结构方程模型-lecture1.ppt
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1、SEM简介,路径分析,验证性因子分析,SEM,线性因果关系,SEM的产生与发展,SEM的基本形式,因果推断方法,AMOS简介,本讲内容,Sewall Wright (1921,1934)提出路径分析 路径图 1960年代以前,路径分析基本处于休眠状态 Otis Duncan(1966)以及其他学者将其引入社会学研究 1930年代凯恩斯创立了联立方程模型 模型识别,SEM的产生与发展,SEM的产生与发展(续1),Jreskog(1966,1967)开发了验证性因子分析(CFA) Jreskog提出卡方检验,用来比较可测变量的观测相关结构与假定模型所隐含的相关结构,从而否定(或暂时验证)假设模型,
2、是SEM发展的里程碑,Exploratory data analysis is detective in character. Confirmatory data analysis is judicial or quasi-judicial in character Unless the detective finds the clues, judge or jury has nothing to consider. Unless exploratory data analysis uncovers indications, usually quantitative ones, there i
3、s likely to be nothing for confirmatory data analysis to consider. (Tukey, 1977),SEM的产生与发展(续2),将Wright的路径分析与Jreskog的CFA融合在一起,从而诞生了SEM,SEM的产生与发展(续3),基本假定,所涉变量,路径分析,可测变量,潜变量与可测变量,CFA,SEM,潜变量无关,潜变量与可测变量,可测变量可以有测量误差潜变量可以相关,变量没有测量误差,SEM的产生与发展(续4),1970年代,LISREL的诞生极大地促进了SEM的研究与应用 1994年,创立了专门的杂志Structural E
4、quation Modeling 20世纪末,计算科学家和科学哲学家进一步发展了线性因果关系理论与算法,使得SEM在线性因果关系建模中的应用在理论、统计以及计算方面都得以深化和推广,其他SEM分析软件 EQS,Amos,EZPath,SEPath,COSAN,Mx R中的SEM,SAS中的CALIS,Family Tree of SEM,T-test,ANOVA,Multi-way ANOVA,Repeated Measure Designs,Growth Curve Analysis,Bivariate Correlation,Multiple Regression,Path Analysi
5、s,Structural Equation Modeling,Factor Analysis,Exploratory Factor Analysis,Confirmatory Factor Analysis,SEM的优势与局限,优势(与多元回归相比) more flexible assumptions (particularly allowing interpretation even in the face of multicollinearity) use of confirmatory factor analysis to reduce measurement error by havi
6、ng multiple indicators per latent variable the attraction of SEMs graphical modeling interface the desirability of testing models overall rather than coefficients individually the ability to test models with multiple dependents the ability to model mediating variables rather than be restricted to an
7、 additive model the ability to model error terms the ability to test coefficients across multiple between-subjects groups ability to handle difficult data (time series with autocorrelated error, non-normal data, incomplete data where regression is highly susceptible to error of interpretation by mis
8、specification, the SEM strategy of comparing alternative models to assess relative model fit makes it more robust 局限:SEM cannot itself draw causal arrows in models or resolve causal ambiguities. Theoretical insight and judgment by the researcher is still of utmost importance.,SEM的基本形式:结构模型,潜变量(Laten
9、t/unobserved variables)之间的因果关系 外生变量(Exogenous variables): 外生变量(Endogenous variables):,无关,SEM的基本形式:测量模型,反映潜变量与可测变量(Observed/measured variables) 之间的关系,因子载荷 (loadings),无关,结构方程图,Observed Variable,Latent Variable,: Loading,Observed Variables,Latent Variables,0.15,Loadings,图例,Error Var.,SEM示例:stability of
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