Introduction | Part 1: Data preparation | Loading package and data | Network data manipulations | Compiling nodal attribute data | Independent and control variables | The role of zero-values in covariates | Change statistics to calculate endogenous network statistics | Reciprocity | Triadic closure | Homophily | Creating custom covariates | (Attribute-based) Degree measures | Creating the dummy variables to encode the zero values of each covariate | Part 2: Running gHypEG regressions | Regression set up (how to) | What are initial values? | Regression table export (using the texreg package) | Regression with degree correction (standard version) | Regression without degree correction (and when to use it) | Part 3: Model assessment, network simulations, gof | Model comparisons | Predicted probabilities | Network simulations

Load Packages | Estimate the ensemble | Finding the significance of the links | Plot the results | Block Model

Fitting a gHypEG Model | Block-Constrained Configuration Model | Goodness of Fit