Extract all the results (coordinates, squared cosine, contributions and inertia) for the active row/column variables from Correspondence Analysis (CA) outputs.

  • get_ca(): Extract the results for rows and columns
  • get_ca_row(): Extract the results for rows only
  • get_ca_col(): Extract the results for columns only

get_ca(res.ca, element = c("row", "col"))

get_ca_col(res.ca)

get_ca_row(res.ca)

Arguments

res.ca
an object of class CA [FactoMineR], ca [ca], coa [ade4]; correspondence [MASS].
element
the element to subset from the output. Possible values are "row" or "col".

Value

a list of matrices containing the results for the active rows/columns including :

References

http://www.sthda.com

Examples

# Install and load FactoMineR to compute CA # install.packages("FactoMineR") library("FactoMineR") data("housetasks") res.ca <- CA(housetasks, graph = FALSE) # Result for column variables col <- get_ca_col(res.ca) col # print
#> Correspondence Analysis - Results for columns #> =================================================== #> Name Description #> 1 "$coord" "Coordinates for the columns" #> 2 "$cos2" "Cos2 for the columns" #> 3 "$contrib" "contributions of the columns" #> 4 "$inertia" "Inertia of the columns"
head(col$coord) # column coordinates
#> Dim 1 Dim 2 Dim 3 #> Wife -0.83762154 0.3652207 -0.19991139 #> Alternating -0.06218462 0.2915938 0.84858939 #> Husband 1.16091847 0.6019199 -0.18885924 #> Jointly 0.14942609 -1.0265791 -0.04644302
head(col$cos2) # column cos2
#> Dim 1 Dim 2 Dim 3 #> Wife 0.801875947 0.1524482 0.045675847 #> Alternating 0.004779897 0.1051016 0.890118521 #> Husband 0.772026244 0.2075420 0.020431728 #> Jointly 0.020705858 0.9772939 0.002000236
head(col$contrib) # column contributions
#> Dim 1 Dim 2 Dim 3 #> Wife 44.462018 10.312237 10.8220753 #> Alternating 0.103739 2.782794 82.5492464 #> Husband 54.233879 17.786612 6.1331792 #> Jointly 1.200364 69.118357 0.4954991
# Result for row variables row <- get_ca_row(res.ca) row # print
#> Correspondence Analysis - Results for rows #> =================================================== #> Name Description #> 1 "$coord" "Coordinates for the rows" #> 2 "$cos2" "Cos2 for the rows" #> 3 "$contrib" "contributions of the rows" #> 4 "$inertia" "Inertia of the rows"
head(row$coord) # row coordinates
#> Dim 1 Dim 2 Dim 3 #> Laundry -0.9918368 0.4953220 -0.31672897 #> Main_meal -0.8755855 0.4901092 -0.16406487 #> Dinner -0.6925740 0.3081043 -0.20741377 #> Breakfeast -0.5086002 0.4528038 0.22040453 #> Tidying -0.3938084 -0.4343444 -0.09421375 #> Dishes -0.1889641 -0.4419662 0.26694926
head(row$cos2) # row cos2
#> Dim 1 Dim 2 Dim 3 #> Laundry 0.7399874 0.1845521 0.07546047 #> Main_meal 0.7416028 0.2323593 0.02603787 #> Dinner 0.7766401 0.1537032 0.06965666 #> Breakfeast 0.5049433 0.4002300 0.09482670 #> Tidying 0.4398124 0.5350151 0.02517249 #> Dishes 0.1181178 0.6461525 0.23572969
head(row$contrib) # row contributions
#> Dim 1 Dim 2 Dim 3 #> Laundry 18.2867003 5.563891 7.968424 #> Main_meal 12.3888433 4.735523 1.858689 #> Dinner 5.4713982 1.321022 2.096926 #> Breakfeast 3.8249284 3.698613 3.069399 #> Tidying 1.9983518 2.965644 0.488734 #> Dishes 0.4261663 2.844117 3.634294
# You can also use the function get_ca() get_ca(res.ca, "row") # Results for rows
#> Correspondence Analysis - Results for rows #> =================================================== #> Name Description #> 1 "$coord" "Coordinates for the rows" #> 2 "$cos2" "Cos2 for the rows" #> 3 "$contrib" "contributions of the rows" #> 4 "$inertia" "Inertia of the rows"
get_ca(res.ca, "col") # Results for columns
#> Correspondence Analysis - Results for columns #> =================================================== #> Name Description #> 1 "$coord" "Coordinates for the columns" #> 2 "$cos2" "Cos2 for the columns" #> 3 "$contrib" "contributions of the columns" #> 4 "$inertia" "Inertia of the columns"