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Summarizes a fitted AME (Additive and Multiplicative Effects) model, including parameter estimates, standard errors, credible intervals, and model diagnostics.

Usage

# S3 method for class 'ame'
summary(object, ...)

Arguments

object

an object of class "ame", typically the result of fitting an AME model using the ame function

...

additional parameters (currently not used)

Value

A list of class "summary.ame" containing:

call

The original function call

beta

Matrix of regression coefficient estimates and statistics

variance

Matrix of variance component estimates

Details

The summary includes:

Regression coefficients

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.

Variance components

Estimates and standard errors for:

va

Variance of additive sender/row effects (asymmetric networks)

cab

Covariance between sender and receiver effects

vb

Variance of additive receiver/column effects (asymmetric networks)

rho

Dyadic correlation (reciprocity in directed networks)

ve

Residual variance

For symmetric networks, only va and ve are estimated.

Author

Cassy Dorff, Shahryar Minhas, Tosin Salau