This leads to model-fit values comparable to those with imputed data (n = 342).
The appropriateness of these results was emphasized by model fit values of the different Q matrix models.
With regard to empirical evaluation of these four single Q matrix models (Q-I, Q-ERC, Q-ATAC, Q-ATAS), models based on apprentices' think-aloud studies usually show better model fit values than researchers'/experts' Q matrix models.
Looking at R 2 values determined through the model fit (values close to 1) and to the model curves superimposed to the experimental data (in Figure 1A and B), it is possible to conclude that the Gompertz model can be correctly applied to describe microalgal recovery in the studied conditions.
While the unidimensional shows a deviance (equals −2 Log-Likelihood) of 16,178.8, the multidimensional model shows a deviance of 16,058.6, which results in a significant Chi Square test (df = 9) as well as AIC and BIC model fit values (16,283 vs. 16,181 and 16,504 vs. 16,440, respectively) in favor of the multidimensional model.
The model fit values were CMIN 24.146 (df 19, p.191) and.962 (comparison fit index (CFI)), implying that the model had a very good fit.
Since conducting both the exploratory factor analyses (EFA) and the confirmatory factor analyses (CFA) using the same sample would lead to artificially increased model fit values, the sample was randomly divided into two partial samples, one for each procedure (nEFA = 1,190, nCFA = 1,149).
High levels of agreement implied that the model's fitted values closely matched the observed values.
For the two-stage Cox model the fitted values were calculated at the failure times of the simulated data.
