Thank you so so much noor for this! Though I was a little confused till the very end but that Reye Syndrome example made everything clear! If you can add like 3-4 more examples they would really help. Best!
i spent hours trying to understand the difference between confounding and effect modifier . your video explained the difference very simply and clearrly Thank you so much. Keep up your good work!
Can you tell me if this is right: Confounding: The relation you see is not real, there is something else that is the actual cause of relation. Effect Modification: The relation you see is real, but this relation will only be seen when a modifier is present/absent.
Such a great explanation. My particular case is funny because right now i'm doing a question from UWorld Qbank for Step 1 from Biostatistics and is exactly the same as your example. Thanks for the insights!
Hello Noor. In the example of effect modification, there is no increased risk of DVT in patients treated with Estrogen who dont smoke but increased risk in those who smoke. This shows that estrogen dosent lead to DVT alone who dont smoke. Cant this be called as cofounding due to smoking?
Loved it! Made more sense and last example of Reyes sx summarized it all. So to avoid confounding, do u use stratification? U hinted on it somehow. Thanks lots
Thank you Solomon! To avoid confounding from the start we match all variables (some of which are potential confounders) except the variable we are interested in. So we should match all smokers together and then start asking about alcohol use. Now if we didn’t match from the start but suspected there may be a confounder after we saw the results then stratification should eliminate the confounding effect. I hope this makes sense
Very clear and thanks. but I still have a quick question. could we say there is no association between determinants and outcomes regardless of confounders? (which is mentioned at 8:52 in this video.) I think the etiologic research is interested in finding the causal relationship between the determinant and outcomes. The researchers have to try to eliminate the effect that the confounders make in the occurrence relation but should we say the opinion above?
In 8:50, there’s a true association only in the presence of the effect modifier (age). There’s no true association in adults. Aspirin is the determinant, liver failure is the outcome and there’s no confounders
the part of the question that says "In non-smokers, no increased risk of DVT is evident with the use of drug RR:0.96" Implies that the drug doesnt actually have an effect. While in effect modification the primary variable [drug] has an effect and the effect modifier plays on the extent of the effect either by increasing it or decreasing it... do you get what I mean?
@@nooreweis I did watch the entire video. I really love your other videos. I felt that this video was worded a little complicated. I watched it a couple of times and I understood it though. With peace and love 💞
I have an MPH degree but I haven't understood this so clearly until now. You're a good teacher! Thank you!
Thank you so much this comments means so much!!❤️
Thank you so so much noor for this! Though I was a little confused till the very end but that Reye Syndrome example made everything clear! If you can add like 3-4 more examples they would really help. Best!
i spent hours trying to understand the difference between confounding and effect modifier
. your video explained the difference very simply and clearrly
Thank you so much. Keep up your good work!
It’s my pleasure!
I finally understand the concept. Thank you for simplifying!
I’m so glad Suneet!
I’m going crazy with this topic now on Epi 2, thanks for making this video. In 9 minutes I understood more than reading the textbook.
I’m so happy it helped thank you!❤️
The last example made so much sense! Thank you!!
You're welcome! I'm glad it helped :)
Noor I'm so grateful to you, the Reye's syndrome example in the end really helped❤️
My pleasure!
THIS IS REALLY GOOD. I can't believe I understand everything. THANK U
You’re welcome! Glad you liked it :)
elegant as usual, Very very good examples, Thank you
Thank you so much I’m glad you liked it!
Thanks a lot from the heart.. i got cleared of the concept now ..
You’re welcome Saima!
Very good explanation with precise images!
Thank you!
Thanks a lot for the explanation. I got the exact question (4:00) in Uworld and your explanation made so much more sense.
I’m so glad it helped!
Can you tell me if this is right:
Confounding: The relation you see is not real, there is something else that is the actual cause of relation.
Effect Modification: The relation you see is real, but this relation will only be seen when a modifier is present/absent.
Exactly!
Such a great explanation. My particular case is funny because right now i'm doing a question from UWorld Qbank for Step 1 from Biostatistics and is exactly the same as your example. Thanks for the insights!
You’re welcome! My pleasure
Beautiful explanation. Thank you!!!
Glad it was helpful!
Such a great video, thank you so much!!!
You’re welcome! Glad to help :)
How about intermediate factor (something that underly in causal pathway)? Do you have any explanation for this?
well prepared thank you very much 👍🏻
I'm glad it helped Osman!
Its a good way to explain but it would be highly appreciated if u could come up with more examples
lovely explanation!! thank you so much!
You’re welcome ! Glad it helped :)
Love this video thanks so much!!
Glad you enjoyed it! anytime :)
Hello Noor. In the example of effect modification, there is no increased risk of DVT in patients treated with Estrogen who dont smoke but increased risk in those who smoke. This shows that estrogen dosent lead to DVT alone who dont smoke. Cant this be called as cofounding due to smoking?
very helpful video thank you
You’re welcome!
Thanks alot for the helpful explanation
Anytime!
Loved it! Made more sense and last example of Reyes sx summarized it all. So to avoid confounding, do u use stratification? U hinted on it somehow. Thanks lots
Thank you Solomon! To avoid confounding from the start we match all variables (some of which are potential confounders) except the variable we are interested in. So we should match all smokers together and then start asking about alcohol use. Now if we didn’t match from the start but suspected there may be a confounder after we saw the results then stratification should eliminate the confounding effect. I hope this makes sense
Great Video
Thank you!!
Thank you so much! Helping with grad school epi:)
I’m glad it’s helping :) ❤️❤️
great explanation🤩🤩🤩
Thank you!
Good topic👏
Thank you!
Very clear and thanks. but I still have a quick question. could we say there is no association between determinants and outcomes regardless of confounders? (which is mentioned at 8:52 in this video.) I think the etiologic research is interested in finding the causal relationship between the determinant and outcomes. The researchers have to try to eliminate the effect that the confounders make in the occurrence relation but should we say the opinion above?
maybe is at 8:50
In 8:50, there’s a true association only in the presence of the effect modifier (age). There’s no true association in adults. Aspirin is the determinant, liver failure is the outcome and there’s no confounders
Great thank u❤
You’re welcome!
It was really thorough
Glad you liked it!
once again noor rocked and we shocked such an easy explanation ...keep it up...thank you for ur hard work ..jazakALLAH
Thank you so much! Glad it helped!
Thank you for this ❤
You’re welcome!
WOW THANK YOU😍
You’re welcome!
thank you
you're welcome!
Te quiero mucho Noor 😁
You’re welcome anytime!
Very nice explanation.
P.S. Also loved the donkey sound in the background at 3:00.
😂😂 sorry was recording in the farm
The second question got me so confused
the part of the question that says "In non-smokers, no increased risk of DVT is evident with the use of drug RR:0.96" Implies that the drug doesnt actually have an effect. While in effect modification the primary variable [drug] has an effect and the effect modifier plays on the extent of the effect either by increasing it or decreasing it... do you get what I mean?
I found this video difficult to understand. 😕☹️
I’m really sorry if it wasn’t up to expectations, did you watch till the end? If you have any questions DM me on instagram
@@nooreweis I did watch the entire video. I really love your other videos. I felt that this video was worded a little complicated. I watched it a couple of times and I understood it though. With peace and love 💞
@@tejasviniv6902 I’m sorry again Tejasvini, thank you for rewatching. Will try to simplify my next videos more. All the best on your journey ❤️