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Hi, I was trying to find some details on how the Wald test was calculated when the model test: option is used. I couldn't find any details on the website  are there some anywhere, or can you recommend a reference? Thanks, Jeremy 


See the following link for information about the Wald test: http://en.wikipedia.org/wiki/Wald_test#cite_note1 


Hello, I was running a Wald test and now I wonder if it is possible to compute an effect size for a significant wald test?! I read something about Cohens's q (Cohen, 1988). Would that be appropriate or is there any other option you would suggest? 


This question is probably more appropriate for a general discussion forum like SEMNET. 


Thanks Linda for your reply. I have got two further questions. 1) The Semnet forum suggested W = ?(chisqu/N) by rosenthal & rostow. My problem now is that my model uses the complex option and I don't know how MPlus calculates the "clustered" N. I thought N must be between my observed N and ncluster. Is that correct? How is the N calculated in a complex model? 2) I also calculated the effect size using Cohens q because it is independet of N. I got two medium sized effects (.44, .42) in the same sample. One effect size is significant and the other is not. How is that possible? Thanks Sofie 


1. How does Rosenthal and Rostow suggest doing this? 2. Significance is based on the ratio of the parameter estimate to its standard error. One effect must have a larger standard error than the other. 


1. They suggest omega = (Waldchisqu/N)^0.5. But they don't refer to a clustered sample. When I use the complex option in Mplus SE's and N will be corrected but I don't know how. And I guess I have to use the corrected N to calculate the effect size suggested by Rosenthal and Rostow. 2. The standard errors are approximately equal in my model. 


1. It sounds like they did not develop for clustered data. I would not know how to generalize this to clustered data. 2. Significance is determined by the ratio of the parameter estimate to its standard error. 


Thanks again for your response. Can you provide or suggest any information or literature that describes how N is adjusted in a complex model? 


I don't know. You may want to ask on a general discussion forum like SEMNET. 


hello I have a problem considering wald test in mplus. i want to test if moderator effects at two different values of a moderator are different from each other. given the following code: model constraint: diff=(b1+b2*1)(b1+b2*1.01); model test: diff=0;  I can change the constant numbers (above 1 and 1.01) in the the equation, the wald test constantly gives Wald Test of Parameter Constraints Value 24.473 Degrees of Freedom 1 Value 0.0000 the b1 and b2 parameters are values from the model command (regression parameters). is there a wrong specification ? thanks Alex 


I think diff is a new variable so your MODEL CONSTRAINT is wrong. I'm not sure what is happening. I would need to see the files and your license number at support@statmodel.com to figure it out. MODEL CONSTRAINT should be: model constraint: NEW (diff); diff=(b1+b2*1)(b1+b2*1.01); The ztest of diff tell you if diff is significant. In a Wald test, if the pvalue is less than .05 diff is different from 0. 

Huan Liu posted on Friday, September 12, 2014  4:04 am



Dear Linda, I have a problem in considering wald test in mplus. I want to test if two mediator effects are different from each other. given the following code: model:zgxfg by shmyd jjqx xjqx; qzyl by mzyl fzyl; jtzz by jtcy jtnb jtwb jtrt; zgxfg on jtzz(b1); zgxfg on gtzz(b2); zgxfg on tbyl qzyl; jtzz on tbyl(a1); jtzz on qzyl(a3); gtzz on tbyl(a2); gtzz on qzyl(a4); gtzz with jtzz; tbyl with qzyl; model constraint:new(t1 t2); t1=a1*b1; t2=a2*b2; model test: t1=t2; I wonder that is it proper to apply wald test to this case? Because in my experience doing this wald test, the result is always not significant. Thank you in advance. Huan Liu 


Looks correct. Perhaps your sample is small or the effects have large SEs, so that you don't have much power. 

Huan Liu posted on Friday, September 12, 2014  7:54 pm



Dear Linda, Thank you very much for your reply, I will check the sample size and SEs. Huan Liu 


Hello Linda and Bengt, I am trying to use the Wald Test as implemented in MODEL TEST, specifically to test equalities of parameteres estimated and labeled under the MODEL section of my code. (I have also tried imposing these constraints using only parameter labels in the MODEL section, but my loglikelihood comparisons are coming out negative, as is Satorra and Bentler's stictly positive chisquare test, so I am trying to get the Wald test to work.) I have written in my Mplus syntax: MODEL TEST: m1a=m1b; m1b=m1c; I also tried running this using MODEL CONSTRAINT rather than MODEL TEST. However, either way I run it, I receive output saying that a parameter label or the constant zero must appear on the lefthand side of a MODEL CONSTRAINT or MODEL TEST command. I do not understand, since I have used m1a, m1b, and m1c as parameter labels in my model. Can you suggest a solution for comparing two models: one with, and one without the equality constraints? Thank you. 


You should say in MODEL TEST 0 = m1a m1b; 0 = m1b  m1c; In MODEL CONSTRAINT you should create new parameters, for example, diff1 and diff2 and say diff1 = m1a m1b; diff2 = m1b  m1c; 


Greetings, I am analyzing an SEM. I am using Wald tests to test whether the difference in a given coefficent across two groups (n=377, n=343) is statistically significant. Specifically, I am testing 18 differences, one at a time. When I do my Wald tests, I get an error of: *** ERROR P30 – P12 ^ ERROR However, I also get results for each Wald test, for example: Wald Test of Parameter Constraints Value 7.879 Degrees of Freedom 1 PValue 0.0050 So, I thought that error might be something I can ignore. However, there is a great inconsistency in my results. Very minor coefficient differences across the two groups are statistically significant, while another one of my largest differences is NOT statistically significant . . . while another large difference IS statistically significant. I expected my large differences to be statistically significant and look like the results I included above . . . and my small differences to not be statistically significant. Thoughts on the error message? Or, how I may be interpreting the output incorrectly? Thank you! 


