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The aim of IPV is to handily create item pool visualizations, asintroduced in:Dantlgraber, M., Stieger, S., & Reips, U. D. (2019).Introducing Item Pool Visualization: A method for investigation ofconcepts in self-reports and psychometric tests. MethodologicalInnovations, 12(3), 2059799119884283.
You can install the released version of IPV fromCRAN by calling:
install.packages("IPV")And the development version fromGitHub bycalling:
# install.packages("devtools")devtools::install_github("NilsPetras/IPV")
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 datax<- 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 appearanceFor further introduction, please check out the vignette.
browseVignettes("IPV")#> No vignettes found by browseVignettes("IPV")
When using item pool visualization, please cite:
Dantlgraber, M., Stieger, S., & Reips, U. D. (2019). Introducing ItemPool Visualization: A method for investigation of concepts inself-reports and psychometric tests. Methodological Innovations, 12(3),2059799119884283.
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Item Pool Visualization: A new way of factor structure visualization
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