Reliable Change Index (RCI) is a concept in measurement and assessment. The statistic addresses two concerns: (1) For a given client, is the change in scores on a specific psychometric instrument across 2 measurement points reliable; and (2) Is the extent of change large enough such that it is clinically significant? The rci package provides a convenient solution to RCI computations. The package includes the various RCI formulas available in the academic literature.
To install the development version, you need to run the following code:
devtools::install_github("dtyk/rci")
The rci function takes in four arguments: (1) a data frame, (2) column containing pre-test scores, (3) column containing post-test scores, and (4) the RCI formula to be used. If no formula is provided, the Jacobson & Truax (1991) formula will be used.
The formulas are:
| Formula | Article | Description |
|---|---|---|
| JT | Jacobson & Truax, 1991 | The standard error of measurement of the difference score, when variances are equal |
| CM | Christensen & Mendoza, 1986 | The standard deviation of difference scores |
| I | Iverson et al., 2003 | The standard error of measurement of the difference score |
| L | Lewis et al., 2007 | The within-subjects standard deviation |
| M | McSweeney et al., 1993 | The standard deviation of the least-squares regression residuals |