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### Accompanying Code for:
## Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R - A Workbook (2021)
## Hair, J.F. (Jr), Hult, T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., and Ray, S.
## Chapter 8: Moderation analysis
# Load the SEMinR library
library(seminr)
# Load the data
corp_rep_data <- corp_rep_data
# Create measurement model ----
corp_rep_mm_mod <- constructs(
composite("QUAL", multi_items("qual_", 1:8), weights = mode_B),
composite("PERF", multi_items("perf_", 1:5), weights = mode_B),
composite("CSOR", multi_items("csor_", 1:5), weights = mode_B),
composite("ATTR", multi_items("attr_", 1:3), weights = mode_B),
composite("COMP", multi_items("comp_", 1:3)),
composite("LIKE", multi_items("like_", 1:3)),
composite("CUSA", single_item("cusa")),
composite("SC", multi_items("switch_", 1:4)),
composite("CUSL", multi_items("cusl_", 1:3)),
interaction_term(iv = "CUSA", moderator = "SC", method = two_stage, weights = mode_A))
# Create structural model ----
corp_rep_sm_mod <- relationships(
paths(from = c("QUAL", "PERF", "CSOR", "ATTR"), to = c("COMP", "LIKE")),
paths(from = c("COMP", "LIKE"), to = c("CUSA", "CUSL")),
paths(from = c("CUSA", "SC", "CUSA*SC"), to = c("CUSL"))
)
# Estimate the model ----
corp_rep_pls_model_mod <- estimate_pls(
data = corp_rep_data,
measurement_model = corp_rep_mm_mod,
structural_model = corp_rep_sm_mod,
missing = mean_replacement,
missing_value = "-99")
# Extract the summary
sum_corp_rep_mod <- summary(corp_rep_pls_model_mod)
# Bootstrap the model ----
boot_corp_rep_mod <- bootstrap_model(seminr_model = corp_rep_pls_model_mod,
nboot = 1000)
# Summarize the results of the bootstrap
sum_boot_corp_rep_mod <- summary(boot_corp_rep_mod, alpha = 0.05)
# Inspect the bootstrapped structural paths
sum_boot_corp_rep_mod$bootstrapped_paths
# Simple slope analysis plot
slope_analysis(
moderated_model = corp_rep_pls_model_mod,
dv = "CUSL",
moderator = "SC",
iv = "CUSA",
leg_place = "bottomright")
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