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Summary of a LAME object

Source: R/summary.lame.R
summary.lame.Rd

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

Usage

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

Arguments

object

an object of class "lame", typically the result of fitting a longitudinal AME model using the lame function

...

additional parameters (currently not used)

Value

A list of class "summary.lame" containing:

call

The original function call

beta

Matrix of regression coefficient estimates and statistics

variance

Matrix of variance component estimates

n.periods

Number of time periods in the longitudinal data

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

cab

Covariance between sender and receiver effects

vb

Variance of additive receiver/column effects

rho

Dyadic correlation (reciprocity)

ve

Residual variance

Dynamic coefficients per period

Only printed when the fit was produced with dynamic_beta on at least one coefficient. The table has one row per coefficient with columns:

Mean

average of the per-period posterior means across t

Min, Max

smallest and largest per-period posterior mean

Drift

Max - Min: the absolute range of the per-period posterior means, in coefficient units

Drift_pct

100 * Drift / |Mean|, the drift as a percentage of the average level. Reported as NA when the time-average is near zero (within 5\ range), because a trajectory that crosses zero makes the percentage explode; read Drift in that case

Dynamic

"Y" if the coefficient was flagged as dynamic, "N" if it was held static

The block also prints the per-block AR(1) hyperparameters (rho_beta = ...). For per-period credible intervals use confint.lame.

See also

lame, print.summary.lame

Author

Cassy Dorff, Shahryar Minhas, Tosin Salau