seminrExtras (version 0.9.0)

congruence_test: SEMinR function to bootstrap calculate the congruence coefficient

Description

`congruence_test` conducts a single bootstrapped congruence test.

Usage

congruence_test(
  seminr_model,
  nboot = 2000,
  seed = 123,
  alpha = 0.05,
  threshold = 1
)

Value

A matrix of the estimated congruence coefficient and results of significance testing.

Arguments

seminr_model

The SEMinR model for CVPAT analysis

nboot

The number of bootstrap subsamples to execute (defaults to 2000).

seed

The seed for reproducibility (defaults to 123).

alpha

The required level of alpha for statistical testing (defaults to 0.05).

threshold

The threshold with which to compare significance testing H0: rc < 1 (defaults to 1).

References

Franke, G. R., Sarstedt, M., & Danks, N. P. (2021). Assessing measure congruence in nomological networks. Journal of Business Research, 130, 318-334.

Examples

# Load libraries
library(seminr)
library(seminrExtras)

# Create measurement model ----
corp_rep_mm <- 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))
)

# Create structural model ----
corp_rep_sm <- relationships(
  paths(from = c("QUAL", "PERF", "CSOR", "ATTR"), to = c("COMP", "LIKE"))
)

# Estimate the model ----
corp_rep_pls_model <- estimate_pls(
  data = corp_rep_data,
  measurement_model = corp_rep_mm,
  structural_model  = corp_rep_sm,
  missing = mean_replacement,
 missing_value = "-99")

# Assess the base model ----
congruence_test(seminr_model = corp_rep_pls_model,
                nboot = 20,
                seed = 123,
                alpha = 0.05,
                threshold = 1)