as_survey_design: Create a tbl_svy survey object using sampling design

In srvyr: 'dplyr'-Like Syntax for Summary Statistics of Survey Data

Create a tbl_svy survey object using sampling design

Description

Create a survey object with a survey design.

Usage

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"),
  ...
)

Arguments

.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 svydesign for more details.
nest	If TRUE, relabel cluster ids to enforce nesting within strata.
check_strata	If TRUE, check that clusters are nested in strata.
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

Details

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

Value

An object of class tbl_svy

Examples

# 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)

srvyr documentation built on Sept. 11, 2024, 8:43 p.m.