Version info: Code for this page was tested in R Under development (unstable) (2012-07-05 r59734)
On: 2012-08-08
With: knitr 0.6.3
There are times when you want to do correspondence analysis and the data have been collapsed into a summary with counts for each of the categories. For example, here is a text table with the number of degrees given in 12 disciplines over eight different years.
degrees <- read.table(text = " disc v60 v65 v70 v71 v72 v73 v74 v75 Eng 794 2073 3432 3495 3475 3338 3144 2959 Math 291 685 1222 1236 1281 1222 1196 1149 Phy 530 1046 1655 1740 1635 1590 134 1293 Chem 1078 1444 2234 2204 2011 1849 1792 1762 Earth 253 375 511 550 580 577 570 556 Bio 1245 1963 3360 3633 3580 3636 3473 3498 Agri 414 576 803 900 855 853 830 904 Psych 772 954 1888 2116 2262 2444 2587 2749 Soc 162 239 504 583 638 599 645 680 Econ 341 538 826 791 863 907 833 867 Anth 69 82 217 240 260 324 381 385 Oth 314 502 1079 1392 1500 1609 1531 1550", row.names = 1, header = TRUE) ## print the data frame degrees
## v60 v65 v70 v71 v72 v73 v74 v75 ## Eng 794 2073 3432 3495 3475 3338 3144 2959 ## Math 291 685 1222 1236 1281 1222 1196 1149 ## Phy 530 1046 1655 1740 1635 1590 134 1293 ## Chem 1078 1444 2234 2204 2011 1849 1792 1762 ## Earth 253 375 511 550 580 577 570 556 ## Bio 1245 1963 3360 3633 3580 3636 3473 3498 ## Agri 414 576 803 900 855 853 830 904 ## Psych 772 954 1888 2116 2262 2444 2587 2749 ## Soc 162 239 504 583 638 599 645 680 ## Econ 341 538 826 791 863 907 833 867 ## Anth 69 82 217 240 260 324 381 385 ## Oth 314 502 1079 1392 1500 1609 1531 1550
Now, we will run the actual correspondence analysis using the corresp() functions from the MASS package. This will be followed by the biplot() function.
library(MASS) corresp(degrees)
## First canonical correlation(s): 0.127 ## ## Row scores: ## Eng Math Phy Chem Earth Bio Agri Psych ## 0.11919 -0.16049 2.73374 0.79224 0.00146 -0.14336 0.16112 -1.09433 ## Soc Econ Anth Oth ## -0.96228 -0.02684 -2.15293 -1.16465 ## ## Column scores: ## v60 v65 v70 v71 v72 v73 v74 v75 ## 0.9020 1.4345 0.8278 0.5481 0.1992 -0.0903 -2.0635 -0.6783
biplot(corresp(degrees, nf = 2))
