Next the user runs the nested model (with fewer parameters freely estimated than in the previous model). A new line is added to the ANALYSIS options. TITLE: Measurement Model of Job Satisfaction and Commitment, Categorical Variables, Missing Values, Clustered Data, and DIFFTEST Analysis Option DATA: FILE IS “C:\Mplus\jobdata.dat”; VARIABLE: Same as previous ANALYSIS: The last option the ANALYSIS TYPE IS COMPLEX; command tells the program to use the TYPE IS MISSING H1 ; data saved in file created when the ESTIMATOR IS WLSMV; first model was run, to test whether ITERATIONS = 1000; the fit of the more restrictive (second) CONVERGENCE = 0.00001; model is significantly worse than the DIFFTEST=jobsat1; fit of the first. MODEL: Any nested in previous model OUTPUT: STANDARDIZED MODINDICES (.5) RESIDUAL; The output for the second model will include results of the difference test. If the difference has a value less than .05, the restrictions added to create the nested model make the fit p significantly worse and the first model is retained. If did not become significantly worse (p > .05), the second, more parsimonious, model should be retained. Example 9. Second Order Factor Model Measurement Model C. The diagram here shows a higher order factor Experience” that “Work influences the three lower order factors: Place Figure 3 about here Second Order Factor Model with Categorical Variables and Missing Values DATA: FILE IS "C:\Mplus\jobdata.dat"; VARIABLE: NAMES ARE agency sat1 sat2 sat3 sup1 sup2
Next the user runs the nested model (with fewer parameters freely estimated than in the previous model). A new line is added to the ANALYSIS options. TITLE: Measurement Model of Job Satisfaction and Commitment, Categorical Variables, Missing Values, Clustered Data, and DIFFTEST Analysis Option DATA: FILE IS “C:\Mplus\jobdata.dat”; VARIABLE: Same as previous ANALYSIS: TYPE IS COMPLEX; TYPE IS MISSING H1 ; ESTIMATOR IS WLSMV; ITERATIONS = 1000; CONVERGENCE = 0.00001; DIFFTEST=jobsat1; The last option the ANALYSIS command tells the program to use the data saved in file created when the first model was run, to test whether the fit of the more restrictive (second) model is significantly worse than the fit of the first. MODEL: Any nested in previous model OUTPUT: STANDARDIZED MODINDICES (.5) RESIDUAL; The output for the second model will include results of the difference test. If the difference has a p value less than .05, the restrictions added to create the nested model make the fit significantly worse and the first model is retained. If did not become significantly worse (p > .05), the second, more parsimonious, model should be retained. Example 9. Second Order Factor Model Measurement Model C. The diagram here shows a higher order factor “Work Experience” that influences the three lower order factors: Place Figure 3 about here Second Order Factor Model with Categorical Variables and Missing Values DATA: FILE IS "C:\Mplus\jobdata.dat"; VARIABLE: NAMES ARE agency sat1 sat2 sat3 sup1 sup2
SEMMplusSyntax.docx