| likert2int {mirt} | R Documentation |
Given a matrix or data.frame object consisting of Likert responses return an object of the same dimensions with integer values.
likert2int(x, levels = NULL)
x |
a matrix of character values or data.frame of character/factor vectors |
levels |
a named character vector indicating which integer values
should be assigned to which elements. If omitted, the order of the elements
will be determined after converting each column in |
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06
## No test:
# simulate data
dat1 <- matrix(sample(c('Disagree', 'Strongly Disagree', 'Agree',
'Neutral', 'Strongly Agree'), 1000*5, replace=TRUE),
nrow=1000, ncol=5)
dat1[2,2] <- dat1[3,3] <- dat1[1,3] <- NA # NAs added for flavour
dat2 <- matrix(sample(c('D', 'SD', 'A', 'N', 'SA'), 1000*5, replace=TRUE),
nrow=1000, ncol=5)
dat <- cbind(dat1, dat2)
# separately
intdat1 <- likert2int(dat1)
head(dat1)
## [,1] [,2] [,3] [,4]
## [1,] "Agree" "Neutral" NA "Strongly Disagree"
## [2,] "Strongly Agree" NA "Neutral" "Strongly Agree"
## [3,] "Agree" "Strongly Agree" NA "Strongly Disagree"
## [4,] "Strongly Agree" "Agree" "Disagree" "Strongly Agree"
## [5,] "Strongly Agree" "Disagree" "Neutral" "Neutral"
## [6,] "Neutral" "Agree" "Agree" "Neutral"
## [,5]
## [1,] "Agree"
## [2,] "Disagree"
## [3,] "Agree"
## [4,] "Agree"
## [5,] "Agree"
## [6,] "Agree"
head(intdat1)
## V1 V2 V3 V4 V5
## 1 NA NA NA NA NA
## 2 NA NA NA NA NA
## 3 NA NA NA NA NA
## 4 NA NA NA NA NA
## 5 NA NA NA NA NA
## 6 NA NA NA NA NA
# more useful with explicit levels
lvl1 <- c('Strongly Disagree'=1, 'Disagree'=2, 'Neutral'=3, 'Agree'=4,
'Strongly Agree'=5)
intdat1 <- likert2int(dat1, levels = lvl1)
head(dat1)
## [,1] [,2] [,3] [,4]
## [1,] "Agree" "Neutral" NA "Strongly Disagree"
## [2,] "Strongly Agree" NA "Neutral" "Strongly Agree"
## [3,] "Agree" "Strongly Agree" NA "Strongly Disagree"
## [4,] "Strongly Agree" "Agree" "Disagree" "Strongly Agree"
## [5,] "Strongly Agree" "Disagree" "Neutral" "Neutral"
## [6,] "Neutral" "Agree" "Agree" "Neutral"
## [,5]
## [1,] "Agree"
## [2,] "Disagree"
## [3,] "Agree"
## [4,] "Agree"
## [5,] "Agree"
## [6,] "Agree"
head(intdat1)
## V1 V2 V3 V4 V5
## 1 4 3 NA 1 4
## 2 5 NA 3 5 2
## 3 4 5 NA 1 4
## 4 5 4 2 5 4
## 5 5 2 3 3 4
## 6 3 4 4 3 4
# second data
lvl2 <- c('SD'=1, 'D'=2, 'N'=3, 'A'=4, 'SA'=5)
intdat2 <- likert2int(dat2, levels = lvl2)
head(dat2)
## [,1] [,2] [,3] [,4] [,5]
## [1,] "SD" "SD" "A" "A" "N"
## [2,] "SD" "D" "N" "SA" "A"
## [3,] "D" "A" "N" "SD" "N"
## [4,] "D" "SD" "A" "SA" "SA"
## [5,] "N" "D" "SA" "SA" "D"
## [6,] "A" "D" "SD" "SA" "SA"
head(intdat2)
## V1 V2 V3 V4 V5
## 1 1 1 4 4 3
## 2 1 2 3 5 4
## 3 2 4 3 1 3
## 4 2 1 4 5 5
## 5 3 2 5 5 2
## 6 4 2 1 5 5
# full dataset (using both mapping schemes)
intdat <- likert2int(dat, levels = c(lvl1, lvl2))
head(dat)
## [,1] [,2] [,3] [,4]
## [1,] "Agree" "Neutral" NA "Strongly Disagree"
## [2,] "Strongly Agree" NA "Neutral" "Strongly Agree"
## [3,] "Agree" "Strongly Agree" NA "Strongly Disagree"
## [4,] "Strongly Agree" "Agree" "Disagree" "Strongly Agree"
## [5,] "Strongly Agree" "Disagree" "Neutral" "Neutral"
## [6,] "Neutral" "Agree" "Agree" "Neutral"
## [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] "Agree" "SD" "SD" "A" "A" "N"
## [2,] "Disagree" "SD" "D" "N" "SA" "A"
## [3,] "Agree" "D" "A" "N" "SD" "N"
## [4,] "Agree" "D" "SD" "A" "SA" "SA"
## [5,] "Agree" "N" "D" "SA" "SA" "D"
## [6,] "Agree" "A" "D" "SD" "SA" "SA"
head(intdat)
## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 1 4 3 NA 1 4 1 1 4 4 3
## 2 5 NA 3 5 2 1 2 3 5 4
## 3 4 5 NA 1 4 2 4 3 1 3
## 4 5 4 2 5 4 2 1 4 5 5
## 5 5 2 3 3 4 3 2 5 5 2
## 6 3 4 4 3 4 4 2 1 5 5
#####
# data.frame as input with ordered factors
dat1 <- data.frame(dat1)
dat2 <- data.frame(dat2)
dat.old <- cbind(dat1, dat2)
colnames(dat.old) <- paste0('Item_', 1:10)
