Structural Equation Modeling: what is it and what can we use it for? (part 1 of 6)

Professor Patrick Sturgis, NCRM director, in the first (of three) part of the Structural Equiation Modeling NCRM online course.

[aliothrosen]

This series is so great! I learn more from merely ten-minutes of watching this than from 10-hours of literature reading.

[Kerem-hmxl]

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.

[lihlendlovu]

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

[lingfeitang]

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.

[kriangkraicherngwiwatkit]

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.

[reanalytics]

Quite impressive, always thought it was difficult until I meet him teach it so lively

[baagh]

I did not believe I can find such a good file. Really thank you for sharing...

[bobbyyankey]

I am impressed with the simplicity of explanation /presentation

[martinandersen]

Fantastic and clear explanation. The more I work with SEM the better these videoes become.

[englishstudies]

Lovely! The pace and the language used inevitably lead to a good understanding of the topic in hand. Your efforts are highly appreciated.

[rohitekka]

This is a great video. Loved how professor Sturgis lucidly explained and covered all the points. Thank you NCRM for this video.

[sarojadhikari]

Thats really the easiest way of learning SEM. Great lecture

[Spiray]

This is fantastic, not only understandable but also presented in a very interesting way. Thank you so much!

[martin-luthertopico]

Incredibly straight to the point tutorial. Good job. :)

[makhosimadimabe]

Thank you so much Professor Sturgis!This is fantastic indeed, i gained a lot from this presentation.

[sarathchandran]

Thanks professor for a very clear explanation, loved it.

[gsiyoum]

I thank you so much Professor for your helpful Lecture.

[davidjenkins]

A wonderfully clear explanation of SEM. Each slide was a revelation.

[liwenzhang]

Very clear and simple explained. Thank you so much!

[jedidiahsingco]

Wow, this is very simply explained and yet it's also rather comprehensive. Thank you so much for this content!