Questions tagged [survival]

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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A question about the effective sample size in life tables

I am currently studying basic methods of survival analysis and I came across this strange estimator of the effective sample size at a given interval. For the jth interval say, the estimator $n^{\prime}...
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Error term interpretation in the Cox PH model

I am preparing a presentation on Survival Analysis models, with specific focus on the Cox model. Suppose I am in the simple bivariate survival analysis case (with $x_1$ and $x_2$). The Cox model ...
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R neural network model with target vector as output containing survival predictions

Overview I want to simulate the survival prediction using neural networks described in this paper entitled "Application of Artificial Neural Network-Based Survival Analysis on Two Breast Cancer ...
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339 views

Survival analysis, one cohort, two classifications

I'm wondering about this question: short version: how to adequately compare the effect of a reclassification of the same subjects on survival long version: I have one cancer cohort that was sorted ...
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Difference between Kaplan Meier Estimator and the Empirical CDF

In survival analysis, you often use the nonparametric maximum likelihood estimator (i.e. Kaplan-Meier estimator) of the survival function $S(t)$. Since $S(t) = 1 - F(t)$, shouldn't we also be able to ...
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Confidence interval before the first event in a Kaplan–Meier curve

The confidence intervals for Kaplan–Meier curves in survival analysis only exist for times after the first (non-censored) event. Example R code: ...
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R packages (or SAS code) to produce two simultaneous Kaplan-Meier curves?

There's a way to do survival analysis of two (or more I suppose) mutually exclusive competing risks as a mixture of two different survival curves. Something like what you see in A.C. Ghani et al. ...
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Robust nonparametric estimation of hazard/survival functions based on low count data

We're trying to use a Gaussian process to model h(t) -- the hazard function -- for a very small initial population, and then fit that using the available data. While this gives us nice plots for ...
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Using random forest for survival analysis with time varying covariates

I've been trying to train a model that predicts an individual's survival time. My training set is an unbalanced panel; it has multiple observations per individual and thus time varying covariates. ...
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641 views

Obtaining a log-normal waiting time via sequential exponential or gamma distributions - is it possible?

Assume you've use a accelerated failure time model to find that the transition of subjects from State A to State B is log-normally distributed with parameters $\mu$ = X and $\sigma$ = Y. This now ...
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Predicting the time until an expected event occurs

I have a situation where an event is supposed to occur every x minutes for a number of different sites (each site could be configured for a different time interval x). From time to time the event may ...
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Inferring likely dates based on other related dates in incomplete data set

I'm taking my first steps in data science and machine learning. I'm experimenting with a project where I have no idea even what approaches I might start with, so I'd appreciate any leads: I have a ...
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glmnet, categorical variable, group lasso?

I am using glmnet for LASSO. My data set contains several continuous variables and one categorical variable (it has four levels). I wondered if I could treat three dummy variables as other continuous ...
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Kaplan-Meier p-values

I have breast cancer trial data where, for subgroups 1 and 2, two treatment arms are being compared. The results are: For subgroup 1, N=33, median survival in <...
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Mean survival time of a Weibull distribution

I'm trying to calculate the mean survival time of a Weibull distribution, and am getting what feels like an errant estimate of the mean--and each source I look up for how to calculate the mean gives a ...
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Cox model with LASSO

Rob Tibshirani propose to use lasso with Cox regression for variable selection in his 1997 paper "The lasso method for variable selection in the Cox model" published in Statistics In Medicine 16:385. ...
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Why does my proof for showing that the Kaplan-Meier estimate is unbiased not work?

I know that the Kaplan-Meier estimator is biased because my textbook says so. However, I don't understand why the following proof doesn't work: Let $\hat{S}(t)$ be the Kaplan-Meier estimate for the ...
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How to interpret and compare models in Cox regression?

I am trying to interpret the results of a Cox regression; I am doing a PhD in medicine. I love statistics but my question is still pretty basic, I think, and I did not find an answer in previous ...
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How should I deal with the consequences of proportional hazards violations in log-rank (and related) tests?

I have (censored) time-to event data for subjects in four groups. I would like to do something like a logrank test, but the survival curves do not satisfy the proportional hazards assumption. I ...
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Plotting interval censored follow-up time as a line chart

I'm working on a survival analysis project where it would be useful to visualize everyone's followup time and event times. The data is made up of an ID, which of two possible events they had (A or B), ...
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Cox Regression when survival doesn't go to 0?

Is it appropriate to use cox regression to study a process that doesn't result in the survival function going to 0 when time = infinity? Cox regression is interested in hazard ratios, and it makes no ...
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Interpreting interaction terms in Cox Proportional Hazard model

I am new to survival analysis, so forgive me if this questions is stupid - but I couldn't find the answer anywhere else. We are looking at readmission to a treatment program, which is defined as ...
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Hazard Function - Survival Analysis

I just started taking survival analysis class and I'm stumped on this question. Let $T_1,...,T_n$ random independent continuous variables, with hazard function of $h_1(t),...,h_n(t)$. $T=min(T_1,...,...
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Right-censored survival fit with JAGS

Update: I got the JAGS model running and this eliminates the distracting part of my question. It's really about the proper preparation of data for dinterval() and inits. I can't find a concrete ...
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Which algorithm to compute p-value of logrank test with three or more groups is best?

