estimate_lavaan_ten_berge: seminr estimate_lavaan_ten_berge() function

Description Usage Arguments Value Examples

Description

Estimates factor scores using ten Berge method for a fitted Lavaan model

Usage

1

Arguments

fit

A fitted lavaan object – can be extracted from cbesem estimation or from using Lavaan directly.

Value

A list with two elements: ten berge scores; weights for calculating scores

Examples

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#' #seminr syntax for creating measurement model
mobi_mm <- constructs(
  reflective("Image",        multi_items("IMAG", 1:5)),
  reflective("Quality",      multi_items("PERQ", 1:7)),
  reflective("Value",        multi_items("PERV", 1:2)),
  reflective("Satisfaction", multi_items("CUSA", 1:3)),
  reflective("Complaints",   single_item("CUSCO")),
  reflective("Loyalty",      multi_items("CUSL", 1:3))
)

#seminr syntax for freeing up item-item covariances
mobi_am <- associations(
  item_errors(c("PERQ1", "PERQ2"), "IMAG1")
)

#seminr syntax for creating structural model
mobi_sm <- relationships(
  paths(from = c("Image", "Quality"), to = c("Value", "Satisfaction")),
  paths(from = c("Value", "Satisfaction"), to = c("Complaints", "Loyalty")),
  paths(from = "Complaints",   to = "Loyalty")
)

# Estimate model and get results
cbsem <- estimate_cbsem(mobi, mobi_mm, mobi_sm, mobi_am)
tb <- estimate_lavaan_ten_berge(cbsem$lavaan_output)
tb$scores
tb$weights

seminr documentation built on Sept. 5, 2021, 5:36 p.m.