Confounding

[@katomoon6170]

I think a confounding variable is an extraneous variable (non-treatment) variable which we are not testing in our experiment / study but it (the confounding / extraneous variable) has an effect on the response variable. I will be glad if I'm corrected but that's how I understand this concept. Thank you from Uganda East Africa

[@brishannahinton650]

thank you so much for this!!! I just was NOT understanding confounding variables but you made it so easy so thank you sincerely from the bottom of my heart! -a psychology student

[@docrock15]

Put playback speed at 1.25x Thank me later

[@duartesilva7907]

I'd say 1.5x. And it's still too slow..

[@laylajameel1836]

I would say 2x

[@smurfaka]

Thanks for a good video. Not sure if the arrow from smoking coronary heart disease should be double though.

[@rossc8160]

Agreed - coronary heart disease does not cause smoking so it should be a one way arrow. Otherwise this is very good.

[@KK-rh6cd]

It was great explained, this really helps me to complete my assignment. Thank you for making this video.

[@Aadicura_Taniya_Time]

Thank you!! Very excellent video

[@tomf.7360]

Thank you so much for posting these videos! Very well explained and clear. It will definitely help me doing my Epidemiology exam. ;)

[@tsosamph_ches5832]

Oh my goodness, you take the absolute sting out of epidemiology. Thank you!

[@lisama2748]

Omg I love u after like 8 years... u just saved my test

[@sdal4244]

Firstly. Thank you Liz for this, you saved my Life. Put playback speed at 1.5x if you are native speaker. Put playback speed at 1.25x if English is second language. Thank me later

[@siIverspawn]

I'm not a native speaker. I put it at 1.75x

[@panchitoborja]

Madam you are truly extraordinary! Very well and clearly explained!

[@tymothylim6550]

Excellent video! Liked how it's clear regarding the issue of establishing causal relationships! :)

[@yvonneurquieta1864]

Thank you Elizabeth! greatly appreciated! Do you have any videos for Effect modifier by any chance?

[@KhadijahYeedah]

Thank you so much for explaining ❤️❤️ anyone else from 2024 😍??

[@jazzyproductions9806]

I was looking through my playlist from when I was in 2nd-5th grade and I came across this- I’m honestly so confused and concerned

[@黄昭-z7w]

I am wondering does the present of confounding always mean a spurious association between risk factor and outcome? Is it possible that confounding can also mask the association between them?

[@ABo-jr8pg]

It can! It just depends on which relattionships are positive and which ones are negative.

[@asaiasoluna3344]

how does confounding variable affect the validity of the study?

[@highndreamin]

thank you u are so good at explaining that i understood just with the first example thank you so much

[@MrGotro1]

wouldn't age and physical activity be negatively related. As age goes up, physical activity goes down?

[@estherernest5353]

At last i came to understand the concept of confounding.. thank you indeed

[@ABo-jr8pg]

Isn't fluid intake related to blood pressure though?

[@Moebik]

Where were you? I finally find my place to rest. Thank you so much

[@siddarthramkumar8763]

Could it be both?

[@shortandsweet2767]

Can you explain about blocking variable in statistics, please?

[@toyinokunuga3605]

Thank you so much!! That was made so easy to understand xx

[@HeyYall398]

Excellent 👌👍

[@jeneseJonEs]

How do I include confounding in a review question?

[@AnkushSharma-zv5hv]

last two examples cleared everything

[@sherinvgeorge6805]

Excellent video, thanks..

[@wenkangma4301]

Come before my epid exam. Clear and helpful. Thank you!

[@sabrinayasmin1359]

Awesome explanation

[@varsshasangani8699]

Can u explain confounding in handedness

[@servicetothecross8914]

Best explanation ever!!!!! 🤩🤩🤩🤩🤩

[@loneayat1973]

Thanks mam What kind of variable now blood pressure is ..... Which is caused by during experiment

[@extramiles3831]

total? partial? and balanced confounding? please :)

[@SoichiHayashi2014]

Hello! Thank you for this video. Everything made sense until the very last example. Earlier, you gave the example of "young age" as confounder, but then you replaced that with blood pressure and all the sudden it is not a confounder. I am failing to see the difference. Why could "age" be a confounder but not "blood pressure"?

[@vivianalomeli2254]

I WISH you were my professor. Mine is so bland. I like your teaching

[@furongli361]

I am wondering whether those arrow directions are right, in particular to physical activity and age

[@GradualReportSerbia]

Looks like there is an error in there

[@hemoisthebestemo1234]

The arrows are correct. in this example she was saying that’s it’s a negative (inverse) correlation, meaning that the younger you are the less likely you’re getting MI, and the more you engage in physical activity the less likely you’re of getting MI

[@hemoisthebestemo1234]

The confounding factor is that younger people are more likely to to exercise so it’s hard to tell which of these two is protective from MI

[@aidangollaglee3531]

Yeah they were wrong- she drew young age as a mediator. To be a confounder you need arrows pointing from young age to both physical activity and MI

[@mustafeibrahim-xx1fk]

@@aidangollaglee3531 i agree you right. i was thinking like that.

[@zahirraihan2402]

Great!! Helpful. Thanks

[@muwongejosephjunior6131]

Thank you, understood it better watching this video

[@hashemfathi1646]

Best explanation ever

[@archanam5522]

Nice explanation thank you mam

[@persephone1015]

This was amazing, thank you!

[@adityachouhan5589]

classic explanation

[@wisamtariq4412]

Great explanation... Many thanks.

[@yasiralsarraj9235]

Super helpful... really appreciate the effort

[@omarkhaled9026]

thank you, i hope my doctor teach like you

[@TheProfessor1908]

Awesome! Thanks.

[@theobserver5600]

Best explanation ever! Thank you so much

[@midozakaria7976]

really merci ...v beutiful videos

[@d7omi111]

thank you, I was about to give up.

[@youssefnasrallah1660]

Thank you a lot . its so helpful

[@austina696]

Well done

[@tokfooqueen]

thank you

[@v.tunglc]

clearly explained.

[@imadsaddik]

Thanks

[@zakorato]

WTH--i mean look how good you are--thanks alot

[@multipurpose1530]

Last two examples confused me again . Its not an easy task when you are doing confounding, mediation and interaction simultaneously

[@sidraashraf4731]

Thanku mam

[@mgmmac]

good vid

[@bravething2011]

thank you so much :D

[@samon3065]

I'm 68 and planning on competing in the olympics, I see a positive relationship between age and physical activity.

[@kocur4d]

Association does not imply causation! This is what my statistic book has written down on every page. How come you are throwing this causes this and that causes this all over the place? :)

[@MelbourneMaster]

These examples are so cut and clear that your argument is basically invalid. But yes sometimes it can be difficult to deem something an association or causation.

[@MelbourneMaster]

Your example with age is throwing me off. Usually age is an effect modifier. Is it because you portrayed age as a dichotemous variable i.e young or not young that it works? Age and physical exercise would be a continuum spectrum where physical activity would drop gradually as age increases, therefore this is a bad example since there is no singular point where you suddenly shift from being young to not being young anymore. Age is almost always an effect modifier in my opinion, as effect modifiers are usually biologically rooted.