Evaluating and Improving CFA and General Structural Models
Natasha K. Bowen, Shenyang Guo · Oxford University Press eBooks · 2011
Sometimes instead of getting results when they run an SEM analysis, researchers are confronted with discouraging messages about programming errors, data problems, or other causes of estimation failures. This chapter first summarizes possible causes of estimation failures. It then provides guidelines for interpreting the results of successful estimation procedures both statistically and substantively. Finally, it discusses strategies for improving fit when model test results are valid (i.e., the model ran and converged, all parameters estimates are within valid ranges, and no errors are reported by the program) but unsatisfactory (i.e., fit criteria are not met).