# confint.svyglm: Confidence intervals for regression parameters In survey: Analysis of Complex Survey Samples

## 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

 ```1 2``` ```## S3 method for class 'svyglm' confint(object, parm, level = 0.95, method = c("Wald", "likelihood"), ddf = NULL, ...) ```

## 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 norma. If `NULL`, use `object\$df.residual` `...` for future expansion

## Value

A matrix of confidence intervals

## References

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

`confint`
 ```1 2 3 4 5 6``` ```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")) ```