Calculate mean scores on circumplex scales from item responses by using the scoring instructions stored in an instrument object from the package.
Arguments
- data
Required. A data frame or matrix containing at least circumplex scales.
- items
Required. The variable names or column numbers for the variables in
.datathat contain all the circumplex items from a single circumplex measure, in ascending order from item 1 to item N.- instrument
Required. An instrument object from the package. To see the available circumplex instruments, use
instruments().- na.rm
Optional. A logical that determines if missing values should be omitted from the calculation of scores (default = TRUE). When set to TRUE, scales with missing data are essentially calculated with mean imputation.
- prefix
Optional. A string to include at the beginning of the newly calculated scale variables' names, before
Abbrevfromkeyandsuffix(default = "").- suffix
Optional. A string to include at the end of the newly calculated scale variables' names, after
Abbrevfromkeyandprefix(default = "").- append
Optional. A logical that determines whether the calculated score variables will be appended to
dataor returned on their own (default = TRUE).
Value
A data frame that matches .data except that new variables are
appended that contain mean scores on each variable included in key.
See also
Other tidying functions:
ipsatize(),
norm_standardize(),
self_standardize()
Examples
data("raw_iipsc")
score(raw_iipsc, items = 1:32, instrument = iipsc, prefix = "IIPSC_")
#> IIP01 IIP02 IIP03 IIP04 IIP05 IIP06 IIP07 IIP08 IIP09 IIP10 IIP11 IIP12
#> 1 0 0 0 0 1 0 1 0 2 1 0 0
#> 2 1 1 0 0 3 2 2 1 0 1 0 1
#> 3 1 0 1 0 1 1 1 3 0 1 0 0
#> 4 3 2 3 NA 2 3 2 3 2 3 2 4
#> 5 0 0 0 1 0 0 1 1 0 1 0 2
#> 6 0 0 0 0 0 0 1 1 0 0 0 0
#> 7 1 0 0 0 2 1 1 0 1 0 0 0
#> 8 1 0 1 0 1 1 2 1 1 0 0 0
#> 9 0 0 2 2 0 1 3 0 1 0 1 1
#> 10 0 0 0 0 0 0 2 0 0 0 0 0
#> IIP13 IIP14 IIP15 IIP16 IIP17 IIP18 IIP19 IIP20 IIP21 IIP22 IIP23 IIP24
#> 1 0 1 4 3 2 4 2 0 1 0 0 0
#> 2 4 3 3 1 0 0 1 0 1 2 0 0
#> 3 2 3 3 2 2 1 1 0 3 2 3 1
#> 4 2 1 2 3 1 2 2 1 3 2 3 2
#> 5 1 1 3 1 0 1 0 1 1 0 1 1
#> 6 0 0 2 1 1 0 0 0 0 0 1 1
#> 7 1 1 1 0 1 0 0 0 0 1 1 1
#> 8 1 NA 2 1 1 0 1 0 0 0 1 1
#> 9 0 2 2 2 1 2 2 0 0 0 3 0
#> 10 0 2 2 1 0 0 0 0 0 0 0 0
#> IIP25 IIP26 IIP27 IIP28 IIP29 IIP30 IIP31 IIP32 IIPSC_PA IIPSC_BC IIPSC_DE
#> 1 3 3 3 0 0 0 1 0 1.75 2.00 1.25
#> 2 0 0 0 1 0 0 0 2 0.25 0.50 0.25
#> 3 1 1 1 0 3 2 3 2 1.00 0.75 0.75
#> 4 1 2 3 2 3 2 3 2 1.75 2.25 2.50
#> 5 2 1 0 0 0 0 0 0 0.50 0.75 0.00
#> 6 0 0 0 0 0 0 0 1 0.25 0.00 0.00
#> 7 1 0 0 0 1 1 0 0 1.00 0.00 0.00
#> 8 1 1 1 0 0 1 2 1 1.00 0.25 0.75
#> 9 1 0 1 0 0 1 3 0 0.75 0.50 1.50
#> 10 0 0 0 0 0 0 0 0 0.00 0.00 0.00
#> IIPSC_FG IIPSC_HI IIPSC_JK IIPSC_LM IIPSC_NO
#> 1 0.000000 0.50 0.2500000 1.50 0.75
#> 2 0.500000 2.00 1.7500000 1.25 1.00
#> 3 0.000000 2.25 2.0000000 2.50 2.00
#> 4 2.333333 2.50 2.0000000 2.50 2.50
#> 5 1.000000 0.50 0.2500000 1.25 0.75
#> 6 0.000000 0.00 0.0000000 1.00 1.00
#> 7 0.000000 1.00 1.0000000 0.75 0.25
#> 8 0.000000 0.50 0.6666667 1.75 1.00
#> 9 0.750000 0.00 1.0000000 2.75 0.50
#> 10 0.000000 0.00 0.5000000 1.00 0.25