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.

## Documentation

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.

## Installation

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")

## Citing 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

## Contact

If you have ideas, comments, or issues you would like to raise, please get in touch.