Could anyone please explain me about the difference between Absolute/Relative fit indices Vs Maximum likelihood, Generalised least squares in assessing Model fit?? In the Maximum likelihood/ Generalised least squares, we try to minimize the value between the Sample Covariance Matrix (S) & Population Covariance Matrix (E) & calculate some value. So, based on that value, calculated by the "Maximum likelihood/ Generalised least squares", can't we assess the Model fit?? Why there is a requirement of Absolute/Relative fit Indices, after having calculated the value by Maximum likelihood/ Generalised least squares??

More BHARATH SHASHANKA KATKAM's questions See All
Similar questions and discussions