Factor analyses conducted within this confirmatory factor analytic framework produce goodness of fit statistics and chi-square statistics. The chi-square statistic is often used to assess model fit in these analyses. However, because the chi-square statistic is highly sensitive to large sample sizes, as in the case here, and may overstate the lack of fit of a structural model (Bollen, 1989), this test statistic was not used. Instead, a number of additional fit indices that have been developed to address the problem associated with the chi-square statistic were used. Hu and Bentler (1999) provided a test of the “rules of thumb” cutoffs for the most commonly used fit indices. They advocated a two-index strategy to assess the adequacy of fit of structural models. Hu and Bentler (1999) suggest a cutoff of 0.95 or above on either the Tucker Lewis Index (TLI; Tucker and Lewis, 1973) or the Comparative Fit Index (CFI; Bentler, 1990). A root mean squared error of approximation (RMSEA) “close to 0.06” also indicates good fit of a factor model.
