DEAR VIEWERS: I A NEW VIDEO ON CONFIRMATORY FACTOR ANALYSIS (CFA) WITH AMOS THAT IS HOT OFF THE PRESS (AS OF SEPT 2020). THE VIDEO IS A BIT HIGHER QUALITY AND ALSO CONTAINS A POWERPOINT AND DATA YOU CAN DOWNLOAD FOR FREE UNDERNEATH THE VIDEO DESCRIPTION). PLEASE CONSIDER CHECKING IT OUT AT th-cam.com/video/bbmOMh1hDpA/w-d-xo.html (Confirmatory factor analysis in AMOS with Personality Disorder Scale items (Sept 2020))
Thanks for visiting Kathy! I'm glad they are helpful. By the way, don't forget to visit my most recent videos on CFA using AMOS: CFA video (2020): th-cam.com/video/bbmOMh1hDpA/w-d-xo.html Second-order CFA: th-cam.com/video/r4khWjiePBE/w-d-xo.html Best wishes!
thank you so much for your efforts. I wish the audio and the video were more synced though, sometimes it would get perplexing as the video has a bit of delay
Thanks for such a good tutorial. Before watching this video, I didn't know what to do with latent constructs and how to measure them. As we know that latent constructs cannot be directly measured and can only be observed from the observed variables. So, how to define them in an application? Now, I know that we are actually choosing one of the observed variables or items and assuming it to have a regression coefficient of 1.
Thank you for this nice explanation. I get the error: "An error occured while attempting to fit the model. An error occured while attempting to read the file, [...]" when trying to calculate estimates. Do you have any idea what the problem could be? thank you!
Why did you draw all the boxes separately? use the third option on the right in the first column, that draws all factors, variable and error term boxes together
Sir, I have a question. I'm looking forward to having your response. I also am trying the CFA using my variables on Advancement. My problem is in the analysis part. There is a dialog box that keeps on appearing and it says "The observed variable, Advancement, is represented by an ellipse in the path diagram". I cannot proceed to analysis. What shall I do to proceed to analysis? Thank you, Sir.
You're most welcome! Also, just so you know, I do have a much more recent video on CFA with AMOS here (th-cam.com/video/bbmOMh1hDpA/w-d-xo.html). It contains more updated information and supplemental information.
Thanks very much Mr,Trey De Jong for response and advise concerning my question.What shall i do for example if five of my latent variable will proposed to create one endogenous variable as an out come.And there is no indicators for the proposed out come.On other word all the latent variables must have indicators?
Hello sir. Nice to see your video. I have a question. What will happen if corellate among laten construct have little score? Is it used in interpretation or only the loading factor among inside laten construct (variable) used?
At 13:56 you say "right-click this button here" but its not clear what button you are right clicking and I feel like I have followed it accurately up to that point but not getting the output you are, and neither am I able to toggle that other button at the top like you are for some reason when you can pressed calculate.
Hello i have a question ; I am doing a research and i have 3 independent variables (product type ... etc ) and i have 1 moderating variable and 2 independent varibles i watched the tutorial its very helpful but my question how i can input my independent varible data. I dont have questions for each independent varibles because they are in scenerio based so they are merce in to a scenerio then the participants answer questions about my dependent and moderation varibles. Here is my question how can i enter my independent data in amos. ps; sorry for my english
Thanks so much for your nice tutorial. How can i get the t-values in AMOS. How can I calculate them? In Regression weights tab, some S.E. values are missing because of fixed regression weights. So i cannot calculate the C.R. ratios/t-values. Thanks for your attention and time.
Hi, found this video very useful! Just wanted to ask...what do you do if one of your indicator variables does not load significantly onto it's factor? I'm planning on doing SEM after this factor analysis so should I delete the indicator variable that does not fit or do I just acknowledge that it did not fit when I write up my research and continue with the SEM? Thanks :)
Hi Catherine, the trick is that the overall fit for your full SEM (i.e, path analysis with latent variable) model is not only impacted by the structural relations you specify among your latent variables, but also by the level of fit of your specified measurement model. I think you could adopt either approach you noted when reporting on your results. If the item is causing serious problems with fit in your measurement model, then you could delete it (as it would also create problems with fit of your full SEM model) and note why you did this. If it is not really causing serious problems you could theoretically leave it in. Either way, you'd want to indicate to the reader that the item is not functioning as intended in measuring your construct. Hope this helps.
Hello, is it very important that there are NO paths between the variables? so only covariances, but no relationships like in a structural equation model?!
