Summarizes a fitted AME (Additive and Multiplicative Effects) model, including parameter estimates, standard errors, credible intervals, and model diagnostics.
# S3 method for ame
summary(object, ...)A list of class "summary.ame" containing:
The original function call
Matrix of regression coefficient estimates and statistics
Matrix of variance component estimates
an object of class "ame", typically the result of fitting an
AME model using the ame function
additional parameters (currently not used)
Cassy Dorff, Shahryar Minhas, Tosin Salau
The summary includes:
Posterior means, posterior standard deviations, z-values, approximate p-values, and 95% credible intervals for dyadic, sender, and receiver covariates. Note: the z-values are computed as posterior mean / posterior SD, and the p-values are derived from a normal approximation. These are convenient screening statistics but are not formal frequentist test statistics. For rigorous inference, use the credible intervals or examine the full posterior via the BETA matrix directly.
Estimates and standard errors for:
Variance of additive sender/row effects (asymmetric networks)
Covariance between sender and receiver effects
Variance of additive receiver/column effects (asymmetric networks)
Dyadic correlation (reciprocity in directed networks)
Residual variance
For symmetric networks, only va and ve are estimated.
ame, print.summary.ame