Another comment for potentially confused mathematicans: The hazartd is not actually just the rate of change of the survival function (dS(t)/dt) but it must be further divided by the vylue of S(t) itself. This results from the definition of the conditional probability used in the definition of the hazard ( P(T < t+delta | T > t) = P(T < t+delta and t >t)/P(T>t) = (S(t+delta)-S(t))/S(t) ). Then truely the exponential model has constant hazard. But the video is realy good at explaining the models.
I'm not familiar with Survival Analysis and associated models, but I'd like to check my understanding. One of the limitations of the Kaplan-Meier "model" is that: (1): no simple functional form. It's a step/piecewise function so it's non-smooth i.e., no simple function like S(t) e^{=t} (2): we cannot estimate the Hazard Ratio because the Kaplan-Meier curve is non-smooth. The Hazard (H(t)) is a function of Survival (S(t)) -- namely the derivative of S(t) i.e., H(t) = S'(t) ? We can only estimate the Hazard Ratio for the exponential survival function or Cox Proportional model?
When you were talking about the shortcomings of the exponential model, I expected you to mention earthquakes. It doesn't take into account random acute disasters. Tornadoes, hurricanes, war, and other variables can introduce death spikes that the equation would never be able to predict. That's something that I simply don't trust about physics. At least when taking physics 101, I was very skeptical that anyone could put blind faith into an equation. I want to see everything verified with data.
While explaining KM, you labeled the upper step curve as x=1 and the lower one as x=0. Shouldn't it be the other way around? (as mostly the survival chances of an exposed individual on an average is lesser than an unexposed individual)
Hi, there I was really just trying to talk about having 2 KM curves, and why you can’t calculate a HR. Comparing group A and B. You’re right that most often an exposure will reduce survival. There are cases where exposures can be ‘protective’, although this isn’t what I was getting at. My example was just to compare 2 groups without much context. But you’re right that it’s most common for exposure to be thought of as something harmful that will reduce survival
Another comment for potentially confused mathematicans: The hazartd is not actually just the rate of change of the survival function (dS(t)/dt) but it must be further divided by the vylue of S(t) itself. This results from the definition of the conditional probability used in the definition of the hazard ( P(T < t+delta | T > t) = P(T < t+delta and t >t)/P(T>t) = (S(t+delta)-S(t))/S(t) ). Then truely the exponential model has constant hazard. But the video is realy good at explaining the models.
Yes, you are correct. My audience for these are very conceptual so sometimes I cut corners a bit on the math, but you are absolutely right
thank you for your comment, this solves my doubts exactly!
thank you for your explanation!I finally get this idea!
Thank you so much, ive been looking for explanation like this everywhere
loving the transition sound effects! Thanks for providing free education
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thank u so much u saved me, from a master student stuck with statistics.
Got a new job in which I have to use this and you are a life-saver! So fun and easy to understand
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Thank you so much Professor Marine!
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Thank you for your excellent description
Great video. Cleared up a lot of concepts for me!
Thanks very much. Grateful for these videos.
so helpful
thankyou
Great explanation!
I owe you a big "thank you"!!
As always... excellent..
Why is the CPH model not able to estimate the S(t) function?
thank you for your videos, they are so helpful
Thank you for sharing information
Does the exponential model capture progression-free time? It seems that because of the fitted negative exponential curve, it fails. Is that right?
Thanks for the great video. Could you elaborate more specifically on why "no functional form" is a con?
I guess you can't use it to build a 'model' ; so you can't calculate a specific time point in the past or predict the future
I'm not familiar with Survival Analysis and associated models, but I'd like to check my understanding.
One of the limitations of the Kaplan-Meier "model" is that:
(1): no simple functional form. It's a step/piecewise function so it's non-smooth i.e., no simple function like S(t) e^{=t}
(2): we cannot estimate the Hazard Ratio because the Kaplan-Meier curve is non-smooth. The Hazard (H(t)) is a function of Survival (S(t)) -- namely the derivative of S(t) i.e., H(t) = S'(t) ?
We can only estimate the Hazard Ratio for the exponential survival function or Cox Proportional model?
Yes, all correct :)
When you were talking about the shortcomings of the exponential model, I expected you to mention earthquakes. It doesn't take into account random acute disasters. Tornadoes, hurricanes, war, and other variables can introduce death spikes that the equation would never be able to predict.
That's something that I simply don't trust about physics. At least when taking physics 101, I was very skeptical that anyone could put blind faith into an equation. I want to see everything verified with data.
While explaining KM, you labeled the upper step curve as x=1 and the lower one as x=0. Shouldn't it be the other way around? (as mostly the survival chances of an exposed individual on an average is lesser than an unexposed individual)
I'm assuming you mean by exposure as the exposure to disease. Am i wrong? 🤔
Hi, there I was really just trying to talk about having 2 KM curves, and why you can’t calculate a HR. Comparing group A and B.
You’re right that most often an exposure will reduce survival. There are cases where exposures can be ‘protective’, although this isn’t what I was getting at. My example was just to compare 2 groups without much context. But you’re right that it’s most common for exposure to be thought of as something harmful that will reduce survival
8:45 Whenever you grow up :) :) :)