summary.assoc {logmult}R Documentation

Summarize Association Model Fits

Description

summary method for objects of class assocmod, including rc, rcL, rcL.trans, hmskew, hmskewL and yrcskew models.

Usage

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

## S3 method for class 'summary.assocmod'
print(x, digits = max(3, getOption("digits") - 4), ...)

Arguments

object

an association model of class assocmod.

x

an object of class summary.gnm.

weighting

what weights should be used when normalizing the scores.

digits

the number of siginificant digits to use when printing.

...

further arguments passed to printCoefmat by print.summary.assocmod, and currently ignored by summary.assocmod.

Details

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.

Value

An object of class summary.assoc, with the following components:

call

the call component from object.

diagonal

the diagonal component from the object's assoc component.

deviance.resid

the deviance residuals, see residuals.glm.

coefficients

a matrix holding the association coefficients estimates, standard errors and p-values.

diagonal

a matrix holding the diagonal coefficients, if any.

weighting

the weigthing method used when normalizing the scores.

deviance

the deviance component from object.

chisq

the Pearson Chi-squared statistic for the model fit.

dissim

the dissimilarity index for the model fit.

df.residual

the df.residual component from object.

bic

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).

aic

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).

family

the family component from object.

dispersion

the estimated dispersion

df

a 3-vector of the rank of the model; the number of residual degrees of freedom; and number of unconstrained coefficients.

Author(s)

Milan Bouchet-Valat

See Also

assoc, plot.assoc, rc, rcL, rcL.trans, hmskew, hmskewL, yrcskew


[Package logmult version 0.7.4 Index]