Structural Equation Modeling With Many Variables: A Systematic Review of Issues and Developments

被引:137
作者
Deng, Lifang [1 ]
Yang, Miao [2 ]
Marcoulides, Katerina M. [3 ]
机构
[1] Beihang Univ, Dept Psychol, Beijing, Peoples R China
[2] Univ Notre Dame, Dept Psychol, Notre Dame, IN 46556 USA
[3] Univ Florida, Sch Human Dev & Org Studies Educ, Gainesville, FL USA
基金
美国国家科学基金会;
关键词
structural equation modeling; small sample size; parameter estimates; test statistics; stand errors; COVARIANCE STRUCTURE-ANALYSIS; EXPLORATORY FACTOR-ANALYSIS; GOODNESS-OF-FIT; TEST STATISTICS; SAMPLE-SIZE; CORRELATION-MATRICES; BAYESIAN-ESTIMATION; TESTS; RIDGE; SEM;
D O I
10.3389/fpsyg.2018.00580
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Survey data in social, behavioral, and health sciences often contain many variables (p). Structural equation modeling (SEM) is commonly used to analyze such data. With a sufficient number of participants (N), SEM enables researchers to easily set up and reliably test hypothetical relationships among theoretical constructs as well as those between the constructs and their observed indicators. However, SEM analyses with small N or large p have been shown to be problematic. This article reviews issues and solutions for SEM with small N, especially when p is large. The topics addressed include methods for parameter estimation, test statistics for overall model evaluation, and reliable standard errors for evaluating the significance of parameter estimates. Previous recommendations on required sample size N are also examined together with more recent developments. In particular, the requirement for N with conventional methods can be a lot more than expected, whereas new advances and developments can reduce the requirement for N substantially. The issues and developments for SEM with many variables described in this article not only let applied researchers be aware of the cutting edge methodology for SEM with big data as characterized by a large p but also highlight the challenges that methodologists need to face in further investigation.
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页数:14
相关论文
共 117 条
[1]  
[Anonymous], CHINA J HLTH PSYCHOL
[2]  
[Anonymous], 1993, An introduction to the bootstrap
[3]  
[Anonymous], J SICHUAN U SCI ENG
[4]  
[Anonymous], 1980, ANN M PSYCH SOC IOW
[5]  
[Anonymous], CHINA J HLTH PSYCHOL
[6]  
[Anonymous], 2014, Factor analysis
[7]  
[Anonymous], 2006, EQS 6 STRUCTURAL EQU
[8]  
[Anonymous], 1990, PSYCHOL BULL, DOI DOI 10.1037/0033-2909.107.2.238
[9]  
[Anonymous], 2017, CHINA J HLTH PSYCHOL, DOI DOI 10.13342/J.CNKI.CJHP.2017.08.031
[10]  
[Anonymous], 1975, THESIS U ADELAIDE