F.test.cca | R Documentation |
Tests a series of canonical correlations (sequentially) against the null hypothesis that the tested coefficient and all succeeding coefficients are zero.
F.test.cca(x, ...) ## S3 method for class 'F.test.cca' print(x, ...)
x |
a |
... |
additional arguments. |
Several related tests have been proposed for the evaluation of canonical correlations (including Bartlett's Chi-squared test, which is computed by default within cca
). This function employs Rao's statistic (related to Wilks' Lambda) as the basis for an F test of each coefficient (and all others in ascending sequence) against the hypothesis that the associated population correlations are zero.
An object of class F.test.cca
, whose elements are as follows:
corr |
Canonical correlations. |
statistic |
Squared canonical correlations (shared variance across canonical variates). |
parameter |
Coefficients for the |
p.value |
Coefficients for the |
method |
Canonical variate scores for the |
data.name |
Canonical variate scores for the |
Nicholas L. Crookston <ncrookston@fs.fed.us>
Carter T. Butts <buttsc@uci.edu>
Mardia, K. V.; Kent, J. T.; and Bibby, J. M. 1979. Multivariate Analysis. London: Academic Press.
cca
#Example: perceived personal attributes versus professional performance #for US Judges data(USJudgeRatings) personal <- USJudgeRatings[,c("INTG","DMNR","DILG","FAMI","PHYS")] performance <- USJudgeRatings[,c("CFMG","DECI","PREP","ORAL","WRIT")] cca.fit <- cca(personal, performance) #Test the canonical correlations (see also summary(cca.fit)) F.test.cca(cca.fit)
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