A. Dyrlund posted on Saturday, March 18, 2006 - 10:52 am
I am using the MLMV estimator for my CFA so I am trying to compute the chi-square difference test. I followed the manual by first running the analysis using the DIFFTEST savedata command and then running it a second time with the DIFFTEST analysis command. The file is correctly created by the savedata command but my output keeps telling me "THE CHI-SQUARE DIFFERENCE TEST COULD NOT BE COMPUTED BECAUSE THE H0 MODEL IS NOT NESTED IN THE H1 MODEL." Can anyone tell me what I'm doing wrong?
I'd like to run nested models with 1 factor and 17 categorical variables(WLSMV method). The commands are: First step: H1 (the less restrictive) DATA:FILE IS C:\Dokumentumok\Madat\RS_random_CFA_ASCII.dat; Format IS 20F3.0; VARIABLE: NAMES ARE y1-y20; usevariables = y1-y2 y5-y12 y14-y20; categorical is y1-y2 y5-y12 y14-y20; missing is blank; ANALYSIS: Estimator = WLSMV; MODEL: F1 BY y1 y5 y6 y8 y10 y15 y18 y19 y2 y7 y9 y11 y12 y14 y16 y17 y20; savedata: difftest is C:\Dokumentumok\munkahelyi gep\1faktoralap.dat;
Second step: H0 (the more restrictive) DATA: FILE IS C:\Dokumentumok\Madat\RS_random_CFA_ASCII.dat; Format IS 20F3.0; VARIABLE: NAMES ARE y1-y20; usevariables = y1-y2 y5-y12 y14-y20; categorical are y1-y2 y5-y12 y14-y20; missing is blank; ANALYSIS: Estimator = WLSMV; DIFFTEST IS C:\Dokumentumok\munkahelyi gep\1faktoralap.dat; MODEL: F1 BY y1 y5 y6 y8 y10 y15 y18 y19 y2 y7 y9 y11 y12 y14 y16 y17 y20; y1 with y15;
And the output is: the Chi-square difference test is could not be computed because the H0 model is not nested in the H1 model.
I can't see what is wrong. Could you help me? Thank you for your help,
You have the models reversed. Use the model in the second step to save DIFFTEST and the model in the first step to use it in the ANALYSIS command.
Kaatje Kraft posted on Monday, September 23, 2013 - 11:13 am
I am attempting to run a difftest and I have received the following error message, "THE CHI-SQUARE DIFFERENCE TEST COULD NOT BE COMPUTED BECAUSE THE FILE CONTAINING INFORMATION ABOUT THE H1 MODEL HAS INSUFFICIENT DATA."
I'm not sure how to interpret this error (in the first step I saved the data to a .dat file and used that as my reference file for the difftest analysis; when I ran the original analysis with the WSLMV estimator it terminated normally with no error messages). Help?
I have tested MI (2 groups) for a four-factor model with 21 binary indicators (WLMSV estimator). The total sample size is over 2,000. I have used DIFFTEST chi-square difference, CFI difference, RMSEA difference to evaluate the MI. The results are: chi-square difference is significant at ¦Á = .001, CFI difference = -.008, RMSEA difference = .004. If only using CFI difference, RMSEA difference to interpret the results, it seems the model reaches the MI, but not according to the DIFFTEST result. Is the DIFFTEST chi-square difference influenced largely by the sample size? In my study, how much weight should I give DIFFTEST chi-square difference to interpret the MI, compare to CFI significance, RMSEA significance? Many thanks!
Thank you very much for replying me back. I have more questions on this: (1) Is the adjusted chi-square and DIFFTEST using WLSMV estimator also influenced largely by the sample size? (2) Is it normally for researchers to report the adjusted chi-square and df in the result part of the study? (3) I have tested MGCFA (2 groups; N1 = 1,983, N2 = 395) for a four-factor model with 21 binary indicators (WLMSV estimator). The results for configural model 1: chi-square (df = 193) = 702.249, p < .001; CFI = .943, TLI = .955, RMSEA = .047. The results for partial scalar model 2 (I constrained only the factor loading and threshold of items for one of the four factors): chi-square (df = 193) = 713.615, p < .001; CFI = .941, TLI = .954, RMSEA = .048.
My question is that why the df for model 1 and model 2 are the same, also why in the DIFFTEST, the df difference is 3? For my model with large sample size, what is recommended alpha value for chi-square difference test?
I am attempting to run a difftest between a four bifactor model & four correlated factor model. I run into the following error: "THE MODEL ESTIMATION TERMINATED NORMALLY THE CHI-SQUARE COMPUTATION COULD NOT BE COMPLETED BECAUSE OF A SINGULAR MATRIX."
My first model is: MODEL: Int by SRP7 SRP9 SRP10 SRP15 SRP19 SRP23 SRP26; Aff by SRP3 SRP8 SRP13 SRP16 SRP18 SRP24 SRP28; Life by SRP1 SRP4 SRP11 SRP14 SRP17 SRP21 SRP27; Ant by SRP20 SRP5 SRP6 SRP12 SRP22 SRP25 SRP29; G1 by SRP7 SRP9 SRP10 SRP15 SRP19 SRP23 SRP26 SRP3 SRP8 SRP13 SRP16 SRP18 SRP24 SRP28 SRP1 SRP4 SRP11 SRP14 SRP17 SRP21 SRP27 SRP20 SRP5 SRP6 SRP12 SRP22 SRP25 SRP29; G1 with Int@0; Int with Aff@0; Aff with Life@0; Life with Ant@0; G1 with Aff@0; G1 with Life@0; G1 with Ant@0;Int with Ant@0; Int with Life@0; Aff with Ant@0;
My second model is: MODEL: F1 by SRP7 SRP9 SRP10 SRP15 SRP19 SRP23 SRP26; F2 by SRP3 SRP8 SRP13 SRP16 SRP18 SRP24 SRP28; F3 by SRP1 SRP4 SRP11 SRP14 SRP17 SRP21 SRP27; F4 by SRP20 SRP5 SRP6 SRP12 SRP22 SRP25 SRP29;
My questions: 1. since the Ho is nested in H1 (less restrictive), does it always that the chi-square of Ho is larger than that of H1? Is it possible Ho is smaller than that of H1, like what happened in my result? 2. which one do you prefer, for reporting the difftest, ∆¦Ö2 or ¦Ö2diff?