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plspm (version 0.5.1)

Partial Least Squares Path Modeling (PLS-PM)

Description

Partial Least Squares Path Modeling (PLS-PM), Tenenhaus, Esposito Vinzi, Chatelin, Lauro (2005) , analysis for both metric and non-metric data, as well as REBUS analysis, Esposito Vinzi, Trinchera, Squillacciotti, and Tenenhaus (2008) .

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Install

install.packages('plspm')

Monthly Downloads

2,150

Version

0.5.1

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/gastonstat/plspm

Maintainer

Frederic Bertrand

Last Published

January 23rd, 2024

Functions in plspm (0.5.1)

Check arguments for plspm and plspm.fit

Check tolerance threshold

Check maximum number of iterations

Check congruence between inner and outer models

Check specifications of PLS-PM algorithm

Cronbach's alpha

Non-Metric Dummy

Dummy matrices for categorical manifest variables

Calculate AVE (Average Variance Extracted)

Internal PLS regression (full data)

Check types of measurement scales and metric

Get data frame with bootstrap statistics

Internal PLS regression with missing values

Check path matrix

Arizona vegetation dataset

Check vector of PLS components (for non-metric plspm)

College datasets

Futbol dataset from Spain-England-Italy

get_locals_test

Local groups comparison test

Building data matrix with manifest variables

Dummy by Giorgio

Iterative steps of Response-Based Unit Segmentation (REBUS)

Presence of missing values

Rank of a non-metric variable

get_inner_summary

Inner summary assessment

Goodness-of-fit for plspm

Performs bootstrap validation in plspm

get_data_scaled

Scaling data outside plspm

Calculate Cronbach's alpha

get_PLSRdoubleQ

get_PLSRdoubleQ

Path coefficient effects for plspm

get_path_scheme

Calculate inner weighting path scheme

Non-Metric Ordinal Scale

Group Quality Index

Get general parameters

Spanish football dataset

Simulated data for REBUS with two groups

Two Groups Comparison in PLS-PM

Basic results for Partial Least Squares Path Modeling

PLS-PM for global and local models

Calculate path coefficients for plspm

Russett dataset

PLS regression for plspm

ECSI Mobile Phone Provider dataset

Calculate Dillon-Goldstein's rho

Non-Metric Numerical Scale

Non-Metric Nominal Scale

Type of metric based on scaling measurement

Orange Juice dataset

Satisfaction dataset

Transform factors in MV into numeric

Calculate Latent Variable Scores

Unidimensionality of reflective blocks

Plot inner model

get_weights_nonmetric

Outer Weights Non-Metric Data

Dillon-Goldstein's rho

Rescale Latent Variable Scores

Technology data set

get_treated_data

Apply corresponding treatment to MV

Offense dataset

Normalize a vector

Test Data Set Availibility

Plot outer model

Plots for PLS Path Models

Permutation Test for REBUS Multi-Group Comparison

PLS-PM: Partial Least Squares Path Modeling

test_null_weights

Test outer weights convergence within specified maxiter

Unidimensionality of blocks

test_manifest_scaling

Test scaling of selected manifest variables

Test presence of factors

Clustering on communality and structural residuals

Response Based Unit Segmentation (REBUS)

Quantification Plot

Check well defined blocks

Check bootstrap options