Transform a Multivariate Linear model mlm to a Canonical Representation

This function uses candisc to transform the responses in a multivariate linear model to scores on canonical variables for a given term and then uses those scores as responses in a linear (lm) or multivariate linear model (mlm).

The function constructs a model formula of the form Can ~ terms where Can is the canonical score(s) and terms are the terms in the original mlm, then runs lm() with that formula.

Usage

can_lm(mod, term, ...)

Arguments

mod: A mlm object
term: One term in that model
...: Arguments passed to candisc

Value

A lm object if term is a rank 1 hypothesis, otherwise a mlm object

Author

Michael Friendly

Examples


iris.mod <- lm(cbind(Petal.Length, Sepal.Length, Petal.Width, Sepal.Width) ~ Species, data=iris)
iris.can <- can_lm(iris.mod, "Species")
iris.can
#> 
#> Call:
#> lm(formula = cbind(Can1, Can2) ~ Species, data = scores)
#> 
#> Coefficients:
#>                    Can1     Can2   
#> (Intercept)        -7.6076  -0.2151
#> Speciesversicolor   9.4326   0.9430
#> Speciesvirginica   13.3902  -0.2976
#> 
car::Anova(iris.mod)
#> 
#> Type II MANOVA Tests: Pillai test statistic
#>         Df test stat approx F num Df den Df    Pr(>F)    
#> Species  2    1.1919   53.466      8    290 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
car::Anova(iris.can)
#> 
#> Type II MANOVA Tests: Pillai test statistic
#>         Df test stat approx F num Df den Df    Pr(>F)    
#> Species  2    1.1919   108.41      4    294 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1