BergamiBagozzi2000 {cSEM} | R Documentation |
Data: BergamiBagozzi2000
Description
A data frame containing 22 variables with 305 observations.
Usage
BergamiBagozzi2000
Format
An object of class data.frame
with 305 rows and 22 columns.
Details
The dataset contains 22 variables and originates from a larger survey among South Korean employees conducted and reported by Bergami and Bagozzi (2000). It is also used in Hwang and Takane (2004) and Henseler (2021) for demonstration purposes, see the corresponding tutorial.
Source
Survey among South Korean employees conducted and reported by Bergami and Bagozzi (2000).
References
Bergami M, Bagozzi RP (2000).
“Self-categorization, affective commitment and group self-esteem as distinct aspects of social identity in the organization.”
British Journal of Social Psychology, 39(4), 555–577.
doi:10.1348/014466600164633.
Henseler J (2021).
Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables.
Guilford Press, New York.
Hwang H, Takane Y (2004).
“Generalized Structured Component Analysis.”
Psychometrika, 69(1), 81–99.
Examples
#============================================================================
# Example is taken from Henseler (2021)
#============================================================================
model_Bergami_Bagozzi_Henseler="
# Measurement models
OrgPres =~ cei1 + cei2 + cei3 + cei4 + cei5 + cei6 + cei7 + cei8
OrgIden =~ ma1 + ma2 + ma3 + ma4 + ma5 + ma6
AffLove =~ orgcmt1 + orgcmt2 + orgcmt3 + orgcmt7
AffJoy =~ orgcmt5 + orgcmt8
Gender <~ gender
# Structural model
OrgIden ~ OrgPres
AffLove ~ OrgPres + OrgIden + Gender
AffJoy ~ OrgPres + OrgIden + Gender
"
out <- csem(.data = BergamiBagozzi2000,
.model = model_Bergami_Bagozzi_Henseler,
.PLS_weight_scheme_inner = 'factorial',
.tolerance = 1e-06
)
#============================================================================
# Example is taken from Hwang et al. (2004)
#============================================================================
model_Bergami_Bagozzi_Hwang="
# Measurement models
OrgPres =~ cei1 + cei2 + cei3 + cei4 + cei5 + cei6 + cei7 + cei8
OrgIden =~ ma1 + ma2 + ma3 + ma4 + ma5 + ma6
AffJoy =~ orgcmt1 + orgcmt2 + orgcmt3 + orgcmt7
AffLove =~ orgcmt5 + orgcmt6 + orgcmt8
# Structural model
OrgIden ~ OrgPres
AffLove ~ OrgIden
AffJoy ~ OrgIden"
out_Hwang <- csem(.data = BergamiBagozzi2000,
.model = model_Bergami_Bagozzi_Hwang,
.approach_weights = "GSCA",
.disattenuate = FALSE,
.id = "gender",
.tolerance = 1e-06)