Hi there. CFA is a particular type of structural equation modeling. When you say "no relationships like a structural equation model" I'm assuming you are referring to a path analysis using latent variables. Models using CFA are essentially measurement models, where the focus is on testing a proposed factor structure involving a set of manifest variables. In effect, you are addressing the question, "What factor model explains the association among a set of observed variables?" Unlike exploratory factor analysis, where the focus is on building a factor model, CFA is aimed at testing a proposed factor structure. Oftentimes, CFA is carried out en route to testing a path model involving latent variables. It is generally pointless to carry out path analysis with latent variables if your measurement model (assessed via CFA) exhibits low fit. If your measurement model fits the data well, then it makes sense to move towards specifying predictive relationships among your latent variables. Hope this helps!
many thanks for this vidéo, please i'm looking for the acceptable rang of regression weight and standardised regression weight. Have you some references please.
Technically there is no "data" for a latent variable, as it is just defined by the measurement model (as is being demonstrated in the video). Once you fit the measurement model, you can use SEM (structural equation modeling) to draw paths to other latent variables.
Hi there. If you want to specify orthogonal factors, just leave out the double-headed arrows connecting the factors. Of course, this will make your test of orthogonal factors pretty stringent because you are treating the correlation as zero.
thx for the video. Can you maybe include some sources for when you say that for example the tucker louis index should be over .95 . So the viewer can check if the author maybe had some additional information on why it has to be this and this value or if there are maybe some additional conditions under which the value can be understepped
Hi there. Funny you should ask. I just uploaded a new version of CFA with Amos that includes a powerpoint you can download (following the link underneath the video description). There are citations in it. You can visit the video and get the Powerpoint here: th-cam.com/video/bbmOMh1hDpA/w-d-xo.html Thanks for your comment!
By the way, the CFI & TLI at .95 are generally regarded as more consistent with closer fit. However, in the powerpoint I include references, where .90 or above may be considered acceptable.
If the p-value is not significant, then it indicates that the item may not be a good indicator of the latent construct. I don't know if there is any one thing "to do" when this occurs. If you are trying to maximize fit to the sample data, you could test alternative specifications in an exploratory fashion (e.g., maybe modification indices?) to see if the item might load better on a different factor. Or you could remove the item if it is generally problematic for the model and see if fit improves. The only thing about these kinds of empirical strategies is that you are likely going to end up overfitting your model to the data (reducing generalizability of results to other population samples). Really, the question you should be considering is "Does the item I have written adequately reflect the construct I am trying to measure?" If a coefficient is non-significant, then it would appear you have evidence that this is not the case. When this occurs, you may need to either rewrite the question if it does not adequately reflect the construct definition and/or eliminate it if it is unrelated to the definition and/or include new items that do a better job reflecting the construct definition. I could get into a long protracted conversation regarding construct validity, but these are just a few thoughts I had to keep things manageable in my reply. Hope this helps. Best wishes.
@@mikecrowson2462 Thank you for your explanation. Actually, I try to validate a scale into Indonesian language. I look through the data again and try your suggestion. Thanks
Excellent content, you're definitely a subject matter expert. However, your instructions are riddled with the filler word 'um". It was difficult to follow along. I counted 36 in the first 7 minutes. This is a subconscious filler word used when transitioning between thoughts. Check out your local Toastmasters Int'l club. They can help eliminate subconscious filler words from your lectures. Thank you for your post this will assist me in my Stats II course.
Today was my first time using AMOS and your video got me through super quick. Thanks so much!
DEAR VIEWERS: I A NEW VIDEO ON CONFIRMATORY FACTOR ANALYSIS (CFA) WITH AMOS THAT IS HOT OFF THE PRESS (AS OF SEPT 2020). THE VIDEO IS A BIT HIGHER QUALITY AND ALSO CONTAINS A POWERPOINT AND DATA YOU CAN DOWNLOAD FOR FREE UNDERNEATH THE VIDEO DESCRIPTION). PLEASE CONSIDER CHECKING IT OUT AT th-cam.com/video/bbmOMh1hDpA/w-d-xo.html (Confirmatory factor analysis in AMOS with Personality Disorder Scale items (Sept 2020))
Very helpful video! I couldn't get my covariances to appear, but I was able to figure out that I didn't set my regression weights to 1. Thank you!
You are a life-saver! Thank you so much and best wishes from Innsbruck, Austria! 🇦🇹
innsbruck!
I was looking forward to find that Standadized - Unstandardized estimates option tip! Thank you!!
Thank you so much for this video, it helped me a lot while writing my master thesis!
