demo/modelr-ecsi.R

In ISS-Analytics/modelr: Natural, friendly, domain-specific language for building PLS structural equation models

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# This example recreates the ECSI model on mobile users found at:
#  https://cran.r-project.org/web/packages/semPLS/vignettes/semPLS-intro.pdf

library(modelr)

# modelr syntax for creating measurement model
mobi_mm <- measure(
  reflect("Image",        multi_items("IMAG", 1:5)),
  reflect("Expectation",  multi_items("CUEX", 1:3)),
  reflect("Quality",      multi_items("PERQ", 1:7)),
  reflect("Value",        multi_items("PERV", 1:2)),
  reflect("Satisfaction", multi_items("CUSA", 1:3)),
  reflect("Complaints",   single_item("CUSCO")),
  reflect("Loyalty",      multi_items("CUSL", 1:3))
)

# modelr syntax for creating structural model
# - note, three ways to represent the structure
mobi_sm <- structure(
  paths(from = "Image",        to = c("Expectation", "Satisfaction", "Loyalty")),
  paths(from = "Expectation",  to = c("Quality", "Value", "Satisfaction")),
  paths(from = "Quality",      to = c("Value", "Satisfaction")),
  paths(from = "Value",        to = c("Satisfaction")),
  paths(from = "Satisfaction", to = c("Complaints", "Loyalty")),
  paths(from = "Complaints",   to = "Loyalty")
)

# Regular semPLS functions to create and estimate model, and report estimates
data("mobi")

mobi_pls <- modelr(data = mobi,
                   measurement_model = mobi_mm,
                   structural_model = mobi_sm)

print_paths(mobi_pls)
plot_scores(mobi_pls)
=======
# This example recreates the ECSI model on mobile users found at:
#  https://cran.r-project.org/web/packages/semPLS/vignettes/semPLS-intro.pdf

library(modelr)

# modelr syntax for creating measurement model
mobi_mm <- measure(
  reflect("Image",        multi_items("IMAG", 1:5)),
  reflect("Expectation",  multi_items("CUEX", 1:3)),
  reflect("Quality",      multi_items("PERQ", 1:7)),
  reflect("Value",        multi_items("PERV", 1:2)),
  reflect("Satisfaction", multi_items("CUSA", 1:3)),
  reflect("Complaints",   single_item("CUSCO")),
  reflect("Loyalty",      multi_items("CUSL", 1:3))
)

# modelr syntax for creating structural model
# - note, three ways to represent the structure
mobi_sm <- structure(
  paths(from = "Image",        to = c("Expectation", "Satisfaction", "Loyalty")),
  paths(from = "Expectation",  to = c("Quality", "Value", "Satisfaction")),
  paths(from = "Quality",      to = c("Value", "Satisfaction")),
  paths(from = "Value",        to = c("Satisfaction")),
  paths(from = "Satisfaction", to = c("Complaints", "Loyalty")),
  paths(from = "Complaints",   to = "Loyalty")
)

# Regular semPLS functions to create andestimate model, and report estimates
data("mobi", package = "semPLS")

mobi_pls <- modelr(data = mobi,
                   measurement_model = mobi_mm,
                   structural_model = mobi_sm)

print_paths(mobi_pls)
plot_scores(mobi_pls)
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