Questions tagged [frailty]
The frailty tag has no usage guidance.
56 questions
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Repeated Measures Survival Analysis per ID and per latency
I have chosen survival analysis and mixed effects to be analyzed in a joint model using the frailty pack. I am not sure if I am dong it right and I need more expert insights.
I am testing people's ...
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Applying one frailty value to all observations in mixed effects cox regression and then recalculating the survival probability
I want to test the difference in survival probabilities for if every observation in my dataset was part of the frailty group with the worst or best frailty value. I want to calculate the survival ...
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How is a frailty model in survival analysis expressed
In some sources 1 one reads that the frailty model expands on the cox proportional hazards model
$$h_i(t|x_i)=h_0(t)\exp(\beta x_i)$$
by adding a frailty term $z$ like so
$$h_i(t|x_i,z_i)=h_0(t)\exp(\...
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How to interpret the Wald Chi-square test for the frailty term in a mixed-effects Cox survival model?
Background
I'm fitting a Cox model to assess the relationship between treatment (binary) and time-to-event (event is also binary) while also controlling for 3 or 4 covariates. Because I want to ...
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Cox PH controlling for multiple events
I'm working on a cox proportional hazard analysis in R using the survival package.
I´m analysing covariate effects on fish movement within a study area. The study area is divided into two zones ("...
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Survival model for longitudinal data with overlapping exposures
I have a dataset with info on patient exposures (drug 1 / drug 2) and outcomes (hospitalisation / death) over ten years. All patients were prescribed drug 1 on and off over the period (inclusion ...
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618
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Correct pooling of shared frailty models fitted on multiply imputed datasets
I'm wondering whether the pool() function from R's mice package correctly pools shared frailty models fitted on multiply imputed ...
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Within-cluster correlation in lognormal shared frailty models
According to Peter Austin (ref. below), in a gamma shared frailty model (i.e. a Cox regression model with cluster specific random effects which are iid logarithms of gamma distributions), the within-...
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374
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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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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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785
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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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Cox models in R: cluster, strata, robust, and frailty ... modeling grouped/clustered survival data
Consider a situation where we have individual patient survival data from a series of clinical trials of patients treated in a similar way. We might have a dataset that looks like this, with n total ...
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Plot survival curves from a Cox proportional hazard model with shared frailties
I am interested in deriving and plotting the survival functions from a Cox proportional hazards model with shared frailties. How can I do this?
This question has an answer here, but it is very high ...
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How to decide if frailty term needed
I´d like to ask the following question:
Is there any sound procedure to test event-history/survival data for unobserved heterogeneity or any indicator that shows that a frailty term should be included?...
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Time varying Cox regression, adding in a mixed effect for patient
I've been reading a lot of vignettes and literature on how to approach repeated-measures longitudinal data with time varying components for the purpose of time-to-event or survival analysis.
The ...
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Mixture of two chi-squared distributions
I have a question about something I found in the book Frailty models in survival analysis (Wieneke, 2011). He talks about testing signficance of the frailty term. According to him, Claeskens et al. (...
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Question about adding a frailty term in survival() R
If I add a frailty term in the coxph() function using the survival package in R, we model unobserved heterogeneity of clustered data.
Does this only model unobserved heterogeneity of overlapping ...
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What is the difference between standard errors using the inverse of hessian and calculated using the the inverse of hessian and Fisher information?
In one of R packages for advanced survival analysis, the frailtypack, the output contains standard errors calculated in two ways, named: H (using the inverse of Hessian) and HIH (...
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Using time dependent covariates in Gamma frailty Cox model
I have a dataset with repeated episodes per individual, trying to determine factors associated to the outcome of interest. I am planning to use a gamma frailty Cox model to account for intra ...
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Why did the log likelihood decrease with additional parameters?
I'm trying to decide the effect of some factors on the time for an event to happen . Specifically, I am looking at how long it takes for the subject to pass a test (recognize the stimulus) when ...
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Mixed Effects Model Using Censored Data
I am attempting to analyze left-censored hormone data collected in a repeated measures design, and am having some difficulty employing an appropriate method to account for the censored nature of the ...
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Survival analysis: Frailty vs Sandwich variance estimators
Question
Can someone answer (in as non-technical terms as possible) whether or not frailty models and robust sandwich variance estimators are trying to solve the same problem in different contexts? ...
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random vs. stratified Cox model
What is the difference in interpretation of the effect estimates in a Cox model stratified by sex vs. with a random statement for sex? Thanks.
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Frailty or median values in my cox proportional hazards model?
I am analysing data of woodpecker-made holes and I am interested in seeing what covariates and to what degree affect the survival of these holes (otherwise known as cavities). However, I encounter the ...
