# NOT RUN {
# create some sample data in table form
sex <- c("Male", "Female")
age <- letters[1:6]
education <- c("low", 'med', 'high')
data <- expand.grid(sex=sex, age=age, education=education)
counts <- rpois(36, 100)
data <- cbind(data, counts)
t1 <- xtabs(counts ~ sex + age + education, data=data)
Desc(t1)
## age a b c d e f
## sex education
## Male low 119 101 109 85 99 93
## med 94 98 103 108 84 84
## high 81 88 96 110 100 92
## Female low 107 104 95 86 103 96
## med 104 98 94 95 110 106
## high 93 85 90 109 99 86
# collapse age to 3 levels
t2 <- CollapseTable(t1, age=c("A", "A", "B", "B", "C", "C"))
Desc(t2)
## age A B C
## sex education
## Male low 220 194 192
## med 192 211 168
## high 169 206 192
## Female low 211 181 199
## med 202 189 216
## high 178 199 185
# collapse age to 3 levels and pool education: "low" and "med" to "low"
t3 <- CollapseTable(t1, age=c("A", "A", "B", "B", "C", "C"),
education=c("low", "low", "high"))
Desc(t3)
## age A B C
## sex education
## Male low 412 405 360
## high 169 206 192
## Female low 413 370 415
## high 178 199 185
# change labels for levels of education to 1:3
t4 <- CollapseTable(t1, education=1:3)
Desc(t4)
## age a b c d e f
## sex education
## Male 1 119 101 109 85 99 93
## 2 94 98 103 108 84 84
## 3 81 88 96 110 100 92
## Female 1 107 104 95 86 103 96
## 2 104 98 94 95 110 106
## 3 93 85 90 109 99 86
# }
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