R: Confidence intervals for regression parameters

confint.svyglm {survey} | R Documentation

## 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 class 'svyglm'
    confint(object, parm, level = 0.95, method = c("Wald", "likelihood"), ddf = Inf, ...)

### 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

### 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"))

[Package survey version 3.32-1 Index]