summary.unidiff {logmult}R Documentation

Summarize UNIDIFF Model Fits

Description

summary method for objects of class unidiff.

Usage

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

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

Arguments

object

an object resulting from a call to unidiff

x

an object of class summary.gnm.

digits

the number of siginificant digits to use when printing.

...

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

Details

print.summary.unidiff prints the original call to unidiff; 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.

Layer and two-way interaction coefficients are printed with their standard errors, quasi-standard errors (see qvcalc), p-values (based on standard errors) and significance stars. Constrained coefficients have a value of 0 (by default), and 0 standard errors, but still have quasi-standard errors.

Value

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

call

the call component from object.

deviance.resid

the deviance residuals, see residuals.glm.

layer

a data.frame holding the layer coefficients estimates, standard errors, quasi-standard errors (see qvcalc) and p-values.

phi.layer

a data.frame holding the layer coefficients estimates, standard errors, and quasi-standard errors (see qvcalc) multiplied by the intrinsic association coefficient (see maor) for the first layer; p-values are the same as those for the “layer” component.

interaction

a data.frame holding the two-way interaction coefficients estimates, standard errors and p-values.

deviance

the deviance component from object.

diagonal

the diagonal component from the object's unidiff component.

weighting

the weighting component from the object's unidiff component.

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

unidiff, plot.unidiff


[Package logmult version 0.7.4 Index]