estimate_lavaan_ten_berge {seminr} | R Documentation |
seminr estimate_lavaan_ten_berge() function
Description
Estimates factor scores using ten Berge method for a fitted Lavaan model
Usage
estimate_lavaan_ten_berge(fit)
Arguments
fit |
A fitted |
Value
A list with two elements: ten berge scores; weights for calculating scores
Examples
#' #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
[Package seminr version 2.3.3 Index]