Your videos are so helpful. Thank you so much for making them!
Thanks for visiting Kathy! I'm glad they are helpful. By the way, don't forget to visit my most recent videos on CFA using AMOS:
CFA video (2020): th-cam.com/video/bbmOMh1hDpA/w-d-xo.html
Second-order CFA: th-cam.com/video/r4khWjiePBE/w-d-xo.html
Best wishes!
thank you so much for your efforts. I wish the audio and the video were more synced though, sometimes it would get perplexing as the video has a bit of delay
Thanks for such a good tutorial. Before watching this video, I didn't know what to do with latent constructs and how to measure them. As we know that latent constructs cannot be directly measured and can only be observed from the observed variables. So, how to define them in an application? Now, I know that we are actually choosing one of the observed variables or items and assuming it to have a regression coefficient of 1.
Glad you found this useful! best wishes, Mike
Thank you for this video! It was so easy to follow!!
Thank you for this nice explanation.
I get the error: "An error occured while attempting to fit the model.
An error occured while attempting to read the file, [...]" when trying to calculate estimates. Do you have any idea what the problem could be? thank you!
Thank you so much for your guiding. Its very useful.
Why did you draw all the boxes separately? use the third option on the right in the first column, that draws all factors, variable and error term boxes together
This vid was helpful for me!
Sir, I have a question. I'm looking forward to having your response. I also am trying the CFA using my variables on Advancement. My problem is in the analysis part. There is a dialog box that keeps on appearing and it says "The observed variable, Advancement, is represented by an ellipse in the path diagram". I cannot proceed to analysis. What shall I do to proceed to analysis? Thank you, Sir.
You have to change the figure from an oval to a rectangle since that's how the software distinguish between observed from latent variables.
Thanks for your great instruction.
Very useful. Thank you so much! Keep going...!
Excellent, I learnt a lot
also, you don not need to name every error terms separately, the plugin can handle that
Thank you so much
You're most welcome! Also, just so you know, I do have a much more recent video on CFA with AMOS here (th-cam.com/video/bbmOMh1hDpA/w-d-xo.html). It contains more updated information and supplemental information.
What is "Measurement Error(TD)" termed in AMOS??
Thank you so much! You made it so easy!
Thanks very much Mr,Trey De Jong for response and advise concerning my question.What shall i do for example if five of my latent variable will proposed to create one endogenous variable as an out come.And there is no indicators for the proposed out come.On other word all the latent variables must have indicators?
Hello sir. Nice to see your video. I have a question. What will happen if corellate among laten construct have little score? Is it used in interpretation or only the loading factor among inside laten construct (variable) used?
Good job bro
At 13:56 you say "right-click this button here" but its not clear what button you are right clicking and I feel like I have followed it accurately up to that point but not getting the output you are, and neither am I able to toggle that other button at the top like you are for some reason when you can pressed calculate.
It's ok I fixed it now by removing a rogue item and replacing it with another one that also correlated
Hello i have a question ; I am doing a research and i have 3 independent variables (product type ... etc ) and i have 1 moderating variable and 2 independent varibles i watched the tutorial its very helpful but my question how i can input my independent varible data. I dont have questions for each independent varibles because they are in scenerio based so they are merce in to a scenerio then the participants answer questions about my dependent and moderation varibles. Here is my question how can i enter my independent data in amos. ps; sorry for my english
How do you choose which 3 items to represent the latent construct?
Hey sir i want to ask that if i have 127 items on one factor so how can i graphically represent this data on amos?
Thanks so much for your nice tutorial. How can i get the t-values in AMOS. How can I calculate them? In Regression weights tab, some S.E. values are missing because of fixed regression weights. So i cannot calculate the C.R. ratios/t-values. Thanks for your attention and time.
Hi, found this video very useful! Just wanted to ask...what do you do if one of your indicator variables does not load significantly onto it's factor? I'm planning on doing SEM after this factor analysis so should I delete the indicator variable that does not fit or do I just acknowledge that it did not fit when I write up my research and continue with the SEM? Thanks :)
Hi Catherine, the trick is that the overall fit for your full SEM (i.e, path analysis with latent variable) model is not only impacted by the structural relations you specify among your latent variables, but also by the level of fit of your specified measurement model. I think you could adopt either approach you noted when reporting on your results. If the item is causing serious problems with fit in your measurement model, then you could delete it (as it would also create problems with fit of your full SEM model) and note why you did this. If it is not really causing serious problems you could theoretically leave it in. Either way, you'd want to indicate to the reader that the item is not functioning as intended in measuring your construct. Hope this helps.
