Extract the results for individuals/variables - MCA

Extract all the results (coordinates, squared cosine and contributions) for the active individuals/variable categories from Multiple Correspondence Analysis (MCA) outputs.

get_mca(): Extract the results for variables and individuals
get_mca_ind(): Extract the results for individuals only
get_mca_var(): Extract the results for variables only

get_mca(res.mca, element = c("var", "ind", "mca.cor", "quanti.sup"))

get_mca_var(res.mca, element = c("var", "mca.cor", "quanti.sup"))

get_mca_ind(res.mca)

Arguments

res.mca	an object of class MCA [FactoMineR], acm [ade4], expoOutput/epMCA [ExPosition].
element	the element to subset from the output. Possible values are "var" for variables, "ind" for individuals, "mca.cor" for correlation between variables and principal dimensions, "quanti.sup" for quantitative supplementary variables.

Value

a list of matrices containing the results for the active individuals/variable categories including :

coord

coordinates for the individuals/variable categories

cos2

cos2 for the individuals/variable categories

contrib

contributions of the individuals/variable categories

inertia

inertia of the individuals/variable categories

References

http://www.sthda.com/english/

Examples

# \donttest{
# Multiple Correspondence Analysis
# ++++++++++++++++++++++++++++++
# Install and load FactoMineR to compute MCA
# install.packages("FactoMineR")
library("FactoMineR")
data(poison)
poison.active <- poison[1:55, 5:15]
head(poison.active[, 1:6])
#>     Nausea Vomiting Abdominals   Fever   Diarrhae   Potato
#> 1 Nausea_y  Vomit_n     Abdo_y Fever_y Diarrhea_y Potato_y
#> 2 Nausea_n  Vomit_n     Abdo_n Fever_n Diarrhea_n Potato_y
#> 3 Nausea_n  Vomit_y     Abdo_y Fever_y Diarrhea_y Potato_y
#> 4 Nausea_n  Vomit_n     Abdo_n Fever_n Diarrhea_n Potato_y
#> 5 Nausea_n  Vomit_y     Abdo_y Fever_y Diarrhea_y Potato_y
#> 6 Nausea_n  Vomit_n     Abdo_y Fever_y Diarrhea_y Potato_y
res.mca <- MCA(poison.active, graph=FALSE)

 # Extract the results for variable categories
 var <- get_mca_var(res.mca)
 print(var)
#> Multiple Correspondence Analysis Results for variables
#>  ===================================================
#>   Name       Description                  
#> 1 "$coord"   "Coordinates for categories" 
#> 2 "$cos2"    "Cos2 for categories"        
#> 3 "$contrib" "contributions of categories"
 head(var$coord) # coordinates of variables
#>               Dim 1       Dim 2        Dim 3       Dim 4       Dim 5
#> Nausea_n  0.2673909  0.12139029 -0.265583253  0.03376130  0.07370500
#> Nausea_y -0.9581506 -0.43498187  0.951673323 -0.12097801 -0.26410958
#> Vomit_n   0.4790279 -0.40919465  0.084492799  0.27361142  0.05245250
#> Vomit_y  -0.7185419  0.61379197 -0.126739198 -0.41041713 -0.07867876
#> Abdo_n    1.3180221 -0.03574501 -0.005094243 -0.15360951 -0.06986987
#> Abdo_y   -0.6411999  0.01738946  0.002478280  0.07472895  0.03399075
 head(var$cos2) # cos2 of variables
#>              Dim 1        Dim 2        Dim 3       Dim 4       Dim 5
#> Nausea_n 0.2562007 0.0528025759 2.527485e-01 0.004084375 0.019466197
#> Nausea_y 0.2562007 0.0528025759 2.527485e-01 0.004084375 0.019466197
#> Vomit_n  0.3442016 0.2511603912 1.070855e-02 0.112294813 0.004126898
#> Vomit_y  0.3442016 0.2511603912 1.070855e-02 0.112294813 0.004126898
#> Abdo_n   0.8451157 0.0006215864 1.262496e-05 0.011479077 0.002374929
#> Abdo_y   0.8451157 0.0006215864 1.262496e-05 0.011479077 0.002374929
 head(var$contrib) # contributions of variables
#>              Dim 1       Dim 2        Dim 3      Dim 4      Dim 5
#> Nausea_n  1.515869  0.81100008 4.670018e+00 0.08449397 0.48977906
#> Nausea_y  5.431862  2.90608363 1.673423e+01 0.30277007 1.75504164
#> Vomit_n   3.733667  7.07226253 3.627455e-01 4.25893721 0.19036376
#> Vomit_y   5.600500 10.60839380 5.441183e-01 6.38840581 0.28554563
#> Abdo_n   15.417637  0.02943661 7.192511e-04 0.73219636 0.18424268
#> Abdo_y    7.500472  0.01432051 3.499060e-04 0.35620363 0.08963157

