Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models
结合图形与代数方法识别潜变量结构方程模型参数
Measurement error is ubiquitous in many variables - from blood pressure recordings in physiology to intelligence measures in psychology. Structural equation models (SEMs) account for the process of measurement by explicitly distinguishing between latent variables and their measurement indicators. Users often fit entire SEMs to data, but this can fail if some model parameters are not identified. The model-implied instrumental variables (MIIVs) approach is a more flexible…