Nicely explained, Thank you maam

Thank you maam

Important and informative

Lecture clearly explores how ethics important in research

Thanks

It's a good information 👍

Thanks for providing this information 👍

Thanks for providing this content 👍

It is informative 👍

Thank you for explaining about research ethics in detail and knowledgeable session

Thank you so much for giving us information about the importance of research ethics..

Thank you maam

Informative

Clear and detailed explanation about Research Ethics

In equation 5, why did you substitute Yi once with 556 and the other with 511? Shouldn't both be 1067?!

This is very informative. Thanks to all those who shared their knowledge and understanding.

6:44

I have watched this lecture multiple times and I always come back to it. PRofessor Abbott is one of the reasons I fell in love with Sociology.

Is the Fife dataset available?

i have latent variable which is measured through 2 items, so to avoid the probleme of identification, can i use the score of the two items and treat it as an observed variable?

What is the link for this example? Logit or Probit?

Excellent

Thanks a lot!

Thank you for Valuable lecture on Research Ethics

Thank you for informative session on research ethics.

Ethical Theory : Deontology, consequentialism, virtue ethics, value ethics, and indigenous research ethics. Greatly explained.

That was very clear and helpful, thank you for sharing your work!

Insightful

Nice explanation

Good

Well explained

Easy to understand..

Enriching video!

Clear & detailed explanation

Well explained

Thank you so much

I'm a grad student at ASU. Your text book is required reading reading for our intro to research and evaluation course. I found that even though I have your text book, it helped me to hear your live explanation on multiple topics. Thank you!

Awesome video 😊

A short but clear articulation.

Excellent videos!, please can you profoundize about categorical variables and SEM modelling?

Thank you very much.

nice one

Absolutely excellent video. Thank you so much!

Thank you for your excellent presentation

It is a computational program - contrast with experiment

This lecture is straightforward and easy to understand! Thank you so much for sharing it! There might be a typo in the slides of "Step 2 Estimate measurement error". The number of observations assigned to "abstainer" should be 5 instead of 8?

the refernce at 9:53 has expired, is there a change to provide an alternative link to practice this along? stats.oarc.ucla.edu/other/dae/ordered-logistic-regression -expired stats.oarc.ucla.edu/other/dae/ - alternative model data.

Thats really the easiest way of learning SEM. Great lecture

Useful

Nice