summary method for objects of class assocmod, including rc,
rcL, rcL.trans, hmskew, hmskewL
and yrcskew models.
# S3 method for assocmod
summary(object, weighting, ...)# S3 method for summary.assocmod
print(x, digits = max(3, getOption("digits") - 4), ...)
an association model of class assocmod.
an object of class summary.gnm.
what weights should be used when normalizing the scores.
the number of siginificant digits to use when printing.
further arguments passed to printCoefmat by
print.summary.assocmod, and currently ignored by summary.assocmod.
An object of class summary.assoc, with the following components:
the call component from object.
the diagonal component from the object's assoc component.
the deviance residuals, see residuals.glm.
a matrix holding the association coefficients estimates, standard errors and p-values.
a matrix holding the diagonal coefficients, if any.
the weigthing method used when normalizing the scores.
the deviance component from object.
the Pearson Chi-squared statistic for the model fit.
the dissimilarity index for the model fit.
the df.residual component from object.
the value of the BIC for the model fit (contrary to the value reported by
AIC and extractAIC, the reference is 0 for the
saturated model).
the value of the AIC for the model fit (contrary to the value reported by
AIC and extractAIC, the reference is 0 for the
saturated model).
the family component from object.
the estimated dispersion
a 3-vector of the rank of the model; the number of residual degrees of freedom; and number of unconstrained coefficients.
print.summary.assocmod prints the original call to assoc; a
summary of the deviance residuals from the model fit; the coefficients of
interest of the model; the residual deviance; the residual degrees of freedom;
the Schwartz's Bayesian Information Criterion value; the Akaike's An Information
Criterion value.
Association coefficients are printed with their standard errors, p-values and significance
stars. The “Normalized” columns contains normalized scores, i.e. their (weighted)
sum is 0, their (weighted) sum of squares is 1, and their (weighted) cross-dimensional
correlation is null. For models with only one layer (rc, hmskew,
yrcskew), adjusted scores are printed in the “Adjusted” column:
these correspond to normalized scores times the square root of the corresponding intrinsic
association parameter (phi).
p-values correspond to normalized scores, and are computed under the assumption that estimators
of coefficients are normally distributed, even if jackknife of bootstrap are used. See
se.assoc for details about checking this assumption and the validity of jackknife
or bootstrap results.
Note that setting the weighting argument to a value different from that used at the
time of the fit discards the computed standard errors, if any.
assoc, plot.assoc, rc, rcL,
rcL.trans, hmskew, hmskewL, yrcskew