Rao-Scott weighting.

Rao-Scott weighting of clustered binomial observations.

Usage

rsbWt(fit = NULL, subset.factor = NULL, fit.only = TRUE)

Arguments

fit

A stats::glm object.

subset.factor

Factor for estimating phi by subset. Will be converted to a factor if it is not a factor.

fit.only

Return only the new fit? If FALSE, also returns the weights and phi estimates.

Value

A list with the following elements.

• fit: the new model fit, updated by the estimated weights

• weights: vector of weights

• d: vector of \({d}_{i}\) estimates

Details

Estimates the cluster design effect \({d}_{i}\) as the variance inflation due to clustering by the method of Rao and Scott. Observations are then weighted by the inverse of the \({d}_{i}\).

References

Rao JNK, Scott AJ, 1992. A simple method for the analysis of clustered binary data. Biometrics 48:577-585.

See also

RRor, rsb.

Author

PF-package

Examples

birdm.fit <- glm(cbind(y, n - y) ~ tx-1, binomial, birdm)
RRor(rsbWt(birdm.fit))
#> 
#> 95% t intervals on 4 df
#> 
#> PF 
#>     PF     LL     UL 
#>  0.479 -1.061  0.868 
#> 
#>       mu.hat    LL     UL
#> txcon  0.768 0.968 0.2659
#> txvac  0.400 0.848 0.0737
#
# 95% t intervals on 4 df
#
# PF
#     PF     LL     UL
#  0.479 -1.061  0.868
#
#       mu.hat    LL     UL
# txcon  0.768 0.968 0.2659
# txvac  0.400 0.848 0.0737
#