## 4 Results
### Model Validity Test Results  
Measurement models were developed and evaluated for each latent variable of this study. CFA was completed for each of the measurement models. The measurement models were revised until adequate model fit was achieved. After achieving adequate model fit of each of the measurement models, we constructed the hypothesized model (Figure 3). Final model fit results are shown in Table 5.  
To test the validity of the latent variables in the study, we used CFA. In SEM, validity is considered the degree to which the model results accurately measures the construct that it was designed to measure [60,64,65,67]. Two types of validity were evaluated: convergent validity and discriminant validity. Convergent validity is when evidence shows sufficient overlap of variables measuring a particular construct. The CFA results and convergent validity results are shown in Table 6. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Characteristics** & & **Frequency** & **\%** \\ \hline \# of Projects & 1–5 projects & 47 & 23.2 \\  & 6–10 projects & 49 & 24.1 \\  & 10–15 projects & 26 & 12.8 \\  & 15–20 projects & 18 & 8.9 \\  & 20 or more projects & 63 & 31 \\ LV Experience & Not all LV experience & 58 & 28.6 \\  & All LV experience & 145 & 71.4 \\ Organization Size & Small & 14 & 6.9 \\  & Medium & 67 & 33 \\  & Large & 122 & 60.1 \\ Government Involvement & Little & 2 & 1 \\  & Some & 15 & 7.4 \\  & A lot & 41 & 20.2 \\  & Government agency & 145 & 71.4 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: \(Cont.\) \begin{table}
\begin{tabular}{c c c} \hline \hline
**Model Fit Index** & **Criteria** & **Initial Model** \\ \hline \(\frac{\lambda^{2}}{df}\) & \textless{}5 & 1.764 \\ TLI & \textgreater{}0.90 & 0.904 \\ CFI & \textgreater{}0.90 & 0.915 \\ RMSEA & \textless{}0.08 & 0.061 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Model Fit of Hypothesized Model. Three items were used to evaluate convergent validity: factor loading (item reliability), average variance extracted (AVE), and construct reliability (CR). Factor loadings above 0.5 are considered strong evidence of convergent validity [64]. All indicators in this study had factor loadings of 0.586 or greater. An AVE value greater than 0.5 shows strong evidence of convergent validity [64]. All constructs in this study had an AVE of 0.537 or greater. The final method of examining convergent validity is calculating CR for each construct. Researchers generally accept that a CR greater than 0.7 shows strong evidence \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Construct** & **Indicator** & **Factor Loading** & \(\alpha\) & **CR** & **AVE** \\ \hline  & SEPP1 & 0.753 & — & 0.947 & 0.748 \\  & SEPP2 & 0.848 & — & & \\ Systems Engineering & SEPP3 & 0.941 & — & & \\ Process Performance & SEPP4 & 0.896 & — & & \\  & SEPP5 & 0.871 & — & & \\  & SEPP6 & 0.880 & — & & \\ SE Support & Communication & 0.881 & 0.740 & 0.949 & 0.790 \\  & Planning & 0.868 & 0.726 & & \\  & Personnel & 0.977 & 0.794 & & \\  & T\&I & 0.811 & 0.802 & & \\  & C\&A & 0.900 & 0.732 & & \\ Top & TMS1 & 0.973 & — & 0.933 & 0.874 \\ Management Support & TMS2 & 0.894 & — & & \\  & OC2 & 0.834 & — & 0.889 & 0.730 \\ Organizational & OC4 & 0.938 & — & & \\ Commitment & OC5 & 0.783 & — & & \\ Value of SE & VSE1 & 0.840 & — & 0.773 & 0.537 \\  & VSE2 & 0.749 & — & & \\  & VSE3 & 0.586 & — & & \\ \hline \hline \end{tabular} NOTE: All factor loadings were statistically significant at the \(p<0.001\) level.  
\end{table} 
Table 6: Confirmatory Factor Analysis and Validity Test. Figure 3: Hypothesized Model. of convergent validity [58]. Each construct in this study had a CR of 0.773 or greater. All three indicators, as shown in Table 6, showed strong evidence of convergent validity for the hypothesized model. Discriminant validity is a necessary component for validating constructs. High discriminant validity is present when a construct uniquely measures a phenomenon that other constructs do not measure.