README.md

IPV

The aim of IPV is to handily create item pool visualizations, as introduced in: Dantlgraber, M., Stieger, S., & Reips, U. D. (2019). Introducing Item Pool Visualization: A method for investigation of concepts in self-reports and psychometric tests. Methodological Innovations, 12(3), 2059799119884283.

Installation

You can install the released version of IPV from CRAN by calling:

install.packages("IPV")

And the development version from GitHub by calling:

# install.packages("devtools")
devtools::install_github("NilsPetras/IPV")

Usage

This is an example how charts can be created:

library(IPV)

# Here, a toy example provided in the package is used.
# ?HEXACO

# estimate the underlying model from (clean) raw data
x <- ipv_est(HEXACO[ ,c(2:41, 122:161)], "HA")
#> Negative center distance adjusted to 0
#> Negative center distance adjusted to 0
#> Negative center distance adjusted to 0

# create a nested chart (one of three available chart types)
nested_chart(x$est)
#> Facet circle radius set to 0.204 based on the data.
#> cor_spacing set to 0.23 based on the data.
#> Relative scaling set to 2.1 based on the data.
#> Axis tick set to 0.2 based on the data.
#> dist_construct_label set to 0.333 based on the data.


# the next step would be to customize the appearance

For further introduction, please check out the vignette.

browseVignettes("IPV")
#> No vignettes found by browseVignettes("IPV")

Citation

When using item pool visualization, please cite:

Dantlgraber, M., Stieger, S., & Reips, U. D. (2019). Introducing Item Pool Visualization: A method for investigation of concepts in self-reports and psychometric tests. Methodological Innovations, 12(3), 2059799119884283.



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IPV documentation built on Sept. 30, 2022, 5:08 p.m.