<<<<<<< HEAD
# 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)
>>>>>>> e14f0047c239a8e0a6d91bbe41090564f2e6b37b
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