Questions tagged [competing-risks]

In survival analysis when observation may be terminated or affected by a different event this is termed a competing risk.

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Comparing multiple cumulative incidence functions in the presence of competing risks

I have a survival/duration dataset with competing risks. The start years for the durations vary and range from 2010 to 2019. Each individual may only start once, e.g. during 2010, and therefore cannot ...
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Different Discharge Dispositions in a Competing Risk Model

I am building a data set on which to estimate, via regression, the impact of covariates on the cause-specific and subdistribution hazards for time to discharge from a hospital. The main competing ...
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Cumulative Incidence Variation of Death changing based on competing risk event

When using competing risk analysis, is it expected for cumulative incidence of the same event to change based upon the competing risk? I am looking at time to event for severity of liver disease (...
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Competing Risks without Censoring

I am trying to estimate the probability that an entity goes from state $A$ to either state $B$, $C$, or $D$. The probability should be dependent on how long the entity has been in state $A$. My data ...
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Competing risks cumulative incidence - same results with or without competing risks

I recently got involved in a study on survival of teeth where the time until extraction was measured. The reason for extraction could be either an infection or some other cause. These other causes ...
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Developing a flexible estimation strategy for longitudinal data with heavy clustering, covariates with missings and interval censoring

This is a general question for R users that are familar with interval censoring in survival analyses. I have clinical registry data at hand and aim to compare the one-year incidence for two groups (...
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Cumulative Incidence function and competing risks

Let $R_1,...,R_K$ be competing risks and put $T=\min(R_1,...,R_K)$ and $\delta = i$ if $T=R_i$. The cumulative incidence function is then defined as $F_i(t):=P(T\le t,\delta = i)$. The cause-specific ...
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Survival models with competing risks - what alternatives to the cause-specific Cox models and Fine-Gray proportionate subdistribution hazards?

I am working on a project involving survival analysis with various death causes. Specifically, there are 3 death causes and the question is if people with a particular medical history are more likely ...
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How to simulate clustered interval-censored data in the presence of competing risks?

I would like to simulate a sample of 100 clusters of size 5 in the presence of 3 competitive risks. I would like to have right censored and interval-censored datas.
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Extracting transition-specific estimates from a parametric multi-state survival model

I fit a multi-state survival model following Weibull distribution using function flexsurvreg. This data is about the depression trajectory of people with mild ...
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Cumulative Incidence Function - How to extract the cumulative incidence, n(%) with 95% CI?

I would like to replicate the above study in R on my own data, but I am not sure how to do it. How to extract the cumulative incidence, n(%) with 95% CI? I suppose the cumulative incidence is at the ...
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Is this possible to calculate median survival time for a selected CIF (Cumulative Incidence Function) in a competing-risk approach in R?

I have an event of interest, say X, which can be precluded by 2 other events: death or accident. I want to show only the CIF (Cumulative Incidence Function) for the "adjusted-for-competing-risks&...
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Can I draw 1-CIF (Cumulative Incidence Function) as a survival curve?

I analyze survival data with competing risks. To me, the CIF is fine, but the researchers want to see how fast the survival falls, so they want the 1-CIF. They know it's NOT the Kaplan-Meier, it's a ...
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Is this a competing risks scenario, or just multiple events?

Background I have some car and motorcycle insurance claims data, and I'd like to do a time-to-event analysis on it. Specifically, I'd like to use a semi-parametric method such as a Cox model to ...
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Can coxph() from the R survival package be used to fit bidirectional multistate survival models

I am trying to design an illness-death multistate model (see image below) for survival type data in R. This data is more suited for a Markov model, but the investigator I am working with prefers to ...
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Would you choose a joint frailty model or a multi-state model for survival analysis with recurrent events and competing risks?

I am going to analyse data with multiple recurring events and additional terminal event. The recurrent events are of the same kind, no hierarchy in them (like in the Prentice-Williams-Petersen). The ...
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Which frailty model is better for survival analysis with recurrent events and competing (teminal) risks: joint or shared?

I am going to analyse data with multiple recurring events and additional terminal event. The recurrent events are of the same kind, no hierarchy in them (like in the Prentice-Williams-Petersen). The ...
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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?

The basic methods statistical packages, using K-M or Cox regression, are both to handle both recurrent events and competing risks. This setting is very common in medicine, where we have recurring ...
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multiclass classification with weights vs competing risks with censored data

I want to fit a machine learning model to a dataset which is basically a survival analysis with competing risks with several failure types (e.g. mortality causes). However, I want optimal predictions ...
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"ignoring" non-competing risks or censoring that datapoint

Although another post has raised a similar question - survival analysis with external non-competing events, my question seems slightly different and not addressed by the answers within the post. ...
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how to estimate multi-state frailty models with comxe and coxph?

I aim at estimating a competing risks / multistate model with frailties with the coxme R-package and the survival package. I ...
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How to model competing risks with frailties in R

I am trying to figure out if (a) a competing risks model with frailty-terms is the right method for my data and (b) how to estimate such models in R. My data consists of N ~ 150 individuals with a ...
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How to account for competing events when using a logistic regression model?

I am creating a model to identify which factors predict two different recidivism outcomes (A)new arrest, or (B) return to prison in a group of people who parole, with equal time at risk (2 years). The ...
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What model to use when examining subject specific control variables on the outcome?