Hi Mike, thanks so much for your reply, I think I will delete the uncooperative variable. Your help is really appreciated :)
Thank you!
Is this 1st order or second order cfa?
how can I get youtube vedios?
Can some one tell me what to do if Each of my variable have 14-17 items each?
Is it possible to do a multilevel CFA in SPSS/Amos too?
Hello,
is it very important that there are NO paths between the variables? so only covariances, but no relationships like in a structural equation model?!
Hi there. CFA is a particular type of structural equation modeling. When you say "no relationships like a structural equation model" I'm assuming you are referring to a path analysis using latent variables. Models using CFA are essentially measurement models, where the focus is on testing a proposed factor structure involving a set of manifest variables. In effect, you are addressing the question, "What factor model explains the association among a set of observed variables?" Unlike exploratory factor analysis, where the focus is on building a factor model, CFA is aimed at testing a proposed factor structure. Oftentimes, CFA is carried out en route to testing a path model involving latent variables. It is generally pointless to carry out path analysis with latent variables if your measurement model (assessed via CFA) exhibits low fit. If your measurement model fits the data well, then it makes sense to move towards specifying predictive relationships among your latent variables. Hope this helps!
What if the data is not normally distributed
its a request,sir please use simple English so that, who are watching this video will understand better.
many thanks for this vidéo, please i'm looking for the acceptable rang of regression weight and standardised regression weight. Have you some references please.
please, who can tell me from where i get data for latent variables? because i have only survey questionnaires for only for indicators.
Technically there is no "data" for a latent variable, as it is just defined by the measurement model (as is being demonstrated in the video). Once you fit the measurement model, you can use SEM (structural equation modeling) to draw paths to other latent variables.
my problem is how to specify orthogonal factors, i am assuming that my factors are indipedent so i dont expect them to correlate
Hi there. If you want to specify orthogonal factors, just leave out the double-headed arrows connecting the factors. Of course, this will make your test of orthogonal factors pretty stringent because you are treating the correlation as zero.
thx for the video. Can you maybe include some sources for when you say that for example the tucker louis index should be over .95 . So the viewer can check if the author maybe had some additional information on why it has to be this and this value or if there are maybe some additional conditions under which the value can be understepped
Hi there. Funny you should ask. I just uploaded a new version of CFA with Amos that includes a powerpoint you can download (following the link underneath the video description). There are citations in it. You can visit the video and get the Powerpoint here: th-cam.com/video/bbmOMh1hDpA/w-d-xo.html
Thanks for your comment!
By the way, the CFI & TLI at .95 are generally regarded as more consistent with closer fit. However, in the powerpoint I include references, where .90 or above may be considered acceptable.
what to do when the p-value of an item in section estimate- regression weight is not significant?
If the p-value is not significant, then it indicates that the item may not be a good indicator of the latent construct. I don't know if there is any one thing "to do" when this occurs. If you are trying to maximize fit to the sample data, you could test alternative specifications in an exploratory fashion (e.g., maybe modification indices?) to see if the item might load better on a different factor. Or you could remove the item if it is generally problematic for the model and see if fit improves. The only thing about these kinds of empirical strategies is that you are likely going to end up overfitting your model to the data (reducing generalizability of results to other population samples). Really, the question you should be considering is "Does the item I have written adequately reflect the construct I am trying to measure?" If a coefficient is non-significant, then it would appear you have evidence that this is not the case. When this occurs, you may need to either rewrite the question if it does not adequately reflect the construct definition and/or eliminate it if it is unrelated to the definition and/or include new items that do a better job reflecting the construct definition. I could get into a long protracted conversation regarding construct validity, but these are just a few thoughts I had to keep things manageable in my reply. Hope this helps. Best wishes.
@@mikecrowson2462 Thank you for your explanation. Actually, I try to validate a scale into Indonesian language. I look through the data again and try your suggestion. Thanks
CAN I GET THIS DATA SET ?
The data set is provided as a link under the video description.
How can I find the NNFI index on Amos?
Hi there, the NNFI is called Tucker-Lewis Index (TLI) in AMOS. They are the same.
Thank you
good video #CFA
thanks
Excellent content, you're definitely a subject matter expert. However, your instructions are riddled with the filler word 'um". It was difficult to follow along. I counted 36 in the first 7 minutes. This is a subconscious filler word used when transitioning between thoughts. Check out your local Toastmasters Int'l club. They can help eliminate subconscious filler words from your lectures. Thank you for your post this will assist me in my Stats II course.
Thank you so much
Thanks
Thank you