.png){kind=icon}
Return
Using parcels to convert path analysis models into latent variable models
.png){kind=icon}
PRE
AI
DOI：10.1207/s15327906mbr4002_4.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The biasing effects of measurement error in path analysis models can be overcome by the use of latent variable models. In cases where path analysis is used in practice, it is often possible to use parcels as indicators of a latent variable. The purpose of the current study was to compare latent variable models in which parcels were used as indicators of the latent variables, path analysis models of the aggregated variables, and models in which reliability estimates were used to correct for measurement error in path analysis models. Results showed that point estimates of path coefficients were smallest for the path analysis models and largest for the latent variable models. It is concluded that, whenever possible, it is better to use a latent variable model in which parcels are used as indicators than a path analysis model using total scale scores.
Keywords:
GENERAL-APPROACH
ADOLESCENTS
PERCEPTIONS
PERFORMANCE
VALIDATION
BEHAVIOR
CONSTRUCTS
INDICATORS
CONFLICT
STUDENTS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
M
IF:
3.5
Papers:
1.8K
Citations:
9.4K
Organization
No organization information available
Cited Papers
MATHEMATICS SELF-EFFICACY AND MATHEMATICS PERFORMANCES - THE NEED FOR SPECIFICITY OF ASSESSMENT
PREAI
ShareSaveThree-Dimensional Protein Fold Determination from Backbone Amide Pseudocontact Shifts Generated by Lanthanide Tags at Multiple Sites.png)
Structure
OAAI
StructureIF0
OAAIShareSaveShareSave
View more