score: Factor scores.
In maxheld83/pensieve: Tools for the Scientific Study of Operant Subjectivity

Description Usage Arguments Methods (by generic) See Also Examples

Calculates the factor scores as loadings-weighted averages of raw Q-Sorts (regression scores).

Construct S3 class for pensieve.

Check S3 class.

score(loas, csorts)

QScores(scores, validate = TRUE)

## S3 method for class 'QScores'
check(x)

`loas`	A numerical matrix with loadings.
`csorts`	`[matrix()]` An numeric matrix with people as rows, item handles as columns and item positions in cells.
`scores`	A numerical matrix with factor scores.
`validate`	a logical flag, indicating whether the object will be validated on construction. Defaults to `TRUE`.
`x`	class object created by respective constructor function.

check: validation

Other analysis functions: correlate(), extract()

Other S3 classes from pensieve: correlate(), extract(), psClosedSorts(), psGrid(), psItemContent(), psOpenSorts(), psOpenSort(), psPeople()

csorts <- civicon_2014$qData$sorts[,,"before"]  # preparatory step
cors <- correlate(csorts = csorts)  # preparatory step
loas <- extract(cors = cors, nfactors = 3, fa_type = "pca")  # preparatory step
scores <- score(loas = loas, csorts = csorts)
# this just assigns the class, without validation (not recommended)
scores <- QScores(scores = scores, validate = FALSE)
# this validates the class
check(x = scores)