Additive Breakdowns of Variances

Computes three additive breakdown of variances for the interaction between two supplementary variables

break_interaction(resmca, v1, v2)

Arguments

resmca

object created with MCA, speMCA, csMCA, wcMCA, bcMCA, stMCA or multiMCA function

v1

factor. The first categorical supplementary variable.

v2

factor. The second categorical supplementary variable.

Details

This function reproduces the approach developed in Le Roux & Rouanet (2010) in section 4.4, in particular table 4.5.

Value

A data frame

References

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

Author

Nicolas Robette

See also

ggadd_interaction, ggadd_partial

Examples

# specific MCA of Taste example data set
data(Taste)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA",
          "Comedy.NA", "Crime.NA", "Animation.NA", "SciFi.NA", "Love.NA", 
          "Musical.NA")
mca <- speMCA(Taste[,1:11], excl = junk)
# breakdowns of variance 
# for the interaction between Gender and Age
break_interaction(mca, Taste$Gender, Taste$Age)
#>            variance  dim.1  dim.2  dim.3  dim.4  dim.5
#> 1        between v1 0.0000 0.0071 0.0001 0.0012 0.0000
#> 2      v2 within-v1 0.0053 0.0163 0.0027 0.0006 0.0038
#> 3        between v2 0.0052 0.0166 0.0027 0.0004 0.0033
#> 4      v1 within-v2 0.0001 0.0067 0.0002 0.0014 0.0005
#> 5          additive 0.0053 0.0232 0.0028 0.0016 0.0034
#> 6       interaction 0.0001 0.0002 0.0000 0.0002 0.0004
#> 7           v1 x v2 0.0053 0.0234 0.0029 0.0018 0.0038
#> 8 ratio interaction 0.0160 0.0088 0.0092 0.1129 0.1093