There seem to be two different algorithms for comparing three or more survival curves using the logrank test. Algorithm A. Found in books by Altman and Machin. Computed by GraphPad Prism. This ...
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What does muhaz return?

A pretty basic question. I have read somewhere that the muhaz function in muhaz package will return the baseline hazard rate for COX model. The muhaz document states that it "Estimates the hazard ...
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log-rank test in R

I need to use the survdiff function to statistically compare (using log-rank test) the following survival functions: (1) Male (Sex=1) and Female (Sex=2) (2) ...
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Cox regression when reference group had zero events

I would appreciate some advise on an a problem I ran into. I use SPSS for statistical analysis of a study. The study look into how a blood test predicts mortality with patients followup of 1 year. ...
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Performing contrasts among treatment levels in survival analysis

I'm reviewing a paper where the authors compare the survival of an insect fed on three different diets. Following the survival analysis (using Surv) they perform ...
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Assumptions and pitfalls in competing risks model

Question: What are the major pitfalls and assumptions for competing risk analysis? Background I'm trying to learn competing risks and I use the cmprsk package in ...
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Question about combining hazard ratios - Maybe Simpson's paradox?

I’m reviewing an article, and can’t give details but here is the situation, and it’s got me puzzled Patients were divided into 4 categories (call them A B C and D), which were exhaustive and ...
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EM algorithm R code on Cox PH model with frailty

Let say I have a 'kidney catheter' data set. Data are about the recurrence times to infection, at the point of insertion of the catheter, for kidney patients using portable dialysis equipment. ...
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Recurrent event analysis

I want to model patient visits. My assumptions are: Patients visit the hospital until they stop visiting at all. I don't know if their last visit was the last one. Patients visit at certain intervals....
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Relative importance of variables in Cox regression

I've understood that relative importance of predictors is a tricky question. Suggested methods range from very complex models to very simple variable transformations. I've understood that the ...
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What’s wrong with this way of fitting time-dependent coefficients in a Cox regression?

I have a Cox proportional hazards model. Judging by Schoenfeld residual vs. time plots and corresponding tests for zero slope, there is clear violation of the PH assumption for several of the ...
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Is this a problem for Survival analysis?

I have a dataset of individuals. Each individual has the same start time at which we begin observing them. There is also an end time for all individuals. Some individuals fail before they reach the ...
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Prediction on individual cases in survival analysis

It seems that survival models are used mostly to describe (not predict) the change in survival probability over time for all cases or each class (e.g. men vs. women). What I'm interested in, however, ...
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How to determine the cut-point of continuous predictor in survival analysis, optimal or median cut-point?

everyone! I want to do overall Recurrence-free survial analysis for one continuous predictor with Kaplan-Meier method, but the determination of the cut-point for groups really confused me. Most ...
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When (and why) is a conditional logistic regression equivalent to a Cox proportional hazards model?

In the the help for the clogit function in the survival package in R, the details section ...
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Why is coxph() so fast for survival analysis on big data?

I frequently do survival analysis on large data sets. One million samples or more is typical, and this seems to be much more than typical research usage. Many algorithms I've used are prohibitively ...
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Measuring length of intervention effect

I ran a study in which participants were randomized to either a control or an intervention, with outcomes in the form of time-to-event data. While overall time-to-event is shorter in the intervention ...
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Confidence intervals of fitted Weibull survival function?

I'm implementing a Weibull survival analysis fitter, and have successfully estimated the parameters and their standard errors. I can also produce the fitted survival curve. My question is how can I ...
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1answer
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Expected survival time from log-logistic survival model in R from survreg

I am currently estimating a survival model (specifically, accelerated failure time model) with a log-logistic distribution using the survreg function in the ...
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How would you visualize the difference between Cox/Weibull regression?

I'm trying to figure a way of properly displaying the difference\resemblance between various regression values on the same data set, using cox ph, weibull regression and log-normal regression. ...
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Survival analysis with categorical variable

I have event time data for subjects with different categories (A, B, C etc.) yearly observed. To my understanding my data is both right and interval censored (?). Subjects' category can change from ...
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298 views

Are survivor functions meaningful with proportional hazards models?

Does the survivor function estimated after running a Proportional Hazards model give valid predicted probabilities of an event happening after a number of time periods? The only source I've found on ...
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How to compare Harrell C-index from different models in survival analysis?

In a dataset with survival event, I calculated Harrell C-index from three different models. Furthermore, I calculated the 95% C.I. for the three different models. So the next question is to compare ...
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time varying coefficients in cox proportional hazard model

I am trying to fit a coxph model in R. The study can be described as follows: I have a very large dataset, in counting process form, containing whether or not someone responded to a survey or not. ...
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1answer
401 views

Duration analysis of unemployment

I am trying to run a discrete duration model for analyzing (monthly) unemployment using survey data. I have household-level data, and as such I would like to control for the household effects in my ...
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338 views

Proper way to match a reference population for survival analysis

I am performing survival analysis on a specific group under study containing thousands of individuals. I am looking for the best way to obtain a reference population from the total population (...

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