neurotroph/reliability-factor-score-estimators

SPSS and R scripts to calculate reliablity estimates for factor score estimators
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Reliability Estimates for Three Factor Score Estimators

The scripts in this repository accompany our paper (Beauducel, Harms & Hilger, 2016) and reflect the appendices A and B of the publication.

Example for R script

Calculates the reliability estimates for a given factor analysis solution:

```Loadings <- matrix(c(
0.50,-0.10, 0.10,
0.50, 0.10, 0.10,
0.50, 0.10,-0.10,
-0.10, 0.50, 0.15,
0.15, 0.50, 0.10,
-0.15, 0.50, 0.10,
0.10, 0.10, 0.60,
0.10,-0.10, 0.60,
0.10, 0.10, 0.60
),
nrow=9, ncol=3,
byrow=TRUE)
InterCorr <- matrix(c(
1.00, 0.30, 0.20,
0.30, 1.00, 0.10,
0.20, 0.10, 1.00
),
nrow=3, ncol=3,
byrow=TRUE)

reliabilities <- factor.score.reliability(Lambda = Loadings, Phi = InterCorr, Estimators = c("Regression", "Bartlett", "McDonald"))
lapply(reliabilities, round, 3)```

Remark: If a factor solution was obtained through the `fa` package, the factor loadings from the solution can be passed through `Lambda`.

Reference

Beauducel, A., Harms, C., & Hilger, N. (2016). Reliability estimates for three factor score predictors. International Journal of Statistics and Probability, 5(6), 94–107. http://doi.org/10.5539/ijsp.v5n6p94