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silp  

Conditional Process Analysis (CPA) via SEM Approach
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("silp", "1.0.3")



Attach the package and use:
library("silp")
Maintained by
Yi-Hsuan Tseng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-08-23
Latest Update: 2025-04-06
Description:
Provides Reliability-Adjusted Product Indicator (RAPI) method to estimate effects among latent variables, thus allowing for more precise definition and analysis of mediation and moderation models. Our simulation studies reveal that while 'silp' may exhibit instability with smaller sample sizes and lower reliability scores (e.g., N = 100, omega = 0.7), implementing nearest positive definite matrix correction and bootstrap confidence interval estimation can significantly ameliorate this volatility. When these adjustments are applied, 'silp' achieves estimations akin in quality to those derived from latent moderated structural equations (LMS). In conclusion, the 'silp' package is a valuable tool for researchers seeking to explore complex relational structures between variables without resorting to commercial software. Hsiao et al.(2018)<doi:10.1177/0013164416679877> Kline & Moosbrugger(2000)<doi:10.1007/BF02296338> Cheung et al.(2021)<doi:10.1007/s10869-020-09717-0>.
How to cite:
Yi-Hsuan Tseng (2024). silp: Conditional Process Analysis (CPA) via SEM Approach. R package version 1.0.3, https://cran.r-project.org/web/packages/silp. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:04), 1.0.0 (2024-08-23 12:00), 1.0.1 (2025-03-11 14:10), 1.0.2 (2025-04-02 12:40)
Other packages that cited silp R package
View silp citation profile
Other R packages that silp depends, imports, suggests or enhances
Complete documentation for silp
Functions, R codes and Examples using the silp R package
Full silp package functions and examples
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