summary method for objects of class unidiff.
# S3 method for unidiff
summary(object, ...)# S3 method for summary.unidiff
print(x, digits = max(3, getOption("digits") - 4), ...)
an object resulting from a call to unidiff
an object of class summary.gnm.
the number of siginificant digits to use when printing.
further arguments passed to printCoefmat by
print.summary.unidiff, and currently ignored by summary.unidiff.
An object of class summary.unidiff, with the following components:
the call component from object.
the deviance residuals, see residuals.glm.
a data.frame holding the layer coefficients estimates, standard
errors, quasi-standard errors (see qvcalc) and p-values.
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.
a data.frame holding the two-way interaction coefficients
estimates, standard errors and p-values.
the deviance component from object.
the diagonal component from the object's unidiff component.
the weighting component from the object's unidiff component.
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.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.