.png){kind=icon}
返回
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}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
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.
Keyword:
GENERAL-APPROACH
ADOLESCENTS
PERCEPTIONS
PERFORMANCE
VALIDATION
BEHAVIOR
CONSTRUCTS
INDICATORS
CONFLICT
STUDENTS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
M
IF:
3.5
论文数:
1.8K
被引数:
9.4K
机构
暂无机构信息
引用论文
MATHEMATICS SELF-EFFICACY AND MATHEMATICS PERFORMANCES - THE NEED FOR SPECIFICITY OF ASSESSMENT
PREAI
分享收藏Power analysis and determination of sample size for covariance structure modeling协方差结构建模的功率分析和样本量的确定
PREAI
分享收藏Three-Dimensional Protein Fold Determination from Backbone Amide Pseudocontact Shifts Generated by Lanthanide Tags at Multiple Sites由镧系元素标签在多个位点产生的骨架酰胺假接触位移确定三维蛋白质折叠.png)
Structure
OAAI
StructureIF0
OAAI分享收藏分享收藏
查看更多内容