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Structural Equation Modeling
This is a type of multivariate statistical analysis method that is often used to evaluate structural relationships. It encompasses both multiple regression analysis and factor analysis. Structural equation modeling helps researchers identify relationships between estimated variables and latent constructs. It is one of the most widely used statistical techniques because, in just one analysis, it measures several interrelated dependencies.
Ordinary Least Squares
Ordinary least squares is a regression method of analysis that measures associations between one or more independent variables and a dependent variable. This method reduces the sum of the squares found in the difference between the estimated and observed dependent variable values that have been configured as a straight line. Ordinary least squares’ logic extends to a multivariate model that has two or multiple independent variables.
Maximum Likelihood Estimation
The likelihood of a given set of data is the probability of getting that set of the distinct set of data depending on the probability distribution model that has been chosen. The process of computing the maximum likelihood begins with the likelihood function. This function has all the parameters of the unknown model. The maximum likelihood estimates are the values of the function parameters and maximize the likelihood of the sample.