easyRasch
NOTE: This function is borrowed from https://github.com/melissagwolf/dynamic/blob/master/R/RelRep.R,
commit: https://github.com/melissagwolf/dynamic/commit/d31d103ece10d3c62f87fe413e5a1253b81e1286.
See the paper by McNeish & Dumas (2025), full reference below, for details.
This function evaluates how well a reliability summary index like alpha or omega represents the conditional reliability of a distribution of composite scores. It compares the conditional reliability function to a summary index and outputs a representativeness plot, a table of representativeness indices,and the full conditional reliability table for each possible sum score.
Authors of this function: Daniel McNeish & Denis Dumas
Arguments
- data
The original data to which the model was applied.
- items
Column names of the items on the scale being evaluated (entered as strings). If omitted, all variables in the data will be used.
- rel
Reliability coefficient to analyze. Options are "alpha" (the default) or "omega".
- missing
The missing data indicator in the data. Not needed in R, only present to simply use of this function in a Shiny application.
- method
how the test interval is created. Options are "CI" (the default), "width", or "raw". "CI" uses a 95% Bayesian highest posterior density credible interval. "width" builds an interval using a predetermined relative distance from the reliability coefficient (e.g., .05 from alpha). "raw" builds an interval using a predetermined raw values (e.g., .70 to .90)
- width
Only required if method="width". Specifies a predetermined relative distance from the coefficient to each bound of the interval. The total width of the interval will be twice this value (e.g., if .05 is entered, the total interval width is .10 because it will span .05 above the coefficient and .05 below the coefficient)
- raw.low
Only required if method="raw". Manually specifies the lower bound of the test interval. Must be between 0 and 1.
- raw.high
Only required if method="raw". Manually specifies the upper bound of the test interval. Must be between 0 and 1.
References
McNeish, D., & Dumas, D. (2025). Reliability representativeness: How well does coefficient alpha summarize reliability across the score distribution? Behavior Research Methods, 57(3), 93. doi:10.3758/s13428-025-02611-8