R Under development (unstable) (2024-03-08 r86070 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(survey)
Loading required package: grid
Loading required package: Matrix
Loading required package: survival

Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

> 
> # Dummy data for testing nonresponse adjustments
> toy <- data.frame(id = 1:10,
+                   dummy = 1,
+                   class = c(rep("A", 5), rep("B", 5)),
+                   responded = c(rep(TRUE, 8), FALSE, FALSE),
+                   weight = rep(100, 10))
> 
> # With jackknife replicate weights
> toy_repweights <- matrix(rep(1000/9, 100), nrow = 10)
> diag(toy_repweights) <- rep(0, 10)
> 
> # Scramble up which person is in which jackknife group
> toy_repweights <- toy_repweights[sample(1:10, size = 10), ]
> 
> toy_design <- svrepdesign(variables = toy[, 1:4],
+                           weights = toy$weight,
+                           repweights = toy_repweights,
+                           type = "JK1",
+                           scale = 0.9)
> 
> # Get the sum of the weights for the full sample
> poptotals <- as.data.frame(svyby(formula = ~dummy,
+                                  by = ~class,
+                                  design = toy_design,
+                                  FUN = survey::svytotal))
> 
> poptotals$Freq <- poptotals$dummy
> poptotals$dummy <- NULL
> poptotals$se <- NULL
> 
> # Adjust the weights of the responding sample to match to the full sample
> adjusted <-  postStratify(design = subset(toy_design, responded),
+                           strata = ~class,
+                           population = poptotals)
> 
> # This works for the weights...
> svyby(formula = ~dummy,
+       by = ~class,
+       design = adjusted,
+       FUN = survey::svytotal)
  class dummy se
A     A   500  0
B     B   500  0
> 
> # ...and some, but not all, the replicate weights
> stopifnot(all.equal(colSums(toy_design$repweights), colSums(adjusted$repweights)))
> 
> 
> 
> proc.time()
   user  system elapsed 
   1.09    0.07    1.17