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Convert scale to thurstonian binary with n items per block and n blocks

Source: R/GLM_IRT_T.R
rank_df_to_binary.Rd

Convert scale to thurstonian binary with n items per block and n blocks

Usage

rank_df_to_binary(mydata, items, reverse = TRUE)

Arguments

mydata

dataframe

items

number of items in block

reverse

if TRUE assumes that the highest value is first item in rank if FALSE the lowest value is the first item in rank

Examples

set.seed(12345)
mydata<-data.frame(i1=rnorm(10,mean=2,sd=.5),
                   i2=rnorm(10,mean=2,sd=.5),
                   i3=rnorm(10,mean=2,sd=.5),
                   i4=rnorm(10,mean=2,sd=.5),
                   i5=rnorm(10,mean=2,sd=.5),
                   i6=rnorm(10,mean=2,sd=.5))
rank_df_to_binary(mydata[,c("i1","i2","i3","i4")],4)
#>    i12 i13 i14 i23 i24 i34
#> 1    1   0   0   0   0   0
#> 2    0   0   0   1   0   0
#> 3    0   1   0   1   0   0
#> 4    0   1   0   1   0   0
#> 5    1   1   1   1   0   0
#> 6    0   0   0   0   1   1
#> 7    1   1   1   0   0   0
#> 8    1   0   1   0   1   1
#> 9    0   0   0   1   0   0
#> 10   0   0   0   1   1   0
rank_df_to_binary(mydata,3)
#>    i12 i13 i23 i12.1 i13.1 i23.1
#> 1    1   0   0     0     1     1
#> 2    0   0   1     1     1     0
#> 3    0   1   1     1     1     0
#> 4    0   1   1     1     1     1
#> 5    1   1   1     0     1     1
#> 6    0   0   0     0     1     1
#> 7    1   1   0     1     0     0
#> 8    1   0   0     0     0     0
#> 9    0   0   1     1     0     0
#> 10   0   0   1     1     1     1