New answers tagged survival
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What are the differences between PS-match and adjusted Cox regression?
There are huge differences. Suppose for example that age is a strong predictor of time until event. Adjusting for outcome heterogeneity due to age clarifies the picture is makes the proportional ...
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Are there any advantages of survival analysis over regression for prediction?
So I've dug through the literature a bit, and the answer seems to be inconclusive in terms of any theoretical advantages. However I think it's worth trying, especially if framing it as a standard ...
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1
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Accepted
Multi-state Cox models: different formulas for different transitions?
survival package supports specifying terms for specific transitions only. Using your example transitions, it would look something like this:
...
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Can I use age as a time varying covariate in a Cox PH?
First, your use of groupage as a predictor doesn't represent the age of the individual that is at risk of the event, which is the usual ...
- 102k
2
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"Impossible" crossing of Kaplan-Meier curves
This is a very small sample size to start off with. However, even if that were not the case, as the risk set gets smaller the Kaplan-Meier estimate becomes increasingly unstable (you might even say &...
- 35.2k
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"Impossible" crossing of Kaplan-Meier curves
So the below picture, with only 4 patients from the same dataset explains it all, I believe.
Among the 4 patients there are two that have a recurrence and then, later, die. We recognize them in the ...
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Accepted
Is it possible to perform a survival analysis in a patient population only, using their age of onset as time-to-event data?
The answer depends on what specific question you want to address.
Say that your interest is whether the age of onset of a disease differs with gender, your population of interest is only those who ...
- 102k
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Simulating machine maintenance occurrences using Weibull distributions
I don't see a problem with Approach 1, except that it doesn't allow for multiple events in the same day. I assume that multiple events in a single day have very low probability.
If you "generate ...
- 102k
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The logrank test statistic is equivalent to the score of a Cox regression. Is there an advantage of using a logrank test over a Cox regression?
In the simple, semi-parametric Cox model
$$h(t | Z_i) = h_0(t) \exp(Z_i \times \beta)$$
where
$$
Z_i=
\begin{cases}
0 & \text{if subject $i$ is in the 1st group}\\
1 & \...
- 31.6k
2
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Accepted
Setting a reference in Cox regression with splines and interaction
The vignette you cite says:
The approach is appropriate for any term, not just psplines.
In terms of simply setting a reference, you thus are OK. You were smart enough to use the ...
- 102k
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probability that the failure is on the individual as observed
First, the definition of $\lambda(t)$ at the end of the question holds for continuous-time models. That's a general definition of the hazard function for any continuous probability distribution; it's ...
- 102k
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Inverse of hazard function
Unless some special assumptions are made, it is not generally possible to determine the time value from the hazard function, since the latter can take on any values over time. In particular, a common ...
- 133k
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Separate Test Set for Cross-Validation for Small Sample (n=140)
Although a model developed on 126 cases might not be much different from one developed on all 140, the remaining 14 cases will be too few to test the model adequately (as you sense). This is even more ...
- 102k
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Restricted time window for survival analysis using Kaplan Meier estimates
It looks like you have a case of crossing hazard rates. The group with the feature you describe has a lower hazard rate in the first 24 months as compared to the group without this feature, and then ...
- 63
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Note on standard errors reported by `flexsurv` package as compared to `survival` package
As per the documentation in flexsurv: "For the Weibull (and exponential, log-normal and log-logistic) distribution, flexsurvreg simply acts as a wrapper for ...
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