F.test.cca {yacca}

F Test for Canonical Correlations Using Rao's Approximation

Description

Tests a series of canonical correlations (sequentially) against the null hypothesis that the tested coefficient and all succeeding coefficients are zero.

Usage

F.test.cca(x, ...)

## S3 method for class 'F.test.cca'
print(x, ...)

Arguments

x

a cca object.

...

additional arguments.

Details

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.

Value

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 x variables on each canonical variate.

p.value

Coefficients for the y variables on each canonical variate.

method

Canonical variate scores for the x variables.

data.name

Canonical variate scores for the y variables.

Author(s)

Nicholas L. Crookston <[e-mail]>

Carter T. Butts <[e-mail]>

References

Mardia, K. V.; Kent, J. T.; and Bibby, J. M. 1979. Multivariate Analysis. London: Academic Press.

See Also

cca

Examples

#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)