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6 votes
Accepted

Add categorical variable in crr of package cmprsk

Create a model.matrix: ...
rawr's user avatar
  • 208
5 votes

Cox model vs. Fine-Gray: hazard ratios & predicted cumulative incidence under competing risks

... since the Fine Gray method (as I understand it) models the cumulative incidence (i.e. as the response variable), isn't that the best way to get a predicted cumulative incidence curve under ...
EdM's user avatar
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4 votes
Accepted

Model Selection with Competing risks in Cox regression

As you say, one approach is to use cause-specific hazard functions, treating the observations experiencing a competing events as censored. The problem with such approach is that it doesn't have a ...
Federico Tedeschi's user avatar
4 votes

Why do we need Fine-Gray, Andersen-Gill, joint fraily and multiple-state model to model complex survival if basic tools (Cox) can handle it?

Cox and Kaplan-Meier can't handle it all. Competing risk models are hard to interpret. Fine-Gray makes a proportional hazards assumption that Therneau has shown can't usually be satisfied. None of ...
Frank Harrell's user avatar
4 votes
Accepted

How to calculate the sample size (minimal observations needed per event) to perform competing risks regression analysis?

The Fine-Gray competing-risks regression is fit similarly to a Cox model. The difference in a Fine-Gray regression is that individuals who experience one type of event are still included in the risk ...
EdM's user avatar
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3 votes
Accepted

Can coxph() from the R survival package be used to fit bidirectional multistate survival models

The Aalen-Johansen approach used for multi-state modeling in the R survival package is quite flexible. The ...
EdM's user avatar
  • 93.7k
3 votes

Can Cox be used to model recurrent events and competing risks at the same time? How?

To start, the R survival package vignettes contain a good amount of information on how to deal with competing risks and recurrent events until you get more detailed ...
EdM's user avatar
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3 votes
Accepted

Is treating discharged patients as censored ok when using a cox proportional hazard model?

For this study on "Hospitalization and Mortality among Black Patients and White Patients with Covid-19": The models for in-hospital death all considered time to death, with data from ...
EdM's user avatar
  • 93.7k
3 votes
Accepted

How to account for competing events when using a logistic regression model?

This would work better as a competing risks model, which is a specialized form of a survival model. Competing risks is based on the Cox Proportional Hazards model, which uses a lot of the same ...
M.F. Thielbar PhD's user avatar
3 votes
Accepted

Interpretation of model coefficients in competing risks model

After reading the article from Fine and Grey, it seems that they define the subdistributional hazard, $\lambda_1(t; Z)$, as the following: $$\lambda_1(t; Z) = \lim_{\Delta t \rightarrow 0} Pr\left( t ...
AdamO's user avatar
  • 63.1k
3 votes

Cumulative incidence under competing risks: cannot infer event free survival?

That is correct. For concreteness suppose that you are interested in the risk of cancer and there is a competing risk due to fatal heart attack. Event-free survival probability at time $t$ is the ...
Frank Harrell's user avatar
2 votes

Piecewise constant exponential model with competing risk?

In classical time to event or survival analysis the interest is places on the survivor function, which expresses the probability of surviving until a certain time point. However, when various types of ...
Carlos S Traynor's user avatar
2 votes

How to model competing risks with frailties in R

I would recommend modeling with a robust (cluster) variance estimator if you are having problems with a frailty model. (I have little experience with frailty modeling in survival analysis, accounting ...
EdM's user avatar
  • 93.7k
2 votes
Accepted

Extreme point in Schoenfeld residual plot (for competing risks survival analysis)

Schonfeld residuals are calculated as the difference between the observed value of the covariate for the individual having the event, and its expected value. The latter is calculated using, as weight, ...
Federico Tedeschi's user avatar
2 votes

"ignoring" non-competing risks or censoring that datapoint

Much of the answer to your question is included on the page you link. Your question becomes how to apply the principles outlined there. @AdamO notes: A competing event is formally any event that &...
EdM's user avatar
  • 93.7k
2 votes

how to estimate multi-state frailty models with comxe and coxph?

