Hello Ehsan, I need a class on Rstan, can you help me learn for my epidemic stochastic models?
@AB-sl1jx5 ай бұрын
Thank you!
@AB-sl1jx5 ай бұрын
Thank you!
@LanXia-z9g6 ай бұрын
Great video,thank you so much
@ishmail27686 ай бұрын
Great talk
@simonederzi14127 ай бұрын
hello, this website is not working anymore. Could you help me? I need to install Winbugs on my computer...
@gregorycala47757 ай бұрын
bad
@bayuhasmamawhailu14079 ай бұрын
THANKS IT IS NICE. KEEP IT UP. Because it helps my problem
@nurlailatuzzahra695710 ай бұрын
Hi, thanks for the clear explanation, where can we get the code for the example graph that is free to access?
@rafeyferoze476910 ай бұрын
Everytime I try to run this, it gives me an error that I don't have the package "optmatch". Can someone please help me?
@ስብሃተእግዚአብሔር10 ай бұрын
Thank you so much for the introduction to causal inference. Would it be possible for you to share the slides and the R codes?
@phoebussmile578011 ай бұрын
hi ,is anyone know how to fix the issue ? demo_e<-nhanes('DEMO_E') simpleWarning in download.file(url, tf, mode = "wb", quiet = TRUE): downloaded length 0 != reported length 0.As followed the course but the function nhanes('DEMO_E') is not working
@Willi_Zhang11 ай бұрын
many hanks for the video. I came across a recently published paper (onlinelibrary.wiley.com/doi/abs/10.1111/ejn.16084) about interpretation of MLR model, which is RRR (ratio of relative risks). It seems that RRR is quite difficult to interpret when studying association between risk factors and diseases.
@aldelucc Жыл бұрын
Thanks! it was very difficult to find information about this and your explanation helped me a lot!
@mairaluchinicosta4877 Жыл бұрын
Like in your previous video, I cannot find the files you are talking about. Where can I download the demo_bpx.csv file from NHANES? Thank you
@Jennifer-g1t1x Жыл бұрын
damn if it weren't for that difficult-to-understand accent, I may have watched the entire thing. But it was too hard to understand.
@wilberforcejahonga194 Жыл бұрын
This is too fast. wolololo
@-SopanPatil Жыл бұрын
link to download the following pdf
@colouredtwista Жыл бұрын
Hi there. Do you have the code for this please? I can't seem to access it using the link above
@kayrambolage Жыл бұрын
How can I conduct further analyses on the basis of the propensity score matched groups?
@polinarabotyahov9807 Жыл бұрын
Really useful, thank you!
@herjunobaguswicaksonoputro1889 Жыл бұрын
Really enlightening! i've used it to understand the basic concept of ATT and ATE in econometric class
@mirentamayoelizalde1252 Жыл бұрын
Great explanation, thank you so much!
@tobiasjung8198 Жыл бұрын
Great tutorial. Thanks. I may have overlooked that but where can I get the files with the sample data (e.g demo_csv.csv)?
@ankonabanerjee1381 Жыл бұрын
Khoob Dhonyobad Dada
@大学生音楽が好きなマイメン Жыл бұрын
thank you for the great explanation! But I still have a question, then what difference between ATT and ATNT especially when the calcuration??
@user-dl8le5cs6t Жыл бұрын
Hello, Can I get the link to the previous lab where we download the data for R?
@yavarfadavi1234 Жыл бұрын
Brilliant! Thank you for the great explanation! Keep it up please
@letatamiru2341 Жыл бұрын
Excellent
@user-dl8le5cs6t Жыл бұрын
Is there a link to this documentation?
@user-dl8le5cs6t Жыл бұрын
How do we incorporate the weights into the modeling. I am asking in terms of the coding.
@osupermono Жыл бұрын
Hi Ehsan! very good video! Greetings from Peru!
@grecheltaucare9012 Жыл бұрын
Thanks for the video. Where can I have access to the whole course and material?
@tonycardinal413 Жыл бұрын
thank you ! Does the assumption for poisson regression mean that the mean of all the Y values of the observed data points must be equal to the variance of all the Y values of the observed data points in the scatter plot? Or does it mean that the mean of all the oberved the Y values pertaining to a certain x value (each x value) must be equal to the variance of the y values pertaining to a particular x value? thanks !
@ЛюдмилаКшнясева-я5ш Жыл бұрын
What ... about Gama-reg instead OD-Poisson, if all y>0???
@thejll Жыл бұрын
Nice video! My eyes are getting older, however … perhaps you could use a larger font?
@subharthipradhan5987 Жыл бұрын
is there any lecture on strata to cover this area?
@muhammedhadedy4570 Жыл бұрын
Thank you for the amazing tutorial.
@张东-r4l Жыл бұрын
Dear teacher, could you share the materials of lab4 class? Thank you very much.
@eylemtasdagitici Жыл бұрын
Thank you for the video. According to Baron and Kenny, if there is an insignificant relationship between the independent variable and the dependent variable, the full mediation effect occurs, and if there is a decrease in the relationship between the independent variable and the dependent variable, the partial mediation effect occurs. it's called. My analysis revealed both a decreased relationship and a nonsignificant relationship. How should I interpret this situation?
@Ex0722 Жыл бұрын
This is super helpful and clear. Thank you so much!!
@suchitrakulkarni70152 жыл бұрын
Great video sir, beautifully explained. Sir, I wanted to know if you have video lecture on instrumental variable aswell. I went through the playlist, couldn’t find. If not, I would be really grateful if you make video on the same. Thanks!
@qudraterazzaque45872 жыл бұрын
Beautifully explained. Really appreciate your effort
@m.gryphius88512 жыл бұрын
Hello Mr. Karim, do you have a reference for this method of imbalance diagnostics and which other methods for variable adjustment selection do you have in mind? Regards, Max
@imwoman36732 жыл бұрын
Gem 💎
@alebabua2 жыл бұрын
Very helpful video, thank you! Only complaint is that the volume could be louder.
@tuanatnguyen98782 жыл бұрын
Really useful tutorial !! Thanks a lot
@abdullahabdelaziz59592 жыл бұрын
Hi Dr. Karim I benefited a lot from your lessons. Do you make the slides available?
@natagomesdelimastavinski54762 жыл бұрын
Please, may you post the link of the book you used?
@sijibobo25232 жыл бұрын
👍i am learning Survey package to analyse nhanes database. your video is very good,thanks for your hard working.