Generalized Structural Equation Modeling (GSEM) and its Application in Health Researches

Generalized Structural Equation Modeling (GSEM) is a family of statistical techniques utilized in the analysis of multivariate, categorical and ordinal data in order to measure latent variables and their connection with each other. The aim of this study is to consider the structure of data, and introducing GSEM to medical science researchers and presenting a practical example of in medical science researches.
An introduction to Structural Equation Modeling (SEM), along with its advantages and disadvantages was presented, and also GSEM and its all kind of forms was specified. An example to study hypertension risk factors in patients suffering from diabetes was carried out, which was a demonstration of using GSEM method for binary response variables. The data includes a random sample of 2716 people from Golestan province cohort studies.
Age, body mass index, abdominal obesity, residence place, socioeconomic status, salt intake had direct effect on hypertension. Race, education, vitamin D and physical activity had direct and reverse effect on hypertension (p.value Unlike SEM, the limitative hypothesis that our data should have a normal distribution do not needed in this model, also GSEM is powerful tool in the analysis of categorized data. Nevertheless this method cannot perform goodness of fit test, and adjustment and modification method of the model directly, and that they are some limitation in using this method.