summary.svyglm.RDS: Summarizing Generalized Linear Model Fits with Odds Ratios for Survey Data

Description

RDS::summary.svyglm.RDS is a version of summary.svyglm that reports odds-ratios in place of coefficients in the summary table. This only applies for the binomial family. Otherwise it is identical to summary.svyglm. The default in summary.svyglm is to display the log-odds-ratios and this displays the exponetiated from and a 95 p-values are still displayed.

Usage

# S3 method for svyglm.RDS
summary(object, correlation = FALSE, df.resid = NULL, odds = TRUE, ...)

Value

RDS::summary.svyglm returns an object of class "summary.svyglm.RDS", a list with components

call: the component from object.
family: the component from object.
deviance: the component from object.
contrasts: the component from object.
df.residual: the component from object.
null.deviance: the component from object.
df.null: the component from object.
deviance.resid: the deviance residuals: see residuals.svyglm.
coefficients: the matrix of coefficients, standard errors, z-values and p-values. Aliased coefficients are omitted.
aliased: named logical vector showing if the original coefficients are aliased.
dispersion: either the supplied argument or the inferred/estimated dispersion if the latter is NULL.
df: a 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of coefficients (including aliased ones).
cov.unscaled: the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.
cov.scaled: ditto, scaled by dispersion.
correlation: (only if correlation is true.) The estimated correlations of the estimated coefficients.
symbolic.cor: (only if correlation is true.) The value of the argument symbolic.cor.
odds: Are the coefficients reported as odds (rather than log-odds)?

Arguments

object: an object of class "svyglm", usually, a result of a call to svyglm.
correlation: logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
df.resid: Optional denominator degrees of freedom for Wald tests.
odds: logical; Should the coefficients be reported as odds (rather than log-odds)?
...: further arguments passed to or from other methods.

Details

svyglm fits a generalised linear model to data from a complex survey design, with inverse-probability weighting and design-based standard errors.

There is no anova method for svyglm as the models are not fitted by maximum likelihood.

See the manual page on svyglm for detail of that function.

Examples

Run this code


## For examples see example(svyglm)