Package: sitepickR
Type: Package
Title: Two-Level Sample Selection with Optimal Site Replacement
Version: 0.0.1
Date: 2022-11-29
Authors@R: c(
    person("Elena", "Badillo-Goicoechea", , "egoicoe1@jhu.edu", role = c("aut", "cre"),
           comment = c(ORCID = "")),
    person("Robert", "Olsen", , "robolsen@gwu.edu", role = "aut",
           comment = c(ORCID = "")),
    person("Elizabeth", "Stuart", , "estuart1@jhu.edu",role = "aut",
           comment = c(ORCID = ""))
  )
Description: Carries out a two-level sample selection where the possibility of an initially selected site not wanting to participate is anticipated, and the site is optimally replaced. The procedure aims to reduce bias (and/or loss of external validity) with respect to the target population. In selecting units and sub-units, 'sitepickR' uses the cube method developed by 'Deville & Tillé', (2004) <http://www.math.helsinki.fi/msm/banocoss/Deville_Tille_2004.pdf> and described in Tillé (2011) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2011002/article/11609-eng.pdf?st=5-sx8Q8n>. The cube method is a probability sampling method that is designed to satisfy criteria for balance between the sample and the population. Recent research has shown that this method performs well in simulations for studies of educational programs (see Fay & Olsen (2021, under review). To implement the cube method, 'sitepickR' uses the sampling R package <https://cran.r-project.org/package=sampling>. To implement statistical matching, 'sitepickR' uses the 'MatchIt' R package <https://cran.r-project.org/package=MatchIt>.
Imports: MatchIt, sampling, dplyr, ggplot2, reshape2, data.table,
        stats, stringr, tidyr, magrittr, tidyselect, scales
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.2
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, devtools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-12-04 00:22:21 UTC; r1707404
Author: Elena Badillo-Goicoechea [aut, cre],
  Robert Olsen [aut],
  Elizabeth Stuart [aut]
Maintainer: Elena Badillo-Goicoechea <egoicoe1@jhu.edu>
Repository: CRAN
Date/Publication: 2022-12-05 11:00:02 UTC
Built: R 4.2.0; ; 2023-07-11 01:37:06 UTC; unix
