Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

mm() variance clarity #36

Open
leeper opened this issue May 3, 2020 · 0 comments
Open

mm() variance clarity #36

leeper opened this issue May 3, 2020 · 0 comments
Labels
documentation enhancement New feature or request

Comments

@leeper
Copy link
Owner

leeper commented May 3, 2020

Is it sufficiently clear that mm() returns domain estimates rather than SEs based on subsetting the data?

x <- structure(list(level = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L,  2L), .Label = c("John", "Kate"), class = "factor"), outcome = c(0L,  0L, 1L, 1L, 0L, 0L, 1L, 1L), weight = c(1L, 1L, 1L, 1L, 0L, 0L,  0L, 0L)), row.names = 1:8, class = "data.frame")

# what people might be expecting
with(subset(x, level == "John"), sqrt(sum((outcome - mean(outcome))^2)/3/4))
svymean(~outcome, svydesign(ids = ~1, weights = ~ 1, data = subset(x, level == "John")))

# what is actually returned (all are equivalent)
## mm()
mm(x, outcome ~ level)

## unweighted data, subset to John
svymean(~outcome, subset(svydesign(ids = ~1, weights = ~ 1, data = x), level == "John"))

## weighted data (Kate weight == 0), subset to John
svymean(~outcome, subset(svydesign(ids = ~1, weights = ~ weight, data = x), level == "John"))

## weighted data (Kate weight == 0), full data frame
svymean(~outcome, svydesign(ids = ~1, weights = ~ weight, data = x))

[ ] Document this better, pointing to vignette: https://cran.r-project.org/web/packages/survey/vignettes/domain.pdf
[ ] Add option to not calculate variances as if subsets are random samples of population?

@leeper leeper added enhancement New feature or request documentation labels May 3, 2020
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
documentation enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

1 participant