Sample Size for Structural Equation Modeling
SEM is a large sample approach. It is widely recognized that small sample size could cause a series of problems, including, but not limited to, failure of estimation convergence, improper solutions (e.g., negative variance estimate, correlation estimate greater than 1.0 or less than −1.0), lowered accuracy of parameter estimates, small statistical power, and inappropriate model fit statistics. As in any statistical modeling, determination of appropriate sample size is critical to SEM. In this chapter we will first briefly review the rules of thumb for sample size needed for SEM, and then discuss and demonstrate how to use different approaches to estimate an adequate sample size for a SEM model of interest.