powRICLPM
powRICLPM
is an R package that aids researchers with performing a
power analysis for the random intercept cross-lagged panel model
(RI-CLPM) by Hamaker, Kuiper, and Grasman (2015), and the Stable Trait
Autoregressive Trait State Model (STARTS) by Kenny and Zautra (1995) and
Kenny and Zautra (2001). It implements the strategy as proposed by
Mulder (2023). Its main functionalities include:
- Basic power
analysis:
Use Monte Carlo simulations to compute the power to reject the
null-hypothesis (as well as other performance measures such as bias,
mean square error) for all parameters in the RI-CLPM and STARTS, for a
specific experimental condition. A condition is defined by its sample
size, number of repeated measures, proportion of between-unit
variance, and reliability of the indicators.
powRICLPM
can perform
power analyses across multiple experimental conditions simultaneously,
and report the results back in a user-friendly manner.
- Extensions:
The basic power analysis setup can be extended to include the use of
bounded estimation, various (stationarity) constraints over time on
parameters of the estimation model, the generation of nonnormal data,
among other things.
- Mplus:
When Mplus is installed,
powRICLPM
can create Mplus syntax, and run
the power analyses in 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 (2023).
- 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.
- More elaborate descriptions of this package’s functionality and
analysis options are described in vignettes. These are accessible via
the ‘Vignettes’ tab in the menu, or via R using
vignette(package = "powRICLPM")
.
- 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., (2023). Power analysis for the random intercept
cross-lagged panel model using the powRICLPM R-package. Structural
Equation Modeling: A Multidisciplinary Journal, 30(4), 645-658.
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.
References
<div id="refs" class="references csl-bib-body hanging-indent"
entry-spacing="0">
Hamaker, Ellen L., Rebecca M. Kuiper, and Raoul P. P. P. Grasman. 2015.
“A critique of the cross-lagged panel
model.” *Psychological Methods* 20 (1): 102–16.
.
Kenny, David A., and Alex Zautra. 1995. “The
trait-state-error model for multiwave data.” *Journal of
Consulting and Clinical Psychology1* 63 (1): 52–59.
———. 2001. “Trait–state models for longitudinal
data.” In *New Methods for the Analysis of Change*, 243–63.
Washington: American Psychological Association.
.
Mulder, Jeroen D. 2023. “Power Analysis for the Random Intercept
Cross-Lagged Panel Model Using the powRICLPM r-Package.” *Structural
Equation Modeling: A Multidisciplinary Journal* 30 (4): 645–58.
.