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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8 views

Right truncation and right censoring

Is is possible for a survival data to be **right truncated and right censored **. If so, please leave an example for better understanding. Thanks in advance!
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Methods to handle uneven censoring for the monitoring of composite endpoints

Suppose you are doing a cancer study and you compare progression-free survival (PFS) for two groups. A PFS event is either death or disease progression (PD), which ever comes first. People in the ...
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Number of Covariates in Cox PH Model and Overfitting

I have a small time to event dataset (N=20) where patients are given one of two drugs (drug) at varying doses (...
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Recurrent Survival Analysis with Time Dependent Covariates

I am analyzing the time (since 2000) of a policy adoption using R. These policies can be updated and so I think a recurrent Prentice Williams Peterson (PWP) model is appropriate. The challenge is that ...
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How to find the mean lifetime of right-censored data?

Suppose I have a group of patients (the following are their lifetime, * means this individual is censored): 30,67,79*,82*,95,148,170,171,176,193,200,221,243,261,262,263,399,414,446,446*,464,777 The ...
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How is a survival model with constant baseline hazard and time varying covariates called?

The data situation: Supose in different forests data have been collected. These data include the temperature at different time points, the hours of rain, the type of forest and whether the event (a ...
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Modeling survival time which allows 'partial death'? [on hold]

In classical survival analysis, we have $n$ units with different death time $t_1, \cdots, t_n$ (ignoring censoring at first) and we are interested in fitting a survival function $\hat F(t)$ in the ...
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Time and events in a Cox model

I am going to perform survival analysis using the Cox model, but I have some doubts about the input data. The data have the following structure: ...
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Predictive Accuracy of a Survival Model using Concordance

Is there a preferred approach for evaluating the predictive power of a survival regression model (e.g., Weibull Accelerated Failure Time)? The metric of choice, for now, is concordance or c-index. I'm ...
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Statistical comparison of 3 relative survival values

I have to compare relative survival (have 5-year estimates with SEs and patients number per group) across 3 time periods. Cannot use log-rank etc as (probably) it is impossible to operate with raw ...
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Suvival Analysis - Need Help with Converting SAS code to RStudio [closed]

In the past I have used the following SAS code to perform survival analysis for the purpose of predicting retirement. ...
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Likelihood function for a unit $i$ with death at time $t_{i}$ and non - death at time $t_{i}$

The survival function with respect to time is defined to be $S(t) = 1 - F(T) = \int_{t}^{\infty}f(x)dx$ With a bit of algebraic manipulation, one arrives at the time dependent hazard rate ...
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Conditional survival probability up to time $T$ given $t > s$

This is a really basic question I know but for some reason I'm failing to convince myself of the right answer here. Given a survival model that has CDF $F(t) = \mathbb{P}(\text{failure before}\ t)$ ...
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Interaction not significant in Cox regression model?

I ran a cox model with an interaction between two categorical variables (sex and treatment group) included like: ...
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1answer
60 views

Estimate for the standard error of the probability of a residual lifetime

Suppose that we estimate the survival function using the Kaplan-Meier estimator. Based on that KM-curve $\hat{S}(\cdot)$, one can then estimate the probability that the residual lifetime is larger ...
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Comparing survival times in overlapping groups

I have a following statistical setup I don't know how to attack: I have two therapies: say A and B. For some patients A works better, for other B works better. I want to direct patients to their ...
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analysis of cumulative count data

I am comparing the number flowering in normal plants and 3 mutants. I have 60 normal plants and 60 of each mutant plants. The flowering were measured at 6 consecutive weeks and the data is like the ...
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Survival Analysis on conversion rates

I'm trying to implement survival analysis on conversion rates for a free trial product we provide. In general, I understand the applications on survival analysis along with dealing with right censored ...
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Coefficients in Cox model

The output of coxph has coefficients vector as follows: ...
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Time to treatment and survival

I am trying to figure out how time to one event affects time to a subsequent event. For example, how time to treatment affects survival time. In my data, I am focusing on oncology and the time to ...
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Cox regression model - testing the proportionality assumption for an interaction term?

I'm interested in testing sex differences in the outcome Y (e.g., mortality), and if there are sex differences in the effect of BMI on mortality. I planned to use a Cox regression model primary<-...
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Does prediction-at-the-means give the correct survival function in the long run?

If you fit a Cox model, it's possible to come up with an estimate of the baseline hazard function using the Breslow step estimator. In R, this is the basehaz ...
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35 views

Baseline hazard function is the hazard function obtained when all covariates are set to zero

I am trying to learn Cox proportional hazard model but I have hit a wall with the basehaz function. Lets suppose for example I have some data that I want to use ...
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1answer
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Picking from Logistic vs Survival Model

I have a health data set for measuring the effectiveness of a drug. (Age, Gender(0,1), Morbidity(1,2,3), Dosage(0,1), Group (a,b), Effect (Not effective =0, effective = 1), and Time (days needed for ...
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How to choose a model for survival regression when data does not fit assumptions?