I cannot give you a definitive answer, but I faced a very similar problem with a multistate model. Likewise, I could not make frailty(ID) work properly with ...
Alessandro's user avatar
2 votes

Survival models with competing risks - what alternatives to the cause-specific Cox models and Fine-Gray proportionate subdistribution hazards?

I don't think you can circumnavigate these problems with alternative methodological solutions, since they stem from fundamental limitations in survival analysis. Normally, in a Cox competing risks ...
Alessandro's user avatar
2 votes
Accepted

Survival: treat censoring as a competing risk and use multinomial logit

What's typically of interest in survival analysis is the process underlying the distribution of events in time. The tools of survival analysis are designed to deal with missing (censored) event times ...
EdM's user avatar
  • 93.7k
2 votes

Comparison of C-index between Cox Proportional Hazards model and Fine-Gray model

First, the C-index isn't a very sensitive way to compare survival models. Frank Harrell, who introduced the C-index into survival analysis, agrees with that assessment. Second, you can't compare point ...
EdM's user avatar
  • 93.7k
2 votes

cmprsk cumulative incidence - comparing between two curve with different outomes

Just a few suggestions as a start, as there are gaps in my understanding of competing risks. I hope that someone with more expertise can provide a more complete answer. In the meantime, this should ...
EdM's user avatar
  • 93.7k
2 votes

Cumulative Incidence Function given no event before time $t_d$

This is done using the rules of conditional probability. Letting $T$ denote the time until the event $K$ you can write the conditional distribution function of interest as: $$\begin{align} CIF_K(t|...
Ben's user avatar
  • 127k
2 votes

Measuring the association of a variable with 2 different survival outcomes

This is a straightforward competing-risks scenario. There are two mutually exclusive "absorbing" events (no return from either event is possible). Cox regression modeling of such data is ...
EdM's user avatar
  • 93.7k
2 votes
Accepted

Survival analysis vs Cumulative incidence vc Incidence rate for cohort with varying baseline dates

This is a competing-risks situation involving right censoring, with disease diagnosis and death as the competing risks. The right censoring makes simple ANOVA inappropriate. In principle there is no ...
EdM's user avatar
  • 93.7k
1 vote

Would you choose a joint frailty model or a multi-state model for survival analysis with recurrent events and competing risks?

Briefly, the frailty and multi-state models answer different questions, but you have to answer both types of questions in your situation. Even if you didn't have the terminal absorbing event, you ...
EdM's user avatar
  • 93.7k
1 vote
Accepted

Cumulative Incidence Function - How to extract the cumulative incidence, n(%) with 95% CI?

The authors of this paper aren't very clear about how they generated Table II for this study on graft-versus-host disease (GVHD), a common complication following hematopoietic cell transplantation. ...
EdM's user avatar
  • 93.7k
1 vote
Accepted

Is this possible to calculate median survival time for a selected CIF (Cumulative Incidence Function) in a competing-risk approach in R?

There's a problem with what you mean by "median survival" in a situation with strictly competing events. With 2 competing events, one of them will almost never show "median" ...
EdM's user avatar
  • 93.7k
1 vote

Can I draw 1-CIF (Cumulative Incidence Function) as a survival curve?

This seems to be similar to the analysis in Section 2.3.2 of the R survival vignette, where individuals were evaluated until development of (a) plasma cell malignancy or (b) death, whichever came ...
EdM's user avatar
  • 93.7k
1 vote
Accepted

Is this a competing risks scenario, or just multiple events?

No. The key aspect of competing risks is that one event stops you seeing the others. You just have multiple event types.
Thomas Lumley's user avatar
1 vote

multiclass classification with weights vs competing risks with censored data

As you have a common starting state for all cases and multiple final states (deaths from different causes), this is a classic competing-risks situation as explained in the R multi-state survival ...
EdM's user avatar
  • 93.7k
1 vote

how to estimate multi-state frailty models with comxe and coxph?

I don't have experience with frailty models, so I can't speak to why a frailty term seems to be incompatible with a multi-state model. If you are primarily interested in accounting for intra-...
EdM's user avatar
  • 93.7k

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