svrep 0.3.0

• Added helper function as_data_frame_with_weights() to convert
  a survey design object into a data frame with columns of
  weights (full-sample weights and, if applicable, replicate weights).
  This is useful for saving data and weights to a data file.

• Added by argument to summarize_rep_weights() which allows
  the specification of one or more grouping variables to use for summaries
  (e.g. by = c('stratum', 'response_status') can be used to summarize by
  response status within each stratum).

• Added a small vignette "Nonresponse Adjustments" to illustrate how to
  conduct nonresponse adjustments using redistribute_weights().

• Minor Updates and Bug Fixes:

  • Internal code update to avoid annoying but harmless warning message
    about rho in calibrate_to_estimate().
  • Bug fix for stack_replicate_designs() where designs created with
    as.svrepdesign(..., type = 'mrbbootstrap')
    or as.svrepdesign(..., type = 'subbootstrap') threw an error.

v0.2.0

svrep 0.2.0

• Added functions calibrate_to_estimate() and calibrate_to_sample()
  for calibrating to estimated control totals with methods
  that account for the sampling variance of the control totals.
  For an overview of these functions, please see the new vignette
  "Calibrating to Estimated Control Totals".

  • The function calibrate_to_estimate() requires the user
    to supply a vector of control totals and its variance-covariance matrix.
    The function applies Fuller's proposed adjustments to the replicate weights,
    in which control totals are varied across replicates by perturbing the control
    totals using a spectral decomposition of the control totals'
    variance-covariance matrix.

  • The function calibrate_to_sample() requires the user to supply
    a replicate design for the primary survey of interest as well as a replicate
    design for the control survey used to estimate control totals for calibration.
    The function applies Opsomer & Erciulescu's method of varying
    the control totals across replicates of the primary survey by matching each
    primary survey replicate to a replicate from the control survey.

• Added an example dataset, lou_vax_survey, which is a simulated survey
  measuring Covid-19 vaccination status and a handful of demographic variables,
  based on a simple random sample of 1,000 residents of Louisville, Kentucky
  with an approximately 50% response rate.

  • An accompanying dataset lou_pums_microdata provides person-level microdata
    from the American Community Survey (ACS) 2015-2019 public-use microdata sample
    (PUMS) data for Louisville, KY. The dataset lou_pums_microdata includes
    replicate weights to use for variance estimation and can be used to generate
    control totals for lou_vax_survey.

svrep 0.1.0

• Initial release of the package on CRAN.