Odds Ratio, Relative Risk, Risk Difference | Statistics Tutorial #30| MarinStatsLectures

[@Sazzienator]

Doing a masters degree in Public Health/Epidemiology and Im bad at math! I felt so so lost until I found your videos, thank you from Ireland

[@Marco.saviatto]

It's really nice the way that you focus on the concepts and not on the calculation. Also, nice effect you use for writing on our screen hahaha. Already subscribed!

[@LeotheMarvellous]

Very informational video as always! I will keep my eyes on the papers where those terms are used...

[@Camdino55]

Very well explained, thank you so much!

[@marwamokhtar8469]

Great , simple , and to the point , thanks for your efforts

[@sophiaredwall5879]

Great 👍 You are a legend And I can’t believe we have to know this for secondary school GCSE Statistics

[@marinstatlectures]

thanks, glad you found it helpful. and id say not just for school, but knowing statistics is a huge asset for your entire life....ive been able to make much better decisions in my life once i learned about statistics and probability.

[@nathannguyen2041]

Are there distributional assumptions when doing the RR and oods ratio and confidence intervals?

[@RingChewe]

thanks a lot. I finally understand the difference between these terms.

[@mranjiny3963]

Thank you so much sir ☺️ it's useful for my exam ❤️❤️❤️

[@starlvinharryboss]

Thanks a lot, i really appreciate that concept.

[@carolineoreardon2229]

Great video!

[@faresel-katri7518]

Excellent review Dr. FARES EL-KATRI

[@marinstatlectures]

thanks, appreciate that!

[@carlwood7933]

Hi Marin, thank you so much for these excellent posts, we can get an odds ratio with epiR, also, we can calculate the odds ratio with regression through coefficient , could you give some thoughts about the difference?

[@marinstatlectures]

They’re the exact same thing (in the case of one X one Y, both dichotomous). But with logistic regression you can calculate an OR adjusted for other variables (Eg) the OR for X1 effect on Y, adjusting for X2, X3 and so on. Hope that makes sense

[@dellazhang5785]

very nice work! help me a lot! Thank you so much! Could you add some content about longitudinal data analysis?

[@d-talks90]

Thanks, man! Can you suggest the books you refer for your teaching material?

[@marinstatlectures]

i domino really use a book, for my courses, i use a set of notes that i have written myself...they are very much like a text, but nothing that is published.

[@marcoventura9451]

@@marinstatlectures We looking forward for your notes!

[@DustyLambert]

You mention that you can take this a step further and get a p-value. Is there a video on that when considering exposure? (Finishing my dissertation, wish I would found this channel sooner!!)

[@winnifredadiri9259]

Thanks for the lecture, I enjoyed it a lot. Do you have a lecture for sample size calculation. Need to understand sample size calculation for a comparative quantitative variable

[@marinstatlectures]

We have a video showing power calculation for one quantitative variable, although doing this for, say a difference in means, is nearly identical..you can see that here: kzbin.info/www/bejne/qKq6oH-nmpWmmpo

[@melamsurong7747]

If RR is 3.3 (95% CI, 2.4-4.3 p

[@may5362]

Well-explained, and concise video on these concepts! Thank you for your help! Keep up the good work :^)

[@willso93]

Did you learn to write backwards for this video??

[@marinstatlectures]

no, but it certainly looks that way ;)

[@willso93]

@@marinstatlectures i'm impressed!

[@marinstatlectures]

lol, the way it works is I'm writing on a piece of glass with a camera on the other side of the glass. after recording, the image is mirrored, so things appear the right way instead of backwards. it's a cool and simple idea. search "light board" if you want to see more about how it's done

[@willso93]

@@marinstatlectures it's interesting, but I'm not sure it's necessarily something I'll get to use other than perhaps in a few presentations - cheers!

[@hemakumargantepallidataandai]

awesome

[@marcoventura9451]

Great!

[@sulaimanhashemi4754]

thank you

[@marinstatlectures]

You’re welcome :)