Categorical Models with plssem

In plssem: Complex Partial Least Squares Structural Equation Modeling

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(plssem)

Ordered indicators are common in survey-based SEM applications. This vignette reuses the Theory of Planned Behavior example but illustrates how to run the model when the manifest variables are ordinal.

Theory of Planned Behavior (Ordered Indicators)

tpb <- ' 
# Outer Model (Based on Hagger et al., 2007)
  ATT =~ att1 + att2 + att3 + att4 + att5
  SN =~ sn1 + sn2
  PBC =~ pbc1 + pbc2 + pbc3
  INT =~ int1 + int2 + int3
  BEH =~ b1 + b2

# Inner Model (Based on Steinmetz et al., 2011)
  INT ~ ATT + SN + PBC
  BEH ~ INT + PBC 
'

fit_cat <- pls(
  tpb,
  data      = TPB_Ordered,
  bootstrap = TRUE,
  sample    = 50,
  ordered   = colnames(TPB_Ordered) # explicitly specify ordered variables
)
summary(fit_cat)

plssem documentation built on March 23, 2026, 5:08 p.m.