[R] Using calibrate for raking (survey package)

[Michael.Laviolette at dhhs.state.nh.us]

I'm studying the calibration function in the survey package in preparation
for raking some survey data. Results from the rake function below agree
with other sources. When I run calibrate, I get a warning message and the M
and F weights seem to be reversed. Even allowing for that, the deviation
between calibrated and raked weights is much more than I expected. I see
that in the calibrate function "population" is supposed to be a vector or
table, but can't figure out how to adjust. Can you clarify? Thanks.

-M. Laviolette

satisfy <- c(2,5,2,3,4,3,3,3,4,2,2,3,2,3,4,3,3,2,3,3,4,3,3,3,2,
             3,3,3,2,1,4,4,3,3,2,3,4,2,3,3,3,5,3,1,4,3,3,4,4,2,
             3,3,3,5,4,4,5,3,4,4,5,3,3,4,3,3,3,3,2,4,4,3,3,4,3,
             2,4,4,3,4,4,4,5,3,3,4,4,4,3,2,2,4,3,4,3,4,4,3,3,3,
             3,4,4,4,4,3,3,3,3,2,3,3,2,2,5,4,5,2,4,4,4,3,4,4,2,
             4,4,3,4,3,4,2,3,3,2,4,3,4,4,3,5,2,4,4,3,4,5,3,3,3,
             3,2,3,4,4,4,2,4,4,2,3,5,2,2,3,3,3,3,3,4,4,3,3,4,4,
             4,4,4,4,4,4,3,2,3,3,3,3,4,4,4,3,3,4,3,4,4,4,3,3,2)

Gender <-  c(1,2,1,1,2,1,1,2,1,2,1,1,2,1,1,1,1,2,2,1,2,1,1,2,1,
             2,1,1,2,2,1,1,2,1,2,2,1,1,1,1,2,1,1,1,1,1,1,1,2,1,
             1,1,1,1,2,1,1,2,2,2,2,2,2,2,2,2,1,1,1,1,2,1,2,1,2,
             1,1,2,1,1,2,1,1,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,1,2,
             1,1,2,1,2,1,2,2,1,1,1,2,1,1,1,2,1,1,2,1,2,2,2,1,1,
             2,2,1,1,1,2,1,2,1,2,2,1,1,1,2,2,1,2,2,2,2,1,2,2,1,
             2,1,2,1,1,2,2,1,1,1,2,2,1,2,2,2,1,2,2,1,1,1,2,2,2,
             1,2,1,2,2,2,2,1,1,2,1,1,1,2,1,1,2,2,1,1,1,1,2,1,1)

Age <-     c(2,3,2,1,2,2,2,2,3,2,2,1,2,2,2,2,2,2,2,2,2,2,2,3,2,
             3,3,3,1,2,2,3,2,2,2,1,3,2,2,2,2,2,2,3,2,2,2,2,2,1,
             3,3,2,3,2,2,2,2,2,2,2,3,2,2,1,2,2,2,1,2,2,3,2,2,1,
             2,2,1,2,2,1,2,2,2,2,2,2,2,3,2,2,1,3,2,2,2,3,2,2,2,
             3,1,2,1,2,2,1,2,2,2,2,2,2,1,2,2,3,1,2,2,2,2,2,2,2,
             2,3,1,1,2,1,2,2,2,2,2,2,2,2,1,3,2,2,2,1,2,1,1,2,1,
             2,1,1,2,2,2,2,2,2,2,2,3,2,1,2,1,1,2,3,3,1,3,3,2,2,
             2,2,2,2,2,2,2,3,2,3,3,2,2,2,3,1,2,1,2,3,2,2,2,3,2)

emp.dat <- data.frame(Gender = factor(Gender, labels = c("M", "F")),
                      Age = factor(Age, labels =  c("<30", "30-44", "45
+")),
                      satisfy)
pop.gender <- data.frame(Gender = c("M", "F"), Freq = c(3800, 6200))
pop.age <- data.frame(Age = c("<30", "30-44", "45+"),
                      Freq = c(2000, 5000, 3000))

library(survey)
emp.svy <- svydesign(ids = ~0, strata = NULL, weights = ~rep(50, 200),
                     data = emp.dat)
rake.svy <- rake(emp.svy, list(~Gender, ~Age), list(pop.gender, pop.age))

cal.svy <- calibrate(emp.svy,
                     formula = list(~Gender, ~Age),
                     population = list(pop.gender, pop.age), cal.fun =
"raking")
# Warning message:
#   In regcalibrate.survey.design2(design, formula, population,
aggregate.stage # = aggregate.stage,  :Sample and population totals have
different names.

# check weights--M and F seem reversed when "calibrate" used
library(reshape2)
check1 <- with(rake.svy, cbind(variables, weight = 1/prob))
dcast(check1, Gender~Age, sum, value.var = "weight", margins = TRUE)
check2 <- with(cal.svy, cbind(variables, weight = 1/prob))
dcast(check2, Gender~Age, sum, value.var = "weight", margins = TRUE)