Hi Joel, I was lucky to discover your book at early stages of my AMOS endeavor. The book is concise yet very clear. Nevertheless, the section on using marker variable to detect common method bias needs further illustration, I believe. That'd be nice you could add a video on how to analyze and interpret result for detecting CMB using marker variable. Thanks!
Thanks for the feedback. Common method bias is a big topic that would take multiple videos to address. As for marker variables, the key is to choose a variable that is unrelated to any other construct in your study. Once you do that, then you need to partial out the correlation of the marker variable from the other correlations. Then use the adjusted correlation as the input for your model. CMB videos are coming but it might be a little bit before I get to it.
Thanyour for this video. Can you please help me out by answering whether we need to justify the reasons for correlating error terms while reporting SEM results in your research paper?
I will be honest, many papers never even tell the reader if they correlate error terms but as a rule it is a good idea especially if you think there is a lot of repetition in the items.
@@joelcollier9387 Thankyou for your reply, Sir. Can you link some research papers which suggest correlatig error terms to improve mode fit? This will be of immense help to me.
Thank you so much for your interesting video. I have a question. Can I draw a residual covariance between the two residuals of two dependent variables in the path model?
It is not advisable. The reason is a reviewer is going to say that if the error is correlated between constructs....then you probably do not have different constructs. It is just versions of the same construct. The error should behave differently if they are different constructs. This is a little different than correlating errors within construct because they are all supposed to represent the overarching concept. Hope the helps.
There is a lot of debate around this. If you use PROCESS, it does not even give you model fit statistics. If your model fit is bad in SEM, then it points to a model that is not representing the data. In essence, the model does a poor job explaining the data collected. Saying that, it does not mean it poorly explains certain relationships. It means that the totality of your model does not explain the data very well.
@@joelcollier9387 thank you so much for your response. Please would you recommend any references I can check to dig into this discussion ? I am interested in a certain relationship between two constructs of my structural model. The regression weight is 0.24- which is low, but it exists.However, my CFI is 0,.86, Is there any way I can address how reliable this relationship is since the model doesn't fit?
Thank you very much for this very helpful video!! i can only repeat what @nehagahlawat8765 wrote; Can you link some research papers which suggest correlatig error terms to improve mode fit? that would be extermely helpful, thank you very much in advance!!!
waited all summer for the videos to be back! I’m ready to hop back into structural equation models! And of course it was another great video! Thanks!
Very well explained. I have your book too, highly recommend for people who are using AMOS for SEM analysis.
Thank you
Excellent video Prof. Collier!
Hi Joel, I was lucky to discover your book at early stages of my AMOS endeavor. The book is concise yet very clear. Nevertheless, the section on using marker variable to detect common method bias needs further illustration, I believe. That'd be nice you could add a video on how to analyze and interpret result for detecting CMB using marker variable. Thanks!
Thanks for the feedback. Common method bias is a big topic that would take multiple videos to address. As for marker variables, the key is to choose a variable that is unrelated to any other construct in your study. Once you do that, then you need to partial out the correlation of the marker variable from the other correlations. Then use the adjusted correlation as the input for your model. CMB videos are coming but it might be a little bit before I get to it.
Thanyour for this video. Can you please help me out by answering whether we need to justify the reasons for correlating error terms while reporting SEM results in your research paper?
I will be honest, many papers never even tell the reader if they correlate error terms but as a rule it is a good idea especially if you think there is a lot of repetition in the items.
@@joelcollier9387 Thankyou for your reply, Sir.
Can you link some research papers which suggest correlatig error terms to improve mode fit?
This will be of immense help to me.
Thank you so much for your interesting video. I have a question. Can I draw a residual covariance between the two residuals of two dependent variables in the path model?
It is not advisable. The reason is a reviewer is going to say that if the error is correlated between constructs....then you probably do not have different constructs. It is just versions of the same construct. The error should behave differently if they are different constructs. This is a little different than correlating errors within construct because they are all supposed to represent the overarching concept. Hope the helps.
Thank you for your video! If my model does not fit, my regressions weights are not valid? I cannot use them for interpretation?
There is a lot of debate around this. If you use PROCESS, it does not even give you model fit statistics. If your model fit is bad in SEM, then it points to a model that is not representing the data. In essence, the model does a poor job explaining the data collected. Saying that, it does not mean it poorly explains certain relationships. It means that the totality of your model does not explain the data very well.
@@joelcollier9387 thank you so much for your response. Please would you recommend any references I can check to dig into this discussion ? I am interested in a certain relationship between two constructs of my structural model. The regression weight is 0.24- which is low, but it exists.However, my CFI is 0,.86, Is there any way I can address how reliable this relationship is since the model doesn't fit?
Thank you very much for this very helpful video!! i can only repeat what @nehagahlawat8765 wrote; Can you link some research papers which suggest correlatig error terms to improve mode fit? that would be extermely helpful, thank you very much in advance!!!