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powRICLPM  

Perform Power Analysis for the RI-CLPM and STARTS Model
View on CRAN: Click here


Download and install powRICLPM package within the R console
Install from CRAN:
install.packages("powRICLPM")

Install from Github:
library("remotes")
install_github("cran/powRICLPM")

Install by package version:
library("remotes")
install_version("powRICLPM", "0.2.1")



Attach the package and use:
library("powRICLPM")
Maintained by
Jeroen Mulder
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-07
Latest Update: 2023-02-07
Description:
Perform user-friendly power analyses for the bivariate random intercept cross-lagged panel model (RI-CLPM). The strategy as proposed by Mulder (2022) is implemented. Extended power analysis options include the use of bounded estimation, inclusion of measurement error in the data generating model and estimation model (i.e., the stable trait autoregressive trait state, STARTS, model), imposing various constraints over time on the parameters of the estimation model, among others.
How to cite:
Jeroen Mulder (2022). powRICLPM: Perform Power Analysis for the RI-CLPM and STARTS Model. R package version 0.2.1, https://cran.r-project.org/web/packages/powRICLPM. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.0 (2022-10-07 18:00), 0.1.1 (2023-02-07 17:12), 0.2.0 (2024-09-25 14:40)
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Other R packages that powRICLPM depends, imports, suggests or enhances
Complete documentation for powRICLPM
Functions, R codes and Examples using the powRICLPM R package
Some associated functions: check_Phi . give . plot.powRICLPM . powRICLPM . powRICLPM_Mplus . print.powRICLPM . summary.powRICLPM . 
Some associated R codes: Mplus.R . bootstrap-uncertainty.R . check-give.R . check-plot.R . check-summary.R . check.R . give.R . lavaan.R . parameters.R . plot.R . population-values.R . powRICLPM.R . print.R . run.R . setup.R . summary.R . user-help.R . zzz.R .  Full powRICLPM package functions and examples
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