survey (version 4.5)

confint.svyglm: Confidence intervals for regression parameters

Description

Computes confidence intervals for regression parameters in svyglm objects. The default is a Wald-type confidence interval, adding and subtracting a multiple of the standard error. The method="likelihood" is an interval based on inverting the Rao-Scott likelihood ratio test. That is, it is an interval where the working model deviance is lower than the threshold for the Rao-Scott test at the specified level.

Usage

# S3 method for svyglm
confint(object, parm, level = 0.95, method = c("Wald", "likelihood"), ddf = NULL, ...)

Value

A matrix of confidence intervals, possibly with additional attributes levels and/or degf.

Arguments

object

svyglm object

parm

numeric or character vector indicating which parameters to construct intervals for.

level

desired coverage

method

See description above

ddf

Denominator degrees of freedom for "likelihood" method, to use a t distribution rather than normal. If NULL, use object$df.residual for Taylor-series standard errors, or object$df.coef for Bell-McCaffrey standard errors with adjusted degrees of freedom.

...

for future expansion

References

J. N. K. Rao and Alastair J. Scott (1984). On Chi-squared Tests For Multiway Contigency Tables with Proportions Estimated From Survey Data. Annals of Statistics 12:46-60.

Robert M. Bell and Daniel F. McCaffrey (2002). Bias Reduction in Standard Errors for Linear Regression with Multi-Stage Samples. Survey Methodology 28 (2), 169-181. https://www150.statcan.gc.ca/n1/pub/12-001-x/2002002/article/9058-eng.pdf

See Also

confint

Examples

data(api)
dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)

m<-svyglm(I(comp.imp=="Yes")~stype*emer+ell, design=dclus2, family=quasibinomial)
confint(m)
confint(m, method="like",ddf=NULL, parm=c("ell","emer"))

m2<-svyglm(I(comp.imp=="Yes")~stype*emer+ell, design=dclus2, family=quasibinomial,
    std.errors="Bell-McCaffrey-2", degf=TRUE)
confint(m2)