#This opens up the library which enables using CA, download from CRAN
library(ca)
# This opens up the library which enables reading an SPSS.sav file
library(foreign)
#Read SPSS data file and save it as an R object
#As input we use the indicator matrix (text data in D:/...) either with passive variables

issp <-read.table('D:/DATA/sagebuch/chapter 3/ISSP2003australia2.txt')

#The last seven columns (variables) contain the passive ones, definiton of supplementary variables
subisspsv <- c(57,58,59,60,61,62,63)

# summary statistic for rows and columns with supplementary variables
summary(ca(issp,nd=3,supcol=subisspsv))

# plot of all variables (active and passive) from indicator matrix
plot(ca(issp),dim=c(1,2),what=c("none","all"),col=c("#000000"),pch=c(149,2,149,2))

# plot of respondents from indicator matrix
plot(ca(issp),dim=c(1,2),what=c("all","none"),col=c("#000000"),pch=c(149,2,149,2))

# Definition of different subsets
subissp1 <- c(1,5,9,13,17,21,25,29,33,37,41,45,49,53)
subissp14 <- c(1,4,5,8,9,12,13,16,17,20,21,24,25,28,29,32,33,36,37,40,41,44,45,48,49,52,53,56)
subissp23 <- c(2,3,6,7,10,11,14,15,18,19,22,23,26,27,30,31,34,35,38,39,42,43,46,47,50,51,54,55)
subissp2 <- c(2,6,10,14,18,22,26,30,34,38,42,46,50,54)
subissp3 <- c(3,7,11,15,19,23,27,31,35,39,43,47,51,55)
subissp4 <- c(4,8,12,16,20,24,28,32,36,40,44,48,52,56)

#summary statistics for Subset MCA 

summary(ca(issp,subsetcol=subissp2))
summary(ca(issp,subsetcol=subissp3))
summary(ca(issp,subsetcol=subissp4))
summary(ca(issp,subsetcol=subissp23))
summary(ca(issp,subsetcol=subissp1))

#plot of Subset MCA
plot(ca(issp,subsetcol=subissp1),dim=c(1,-2),what=c("none","all"))
plot(ca(issp,subsetcol=subissp4),dim=c(1,2),what=c("none","all"))