svypredmeans: Predictive marginal means

Description

Predictive marginal means for a generalised linear model, using the method of Korn and Graubard (1999) and matching the results of SUDAAN. The predictive marginal mean for one level of a factor is the probability-weighted average of the fitted values for the model on new data where all the observations are set to that level of the factor but have whatever values of adjustment variables they really have.

Usage

svypredmeans(adjustmodel, groupfactor)

Arguments

adjustmodel

A generalised linear model fit by svyglm with the adjustment variable but without the factor for which predictive means are wanted

groupfactor

A one-sided formula specifying the factor for which predictive means are wanted. Can use, eg, ~interaction(race,sex) for combining variables

Value

An object of class svystat with the predictive marginal means and their covariance matrix.

References

Graubard B, Korn E (1999) "Predictive Margins with Survey Data" Biometrics 55:652-659

Bieler, Brown, Williams, & Brogan (2010) "Estimating Model-Adjusted Risks, Risk Differences, and Risk Ratios From Complex Survey Data" Am J Epi DOI: 10.1093/aje/kwp440

Examples

Run this code

# NOT RUN {
data(nhanes)
nhanes_design <- svydesign(id=~SDMVPSU, strata=~SDMVSTRA, weights=~WTMEC2YR, nest=TRUE,data=nhanes)
agesexmodel<-svyglm(HI_CHOL~agecat+RIAGENDR, design=nhanes_design,family=quasibinomial)
## high cholesterol by race/ethnicity, adjusted for demographic differences
means<-svypredmeans(agesexmodel, ~race)
means
## relative risks compared to non-Hispanic white
svycontrast(means,quote(`1`/`2`))
svycontrast(means,quote(`3`/`2`))
# }