R: Kaiser's Index of Factorial Simplicity

kaisers_index {anomalyDetection} | R Documentation

## Kaiser's Index of Factorial Simplicity

### Description

`kaisers_index` computes scores designed to assess the quality of a factor analysis solution. It measures the tendency towards unifactoriality for both a given row and the entire matrix as a whole. Kaiser proposed the evaluations of the score shown below:

1. In the .90s: Marvelous

2. In the .80s: Meritorious

3. In the .70s: Middling

4. In the .60s: Mediocre

5. In the .50s: Miserable

6. < .50: Unacceptable

Use as basis for selecting original or rotated loadings/scores in `factor_analysis`.

### Usage

    kaisers_index(loadings)

### Arguments

`loadings` | numerical matrix of the factor loadings

### Value

Vector containing the computed score

### References

H. F. Kaiser, "An index of factorial simplicity," Psychometrika, vol. 39, no. 1, pp. 31-36, 1974.

### See Also

`factor_analysis` for computing the factor analysis loadings

### Examples

    # Perform Factor Analysis with matrix \code{x}
    x <- matrix(rnorm(200*3), ncol = 10)

    x %>%
      horns_curve() %>%
      factor_analysis(x, hc_points = .) %>%
      factor_analysis_results(fa_loadings_rotated) %>%
      kaisers_index()

[Package anomalyDetection version 0.2.5 Index]