powRICLPM
is an R
package that performs a power analysis for the
random intercept cross-lagged panel model (RI-CLPM) in a simple and
user-friendly way. It implements the strategy as proposed by Mulder
(2022). Its main
functionalities include:
- Setting up and performing a basic power analysis: Obtain the power to reject the null-hypothesis of no effect (as well as other performance measures, such as bias, mean square error, etc.) for all parameters in the RI-CLPM given a specific sample size, number of repeated measures, and proportion of between-unit variance (among other things). The power analysis can be performed across multiple experimental conditions simultaneously (i.e., with varying numbers of repeated measures, proportions of between-unit variance, etc.).
- Extending the basic power analysis setup: Extend the basic power analysis to include the use of bounded estimation, various (stationarity) constraints over time on parameters of the estimation model, and/or the estimation of measurement error.
- Create Mplus model syntax: Create syntax for performing RI-CLPM power analyses using Mplus.
There are four sources of documentation for powRICLPM
:
- The rationale for the power analysis strategy underlying this package can be found in Mulder (2022).
- Every user-facing function in the package is documented, and the
documentation can be accessed by running
?function_name
in the R console (e.g.,?powRICLPM
). Here, you can find explanations on how to use the functions, as well as technical details. - There are four main vignettes accessible via the ‘Vignettes’ tab,
describing functionalities and analysis options of this package more
generally. The ‘Example’ vignette serves as the online supplementary
material to Mulder
(2022), and contains
the R code for an illustrative example using the
powRICLPM
package. - The FAQ contains answers to frequently asked question that reach me via email.
To install the development version of powRICLPM
, including the latest
bug fixes and new features, run:
install.packages("devtools")
devtools::install_github("jeroendmulder/powRICLPM")
To install the latest release of powRICLPM
from CRAN, run:
install.packages("powRICLPM")
You can cite the R-package with the following citation:
Mulder, J.D., (2022). Power analysis for the random intercept cross-lagged panel model using the powRICLPM R-package. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2022.2122467
If you have ideas, comments, or issues you would like to raise, please get in touch.
- Issues and ideas can be raised on GitHub via https://github.com/jeroendmulder/powRICLPM
- Pull request can be created on GitHub via https://github.com/jeroendmulder/powRICLPM/pulls