Structural equation modeling (SEM) attempts to remove the negative influence of measurement error and allows for investigation of relationships at the level of the underlying constructs of interest. SEM has been regarded as a "large sample" technique since its inception. Recent developments in SEM, some of which are currently available…

Research in structured equation modeling (SEM) suggests that nonnormal data will invalidate chi-square tests and produce erroneous standard errors. However, much remains unknown about the extent to which, and the conditions under which nonnormal data can affect SEM application, especially when excessive skewness and kurtosis are present in data.…