**5.3 Model assessment**

The estimation method used in this example is the maximum likelihood method. To obtain results, it is common to use the function *summary* that provides the results of the chi-square test, the indices for the adjustment of the model (RMSEA, CFI, AGFI, among others), the estimations of the factor loads, the coefficients of regression, standard errors, Z values, and p values for each estimated coefficient. In this example, only the estimates for both periods are included, since we are interested in identifying the change or effect in each parameter estimate.

summary(fit.RC, fit.measures= TRUE).

It is common that before interpreting the results of the fitted model, it is necessary to verify that the fit is suitable. **Table 2** presents the results of chi-square, degrees of freedom, p-value and some fit indices to make decisions about evaluating the fit of the model for Before RC and RC case.

The chi-square results for the case of RD period are better than those of Before RD. Because the chi-square statistic is sensitive to sample size, correlation size, and nonnormality, it is suggested that other adjustment indices be used. However, since there is no consensus on which goodness of fit index is the best to use, several of the indices available in the lavaan library of the R software are used here. The results of the goodness of fit indices: (a) CFI: 0.915 for RD is greater than 0.803 for Before RD, and is greater than the reference value (≥0*:*90); (b) the value of RMSEA for RD (0.029) is less than Before RD (0.068), and is even less than the reference value (0.05–0.08); and (c) the SRMR value for Before RD is less than for the RD case, both results very close to the reference value (≤0*:*08).

Finally, the values of AGFI for both periods Before RD and RD are close to the reference value of 0.90. In summary, according to the General Rules Guidelines in the SEM literature for selecting indices and model fit statistics, cited by [1, 2], these results indicate a good fit of both models, in particular, for the RD case.

#### **5.4 Model interpretation**

The interpretation for FHS is as follows: in the Before RC period, when the FHS increases by one unit, then BP1, BF1, HR1, Tm1, and NC increase by 1.0, 1.41, 1.73, 1.33, and 0.55, respectively. While for the RC period, when FHS increases by one unit, then BP1, HR1, and Tm1 increase by 1.0, 4.4, and 0.10, respectively, but BF1 and NC

decrease by 1.76 and 1.98, respectively. The interpretation of the other latent variables is done in a similar way.

The observed variables that have the greatest impact or effect on each latent variable in the measurement model are: (a) In FHS: BF1 in both periods Before RC and RC (1.41 and 1.76, respectively) and HR1 for Before RC (1.73) and for RC (4.40).

Additionally, all the factor loadings for Before RC are Significant, while for the RC period are Not Significant; (b) In SHS: All factor loadings have similar effects in both periods and also resulted in NS; (c) In OGH: the effect of NVD increased from 2.58 for the Before RC period to 30.96 for the RC period. In contrast, the effect of NumAb decreased from 0.84 for Before RC to 6.99 for period RC. However, all loads resulted in NS in both periods; (d) In Treat: The effect of the PLAS variable increased from 0.95 of the Before RC period to 1.48 of the RC period. In this latent variable, all factor loadings were significant in both periods; and (e) In Remoc: the effects of the observed variables NW and GW increased from the Before RC period to the RC period from 13.85 to 5.65 and from 18.22 to 5.14, respectively; however, all factor loadings were NS.

Although the results presented in **Table 3**, for the structural model, in both periods, are not significant, it can be said that: (a) when OGH increases one unit, then FHS increases 0.11 units in the Before RC period, but decreases by 1.27 units in the RC



*\*\*\* : P(> |Z|) < 0.05. That is, a value of statistical significance less than 0.05.*

#### **Table 3.**

*Estimates of the measurement model and structural model for both models.*

**Figure 5.** *Diagram path of SEM for RC period.*

period; (b) When FHS increases by one unit, then SHS increases by 1.23 units in the Before RC period, but decreases by 0.25 units in the RC period. In a similar way, the other interpretations of the results of the structural model are made in both periods.

Finally, it is convenient to say that although the number of observations corresponding to the Before RC (230) is greater than the total number of observations to the RC period (106), the results of the fit indices are better for the RC case.
