seminr fSquared Function
The fSquared function calculates f^2 effect size for a given IV and DV
fSquared(seminr_model, iv, dv)
seminr_model |
A |
iv |
An independent variable in the model. |
dv |
A dependent variable in the model. |
A matrix of the estimated F Square metric for each construct.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
mobi_mm <- constructs(
reflective("Image", multi_items("IMAG", 1:5)),
reflective("Expectation", multi_items("CUEX", 1:3)),
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))
)
mobi_sm <- relationships(
paths(from = "Image", to = c("Expectation", "Satisfaction", "Loyalty")),
paths(from = "Expectation", to = c("Quality", "Value", "Satisfaction")),
paths(from = "Quality", to = c("Value", "Satisfaction")),
paths(from = "Value", to = c("Satisfaction")),
paths(from = "Satisfaction", to = c("Complaints", "Loyalty")),
paths(from = "Complaints", to = "Loyalty")
)
mobi_pls <- estimate_pls(data = mobi,
measurement_model = mobi_mm,
structural_model = mobi_sm)
fSquared(mobi_pls, "Image", "Satisfaction")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.