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180
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Cox model with frailty (partial loglikelihood and df)
I am fitting a Cox propotional hazard model with a frailty term using the survival package in R. When I remove a fixed efect, I ...
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Can someone explain the meaning of "shared frailty" in survival analysis
Can someone explain the meaning of "shared frailty" in survival analysis in layman english ? a concrete example of where one would use this would also be very helpfull. thx
kindly Stig
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Responding to a reviewer: How to apply frailty to a Cox regression analysis in this situation
I am a medical doctor not a statistician. I have 60 patients who were assessed by 400 doctors (each doctor individually evaluated the clinical data on each patient). The doctor was then asked to say ...
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Comparison of longitudinal change in several parameters in same individuals: violations of survival analysis?
I am trying to compare 4 different (but correlated) parameters (biomarkers of a disease with continuous values) to identify which parameters would detect more deteriorating subjects and in a shorter ...
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523
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Survival analysis for patients that have been subjected to multiple treatments
I have data for patients that were subjected to either one treatment or multiple treatments at various points in time and I need to analyse their survival times after treatments. This of course means ...
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Unobserved heterogeneity in Cox model
I have some questions about the Cox model and unobserved heterogeneity.
I work on a sample of firms divided in two categories: cooperatives and corporations. I want to test the influence of some ...
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990
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Software for survival regression with interval censoring and frailty
I'm conducting regression analysis on sleeping time data. The data is survey data and the answer possibilities are of type "less than 4 h", "5 h", "6 h", etc. so they can be thought to be interval ...
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How to plot splines in a coxph model that includes a frailty term?
I have a Cox PH model including a smoothing spline and a frailty term as follows:
fit<-coxph(Surv(start,end,exit) ~ x + pspline(z) + frailty(a))
When I run a ...
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Determine number of excess events in survival analysis
I have run a survival analysis on two group of people that saw different ads during an ad campaign.
I would like to calculate the number of excess events that occurred due to the exposure to the ad.
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Precisely how does R's coxph() handle repeated measures?
Context
I'm attempting to understand how R's coxph() accepts and handles repeated entries for subjects (or patient/customer if you prefer). Some call this Long format, others call it 'repeated ...
user76943
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Survival Analysis/Frailty Model
I am trying to build a probability model for the following situation:
I have a very large dataset, whose rows are users and columns are the features.
All the users visit a particular store X (once ...
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Survival analysis with Frailty on large dataset
I am trying to fit a survival analysis in R with non-recurrent events and time-varying coefficients. The baseline distribution is exponential or Weibull and the ...
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Frailty Models: Gamma distributed frailty and Inverse Gaussian distributed frailty
In modelling of frailty using assumptions distributions of frailty are Gamma distributed frailty and Inverse Gaussian distributed frailty. Frailty is unobservable risk factor of mortality. How to ...
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Model assumptions and diagnostics for proportional hazard regression model with frailty in R
I am wondering are there any assumptions that must be met in the proportional hazard regression model with frailty? I remember that in regular proportional hazard model without frailty all variables ...
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Result of the summary of the proportional hazard model with frailty in R
I am trying to fit coxph a model with frailty with syntax below:
...
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Should I bootstrap at the cluster level or the individual level?
I have a survival model with patients nested in hospitals that includes a random-effect for the hospitals. The random effect is gamma-distributed, and I am trying to report the 'relevance' of this ...
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618
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Link function for log-logistic shared gamma frailty model
I've been asked to replicate a study that models an accelerated failure time survival model with a log-logistic distribution and gamma distributed frailty (a 'log-logistic shared gamma frailty model') ...
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Poor parameter estimation in frailty models
I fitted a one-parameter gamma shared frailty model with Weibull and exponential baseline hazards for recurrent event data (the dataset contained 80 subjects of which 16 patients had events (13 ...
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Survival analysis in SAS-is there a way to include a random effect with interval censored data?
I'm trying to use some form of survival analysis (e.g. accelerated failure time or proportional hazards) to study seed germination time. My data is interval censored (also called "grouped-time") and ...
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How to interpret the frailty terms in a coxph.penal model?
I have the following coxph model:
Surv(Y) ~ genotype + treatment + age + frailty(batch) + genotype:frailty(batch)
...
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Frailty model using bootstrap sampling
Let say I have a 'kidney catheter' data set which is built in survival package. Data are about the recurrence times to infection, at the point of insertion of the ...
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786
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Proportional odds model with random effects
I have a survival data set. I want to see the cluster specific variation, which we usually can do by using Cox proportional hazard model with frailty. But, the constant hazard ratio assumption of Cox ...
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Variance of a random effect in Cox PH
I want to fit a Cox PH model with random effect (Gamma frailty). Here is an example with 'kidney catheter' data set:
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