The stock market is an uncertain market consisting of opportunities to gain and lose. The risk presence in the market creates the need for a stock market forecasting model for the movements of stocks and an understanding of the possible position of stocks in position. Information on future stock movements can enable the investor to […]
hypothesis testing, stock market analysis, time series analysisPartial Least Square Structural Equation Modeling (PLS-SEM) is a statistical multivariate analysis method which combines linear relationship and regression analysis methodologies.
analysing with amos, SEM modulePath analysis model is a statistical method used for establishing a causal relationship between variables. It is used when there are multiple variables in a study.
analysing with amos, SEM moduleStructural equation modelling (SEM) is a century-old statistical method that witnessed progression over time. Initially, the model focused only on path analysis. However, with the growth in usage of SEM in social science, the factor analysis technique was integrated into it. Presently SEM is a powerful multivariate technique applicable in scientific investigations to evaluate and test the multivariate casual relationships. The challenge today is that research problems are of different kinds and there are multiple models. Therefore, it is essential to understand the basics before applying structural equation modelling in research.
sem introduction, SEM moduleThere are five major types of structural equation modeling analysis. Each of them helps to build a relationship between variables.
sem introduction, SEM moduleStructural equation modeling (SEM) is a powerful multivariate technique used increasingly in scientific investigations for evaluating and testing the relationships between variables.
sem introduction, SEM moduleSEM establishes the relationship between two or more variables. It also determines the efficiency of the model created in the process.
sem introduction, SEM module