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
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prcr.pdf |prcr.html✨
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:

4.65 score 5 stars 18 scripts 547 downloads 4 exports 40 dependencies

Last updated 5 years agofrom:95db5c839d. Checks:OK: 1 WARNING: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 14 2024
R-4.5-win	WARNING	Nov 14 2024
R-4.5-linux	WARNING	Nov 14 2024
R-4.4-win	WARNING	Nov 14 2024
R-4.4-mac	WARNING	Nov 14 2024
R-4.3-win	WARNING	Nov 14 2024
R-4.3-mac	WARNING	Nov 14 2024

Exports:create_profiles_cluster detect_outliers estimate_r_squared plot_profiles

Dependencies:class cli colorspace cpp11 dplyr fansi farver forcats generics ggplot2 glue gtable irr isoband labeling lattice lifecycle lpSolve magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig purrr R6 RColorBrewer rlang scales stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

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

Joshua Rosenberg

Rendered fromintroduction_to_prcr.Rmdusingknitr::rmarkdownon Nov 14 2024.

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