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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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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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Survival regression on an interval

I am experimenting with survival regressions (like weibull) on on interval of a data. For instance, if I use the lung data in R I want to use the data in a certain ...
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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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Why is likelihood ratio test preferred over log rank and Wald in 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 ...
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Homogeneity test in survival meta-analysis with adjusted HR

I was wondering what was the way to measure heterogeneity in a survival meta-analysis. I have for each study, an hazard ratio calculated with a penalized cox model (...
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Cox model’s Proportionality assumption?

What does it mean that a hazard ratio is constant over time? For example if disease resolution is the endpoint, the hazard ratio indicates the relative likelihood of disease resolution in treated ...
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60 views

lasso with *extended* cox regression (time-varying covariates using counting process notation)

I'm trying to find a way to build a predictive model the development of a disease. However, some of our predictors are time-varying (aka time-dependent) -- for example, the appearance of other, age-...
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Person-Years of Follow Up

How can one calculate person years of follow up in survival analysis settings where censoring occurs? Is it appropriate simply to sum the survival time (including censored cases). Thanks for the ...
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Control for baseline incidence of disease in Kaplan-Meier curve

I would like to construct a survival curve from retrospectively gathered data that represents the time to onset ($t$) of disease ($d$) after some specific event ($x$). We know that $x$ predisposes to ...
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obtaining time-dependent survival ROC estimates in test data set

I have survival times and fixed baseline values of biomarkers and risk factors ( I actually have them measured longitudinally but want to deal with the baseline values first). I'd like to (ideally ...
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Full-parametric Weibull accelerated failure time model using deep-learning library Keras

I wonder if it is possible to fit a full parametric AFT model with the deep-learning library keras. My AFT model assumes that survival function is influenced by some covariate specific acceleration ...
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1answer
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Survival Analysis - 30% right censored data

Just looking for some clarity regarding time-to-event (death) data when there is a large proportion of right censored data (lots of survival). Is this a serious problem for a proportional hazards ...
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60 views

glmnet cox regression and survival prediction

I want to use glmnet cox regression approach to predict survival from methylation data for cancer patients. But I couldn't find any proper reference except this one https://cran.r-project.org/web/...
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Adjusted Survival Curves

Has anyone looked into the article, Adjusted Survival Curves, implemented in the survminer package? I cannot find much information regarding it nor many papers that ...
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Time variable as a fraction when using Cox proportional hazard model

We are trying to estimate the lifetime cumulative default rates for consumer loans, using the Cox proportional hazard model. Since we have a number of different maturities (and the majority have not ...
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Inexplicable bad estimation in a Poisson regression (GLMM)

I need to use a Poisson regression to obtain the equivalent of a piecewise exponential estimation for the survival curve. So far so good. The problem occurs when I add a covariate to my time variable....
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Complementary log-log or log-log transformation when combining estimates from multiple imputation after cox regression

Can anyone give me an argument for or against using the complementary log-log transformation as opposed to the log-log transformation on survival estimates after cox regression in multiple imputation ...
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1answer
49 views

MLE of Weibull hazard and lognormal frailty in R

Consider a Gaussian random variable log(U), with mean mu and variance sigma^2. How can the parameter estimates of the corresponding log-normal frailty model (i.e the frailty random variable is U which ...
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Survival analysis: Individuals with event time = 0, exclude or not?

Data set: 50000 participants Assessments of various risk factors at baseline Dates when participants were included in the study Dates when participants died or were censored (after 2 years) ...
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39 views

Interpretting Cox Regression ANOVA

I'm having difficulty interpreting the results from anova() in the rms package. My confusion arises from what information the <...
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1answer
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Plot Survival by Kaplan-Meier and Fleming on same plot in R [closed]

I need simple help on how to plot kaplan-Meier and Fleming-Harrington Survival estimators on same plot. I have tried several efforts with ggplot2 to no avail. A kind help by anyone would be highly ...
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Survival analysis with quarterly data: Is it really interval-censored?

