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