str(dat.old) # factors are leveled alphabetically by default
## 'data.frame': 1000 obs. of 10 variables:
## $ Item_1 : chr "Agree" "Strongly Agree" "Agree" "Strongly Agree" ...
## $ Item_2 : chr "Neutral" NA "Strongly Agree" "Agree" ...
## $ Item_3 : chr NA "Neutral" NA "Disagree" ...
## $ Item_4 : chr "Strongly Disagree" "Strongly Agree" "Strongly Disagree" "Strongly Agree" ...
## $ Item_5 : chr "Agree" "Disagree" "Agree" "Agree" ...
## $ Item_6 : chr "SD" "SD" "D" "D" ...
## $ Item_7 : chr "SD" "D" "A" "SD" ...
## $ Item_8 : chr "A" "N" "N" "A" ...
## $ Item_9 : chr "A" "SA" "SD" "SA" ...
## $ Item_10: chr "N" "A" "N" "SA" ...
# create explicit ordering in factor variables
for(i in 1:ncol(dat1))
levels(dat1[[i]]) <- c('Strongly Disagree', 'Disagree', 'Neutral', 'Agree',
'Strongly Agree')
for(i in 1:ncol(dat2))
levels(dat2[[i]]) <- c('SD', 'D', 'N', 'A', 'SA')
dat <- cbind(dat1, dat2)
colnames(dat) <- colnames(dat.old)
str(dat) # note ordering
## 'data.frame': 1000 obs. of 10 variables:
## $ Item_1 : chr "Agree" "Strongly Agree" "Agree" "Strongly Agree" ...
## ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
## $ Item_2 : chr "Neutral" NA "Strongly Agree" "Agree" ...
## ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
## $ Item_3 : chr NA "Neutral" NA "Disagree" ...
## ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
## $ Item_4 : chr "Strongly Disagree" "Strongly Agree" "Strongly Disagree" "Strongly Agree" ...
## ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
## $ Item_5 : chr "Agree" "Disagree" "Agree" "Agree" ...
## ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
## $ Item_6 : chr "SD" "SD" "D" "D" ...
## ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
## $ Item_7 : chr "SD" "D" "A" "SD" ...
## ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
## $ Item_8 : chr "A" "N" "N" "A" ...
## ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
## $ Item_9 : chr "A" "SA" "SD" "SA" ...
## ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
## $ Item_10: chr "N" "A" "N" "SA" ...
## ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
intdat <- likert2int(dat)
head(dat)
## Item_1 Item_2 Item_3 Item_4 Item_5 Item_6
## 1 Agree Neutral <NA> Strongly Disagree Agree SD
## 2 Strongly Agree <NA> Neutral Strongly Agree Disagree SD
## 3 Agree Strongly Agree <NA> Strongly Disagree Agree D
## 4 Strongly Agree Agree Disagree Strongly Agree Agree D
## 5 Strongly Agree Disagree Neutral Neutral Agree N
## 6 Neutral Agree Agree Neutral Agree A
## Item_7 Item_8 Item_9 Item_10
## 1 SD A A N
## 2 D N SA A
## 3 A N SD N
## 4 SD A SA SA
## 5 D SA SA D
## 6 D SD SA SA
head(intdat)
## Item_1 Item_2 Item_3 Item_4 Item_5 Item_6 Item_7 Item_8 Item_9 Item_10
## 1 4 3 NA 1 4 1 1 4 4 3
## 2 5 NA 3 5 2 1 2 3 5 4
## 3 4 5 NA 1 4 2 4 3 1 3
## 4 5 4 2 5 4 2 1 4 5 5
## 5 5 2 3 3 4 3 2 5 5 2
## 6 3 4 4 3 4 4 2 1 5 5
## End(No test)