I am trying to perform survival regression (prediction) on a dataset of lifetimes, which is highly concentrated around 1, with a significant right skew. The below photo is how it looks when log-...
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1answer
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Sample size calculation for multivariable Cox regression for treatment comparison

I am trying to calculate the required sample size for a future study. Specifically, the goal is to compare two treatments based on their survival. The Cox model will be used, and along with the ...
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Standard error for the expected survival time

Does anyone know what is the equation to obtain the confidence interval for the expected survival time (median), and the predicted survival rate at a given timepoint, for a lognormal AFT model?
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Test assumption of common baseline - Adersen-Gill Cox regression?

I'm running a Andersen-Gill recurrent (multiple events) cox model and I want to test the assumption of common baseline across events. Is this as simple as entering 'event' into the model and checking ...
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Interpreting a hazard ratio for time-dependent coefficients

I have a cox model with two main effects (x,y) and two interaction terms (xt, yt) where t is time. I am having some trouble interpreting the hazard ratios. Does the hazard ration become more of an ...
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Age as a time-dependent covariate

I have some confusion around time-dependent covariates / coefficients. I'm trying to run a cox regression with age as a time-dependent covariate. Lets say the variable is age-at-first-drivers-license (...
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How to conceptualise Hierarchial m-state time-event model with multiple absortion states;non exclusive states

I am designing a clinical study to investigate factors modifying the relationship between toxin exposure and its consequences. Since the original work is sensitive, I share an identical scenario. ...
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When using using predictCox, why does cumhaz change while time is constant?

I'm trying to understand how to predict survival probabilities. I found this, which was helpful. However, after trying to practice on my own and compare my results to predictCox I got some confusing ...
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1answer
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Prediction of regression coefficients with XGBoost

I am doing survival analysis. There is a dataset of items (id, group_id, observed lifetime, censorship status), each item belongs to a certain group. Each item is ...
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survival analysis on log rank test

I am studying log rank test on survival analysis. While studying, I have two questions. The first question is that weather there is any way to know which group lives longer that other group. It means ...
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Interpreting hazard ratios in stratified models

I am unsure how to interpret hazard ratios from cox-proportional hazard models that include 1 or more stratified terms. For example, say I run a cox regression with treatment as a covariate and ...
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Coefficient test (Wald) vs model test (Wald, LR and Score) in multiple regression cox model

I am aware that, in multiple regression cox model, we test (Wald) each variate to show if it has significant impact on survival. Also, we got the significance of overall model using Wald, LR and Score ...
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What to do if a specific parametric survival model does not converge but most other model do (implications for decision analysis)?

Please consider the following: In (health) decision modelling, an often-used approach is to extrapolate observed survival data with parametric functions. The NICE Technical Support Unit summarised ...
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What do LR / Wald / Score test represent in Cox model?

It said that these three tests represents the global statistical significance. What does this mean? There is a p-value for each variate indicating whether that variate affects survival significantly. ...
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Standard error of conditional survival probability using delta method

I need to estimate the standard error of the conditional survival probability using the delta method. I fitted a kaplan meier curve for these probabilities.I know how the delta method works, I just ...
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1answer
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GAM discrete time survival prediction in R [closed]

So I've been trying to perform a discrete time survival analysis in R. I have been using the discSurv package to generate the augmented data matrix for the full ...
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Comparing hazard function of subset and whole data

Is there a way to compare the hazard function that comes from a stochastic process with the hazard function which comes from a subset of that process? Simulations of a stochastic process generate ...
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Adapting Cox Regression to Time dependent continuous variables [duplicate]

I am interested in using cox survival regression model when the covariates are not expected to be constant over time and also continuous. I did check a few books and the time dependent Cox Regression ...
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survival probability to proportional hazard ratios in r

I am using Cox proportional hazard regression to determine the association between physical behaviors (physical activity, sedentary behavior, and sleep) and mortality. to elaborate on these results, I ...
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Modeling Time in the Discrete Time Analysis using Left-truncated Data

I am doing multiple-spell, discrete-time analysis to examine factors shaping time to exiting a renter spell, with time-varying covariates at monthly interval. My data has left-truncated spells, ...
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Kaplan Meier Diagnostic Utility

I'm trying to understand a paper that claims to have identified a gene expression signature that can distinguish primary from metastatic tumors. The authors stratify their data into patients with and ...
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How does the probability of events change if an event does not occur

Suppose that someone tells me I will collect $\$100$ dollars within some time interval. Those time intervals are 1 to 7 days, 8 to 30 days and eventually after 30 days. Let $A$ be the event I ...
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Interim analysis: probability of stopping

Say we do some time-varying study. We check yearly if early stopping is necessary, which is done via interim analysis (O'Brien-Fleming stopping boundaries). The 4 p-values for stopping in 4 ...
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1answer
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Why is likelihood ratio test preferred Cox model for small sample sizes?

It looks like a common consensus that likelihood ratio (LR) test is preferred over log rank and Wald in Cox model when sample size is small. I did some research and couldn't find any clear answer My ...
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Interval Censoring and Ecological or Temporal Bias

I am trying to motivate a secondary analysis of a trial that had event related data. The primary study treated the data as an interrupted time series (ITS). I would like to justify using survival ...
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Why are Logrank, Wald and likelihood ratio test asymptotically equivalent?

I am trying survival analysis and it seems like a common consensus that Logrank, Wald and likelihood ratio are asymptotically equivalent I don't understand why they are asymptotically equivalent. As ...