

Degrees of freedom in DIFFTEST 

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Peter Ji posted on Friday, March 27, 2009  9:50 pm



Hello, I am using DiffTest to compare the fit of a one factor, 6 correlated factor model, and a second order factor model. My colleague and I were wondering about the fact that the changes in df are not consistent across the waves when we conduct the DiffTest. For Wave 1 One factor compared to 6 correlate factor model: chisquare difftest = 108.22, df = 13 6 correlated factor model compared to 2nd order factor model: chisquare difftest = 28.88, df = 8 2nd order factor compared to one factor model: chisquare difftest = 90.35, df = 6 For Wave 2 One factor compared to 6 correlate factor model: chisquare difftest = 229.57, df = 12 6 correlated factor model compared to 2nd order factor model: chisquare difftest = 9.70, df = 8 2nd order factor compared to one factor model: chisquare difftest = 197.14, df = 5 For Wave 3 One factor compared to 6 correlate factor model: chisquare difftest = 247.49, df = 12 6 correlated factor model compared to 2nd order factor model: chisquare difftest = 16.78, df = 8 2nd order factor compared to one factor model: chisquare difftest = 219.08, df = 5 We expected that the df's would be the same because the model structures are the same across the waves. Is there a cite for why the different df's occured? Thank you. Peter 


With WLSMV, you should be looking only at the pvalue for both model results and DIFFTEST. If you want to see degrees of freedom as expected, use WLSM. 

Peter Ji posted on Saturday, March 28, 2009  1:38 pm



thank you. one followup. does it matter that the diff test is run with WLSMV vs. WLSM? Will reviewers take note that the df is not as expected because of the DiffTest used WLSMV vs. WLSM? 


DIFFTEST is only for estimators ending in MV. If you use WLSM, you need to use the scaling correction factor that is given and complete the difference test by hand. The difference in the number of free parameters between the two models is the same as the difference in the degrees of freedom. 

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