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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:

# Load {EGAnet}

# Check variables 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: