Amos Plugin Specific Bias Test (CMB)
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- Опубликовано: 11 сен 2024
- In this video I show off a new plugin for testing specific bias and common method bias. This plugin might not work for AMOS versions 26+ (IBM changed the way it handles variables across multiple runs...)
I am really grateful to you Professor. I have published one of my journal article with Taylor & Francis just by following your extra-ordinary Lecture on SEM. In the era of globalization and technological advancement, you are not only a Professor of BYU, but also a professor of the world. Thank you Professor, and the best wishes for you.
Thank you, Professor. It is not clear why unconstrained would be compared against zero constrained. Intuitively, comparing equal constrained against zero constrained makes more sense. Can you please advise why equal constrained vs zero constrained is wrong?
Unconstrained is the proposed model. We can compare this against a model that implies zero common variance. If they are the same, then their is no significant common variance (i.e., the model proposed is no different from the model constrained to zero).
@@Gaskination Thank you! I see that your videos in the past focused on comparing equal constrained against the original model without CLF (or, zero constrained model), which I find much more intuitive. By "common" variance, I find it intuitive to constrain the paths from CLF equal. I was curious what made your thoughts change over time. I understand that unconstrained vs zero constrained is more rigorous, but hard to understand when assuming the nature of commonness (i.e., a latent factor having equal/common influence). I find the usage of unconstrained in--comparing that against equal-constrained to see if that assumption is true or not. So to check whether there is CMV or not, I thought comparing equal against zero is the first step. This is all difficult because there is no clear guideline regarding CLF...
James: Excellent tool. You must have the most dedicated resources in the world who develop all these fantastic add-ins. It is very generous of you for sharing these tools with the public.
There are two more tools that I want to request which will make life easier for many researchers. In case those are not difficult, kindly see if there is any possibility to creat them.
1. On the results window, for a path model, we see p values and standardized regression weights on two separate tables. Also their first columns shows relationships are in reverse order (dependent variable proceeds independent variable). This is little confusing. Can a addin make a good reportable table?
2. Is it possible to view t values or p values with standardized regression weights on the actual path diagrams after a test is run? If not, there is an opportunity to creat a tool that does this.
Thanks you again.
1. This would be easy. I'll ask John to see if he's willing.
2. Unfortunately, you cannot change the display measures (as far as I know). I'll have John look into it, but I'm pretty sure it is not changeable.
Thanks for the ideas!
Dear James, thanks for your work and making our lifes easier with your plugins.
When attempting to run the Common latent factor test with the ModelBias plugin for AMOS 26 I receive the error message "(Name of one of the variables with 15 items) is broken. Attempting to fix the model". What does this mean?
I also tried to conduct the CLF the "old way" you described in one of your previous videos and compared the standardized regression weights of the model, both with and without the CLF. The results showed that for most of the items of the variable which is mentioned in the error message above, the difference is >.20. This might be by chance but it seems rather odd that it´s exactly this variable which is reported in the error message that seems to have a problem with common method bias?
I just don´t know what to do with it and how to overcome the error message to get the plugin results?
Any advice would be much appreciated. Thanks a lot!
Got the same error, Catherine. Were you able to fix it?
Thanks Professor James for your help. However, my SDB has broken my model. when I constrain the path coefficients to Zero the amos keeps telling me to put additional constraint and it never works. Did I forget something? should I constrain the variance of sdb to zero for example?
Every latent factor needs a parameter constraint. This can be on the first indicator regression path or it can be on the latent factor variance. Set either one to 1.00
Remarkable work!! Thanks for every video!
Hello, I appreciate your works helping many scholars in the world! I have one question about this new plugin. After I compared the outcome of new plugin and that of the previous plugin with a stat tool, the outcomes were different: the outcome from the new plugin = p-value was 1.000, whereas the outcomes from the previous method = p-value = 0. Seemingly, the figure of a chi-square wrongly inserted into the DF column on the outcome screen..., it made the outcomes of the new plugin different. I am not sure if this only happens on my computer, just in case I let you know. ( I am using AMOS 24)
That is odd. I would have to test it on my end I think. I wonder if it incorrectly input the DF or X2...
Dear james, what would happen if we use CLF but we dont have the marker variable such as Socdes? Can we still run the CLF in the absence of something like SocDes.
Yes, you can run with just the CLF. This will work better if your model has lots of observed variables. If the model has fewer than 20 observed variables, then there is a possibility that the CLF will break the model and ruin the validity of your factors. If this happens, it would be better to use a different approach that detects but does not extract shared variance.
James, thanks. Any idea why I might be getting an error "solution could not be generated" on AMOS25? The models run without the CLF. Any videos on how to run a different approach?
Try running the model with the CLF but without the plugin. Sometimes the CLF breaks the model (e.g. negates regression weights or makes them non-significant).
Thank you Prof! I am having trouble with the plugin for version 26 and above. When selecting the plugin in Amos it reads " The file AMOS-ModelBias.dll contains syntax errors". I'm uncertain how to resolve this. Please help me.
Sorry I resolved it, I needed to unblock the file (as you've indicated so many times in other videos).
Hello Gaskin, thank you for all the videos.
I have a problem with testing the multivariate normality, In the AMOS I can calculate the Mardia multivariate normal distribution coefficient, It is said that the coefficient should be less than 8, I can not meet this criterion even though I remove the outliers from the dataset,
are there any other methods for testing he multivariate normality? If the multivariate normality assumption is not met we can not use the maximum likelihood method estimate? I can met the univariate normality.
Multivariate normality is almost never met if tested in AMOS. If you are concerned about multivariate influentials, you can do a cook's distance analysis: ruclips.net/video/J2EkjIeK-PE/видео.html
I would recommend against removing many cases due to multivariate normality. It is hard to justify.
James, thank you for making it so easier. I get this error when I run the plugin-
"solution could not be generated, try running the model without the model bias plugin to troubleshoot. This is not a plugin problem but a model problem. Adding a common latent factor often creates instability in measurement models".
Will you please suggest how to overcome this?
Try running the model without the common latent factor. If it doesn't run, then fix that issue first. If it does run without it, then the CLF is breaking the model. In this case, it is better to assess method bias a different way, such as through VIFs.
@@Gaskination Thank you very much for these plugins! I have the same problem. Were could I find a video about CME using VIFs? I
@@martinamori506 ruclips.net/video/J7eeu4O80_M/видео.html
Thank you, James, for this fantastic tool. I have a question. In my data set the conclusion is: “a test of equal specific bias demonstrated evenly distributed bias” (contrary to your example). The zero constraints test is significant whereas the Equal constraints tests is not significant. So, what does this mean? There is bias, but it is evenly distributed. Is it better or worse than unevenly distributed bias?
Your interpretation is correct. Bias exists, but it is evenly distributed. So, it is neither good nor bad. It just is present. So, we keep the marker variable as we move forward.
I'm getting an error on AMOS 26 "Resolve conflict: You are attempting to draw an arrow that points to a variable whose variance (...) is constrained. An endogenous variable is not allowed to have a constrained variance. Please select one of the following options." with options being "Do not draw the arrow." and "Remove the constraint on the variance, and draw the arrow." This happens after the unconstrained model test - when drawing lines for the zero-constrained model. This is not a fatal issue as you can click through. However, the zero-constrained model does not seem to have constraints set to 0 so the plugin just tests the unconstrained model again (and finds no specific bias by default).
I found the exact same issue when I tried it yesterday. I will have my RA look at it and see what can be done.
Thank you, James, for your amazing videos. I think this plugin does not work on second-order CFA - it did not in my case. As a response to one of the comments, you suggested using VIF. - and my data fulfils that threshold - means there is no bias. But, If I run this CLF (specific Bias test) at first order, it does show me that CMB is present. So, what should I rely on? Any advice on that would be highly appreciated. Because, if the bias is present, how can I do the data imputation at 2nd order level - as this CLF does not run? Should I just proceed to the structural model without data imputation controlling for the bias? .
VIF approach is meant for non-covariance based methods (such as PLS). If you found bias at the first order level, but the model won't run at a 2nd order level, then you could impute at the first-order level and then just use those factor scores as dimensions in a latent factor during your causal analysis.
@@Gaskination Thank you very much, James. Highly appreciate that. I was thinking along the same line but was not sure. So, thank you for your advice.
Hi James, Thank you very much again for your efforts. when I downloaded the plugin, it appears in a name different from the one that in your AMOS. it is name is "CFA zero and equal constraint test". When I run this plugin, it gives outcome different from that you showed us. more specifically, it shows me only zero constraints test box but not equal constraints test. Also, this zero constraints test box does not include p-value.
Could you please check if it is the right plugin.
Best regards,
Yikes! I'll check. thanks!
Thank you for this video, prof. James, but I had a problem when running common method bias. When using the plugin as you taught, it says that my one latent variable could not be fixed. This is not a plugin problem, but a model problem. I am using a multidimensional scale, could it be a problem for that? Thank you for your advice in advance.
Ahh. yes, that might be the problem if you have a higher order factor. I don't know if I tested this with a higher order factor.
@@Gaskination Appreciate it, Sir.
Hi Prof. Gaskin, this is Alvin Hadiono from Univ. of Glasgow. Quick question, can / should we add CMB in the causal model after we impute the factor scores? Thank you so much for your help.
If you imputed the factor scores while the CLF or specific bias factors were still connected to the observed variables, then you do not need to include them again in the structural model (because they're already accounted for in the factor scores).
@@Gaskination Thank you so much, Dr. James. I haven't done that as it breaks my structural model. So am thinking to put them "later", i.e. during the causal model. Can this be done, Dr.?
@@alvinhadiono If it breaks your CFA, then you should not use it and you should not impute factor scores while the CLF is present. In this case, you also cannot include it as a control in the causal model with factor scores, because it does not exist at that point. Instead, you would need to do some sort of other test, like the VIF test here: ruclips.net/video/J7eeu4O80_M/видео.html
@@Gaskination Thank you Dr. James. Appreciate your help. Have a blessed and relaxing YE holiday!
Hi Dr. James, thank you for your video. Do I have to conduct CMB / CLF test for my moderating factors? Thank you and looking forward to hear from you.
CMB is usually tested on all reflective latent factors. So, if your moderators are reflective and latent, then yes.
Thank you so much Dr James for your kind reply. I was one of your students in your SEM MyEducator course. I learned a lot from you through the course. Thank you so much for everything. I hope you and your loved ones are happy and healthy always!
thanks james for new plugin. i followed steps to download common method bias plugin, but get "modelbias.dll " instead of "modelbias24.dll". further when i download and run on data, i receive "contains syntax error" error. please do recommend any solution
That is the correct plugin. I've renamed it since making this video. As for the syntax error, see this troubleshooting guide: statwiki.kolobkreations.com/index.php?title=Plugins#Troubleshooting
Hello James, when I attempt data imputation with CLF (I tried with your tools and manually) I get the following error messages: "A sample of parameter values was inadmissible", then "1 parameter samples were inadmissible. 0 completed data sets have been created." I have used the tools before with other extractions and I never had a problem. I don't have missing values. Do you have any idea of what could cause that? Thank you in advance . Nico
This can also be caused by a factor name that includes a space or hard return.
Hello James. I double-checked to be sure but I don't see any issue with that. Please know that I used your pattern matrix import tool then your CLF tool so the potential for human error seems limited. CLF works great but reveals CMB so I tried to impute the factors with the CLF (and saw the error message that led to my post). The imputation without CLF is successful (so no issue with coding of variables). Last, this measurement model is part of a larger research and I used the same variable names and labels from one study to the next (and the imputations worked). I use AMOS 24. Could it be a problem with my data? (e.g. needs more thorough screening?). Should I consider that the CLF breaks the model, explain that, and continue with factors imputed without CLF? Thanks a lot for your help! and the awesome videos of course! Best, Nico
In this case, it is probably an identification issue. Make sure to remove any covariances between errors (if any). Otherwise, you might try a different CMB approach, as the CLF approach is known to cause model instability (see Podsakof et al 2012).
Thank you!
Another "win" from you, James! Thank you for the plugin... however, upon downloading and following the directions to add to AMOS 25 as a plugin, I receive an error "contains syntax error." Has anyone else experienced this lately?
dang. Every system seems to be different. Here are some troubleshooting tips: statwiki.kolobkreations.com/index.php?title=Plugins#Troubleshooting
Thank you for pointing me to the Troubleshooting Tips - I was able to use the plugin successfully after using the "Run as Administrator" for my version of AMOS 25. Bravo!
if we have amos 22 is there any video for manually calculate CMB ?
Here is a video using an earlier version of AMOS: ruclips.net/video/CFBUECZgUuo/видео.htmlsi=5YmpLUangEC5Zs8A
And here's an even older one: ruclips.net/video/Y7Le5Vb7_jg/видео.htmlsi=pLleHhygXAM_nY8v
Hello professor, first, thank you for your video. After following steps of the video, I got two error signs, one is " (latent factor name) is broken. Attempting to fix the mode.", and after forcing to proceed the analysis, "(latent factor name) could not be fixed. This is not a plugin problem, but a model problem. Adding a common latent factor often creates instability in measurement models." I tried to two different models, but got the same error signs. Can I ask why this happened? I found that one difference between your video and my analysis is that my AMOS were not able to create the 0.1 after creating the CLF and the latent factors were not constrained to 0. Do I need to manually constrain them? After I did it, I got a result, but p value was 1.00 and the chi-square and DF were 0.. so I guess this is not right.... Thanks!!
This happens when the CLF breaks one or more factors - e.g., their indicator weights flip to negative or become non-significant. Try running the model without the plugin to see if this is the case.
@@Gaskination Thank you for your answer! Yes, there are some indicators that are negative. I tried the traditional method and it worked!
Dear James, thank you for very helpful tools. Do you have any video that shows how we can run a Quadratic Effect model in Structural Equation Modeling in AMOS?
Hi Prof. James,
Thanks for this wonderful resource.
Could you please provide any reference for this kind of procedure in testing CMV?
Regards
Pankaj
Here are my CMB references: statwiki.kolobkreations.com/index.php?title=References#Method_Bias.2C_Response_Bias.2C_Specific_Bias
Dear Sir, Thank you so much for the video.
I'm facing problem as to how to choose marker variable for my study. Please help with any research paper in HR/OB domain-
Marker Variable is choosen on the basis of Dependent or Independent Variable? Does it get affected by Moderator and mediator? What should be the keywords used in search database?
Thanks a ton
Marker variables are chosen theoretically to identify specific biases. The most common one is social desirability bias. However, if you’ve already collected data, you can use any latent variable in your dataset that is theoretically unrelated to the other variables of interest.
@@Gaskination Sure thing Prof. Thank you so much for the advice. Really Helpful.
Dear Sir, I will be very grateful to you if you kindly suggest some solution to "covariance matrix is not positive definite" resulting in correlation greater than 1 between two latent factors.
In such a case, there is some instability. Perhaps you have factors with only two indicators, or perhaps you have included a categorical variable in your factor, or perhaps you did not do EFA first.
Thank you very much sir for your guidance. I have four factors with three items each and there is no categorical variable in the model. However, I didn't run the efa. What should I do now. Once again thank you very much for your gracious support
If you did the EFA, and the two factors did not load together, then I'm not sure. I think I would have to see the model and data. You are welcome to send them to me. I would need the .sav and .amw files. james.gaskin@byu.edu
Thank you very much sir. You have been a source of inspiration and learning to me since the last 05 years and will continue to be the same in the rest of my life. I owe a great debt to you for your support, availability, and graciousness. I simply cant express my love and respect for you. stay blessed always. I have sent you the required files via email. once again thank you very much.