Learn to test for metric invariance using multi-group confirmatory factor analysis (MGCFA) in SPSS AMOS with data from the International sponsorship study (2016) / Rob Angell.
This dataset is designed for learning about Multi-Group Confirmatory Factor Analysis (MGCFA) using the AMOS software package. The dataset is a subset derived from the 2016 International Sponsorship Study (ISS 2016) conducted by researchers at Cardiff University. The example builds upon the confirmat...
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| Online Access: |
Full Text (via SAGE) |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2019.
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| Subjects: |
| Summary: | This dataset is designed for learning about Multi-Group Confirmatory Factor Analysis (MGCFA) using the AMOS software package. The dataset is a subset derived from the 2016 International Sponsorship Study (ISS 2016) conducted by researchers at Cardiff University. The example builds upon the confirmatory factor analysis (CFA) dataset in which a baseline CFA model for animosity and ethnocentrism was specified, tested, and validated. Here, we continue to establish whether any observed heterogeneity exists in the factorial structure of both latent variables attributable to gender (male vs. female). An invariance testing protocol is followed in testing for this. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for AMOS. |
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| Physical Description: | 1 online resource : illustrations |
| ISBN: | 9781526469625 1526469626 |
| Source of Description, Etc. Note: | Description based on XML content. |