.png){kind=icon}
返回
Principles and practice in reporting structural equation analyses
.png){kind=icon}
PRE
AI
DOI：10.1037//1082-989X.7.1.64.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here.
Keyword:
COVARIANCE STRUCTURE-ANALYSIS
MAXIMUM-LIKELIHOOD
TEST STATISTICS
2-STEP APPROACH
FIT INDEXES
MODEL
4-STEP
ASSUMPTIONS
ROBUSTNESS
PSYCHOLOGY
