To get started with {EGAnet}, you can use the Wiener Matrizen Test 2 (WMT-2) that is included in the package. The WMT-2 dataset is a German matrices intelligence test (in English, the name translates to Vienna Matrices Test 2). The test was designed using Rasch modeling to derive a short measure of (fluid) intelligence.
The dataset is comprised of some demographic variables as well as the test items. Here’s the variable names:
[1] "education" "monthly_income" "income_group" "sex"
[5] "age" "age_group" "wmt1" "wmt2"
[9] "wmt3" "wmt4" "wmt5" "wmt6"
[13] "wmt7" "wmt8" "wmt9" "wmt10"
[17] "wmt11" "wmt12" "wmt13" "wmt14"
[21] "wmt15" "wmt16" "wmt17" "wmt18"
For the EGA analysis, only the variables of interest are necessary –
that is, only the "wmt*"
variables are necessary. EGA is
performed on the subset of these variables below:
# Perform EGA
ega_wmt <- EGA(wmt2[,7:24])
That’s it! You’re up and running with EGA
.
To explore other features of the package, some quick links are provided below: