bar_terminal {genpathmox}

Comparative plot for the Pathmox terminal nodes

Description

bar_terminal returns the path coefficient bar plots of the Pathmox terminal nodes.

Usage

bar_terminal(
  x,
  .LV,
  .bycoef = FALSE,
  .cex.names = 1,
  .cex.axis = 1.2,
  .cex.main = 1,
  ...
)

Arguments

x

An object of the class "plstree".

.LV

A string indicating the name of the dependent latent variable. The label must be the same as used to define the structural model in the (lavaan syntax).

.bycoef

Logical value indicating if the comparison is done by nodes or by path coefficients. By default, FALSE means that the comparison is done by nodes.

.cex.names

Expansion factor for axis names (bar labels).

.cex.axis

Expansion factor for numeric axis labels.

.cex.main

Allows fixing the size of the main. It is equal to 1 to default.

...

Further arguments are ignored.

Details

This function aims to visualize, using bar plots, the path coefficients of the dependnet latent construct associated with the terminal nodes. The user indicates the dependnet latent construct they want to visualize. This is done using the same label as used in the structural model definition (lavaan syntax). The comparison is done by analyzing the path coefficient values for each node, or the values estimated in each node for each path coefficient. In the former, the plot also returns the R^2. In the latter, the bar corresponding to the node with the highest path coefficient value shows in a different color. By default the comparison is done by analyzing the path coefficient values for each node.

Author(s)

Giuseppe Lamberti

References

Lamberti, G., Aluja, T. B., and Sanchez, G. (2016). The Pathmox approach for PLS path modeling segmentation. Applied Stochastic Models in Business and Industry, 32(4), 453-468. doi: 10.1002/asmb.2168

Lamberti, G. (2015). Modeling with Heterogeneity, PhD Dissertation.

Sanchez, G. (2009). PATHMOX Approach: Segmentation Trees in Partial Least Squares Path Modeling, PhD Dissertation.

See Also

summary.plstree, print.plstree, pls.pathmox, plot.plstree, and bar_impvar

Examples

 ## Not run: 
# Example of PATHMOX approach in customer satisfaction analysis 
# (Spanish financial company).
# Model with 5 LVs (4 common factor: Image (IMAG), Value (VAL), 
# Satisfaction (SAT), and Loyalty (LOY); and 1 composite construct: 
# Quality (QUAL)

# load library and dataset csibank
library(genpathmx)
data("csibank")

# Define the model using the lavaan syntax. Use a set of regression formulas to define 
# first the structural model and then the measurement model

CSImodel <- "
# Structural model
VAL  ~ QUAL
SAT  ~ IMAG  + QUAL + VAL
LOY  ~ IMAG + SAT

# Measurement model
# Composite
QUAL <~ qual1 + qual2 + qual3 + qual4 + qual5 + qual6 + qual7 
     
# Common factor
IMAG =~ imag1 + imag2 + imag3 + imag4 + imag5 + imag6 
VAL  =~ val1  + val2  + val3  + val4
SAT  =~ sat1  + sat2  + sat3           
LOY  =~ loy1  + loy2  + loy3           

"

# Run pathmox on one single variable 
age = csibank[,2]

# Transform age into an ordered factor
age = factor(age, levels = c("<=25", "26-35", "36-45", "46-55",
                                      "56-65", ">=66"),ordered = T)
                                     
csi.pathmox.age = pls.pathmox(
 .model = CSImodel ,
 .data  = csibank,
 .catvar= age,
 .alpha = 0.05,
 .deep = 1
)  

# Visualize the bar plot by comparing the nodes
bar_terminal(csi.pathmox.age, .LV = "SAT")

# Visualize the bar plot by comparing path coefficients
bar_terminal(csi.pathmox.age, .LV = "SAT", .bycoef = TRUE)


## End(Not run)