predicted.validity | R Documentation |
The validity of a scale varies as a function of the number of items in the scale, their average intercorrelation, and their average validity. The asymptotic limit of a scales validity for any particular criterion is just the average validity divided by the square root of the average within scale item correlation. predicted.validity
will find the predicted validity for a set of scales (defined by a keys.list) and the average item validity for various criteria.
The function will find (and report) scale reliabilities (using reliability
) and average item validities (using item.validity
)
predicted.validity(x, criteria, keys, scale.rel = NULL, item.val = NULL)
item.validity(x,criteria,keys)
validityItem(x,criteria,keys)
x |
A data set |
criteria |
Variables to predict from the scales |
keys |
A keys.list that defines the scales |
scale.rel |
If not specified, these will be found. Otherwise, this is the output from |
item.val |
If not specified, the average item validities for each scale will be found. Otherwise use the output from |
When predicting criteria from a set of items formed into scales, the validity of the scale (that is, the correlations of the scale with each criteria) is a function of the average item validity (r_y), the average intercorrelation of the items in the scale (r_x), and the number of items in the scale (n). The limit of validity is r_y/sqrt(r_x).
Criteria will differ in their predictability from a set of scales. These asymptotic values may be used to help the decision on which scales to develop further.
predicted |
The predicted validities given the scales specified |
item.validities |
The average item validities for each scale with each criterion |
scale.reliabilities |
The various statistics reported by the |
asymptotic |
A matrix of the asymptotic validities |
William Revelle
Revelle, William. (in prep) An introduction to psychometric theory with applications in R. Springer. Working draft available at https://personality-project.org/r/book/
Revelle, W. and Condon, D.M. (2019) Reliability from alpha to omega: A tutorial. Psychological Assessment, 31, 12, 1395-1411. https://doi.org/10.1037/pas0000754. https://osf.io/preprints/psyarxiv/2y3w9 Preprint available from PsyArxiv
reliability
, scoreItems
, scoreFast
pred.bfi <- predicted.validity(bfi[,1:25], bfi[,26:28], bfi.keys)
pred.bfi
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