Predictive Information Index (PII): Quantifying predictive utility of scores
The piiR
package provides tools for computing the Predictive Information Index (PII), which evaluates how much outcome-relevant information is retained in various types of scores (e.g., sum scores, CFA scores, subscale scores) in predictive models.
```r
remotes::install_github("TheotherDrWells/piiR")
install.packages("piiR")
library(piiR)
set.seed(123) full <- rnorm(100) score <- full + rnorm(100, sd = 0.5)
pii(full, score, type = "rm")
pii(full, score, type = "r2")
📘 Learn More Vignette: vignette("piiR_intro")
Docs: CRAN page (once available)
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