Perfect info. Big thanks

Thank you so much, this is so helpful

Thank you so much ❤

Definitely one of the best explanations I’ve seen

Very nice explanation sir. Which software have you used for doing the animations sir?

by far the best video on internet... amazing

This was exactly the clarification I was after, thank you.

thank you. simple explanation.

Thank you so much for explanation and context. Finally, I got it 😊

Did the post-test probability video ever happen?

Best video on this subject to date.

Do you not upload anything anymore marc? I've always found your videos helpful.

@10:16 working across the rows wouldn't the NPV be 7/17 = 41.2% rather than 7/19 = 36.8% as you have listed?

When to use RR, OR, or HR? Please help to clarify on this.

All questions; theory and practical applications answered.

What are real life examples of inaccurate application of tests? COVID? Cancer Pre Screening?

Excellent explanation of the topic. Well done.

I think I finally got it. I'm not describing the entire bit, but the only thing that made it clear to me. There are TWO variables. P variable and Alpha variable. Both variables get values. The alpha variable gets a standard value that is decided by the scientific field. For example, Alpha is set at 0.01 in drug testing. But Alpha variable is set at 0,05 in psychology. P variable is a variable that gets it value from the actual test. The value that the P variable gets must be smaller than the value of the field-specific value of the alpha value. If the P variable's value < Alpha variable's value, then we reject the null hypothesis. However, if the P variable's value is larger than the value of the Alpha variable, then we stick to the null hypothesis.

Best explanation love the visual!

lol i got it 1 minute in, thanks

Thank you so much

Awesome, thank you so much!

very helpful

Bayes' Theorem and Breast Cancer Screening with mammography. Please update and re-upload this excellent informative video using current scientific data. Sensitivity and Specificity of screening digital mammography in a recent extensive Norwegian clinical trial were 54.1% and 94.2% respectively. So:0.01x0.541 0.01x0.541 + 0.99x0.058 or 0.00541 0.00541 + 0.05742 or 0.00541 0.06283 or 0.0861 or 8.61%! If a woman receives a positive mammography result for breast cancer the probability she actually suffers from the disease is only 8.61% Reference pubs.rsna.org/doi/abs/10.1148/radiol.2019182394

Thank u so much! You made this concept very clear for me ( which I was trying to understand since months).

shouldn't it be 7/17 for npv?

i just watched your four videos , you are a genius period

thank you for good lectures

Dear Dr. Campo, I did two different test for detection of a bacteria in the same population. Is it possible to calculate PPV, NPV, Sensitivity and Specificity of each test Separately with out gold standard ? Could you guide me please. Thank you for your consideration and confirmation would be appreciated. Sincerely, Narjes

Thank you. I really understand your presentation and it make sense for me for the first time

Why do u have such low views, Ur really really good.

Thank you, ur a great teacher. Too bad u only have few videos.

great recording, very useful

Sounds like Bill Murray

Thank you soooo much..

Hi Professor Campo, the numbers during 8:42 don't seem to make sense, across the rows. Since 82+1= 83, not 81. I think it was supposed to be 80TP and 12 FN to even the numbers out. Please let me know if I'm missing something. This is Diana Y.

This video was very helpful, thank you!