Tutorials & deeper dives
Longer-form guides to EGAnet — from a first analysis to how reproducibility is implemented under the hood.
| Quick Start | To get started with {EGAnet}, you can use the Wiener Matrizen Test 2 (WMT-2) that is included in the package. |
| EGA + Transformers NLP | Transformers models are taking the data science world by storm. |
| Using External Networks (and external packages) | Although {EGAnet} features many common methods used in the network psychometric literature, it does not include all possible options. |
| What's Changed? | In a word: everything |
| Argument Passing | A big change to the {EGAnet} structure in version +2.0.0 was that nearly every argument can be passed down through sub-functions in a main function. |
| Reproducibility and Pseudorandom Number Generation (PRNG) | Random number generation is important and some methods are better than others. |
| Errors | For every function in {EGAnet}, there are built-in data checks that may sometimes throw an error. |
| Teaching | - Exploratory Graph Analysis (EGA) |