The updated Stata program also adds how to do propensity score matching using the psmatch2 package, similar to the analysis done with the pscore package. At 17:02 in the video, REDIFF=RE78-RE75 is the difference in outcomes in the after and before period for the difference-in-differences model.
Thank you so much, it was very informative and very well explained. I was wondering if you can name a paper which has used this method, so I can use as an example for reporting the results.
Thanks for uploading, you have calculated the treatment effect on treated (ATT), can you please mention the command for calculating average trt effect on whole population (ATE). thanks
Your video is so informative. I can follow the logic until the nearest neighbor matching. But after I see 185 vs 431 observations after the match. How could I show all of them as a dataset? So I can run regression based on it.
The updated Stata program also adds how to do propensity score matching using the psmatch2 package, similar to the analysis done with the pscore package.
At 17:02 in the video, REDIFF=RE78-RE75 is the difference in outcomes in the after and before period for the difference-in-differences model.
You could not have made your explanations any easier. Thank you so much for such an insightful video on STATA commands and Propensity Scoring.
This is one of my favourite channels on UA-cam. Thank you very much!
It is wonderful all the content that you have prepared for the interested public. It has helped me too! Thank you very much from Brazil.
Many thanks for this comprehensive, clear and concise lesson. I enjoyed it and it has added real value to what I already knew.
Thank you very much! Your series of videos on PSM are very helpful to me!
Thank you for sharing this, it helped me a lot!
Greetings from Chile
Extremely good. very useful
Really nice, very useful... nice and very thanks
Thank you so much!!! This video is very well explained and easy to follow.
This has been really helpful. Thank you very much for sharing the information.
Excellent! Thank you very much. Love u for the rest of my life
nice video. much much appreciated. applied learning from this video in my research
Thank you! You've been always very helpful!
Excellent explanations! Thank you very much!!!
these videos are fantastic, thank you!!!
Thank you very much Ani! I really enjoyed and learned a lot form your videos. Please keep up the good work!
Best, Najib Khan
thank you so much for uploading! it's very useful and helpful!
Thanks! You're a life-saver
Thank you for your wonderful explanation
Thanks so much for this post- so helpful
Thank you so much! This was extremely helpful
Fantastic tutorial. Thank you!
First of all I want appreciate you. Presentation is nice and easily readable how to use PSM. If you have on efficiency please give lecture practice.
Thank you. It is very helpful.
i enjoyed the video. thks a lot
Thank you for the video. I really helped me.
thank you ... you are the best...
thank you!! this is perfect!
Great
Thank you so much for your guidance. It really helps me a lot. Knowing that this analysis method not really popular yet in my country.
DR. THANKS FOR YOUR VALUABLE EXPLANATION. Dr. Would you please explain how can i calculate REDIFF variable?
Thanks, pretty useful! I´m amazed on how can Stata solve a problem that requires so many decisions :0
how to make gaph before and after matching?
Thank you so much, it was very informative and very well explained.
I was wondering if you can name a paper which has used this method, so I can use as an example for reporting the results.
Thank you Ani. Is there anyway I can compare the balance of control variables before and after matching just like the command pstest (in psmatch2)?
Thanks for uploading, you have calculated the treatment effect on treated (ATT), can you please mention the command for calculating average trt effect on whole population (ATE). thanks
Your video is so informative. I can follow the logic until the nearest neighbor matching. But after I see 185 vs 431 observations after the match. How could I show all of them as a dataset? So I can run regression based on it.