Table 4.
Parallel analyses from the items of the GQ6-NL and SGRAT-NL (N = 706).
| Measures and factors | Raw data | 95th percentile | Proportion variance explained (%) |
|---|---|---|---|
|
| |||
| GQ6-NL | |||
| – Factor 1 | 2.668317 | 1.037477 | 35.68 |
| – Factor 2 | 1.176871 | 1.176871 | |
| SGRAT-NL | |||
| – Factor 1 | 4.350429 | 1.315935 | 23.74 |
| – Factor 2 | 2.853171 | 1.246335 | 14.93 |
| – Factor 3 | 1.861935 | 1.199335 | 8.43 |
| – Factor 4 | 0.978189 | 1.157936 | |
Note. Parallel analyses with Monte Carlo simulations determines the number of factors to retain in Exploratory Factor Analysis (Ledesma & Valero-Mora, 2007). The simulation was executed with 1000 parallel datasets based on permutations of the original raw data set, with the criterion set at the 95th percentile. The eigenvalue of the raw data needs to exceed the eigenvalue of the 95th percentile to be defined as a factor (O’Connor, 2000).