View source: R/as_survey_design.r
as_survey_design | R Documentation |
Create a survey object with a survey design.
as_survey_design(.data, ...) ## S3 method for class 'data.frame' as_survey_design( .data, ids = NULL, probs = NULL, strata = NULL, variables = NULL, fpc = NULL, nest = FALSE, check_strata = !nest, weights = NULL, pps = FALSE, variance = c("HT", "YG"), ... ) ## S3 method for class 'survey.design2' as_survey_design(.data, ...) ## S3 method for class 'tbl_lazy' as_survey_design( .data, ids = NULL, probs = NULL, strata = NULL, variables = NULL, fpc = NULL, nest = FALSE, check_strata = !nest, weights = NULL, pps = FALSE, variance = c("HT", "YG"), ... )
.data |
A data frame (which contains the variables specified below) |
... |
ignored |
ids |
Variables specifying cluster ids from largest level to smallest level (leaving the argument empty, NULL, 1, or 0 indicate no clusters). |
probs |
Variables specifying cluster sampling probabilities. |
strata |
Variables specifying strata. |
variables |
Variables specifying variables to be included in survey. Defaults to all variables in .data |
fpc |
Variables specifying a finite population correct, see
|
nest |
If |
check_strata |
If |
weights |
Variables specifying weights (inverse of probability). |
pps |
"brewer" to use Brewer's approximation for PPS sampling without replacement. "overton" to use Overton's approximation. An object of class HR to use the Hartley-Rao approximation. An object of class ppsmat to use the Horvitz-Thompson estimator. |
variance |
For pps without replacement, use variance="YG" for the Yates-Grundy estimator instead of the Horvitz-Thompson estimator |
If provided a data.frame, it is a wrapper
around svydesign
. All survey variables must be included
in the data.frame itself. Variables are selected by using bare column names, or
convenience functions described in select
.
If provided a survey.design2
object from the survey package,
it will turn it into a srvyr object, so that srvyr functions will work with it
An object of class tbl_svy
# Examples from ?survey::svydesign library(survey) data(api) # stratified sample dstrata <- apistrat %>% as_survey_design(strata = stype, weights = pw) # one-stage cluster sample dclus1 <- apiclus1 %>% as_survey_design(dnum, weights = pw, fpc = fpc) # two-stage cluster sample: weights computed from population sizes. dclus2 <- apiclus2 %>% as_survey_design(c(dnum, snum), fpc = c(fpc1, fpc2)) ## multistage sampling has no effect when fpc is not given, so ## these are equivalent. dclus2wr <- apiclus2 %>% dplyr::mutate(weights = weights(dclus2)) %>% as_survey_design(c(dnum, snum), weights = weights) dclus2wr2 <- apiclus2 %>% dplyr::mutate(weights = weights(dclus2)) %>% as_survey_design(c(dnum), weights = weights) ## syntax for stratified cluster sample ## (though the data weren't really sampled this way) apistrat %>% as_survey_design(dnum, strata = stype, weights = pw, nest = TRUE) ## PPS sampling without replacement data(election) dpps <- election_pps %>% as_survey_design(fpc = p, pps = "brewer") # dplyr 0.7 introduced new style of NSE called quosures # See `vignette("programming", package = "dplyr")` for details st <- quo(stype) wt <- quo(pw) dstrata <- apistrat %>% as_survey_design(strata = !!st, weights = !!wt)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.