Nothing
library(seminr)
# Create the measurement model
influencer_mm <- constructs(
composite("SIC", multi_items("sic_", 1:7), weights = mode_B),
composite("PL", multi_items("pl_", 1:4)),
composite("PQ", multi_items("pq_", 1:4)),
composite("PI", multi_items("pi_", 1:5)),
composite("WTP", single_item("wtp")),
composite("PIC", multi_items("pic_", 1:5)),
interaction_term("PQ", "PIC", method = two_stage)
)
# Creating structural model
influencer_sm <- relationships(
paths(from = "SIC", to = c("PL", "PQ", "PI")),
paths(from = c("PL", "PQ", "PIC", "PQ*PIC"), to = c("PI")),
paths(from = "PI", to = "WTP")
)
# Estimating the model
# - note, the influencer_data dataset is bundled with seminr
influencer_pls <- estimate_pls(data = influencer_data,
measurement_model = influencer_mm,
structural_model = influencer_sm)
summary(influencer_pls)
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