Please send the output and your license number to support@statmodel.com. 

Pia H. posted on Tuesday, February 07, 2017  7:54 am



Dear Linda & Bengt I am wondering if it is possible to obtain confidence intervals for the Wald chi square test directly from the Mplus output? Thank you! 


Chisquare tests provide pvalues, not confidence intervals. 

Daniel Lee posted on Wednesday, March 08, 2017  1:30 pm



Hi Dr. Muthen, Are there any other tests available (apart from Walds Test) to assess whether direct and indirect effects are different between multiple groups? Dan 


Yes, you can do 2 runs and compute a likelihoodratio chi2. But it's not going to be much different. 

Daniel Lee posted on Thursday, March 09, 2017  10:32 am



If n = 317, and the chisquare LRT is not significant, but difference in CFI is .05 (between nested models), is it still enough to report a significant difference. Thank you again! 

Daniel Lee posted on Thursday, March 09, 2017  10:54 am



Sorry and to followup on my first question, if I am doing a multigroup (male vs. female) mediation model, I realized that the indirect effect keeps changing as I free of the direct path coefficients that are held equal. So if X> M > Y, and I free X>M, the indirect effect changes. For these models, should we exclude the indirect effect until we begin to test group differences between indirect effects? The indirect effects don't seem to mean much (b/c if path a is freed, path b is constrained). Thank you! 


Hi, I'm running an ordered logistic regression model in Mplus version 7.4 and received an error: "error occurred in the brant wald test for proportional odds" for my outcomes. Does this mean the proportional odds assumption is violated with this outcome and thus ordinal probit or logit are not appropriate? Thank you for your help! 


No, it means that the test failed so you can't use it. 

Xu, Man posted on Friday, August 11, 2017  9:27 am



Dear Dr. Muthens, I would like to ask something along the lines of this thread. When I use MODEL CONSTRAINT for example the following way: model constraint:new(t1 t2 diff); t1=a1*b1; t2=a2*b2; diff=t1t2; model test: t1=t2; The z statistic of diff seems to correspond to square root of the chi_2 of the Wald. Would the result from Wald test (model test) correspond exactly to the result of the new diff parameter, under all conditions (for example under MLR? Thank you! 


Yes, they are close in large samples also for MLR. 


Dear Dr. Muthens, I am somewhat new to Mplus and have a seemingly basic question that I was unable to resolve with the user's guide. I am completing a multigroup curve model and would like to get a Wald's estimate to determine if the difference in I and S are sign different: Variable: Names = h1 h2 h3 hp; missing = all (99); grouping is hp (0 = noperp 1 = perp); Model: i s  h1@1 h2@2 H3@3; Model test: Output: Stand; I have tried a number of options but am unsure on how to differentiate the two groups. Best, Tyler 


Add Model noperp: [i] (p01); [s] (p02); Model perp: [i] (p11); [s] (p12); Then you can refer to these 4 p parameters in Model Test. 


Hello, I am using a wald test for comparing a 1factor and 2factor CFA (based on this webpage: https://www.statmodel.com/download/Testing%20of%20factor%20corr=1.pdf) I was hoping to clarify my interpretation of the output. I ran the following code: MODEL TEST: 0 = 1p1; (where p1 = the labeled covariance between F1 and F2). The wald test is not significant, and I'm wondering if this suggests the 1factor or 2factor model is best. Thanks for your clarification. 


That suggests 1 factor. 

AnhThuy Le posted on Thursday, August 15, 2019  5:21 pm



Hi, I am trying to do a wald test to determine whether a specific mediation path differs between a LOW and HIGH group. When I run the model without the "model test" constraint, this path is significant. However, when I run it with the constraint, it no longer is. Why does the output I get (parameters and estimates) differ between these two if the wald test is just determining whether the paths significantly differ b/w groups? Thanks! 


That doesn't happen unless there is an error in your input  send your full output to Support along with your license number. 

AnhThuy Le posted on Thursday, August 15, 2019  5:48 pm



Dr. Muthen, I only have the text of my input as I'm not in my office currently. In the following, AAMAS_CO AAMAS_EA Age Gender MIBI_C are my control variables. MODEL: AS_TOT BY MASI_OC* RSSI_Tot ZAFD_CD ZAFD_ICV; AS_TOT@1; [CESD_Tot]; CESD_Tot ON FCSL AAMAS_CO AAMAS_EA Age Gender MIBI_C (b1); CESD_Tot ON AS_TOT AAMAS_CO AAMAS_EA Age Gender MIBI_C (cdash); [FCSL]; FCSL ON AS_TOT AAMAS_CO AAMAS_EA Age Gender MIBI_C (a1); FCSL AAMAS_CO AAMAS_EA Age Gender MIBI_C WITH FCSL AAMAS_CO AAMAS_EA Age Gender MIBI_C; MODEL INDIRECT: CESD_Tot IND AS_TOT; CESD_Tot IND FCSL AS_TOT; Model Low: CESD_Tot ON FCSL AAMAS_CO AAMAS_EA Age Gender MIBI_C (a); Model High: CESD_Tot ON FCSL AAMAS_CO AAMAS_EA Age Gender MIBI_C (e); MODEL TEST: 0 = ae; 


Need to have you send your full output. 

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