The utility of the maximum likelihood F-test was demonstrated as an alternative to the omnibus Chi-square test when evaluating model fit in confirmatory factor analysis with small samples, as it has been well documented that the likelihood ratio test (T[subscript ML]) with small samples is not Chi-square distributed.

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

For comparing nested covariance structure models, the standard procedure is the likelihood ratio test of the difference in fit, where the null hypothesis is that the models fit identically in the population. A procedure for determining statistical power of this test is presented where effect size is based on a specified difference in overall fit…