Structural Equation Modeling: what is it and what can we use it for? (part 1 of 6)
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- Опубліковано 20 тра 2024
- Professor Patrick Sturgis, NCRM director, in the first (of three) part of the Structural Equiation Modeling NCRM online course.
This video is part of the online learning resources from the National Centre for Research Methods (NCRM). To access the supporting materials (presentation slides, datasets, recommended reading, links to related publications and resources) visit www.ncrm.ac.uk/resources/onlin...
This series is so great! I learn more from merely ten-minutes of watching this than from 10-hours of literature reading.
Lovely! The pace and the language used inevitably lead to a good understanding of the topic in hand. Your efforts are highly appreciated.
Incredibly straight to the point tutorial. Good job. :)
I did not believe I can find such a good file. Really thank you for sharing...
This is a great video. Loved how professor Sturgis lucidly explained and covered all the points. Thank you NCRM for this video.
Thank you. This is helpful. I'm new in quantitative research and only learning about this concepts a PhD level. Learning them from the book or article can be confusing but this video is making it easy for me to understand
This is fantastic, not only understandable but also presented in a very interesting way. Thank you so much!
Wow, this is very simply explained and yet it's also rather comprehensive. Thank you so much for this content!
Thank you so much for this INCREDIBLY helpful and well-explained video! I will watch all your videos. You are providing free education and spreading knowledge. Thank you!
A wonderfully clear explanation of SEM. Each slide was a revelation.
Absolutely superb. Easy to comprehend and explained so lucidly. Thank you
The lecture is amazing! Clear and concise. Thanks!
Great structure on the lesson (no pun inteded), brilliantly put together. Looking forward to the other two.
Well explained, such a helpfull video! Great prof! Thank you!
Hi Patrick, thank you for your video. It is the first video I have ever seen that explains the academic/research approach that starts with non-academic communication. This is what precisely new students need - explain things in their language, not at an academic level, if you try to support their academic journey.
Making a difference deserves to be congregated and thanked. Thank you again as a newbie research student.
Wow. I've studied SEM so many times and you explanation of how true score (latent variable) and error "caused" the measures is the most clear one I've ever heard. Most people are surprised the arrow points the way they do so it is great you explain so clearly.
I am impressed with the simplicity of explanation /presentation
Thanks professor for a very clear explanation, loved it.
Fantastic and clear explanation. The more I work with SEM the better these videoes become.
very clear and concise explanation. As many already mentioned, watching this short vdo can a better understanding than spending hours reading books on one's own. Thanks professor for making such an excellent vdo to share your knowledge.
Thank you so much Professor Sturgis!This is fantastic indeed, i gained a lot from this presentation.
Excellent quality and perfectly structured. Many thanks!
this is really good! thanks for being straight to the point :')
This video is tremendously helpful! thank you so much!
Excellent explanations, hope to see some practical examples in future tutorials.
Very nice, clear and useful talk. thank you very much Prof. Sturgis!
Awesome, thanks for sharing, prof..
Amazing series Professor Sturgis. I came here first to learn SEM, and I am glad I did!!
i am literally weeping with joy at this!!!
Very easily and well described. Thanks for posting this..
Great explanation. Thank you for developing this video!
This was super helpful. So well explained! Thank you very much.
Quite impressive, always thought it was difficult until I meet him teach it so lively
Great professor!
Great video, very useful! Thank you for sharing with us!
Prof. thanks for such an excellent lecture. best wishes.
Dr. Bilal
Thank you very much! Very clear, easy to follow and so informative! Super !!
Amazing. I am able to understand everything. Love you all!
Thanks these videos have been particularly helpful.
thanks a lot for this informative video. It made my learning easier in SEM and this is gonna be helpful for my Ph.D. research. I'm looking forward to enhancing my understanding more on it. Grateful to u for this simplistic sharing of knowledge.
Thanks Professor for a very excellent lecture :)
Excellent presentation, thanks!
Excellent and clear presentation. Great!
Great lecture - tremendous effect on my understanding of SEM
Excellent introduction to SEM. Thanks !!
brilliantly explained tutorial - Many thanks to professor
Super! Thanks Professor, really easy to understand your videos.
Excellent stuff...thanks Prof
Great Professor, thank you
Thank you very much Prof Sturgis! Greetings from Germany
Thanks professor! very good and clear explanation
Great video. Just one question:
in the "indirect" effect, x1 and x2 are not correlated?
Thank you so much Prof ... though the lecture given was 4 years ago. Well said lecture and good lecture.
very interesting Prof. Sturgis!
Beyond imagination .. a seriously fantastic explanation.
This is so helpful! Thank you :)
Best explanation about SEM
Thank you so much. It is impressively well explained!
This is very good Presentation. Every body who conduct social science research must watch this.
This is phenomenal! Thank you!
Excellent explanation. Love this ❤️
Thank you for your effort and sharing, this is very understandable and helpful! :-)
awesome job, thank you
You are Super Human. super Man.. the true teacher .. Huge Respect
good tutorial, it can make me more understand. thanks for sharing
Thank you, Professor. very understandable video.
Thank u prof. jazakallah
Very clearly explained. Thank you!
Great video!
Thank you for the explanation! I have one question regarding the path diagram at 22:58 in the video: You are comparing this diagram with the multivariate regression and stating that X1 und X2 are independent. The last assumption is of course needed in the multivariate regression to avoid multicollinearity. But why is the diagram showing some relationship between the two variables X1 and X2 by the arrow? Isn't this introducing some kind of relationship between the explanatory variables? Looking forward to your response!
Thanks from Vietnam.
Really too good and helpful. Although I have some questions related to my research work. Is it necessary that the dependent variable to have indicators to measure it. I have several factors to measure the impact of independent variable on the dependent variable (performance ). Please let me know.
Is your centre offering research visits/collaborations for the doctoral students especially from EU
you did great! So clear and understandable!
Really helpful. Thank you
I thank you so much Professor for your helpful Lecture.
Thank you Sir. It is very helpful for me. Wish you great success Professor Patrick.
Very informative and helpful
Well.. starting my proposal.. so I need this now. Thank you.
this was very concise and helpful! Thanks!
Thank you professor for explaining SEM with neat presentation.
many thanks for tutorial
very interesting and valuable
Terrific lecture
Great explanation regarding covariance based SEM. It would have been great to coin it as such (covariance based) and help novices to understand the difference between covariance and variance based approaches.
I'd love to watch a clip about that too Henk
Awesome video, thank you prof
Thank you very much sir, You explained so well. I want to analyze an accumulative data of 10 countries. Do i need to constrain country dummy variables with 'regression weight =1" for fixed effects? or i don't even need to add them in path diagram? Thanks in anticipation
thank you very much Professor Sturgis
wooo... very clear explanations
Well explained, Thanks so much.
Excellent explanation!!
Well explained
Well presented, thanks.
big thank you
Good day Prof Patrick. Your videos are very helpful
i am new to SEM. i am really confused why are constructs drawn using ellipse while making the measurement model may become rectangles and squares while making the structural model. please help me.
you are an absolute hero
THANK YOU PRO.
Great video. Thank you
could you please say somthing about the diagram in your last slide ?how can we read the relation between the cited variables
thanks, professor the lesson is very helpful.