pathmox (version 0.2.0)

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

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).

Value

An object of class "plspm"

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.

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)