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Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
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Likelihood for aggregated survival data?
Most literature on survival models assumes that the data is either a collection of individual survival times or right-censored individual survival times (so you know when some subjects failed but for others … Survival (%)
0 . 100
1 . 95
2 . 93
3 . 87
Essentially, just an empirical survival function.
Edit: The total number of subjects $n$ is also known. …
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Predicting survival probability at a future time for proportional hazard model
I am interested in predicting the probability of survival until some future time $t$ given knowledge of $x(t)$ for all future $t\geq s$ (but not past $t<s$). … But, it seems like I should still be able to get $Pr(T > t | t > s)$ without ever having to calculate the survival function, since I know all future values of the hazard function. …
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Conditional survival probability up to time $T$ given $t > s$
Given a survival model that has CDF $F(t) = \mathbb{P}(\text{failure before}\ t)$
I would like to calculate $\mathbb{P}(t < T\ |\ t > s)$
Is it
1) $\mathbb{P}(t < T\ |\ t > s) = \frac{F(T)}{1-F(s)} …
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Posterior distribution for Weibull scale parameter with censored data
I am modeling a survival problem using a Weibull distribution with known shape parameter $k$ and unknown scale parameter $\theta$. …