 # Extract the results for individuals
 ind <- get_mca_ind(res.mca)
 print(ind)
#> Multiple Correspondence Analysis Results for individuals
#>  ===================================================
#>   Name       Description                       
#> 1 "$coord"   "Coordinates for the individuals" 
#> 2 "$cos2"    "Cos2 for the individuals"        
#> 3 "$contrib" "contributions of the individuals"
 head(ind$coord) # coordinates of individuals
#>        Dim 1       Dim 2       Dim 3       Dim 4       Dim 5
#> 1 -0.4525811 -0.26415072  0.17151614  0.01369348 -0.11696806
#> 2  0.8361700 -0.03193457 -0.07208249 -0.08550351  0.51978710
#> 3 -0.4481892  0.13538726 -0.22484048 -0.14170168 -0.05004753
#> 4  0.8803694 -0.08536230 -0.02052044 -0.07275873 -0.22935022
#> 5 -0.4481892  0.13538726 -0.22484048 -0.14170168 -0.05004753
#> 6 -0.3594324 -0.43604390 -1.20932223  1.72464616  0.04348157
 head(ind$cos2) # cos2 of individuals
#>        Dim 1        Dim 2        Dim 3        Dim 4        Dim 5
#> 1 0.34652591 0.1180447167 0.0497683175 0.0003172275 0.0231460846
#> 2 0.55589562 0.0008108236 0.0041310808 0.0058126211 0.2148103098
#> 3 0.54813888 0.0500176790 0.1379484860 0.0547920948 0.0068349171
#> 4 0.74773962 0.0070299584 0.0004062504 0.0051072923 0.0507479873
#> 5 0.54813888 0.0500176790 0.1379484860 0.0547920948 0.0068349171
#> 6 0.02485357 0.0365775483 0.2813443706 0.5722083217 0.0003637178
 head(ind$contrib) # contributions of individuals
#>      Dim 1      Dim 2        Dim 3        Dim 4      Dim 5
#> 1 1.110927 0.98238297  0.498254685  0.003555817 0.31554778
#> 2 3.792117 0.01435818  0.088003703  0.138637089 6.23134138
#> 3 1.089470 0.25806722  0.856229950  0.380768961 0.05776914
#> 4 4.203611 0.10259105  0.007132055  0.100387990 1.21319013
#> 5 1.089470 0.25806722  0.856229950  0.380768961 0.05776914
#> 6 0.700692 2.67693398 24.769968729 56.404214518 0.04360547

 # You can also use the function get_mca()
 get_mca(res.mca, "ind") # Results for individuals
#> Multiple Correspondence Analysis Results for individuals
#>  ===================================================
#>   Name       Description                       
#> 1 "$coord"   "Coordinates for the individuals" 
#> 2 "$cos2"    "Cos2 for the individuals"        
#> 3 "$contrib" "contributions of the individuals"
 get_mca(res.mca, "var") # Results for variable categories
#> Multiple Correspondence Analysis Results for variables
#>  ===================================================
#>   Name       Description                  
#> 1 "$coord"   "Coordinates for categories" 
#> 2 "$cos2"    "Cos2 for categories"        
#> 3 "$contrib" "contributions of categories"
 # }

Extract the results for individuals/variables - MCA

Arguments

Value

References

Examples

Contents

Author