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powRICLPM
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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]
[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.
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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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