R/likert2int.R
likert2int.RdGiven a matrix or data.frame object consisting of Likert responses return an object of the same dimensions with integer values.
likert2int(x, levels = NULL)a matrix of character values or data.frame of character/factor vectors
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 x to a factor
variable
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
# \donttest{
# 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" "Strongly Agree" NA "Strongly Agree"
#> [2,] "Agree" NA "Agree" "Disagree"
#> [3,] "Disagree" "Disagree" NA "Disagree"
#> [4,] "Strongly Agree" "Agree" "Strongly Disagree" "Strongly Agree"
#> [5,] "Disagree" "Strongly Agree" "Strongly Disagree" "Strongly Disagree"
#> [6,] "Disagree" "Neutral" "Disagree" "Strongly Agree"
#> [,5]
#> [1,] "Strongly Disagree"
#> [2,] "Strongly Disagree"
#> [3,] "Agree"
#> [4,] "Strongly Disagree"
#> [5,] "Agree"
#> [6,] "Neutral"
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" "Strongly Agree" NA "Strongly Agree"
#> [2,] "Agree" NA "Agree" "Disagree"
#> [3,] "Disagree" "Disagree" NA "Disagree"
#> [4,] "Strongly Agree" "Agree" "Strongly Disagree" "Strongly Agree"
#> [5,] "Disagree" "Strongly Agree" "Strongly Disagree" "Strongly Disagree"
#> [6,] "Disagree" "Neutral" "Disagree" "Strongly Agree"
#> [,5]
#> [1,] "Strongly Disagree"
#> [2,] "Strongly Disagree"
#> [3,] "Agree"
#> [4,] "Strongly Disagree"
#> [5,] "Agree"
#> [6,] "Neutral"
head(intdat1)
#> V1 V2 V3 V4 V5
#> 1 4 5 NA 5 1
#> 2 4 NA 4 2 1
#> 3 2 2 NA 2 4
#> 4 5 4 1 5 1
#> 5 2 5 1 1 4
#> 6 2 3 2 5 3
# 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,] "A" "N" "D" "D" "SA"
#> [2,] "SD" "A" "SA" "SD" "A"
#> [3,] "A" "SA" "A" "N" "SA"
#> [4,] "N" "A" "A" "A" "N"
#> [5,] "N" "D" "SD" "N" "N"
#> [6,] "N" "A" "SA" "SA" "A"
head(intdat2)
#> V1 V2 V3 V4 V5
#> 1 4 3 2 2 5
#> 2 1 4 5 1 4
#> 3 4 5 4 3 5
#> 4 3 4 4 4 3
#> 5 3 2 1 3 3
#> 6 3 4 5 5 4
# full dataset (using both mapping schemes)
intdat <- likert2int(dat, levels = c(lvl1, lvl2))
head(dat)
#> [,1] [,2] [,3] [,4]
#> [1,] "Agree" "Strongly Agree" NA "Strongly Agree"
#> [2,] "Agree" NA "Agree" "Disagree"
#> [3,] "Disagree" "Disagree" NA "Disagree"
#> [4,] "Strongly Agree" "Agree" "Strongly Disagree" "Strongly Agree"
#> [5,] "Disagree" "Strongly Agree" "Strongly Disagree" "Strongly Disagree"
#> [6,] "Disagree" "Neutral" "Disagree" "Strongly Agree"
#> [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] "Strongly Disagree" "A" "N" "D" "D" "SA"
#> [2,] "Strongly Disagree" "SD" "A" "SA" "SD" "A"
#> [3,] "Agree" "A" "SA" "A" "N" "SA"
#> [4,] "Strongly Disagree" "N" "A" "A" "A" "N"
#> [5,] "Agree" "N" "D" "SD" "N" "N"
#> [6,] "Neutral" "N" "A" "SA" "SA" "A"
head(intdat)
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
#> 1 4 5 NA 5 1 4 3 2 2 5
#> 2 4 NA 4 2 1 1 4 5 1 4
#> 3 2 2 NA 2 4 4 5 4 3 5
#> 4 5 4 1 5 1 3 4 4 4 3
#> 5 2 5 1 1 4 3 2 1 3 3
#> 6 2 3 2 5 3 3 4 5 5 4
#####
# 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" "Agree" "Disagree" "Strongly Agree" ...
#> $ Item_2 : chr "Strongly Agree" NA "Disagree" "Agree" ...
#> $ Item_3 : chr NA "Agree" NA "Strongly Disagree" ...
#> $ Item_4 : chr "Strongly Agree" "Disagree" "Disagree" "Strongly Agree" ...
#> $ Item_5 : chr "Strongly Disagree" "Strongly Disagree" "Agree" "Strongly Disagree" ...
#> $ Item_6 : chr "A" "SD" "A" "N" ...
#> $ Item_7 : chr "N" "A" "SA" "A" ...
#> $ Item_8 : chr "D" "SA" "A" "A" ...
#> $ Item_9 : chr "D" "SD" "N" "A" ...
#> $ Item_10: chr "SA" "A" "SA" "N" ...
# 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" "Agree" "Disagree" "Strongly Agree" ...
#> ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
#> $ Item_2 : chr "Strongly Agree" NA "Disagree" "Agree" ...
#> ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
#> $ Item_3 : chr NA "Agree" NA "Strongly Disagree" ...
#> ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
#> $ Item_4 : chr "Strongly Agree" "Disagree" "Disagree" "Strongly Agree" ...
#> ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
#> $ Item_5 : chr "Strongly Disagree" "Strongly Disagree" "Agree" "Strongly Disagree" ...
#> ..- attr(*, "levels")= chr [1:5] "Strongly Disagree" "Disagree" "Neutral" "Agree" ...
#> $ Item_6 : chr "A" "SD" "A" "N" ...
#> ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
#> $ Item_7 : chr "N" "A" "SA" "A" ...
#> ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
#> $ Item_8 : chr "D" "SA" "A" "A" ...
#> ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
#> $ Item_9 : chr "D" "SD" "N" "A" ...
#> ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
#> $ Item_10: chr "SA" "A" "SA" "N" ...
#> ..- attr(*, "levels")= chr [1:5] "SD" "D" "N" "A" ...
intdat <- likert2int(dat)
head(dat)
#> Item_1 Item_2 Item_3 Item_4
#> 1 Agree Strongly Agree <NA> Strongly Agree
#> 2 Agree <NA> Agree Disagree
#> 3 Disagree Disagree <NA> Disagree
#> 4 Strongly Agree Agree Strongly Disagree Strongly Agree
#> 5 Disagree Strongly Agree Strongly Disagree Strongly Disagree
#> 6 Disagree Neutral Disagree Strongly Agree
#> Item_5 Item_6 Item_7 Item_8 Item_9 Item_10
#> 1 Strongly Disagree A N D D SA
#> 2 Strongly Disagree SD A SA SD A
#> 3 Agree A SA A N SA
#> 4 Strongly Disagree N A A A N
#> 5 Agree N D SD N N
#> 6 Neutral N A SA SA A
head(intdat)
#> Item_1 Item_2 Item_3 Item_4 Item_5 Item_6 Item_7 Item_8 Item_9 Item_10
#> 1 4 5 NA 5 1 4 3 2 2 5
#> 2 4 NA 4 2 1 1 4 5 1 4
#> 3 2 2 NA 2 4 4 5 4 3 5
#> 4 5 4 1 5 1 3 4 4 4 3
#> 5 2 5 1 1 4 3 2 1 3 3
#> 6 2 3 2 5 3 3 4 5 5 4
# }