Package: prcr 0.2.1

Joshua M Rosenberg

prcr: Person-Centered Analysis

Provides an easy-to-use yet adaptable set of tools to conduct person-center analysis using a two-step clustering procedure. As described in Bergman and El-Khouri (1999) <doi:10.1002/(SICI)1521-4036(199910)41:6%3C753::AID-BIMJ753%3E3.0.CO;2-K>, hierarchical clustering is performed to determine the initial partition for the subsequent k-means clustering procedure.

Authors:Joshua M Rosenberg [aut, cre], Jennifer A Schmidt [aut], Patrick N Beymer [aut], Rebecca R Steingut [ctb]

prcr_0.2.1.tar.gz
prcr_0.2.1.zip(r-4.7-any)prcr_0.2.1.zip(r-4.6-any)prcr_0.2.1.zip(r-4.5-any)
prcr_0.2.1.tgz(r-4.6-any)prcr_0.2.1.tgz(r-4.5-any)
prcr_0.2.1.tar.gz(r-4.7-any)prcr_0.2.1.tar.gz(r-4.6-any)
prcr_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
prcr/json (API)

# Install 'prcr' in R:

install.packages('prcr', repos = c('https://jrosen48.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jrosen48/prcr/issues

Datasets:

pisaUSA15 - Student questionnaire data with four variables from the 2015 PISA for students in the United States

On CRAN:

4.63 score 5 stars 17 scripts 439 downloads 4 exports 33 dependencies

Last updated from:95db5c839d. Checks:7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel	WARNING	148
source / vignettes	OK	199
linux-release	WARNING	150
macos-release	WARNING	210
macos-oldrel	WARNING	214
windows-devel	WARNING	106
windows-release	WARNING	91
windows-oldrel	WARNING	80
wasm-release	OK	110

Exports:create_profiles_cluster detect_outliers estimate_r_squared plot_profiles

Dependencies:class cli cpp11 dplyr farver forcats generics ggplot2 glue gtable irr isoband labeling lifecycle lpSolve magrittr pillar pkgconfig purrr R6 RColorBrewer rlang S7 scales stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

Introduction to use of prcr for carrying a out two-step cluster analysis

Example

Rendered fromintroduction_to_prcr.Rmdusingknitr::rmarkdown

Last update: 2017-10-28
Started: 2017-02-15

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Create profiles of observed variables using two-step cluster analysis	create_profiles_cluster
Identifies potential outliers	detect_outliers
Estimates R^2 (r-squared) values for a range of number of profiles	estimate_r_squared
student questionnaire data with four variables from the 2015 PISA for students in the United States	pisaUSA15
Return plot of profile centroids	plot_profiles
Prints details of prcr cluster solution	print.prcr
Concise summary of prcr cluster solution	summary.prcr