parcels: Find miniscales (parcels) of size 2 or 3 from a set of items

parcelsR Documentation

Find miniscales (parcels) of size 2 or 3 from a set of items

Description

Given a set of n items, form n/2 or n/3 mini scales or parcels of the most similar pairs or triplets of items. These may be used as the basis for subsequent scale construction or multivariate (e.g., factor) analysis.

Usage

parcels(x, size = 3, max = TRUE, flip=TRUE,congruence = FALSE)
keysort(keys)

Arguments

x

A matrix/dataframe of items or a correlation/covariance matrix of items

size

Form parcels of size 2 or size 3

flip

if flip=TRUE, negative correlations lead to at least one item being negatively scored

max

Should item correlation/covariance be adjusted for their maximum correlation

congruence

Should the correlations be converted to congruence coefficients?

keys

Sort a matrix of keys to reflect item order as much as possible

Details

Items used in measuring ability or other aspects of personality are typically not very reliable. One suggestion has been to form items into homogeneous item composites (HICs), Factorially Homogeneous Item Dimensions (FHIDs) or mini scales (parcels). Parcelling may be done rationally, factorially, or empirically based upon the structure of the correlation/covariance matrix. link{parcels} facilitates the finding of parcels by forming a keys matrix suitable for using in score.items. These keys represent the n/2 most similar pairs or the n/3 most similar triplets.

The algorithm is straightforward: For size = 2, the correlation matrix is searched for the highest correlation. These two items form the first parcel and are dropped from the matrix. The procedure is repeated until there are no more pairs to form.

For size=3, the three items with the greatest sum of variances and covariances with each other is found. This triplet is the first parcel. All three items are removed and the procedure then identifies the next most similar triplet. The procedure repeats until n/3 parcels are identified.

Value

keys

A matrix of scoring keys to be used to form mini scales (parcels) These will be in order of importance, that is, the first parcel (P1) will reflect the most similar pair or triplet. The keys may also be sorted by average item order by using the keysort function.

Author(s)

William Revelle

References

Cattell, R. B. (1956). Validation and intensification of the sixteen personality factor questionnaire. Journal of Clinical Psychology , 12 (3), 205 -214.

See Also

scoreItems to score the parcels or iclust for an alternative way of forming item clusters.

Examples

parcels(Thurstone)
keys <- parcels(bfi)
keys <- keysort(keys)
scoreItems(keys,bfi)

psych documentation built on June 27, 2024, 5:07 p.m.