Generate Composite Scores — composite • neuropsytools

This function calculates composite scores based on subtest correlations and their inter-correlations.

Usage

composite(
  r,
  r.between,
  mean = 10,
  sd = 3,
  comp.mean = 100,
  comp.sd = 15,
  dp = 2
)

Arguments

r: A numeric vector of correlations for the included tests.
r.between: A numeric vector of inter-correlations between the included tests.
mean: A numeric value specifying the mean of the included tests. Default is 10.
sd: A numeric value specifying the standard deviation of the included tests. Default is 3.
comp.mean: A numeric value specifying the mean of the composite score. Default is 100.
comp.sd: A numeric value specifying the standard deviation of the composite score. Default is 15.
dp: An integer specifying the number of decimal places for rounding results. Default is 2

Value

A list of class 'gen_comp' containing:

k: Number of subtests.
r: Vector of correlations for the included tests.
r.between: Vector of inter-correlations between the included tests.
composite_r: Composite correlation.
original_mean: Original mean of the composite score.
original_sd: Original standard deviation of the composite score.
original_sem: Original standard error of measurement.
original_semt: Original standard error of the mean transformed.
transformed.mean: Transformed mean of the composite score.
transformed.sd: Transformed standard deviation of the composite score.
transformed.sem: Transformed standard error of measurement.
transformed.semt: Transformed standard error of the mean transformed.

Examples

result <- composite(r = c(.87, .94, .94),
                             r.between = c(0.74, 0.64, 0.73),
                             dp = 3)
print(result)
#> Generate Composite Score
#> 
#> INPUTS:
#> 
#> 
#> Inputs                     Value            
#> -------------------------  -----------------
#> Number of tests included   3                
#> r for included tests       0.87, 0.94, 0.94 
#> r between included tests   0.74, 0.64, 0.73 
#> 
#> OUTPUTS:
#> 
#> 
#> Outputs       Original   Transformed 
#> ------------  ---------  ------------
#> Composite r   0.9650                 
#> Mean          30.0000    100.0000    
#> SD            7.4820     15.0000     
#> SEM           1.3920     2.7910      
#> SEMt (true)   1.3440     2.6950