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qcpm
View on CRAN: Click
here
Download and install qcpm package within the R console
Install from CRAN:
install.packages("qcpm")
Install from Github:
library("remotes")
install_github("cran/qcpm")
Install by package version:
library("remotes")
install_version("qcpm", "0.4")
Attach the package and use:
library("qcpm")
Maintained by
Giuseppe Lamberti
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-24
Latest Update: 2024-02-02
Description:
Implements the Quantile Composite-based Path Modeling approach
(Davino and Vinzi, 2016 ;
Dolce et al., 2021 ). The method complements the traditional PLS Path Modeling approach, analyzing the entire distribution of outcome variables and, therefore, overcoming the classical exploration of only average effects. It exploits quantile regression to investigate changes in the relationships among constructs and between constructs and observed variables.
How to cite:
Giuseppe Lamberti (2022). qcpm: Quantile Composite Path Modeling. R package version 0.4, https://cran.r-project.org/web/packages/qcpm. Accessed 29 Apr. 2025.
Previous versions and publish date:
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Other R packages that qcpm depends,
imports, suggests or enhances
Complete documentation for qcpm
Functions, R codes and Examples using
the qcpm R package
Some associated functions: assessment . boot . get_checks . get_communality . get_element . get_info . get_internal_parameter_estimation . get_loadings . get_names_MV . get_paths . province . qc . qcpm . reliability .
Some associated R codes: 01_province_data.R . 02_qcpm.R . 03_qcpm.summary.R . 04_assessment.R . 05_boot.R . 06_print.qcpm.R . 06_reliability.R . get_checks.R . get_communality.R . get_element.R . get_info.R . get_internal_parameter_estimation.R . get_loadings.R . get_paths.R . get_qc.R . Full qcpm package functions and examples
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