Deprecated SE versions of main srvyr verbs

srvyr has updated it's standard evaluation semantics to match dplyr 0.7, so these underscore functions are no longer required (but are still supported for backward compatibility reasons). See se-deprecated or the dplyr vignette on programming (vignette("programming", package = "dplyr")) for more details.

Usage

as_survey_(.data, ...)

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")
)

as_survey_rep_(
  .data,
  variables = NULL,
  repweights = NULL,
  weights = NULL,
  type = c("BRR", "Fay", "JK1", "JKn", "bootstrap", "successive-difference", "ACS",
    "other"),
  combined_weights = TRUE,
  rho = NULL,
  bootstrap_average = NULL,
  scale = NULL,
  rscales = NULL,
  fpc = NULL,
  fpctype = c("fraction", "correction"),
  mse = getOption("survey.replicates.mse")
)

as_survey_twophase_(
  .data,
  id,
  strata = NULL,
  probs = NULL,
  weights = NULL,
  fpc = NULL,
  subset,
  method = c("full", "approx", "simple")
)

cascade_(.data, ..., .dots, .fill = NA)

Arguments

.data

a data.frame or an object from the survey package

...

other arguments, see other functions for details

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

repweights

Variables specifying the replication weight variables

type

Type of replication weights

combined_weights

TRUE if the repweights already include the sampling weights. This is usually the case.

rho

Shrinkage factor for weights in Fay's method

bootstrap_average

For type = "bootstrap", if the bootstrap weights have been averaged, gives the number of iterations averaged over.

scale, rscales

Scaling constant for variance, see svrepdesign for more information.

fpctype

Finite population correction information

mse

if TRUE, compute variances based on sum of squares around the point estimate, rather than the mean of the replicates

id

list of two sets of variable names for sampling unit identifiers

subset

bare name of a variable which specifies which observations are selected in phase 2

method

"full" requires (much) more memory, but gives unbiased variance estimates for general multistage designs at both phases. "simple" or "approx" use less memory, and is correct for designs with simple random sampling at phase one and stratified randoms sampling at phase two. See twophase for more details.

.dots

Used to work around non-standard evaluation. See vignette("nse", package = "dplyr") for details.

.fill

Value to fill in for group summaries