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

Example

In this example using the built-in to prcr dataset pisaUSA15. Specifically, we use composite variables for broad interest, enjoyment, instrumental motivation, and self-efficacy. More information on these and other items can be found at this link.

devtools::load_all(".")
library(prcr)
df <- pisaUSA15
m3 <- create_profiles_cluster(df, broad_interest, enjoyment, instrumental_mot, self_efficacy, n_profiles = 3)
plot_profiles(m3, to_center = TRUE)

Other functions include those for carrying out comparing r-squared values and perfomring cross-validation. These are documented in the CRAN release and their versions in the in-development version will be documented prior to the CRAN release.



Try the prcr package in your browser

Any scripts or data that you put into this service are public.

prcr documentation built on Feb. 9, 2020, 5:08 p.m.