ABSTRACT
Structural equation modeling (SEM) is a widely used statistical technique for studying relationships in multivariate data. Unfortunately, when the sample size is small, several problems may arise. Some problems relate to point estimation, whereas other problems relate to small sample inference. This chapter contains several potential solutions for point estimation, including penalized likelihood estimation, a method based on model-implied instrumental variables, two-step estimation, and factor score regression. This chapter also contains a brief discussion of inference, including several corrections for the chi-square test statistic, local fit statistics, and some suggestions to improve the quality of standard errors and confidence intervals.
