plspmox: PLS Path Model of a node from a PATHMOX or TECHMOX tree

In gastonstat/pathmox: Pathmox Approach of Segmentation Trees in Partial Least Squares Path Modeling

Description

Calculates a PLS Path Model on a selected node from a pathmox or techmox tree

Usage

  plspmox(pls, treemox, X = NULL, node, boot.val = FALSE,
    br = NULL, dataset = FALSE)

Arguments

pls	An object of class "plspm"
treemox	An object of class "treemox"
X	Optional argument for data table
node	An integer value indicating the number of the node. Must be an integer larger than 1.
boot.val	A logical value indicating whether bootstrap validation is performed (FALSE by default).
br	An integer indicating the number bootstrap resamples. Used only when boot.val=TRUE.
dataset	A logical value indicating whether the data matrix should be included in the list of results (FALSE by default).

Details

Performs a PLS-PM analysis with the elements contained in node, by calling the function plspm. The rest of the parameters to perform the PLS-PM analysis (i.e. inner, outer, modes, scheme, scaled, tol, iter) are inherited from the object in argument pls.
When the object pls does not contain a data matrix (i.e. pls$data=NULL), the user must provide the data matrix or data frame in X.

Value

An object of class "plspm"

Author(s)

Gaston Sanchez

See Also

See Also as plspm, pathmox

Examples

## Not run: 
 ## example of PLS-PM in customer satisfaction analysis
 ## model with seven LVs and reflective indicators
 data(csimobile)

 # select manifest variables
 data_mobile = csimobile[,8:33]

 # define path matrix (inner model)
 IMAG = c(0, 0, 0, 0, 0, 0, 0)
 EXPE = c(1, 0, 0, 0, 0, 0, 0)
 QUAL = c(0, 1, 0, 0, 0, 0, 0)
 VAL = c(0, 1, 1, 0, 0, 0, 0)
 SAT = c(1, 1, 1, 1, 0, 0, 0)
 COM = c(0, 0, 0, 0, 1, 0, 0)
 LOY = c(1, 0, 0, 0, 1, 1, 0)
 mob_path = rbind(IMAG, EXPE, QUAL, VAL, SAT, COM, LOY)

 # blocks of indicators (outer model)
 mob_blocks = list(1:5, 6:9, 10:15, 16:18, 19:21, 22:24, 25:26)
 mob_modes = rep("A", 7)

 # apply plspm
 mob_pls = plspm(data_mobile, mob_path, mob_blocks,
                 modes = mob_modes, scheme="factor", scaled=FALSE)

 # re-ordering those segmentation variables with ordinal scale (Age and Education)
 csimobile$Education = factor(csimobile$Education,
     levels=c("basic","highschool","university"),
     ordered=TRUE)

 # select the segmentation variables
 seg_vars = csimobile[,1:7]

 # Pathmox Analysis
 mob_pathmox = pathmox(mob_pls, seg_vars, signif=.10, size=.10, deep=2)

 # get PLS-PM of nodes 2 and 3
 node2 = plspmox(mob_pls, mob_pathmox, node=2)
 node3 = plspmox(mob_pls, mob_pathmox, node=3)
 
## End(Not run)

gastonstat/pathmox documentation built on May 16, 2019, 5:46 p.m.