I want to study whether a trader will buy or sell a stock from a given set of stocks =[1,2,3,...,n], based on the sentiment scores of these stocks [sent_1, sent_2, sent_3, ..., sent_n]. So basically I ...
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Cause-specific survival function in survival analysis

In survival analysis, when there are competing risks, it is well-known that although the cause-specific hazard function, $\lambda_j^\#(t)$, is interpretable, $S_j^\#(t) = e^{-\Lambda_j^\#(t)}$ may not ...
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Which model should be adopted in survival analysis when events are only partly competing?

In survival analysis, when there are multiple possible events and occurrence of a one doesn't prevent occurence of the other ones, we talk about failure-time data and the Cox model may be used. ...
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Can Cox be used to model recurrent events and competing risks at the same time? How?

I have heard that the Cox model can be extended to handle recurrent events and competing risks. But is this possible to analyse data, where both occur? For example two kinds of fractures that can ...
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Is treating discharged patients as censored ok when using a cox proportional hazard model?

When analyzing the association of in-hospital death (the event) with various independent variables using a cox proportional hazard model, is it acceptable to treat as censored both: (i) the patients ...
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Multi state survival modelling - medical statistics - separate time to relapse / time to death models or combined with mstate?

I've undertaken a survival analysis of a cohort of cancer patients, all of whom relapse and then the vast majority of whom go on to subsequently die of their disease. The approach we've taken so far ...
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Is it possible to compare survival curves from different models (Cox and Fine-Gray)? Ideally in R

I would like to perform a time to event analysis on some biological example with animals. The event of interest is a terminal event X. But the animal may die from other reason before it happens. So I ...
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Cumulative Incidence Rate in R Statistics

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Time-to-event statistical test for toxicity within a 12-month time frame?

I am performing a retrospective study and this is my hypothesis: among patients with metastatic melanoma, antibiotic exposure within the 3 months prior to immunotherapy increases the risk of therapy-...
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Given competing risks, what is the probability of an event within d steps from time t?

In competing risk analysis, we can only identify the cause-specific hazard and functions of that hazard. The cumulative incidence function (CIF) is a function of the cause-specific hazards. Because ...
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Survival analysis with external non-competing events

I'm new to survival analysis and struggling to find the best approach to my problem: Assume that we want to model the time to the death event $X$ given some prior subject data. I'm aware that ...
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Competing Risks Likelihood in each State

I have a competing risks model where every observation starts in state 0 and ends up in either state 1 or state 2. I have the following cumulative hazard functions for each transition to state 1 and ...
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competing risks model with ties

I am fitting a competing risks survival model on a data set. There are 3 types of failures that compete with each other and occurrence of the first event is defined as the failure status. However, I ...
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Calculating risk from multinomial logistic regression and competing risks

I’m interested in predicting certain events an entity can experience. With logistic regression I would estimate the risk of a single event using p= exp(ß0 + ß1*x1 + ... + ßk*xk)/(1+exp(ß0 + ß1*x1 + ......
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Why would results from cmprsk differ from those from riskRegression in competing risk analysis?

I have a dataframe with a number of covariates or different types (binary, numeric, factors) and 2 competing outcomes. The presence of one outcome would preclude the occurrence of the other outcome. ...
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How to test PH assumption with Schoenfeld residuals with simulated paths in presence of competing events

I've obtained Schoenfeld residuals for testing PH for Fine & Gray's Cox regression model in presence of competing events with cmprsk. Here's the code: ...
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Implementation of regularized competing risk models with random effects

Are there any existing software implementations of regularized competing risk cox models with that also allow for random effects (i.e., competing risk frailty models)? That is, models that allow for ...
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Proportional Hazards, Competing Risks, or something else?

I'm looking to do a time-to-event analysis. My data set set has a binary response variable representing 2 distinct outcomes, a time variable, and some censoring. I am mainly interested in the time ...
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Piecewise constant exponential model with competing risk?

dear StackExchange users, I'm struggling with a survival analysis problem. I have longitudinal data, so with multiple observations per individual (about 8 months per person). Each row represents one ...
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Survival trees with competing risk

I'm looking for a way to fit survival trees with competing risk. Can I use the function LTRCART in the LTRCtrees package in R to fit a survival tree using the ...
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Competing risk analysis for clustered data

I am conducted a patient-level meta-analysis focusing on survival outcomes. I would like to add a competing risk analysis to the main analysis based on survey methods in R and Stata with Cox ...
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Want to know proper survival model to understand the factors that influence time to event with recurrent competing risk

I am interested in understanding the factors that influence time to event. So say the event is a disability for Condition X- I want to know how patient characteristics (age, sex) affect that rate. ...
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Cox Proportional-Hazards Regression vs. Regression modeling of competing risk using Fine and Gray

30000 patients all have one diagnosis in common, 3000 of them have been exposed to a potential risk factor before the common diagnosis. 1500 patients develop a malignancy after the common diagnosis. ...
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Modelling time-varying effects in discrete-time event history/survival analysis with competing risks

I have a question with regards to estimating time-varying effects in event history analysis with competing risks. To give more context: the main idea of my study is to gain more insight into the ...
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Extreme point in Schoenfeld residual plot (for competing risks survival analysis)

I'm looking at the Schoenfeld residuals of a competing risks survival model for one of the covariates. There is an extreme point which I am struggling to interpret.
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Interpretation of risk ratios for competing risk from AFT

I want to analyse the time to disease with a competing event with an accelerated failure time model (AFT) with Weibull distribution. I wonder how exactly we can interpret the resulting coefficients ...
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Interpretation of model coefficients in competing risks model

I am fitting a subdistributional hazards model (Fine, Grey 1999) for multiple causes of death in a mortality incidence model following diagnosis of cancer. The researchers are interested in a nomogram,...
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