=<<see below>>, qr=F, contrasts=NULL, ...)
data
is omitted, the current search list is used to find the objects
in
formula
; frequently, a data frame will have been attached.
lm.fit.qr
.
If you can't imagine why you would need this,
you don't.
lm
. In particular, the argument
na.action
can be a function that filters missing values from a data frame, and
subset
can be a vector for selecting observations (rows) from a data
frame.
Error
term
in the model, the object is of class
"manova"
which inherits from
classes
"maov"
,
"mlm"
,
"aov"
and
"lm"
.
See the
aov.object
help file for details on the components of this object.
Error
term in the model, then the object
returned by
aov
has class
"aovlist"
and
is a list of manova objects, one for each stratum.
A manova object is essentially the same as an aov object from a multiresponse
model, only the class is different.
The most important difference is that there is a method for
summary
specific to manova objects.
Hand, D. J. and Taylor, C. C. (1987).
Multivariate Analysis of Variance and Repeated Measures.
Chapman and Hall, London.
Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979).
Multivariate Analysis.
Academic Press, London.
Seber, G. A. F., (1984).
Multivariate Observations.
Wiley, New York.
wafer.manova <- manova(cbind(pre.mean, post.mean) ~ maskdim + visc.tem + spinsp, wafer) summary(wafer.manova) # manova table with Pillai's trace summary(wafer.manova, univar=T) # univariate anova tables summary(wafer.manova, test="wilk") # manova table with Wilks' Lambda