Part 1 of 3 (Interpreting Odds, Risk, and Rate Ratio Results with 95% CI)

[@ZiyadHBakr-tl2ib]

Probably the best video that explains the concept of hazard ratio and confidence interval. I thank you good sir for this great video

[@gesha2001]

You saved my life. I love you so much. God bless you🙏🏼🙏🏼❤️❤️❤️

[@khairillrassidy1569]

This is a succinct and best-explained video for OR and CI. Thanks!

[@drJospaulLukas]

One of the best explanations for Odds ratio and confidence interval. Thank you.

[@adelaredding1594]

Thank you so much!!!!! you are the best!!! clear, direct, simple!!!

[@mr5537]

The best video explained Odds ratio. Thank you, Jason:-)

[@313289]

Thank you! Very helpful.

[@nataliaabesada162]

thank you so much this has been really helpful.

[@aminabbyy]

this saved me! thank you very much

[@selenamakeachange]

very helpful

[@klothzmania781]

what is the term mean statistical precision of the findings? 0R is 12.56 p-value is less than 0.001 95% CI (4.62 -34.15) . The CI window is wide here ,what could be the reason that small sample size?

[@nokajaafa]

Cool stuff

[@colors41]

He knows how to teach

[@priyankachaudhary8950]

Thank you..helpful video..can you please also explain how to interpret the odds ratio for a paper in detail..for example..if the OR is 0.67..is it that the odds of developing the disease in a patient is 0.67 times lower? How do we write that?

[@recreationalstats2219]

Yes, the odds of developing the disease in the patient would be 0.67 times lower than the reference group; however, if it is continuous variable, it would be for each increase in fruit consumption per day (maybe age in grams), the odds were 0.67 times. Please know that when OR values are below 1.0 though, as you may see in the later videos, it is better to think and speak of them in percentages for interpretability. For example, if the OR is 0.67, and it is significant, it is much easier to speak about it as being 33% less. For further example, persons who consume dark fruits daily have a 33% (1-0.67) reduced odds of the outcome compared to the reference group (which may be people who do not consume fruits daily). Another example for a continuous variable is like so... if fruit was measured in dekagrams (10 gram units), for every dekagram of fruit consumption, there was a 33% reduced odds of disease. For OR values of 0.89 (0.81-0.97), you may say that for every pint of drink, there was an 11% reduced odds of whatever.