I'm looking at data where all of the measurements are only available with quarterly time points, e.g. 2005-Q1, 2005-Q2, ..., 2016-Q4, 2017-Q1. This means that the event-of-interest (e.g. death) falls ...
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Lasso acts differently for a large (1mi obs) sample? [closed]

I am fitting Lasso using the glmnet package in R. The data contains 1 million observations and 1500 predictors. We have a survival outcome (time to death) ...
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How to interpret the survival analysis results based on summary results?

I have a gene CFAP97 with expression values and clinical information like FollowupDays and patient_vitalstatus. Using the gene expression data first I classified ...
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1answer
23 views

Simple elaboration on Joint Models' linear equations/trajectory functions

I have been struggling with grasping the intuition behind joint models, and I hope someone can elucidate a particular aspect of theirs. Joint models, first of all, are essentially combinations of ...
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40 views

Estimating death based on repeating sequence?

Currently I'm working on a project, and I reading up on Survival Regression with Cox’s proportional hazard model, which looks like it will work to answer the questions I want to ask. My issue is ...
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1answer
12 views

Data in the Mann-Whitney test

I have a simple question. I wanted to compare two independent survival curves, for example Online resources tell me that the Mann-Whitney test can be used to test two independent groups or ordinal ...
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75 views

Survival analysis: how to account for immortal time with time-dependent exposure

I am working on a survival analysis to look at time to preterm birth (birth before 37 weeks). I have a time-dependent exposure that can occur anytime at or after 28 weeks, defined using a heaviside ...
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Checking PH assumption for a time dependent (T_COV) variable in a Cox PH-regression: with or without the original covariate in the regression?

I am performing a cox proportional hazard regression on survival, in a sample in which almost everyone dies in the follow up period. I have little knowledge on statistics in general but i am reading ...
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1answer
19 views

transformation of continuous variables in accelerated failure time model

Should I do some transformation of continuous variables in accelerated failure time model? In PH model it is needed and martingale residuals are helpful there. I know that PH and AFT models are equal ...
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How would I model underlying probabilities of failure with this data?

I have a dataset with measurements of a machine taken at different timepoints. I'm assuming at every timestep, the underlying state of the machine is a number between 0 and 1, where 1 indicates the ...
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1answer
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How to calculate log-rank test statistic

Depending on which statistics text you read you will get 2 different formulations of the log-rank test statistic. In some texts you will see it specified as: $$ \frac{(O-E)^2}{E} $$ Example 1 Whilst ...
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1answer
29 views

How to interpret if a COX hazard ratio is dependent on 2 variables

Hi so I'm interested in calculating HR for the following variables. age, state and sex. Univariate calculation using R survival package for example looks something like this. ...
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1answer
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Survival Analysis - Truncating follow-up period when there are no events after a certain amount of time

Lets say patients in a trial were followed for over 10 years, but there are no events in either treatment or control group after 5 years (the survival curves are flattened after about 5 years). When ...
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1answer
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How to do “partial” survival analysis on randomly censored data?

Suppose that we monitor a population of devices over an interval $[a,b]$. Some devices are added before $a$ and some are added during $[a,b]$. Furthermore, some devices fail during $[a,b]$ and some ...
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Manually calculating the survival probability S(t) from flexsurv exponential regression parameters in R

I am learning survival analysis for my research. My question is very basic. I created a simulated dataset as shown below: ...
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30 views

ggsurvplot for counting type data showing censoring of all at risk subjects?

I've been trying to create KM plots using the R packages survminer and survival for counting type data. I have the following columns, ...
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Are there unified cure modeling (aka split population modeling) papers in labor economics?

Does anyone know if there are unified cure models (aka split population models) in time-until-employment studies that combine the mixture cure approach with the promotion time approach as described in ...
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1answer
34 views

Survfit function with regression

I'm having trouble understanding what estimator the survfit function produces. For example, if I call ...
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1answer
57 views

Why median is NA for some of the group outcomes in survival analysis?

I'm trying to do survival analysis using the Followup information, patient_vital_status and the expression of gene. I'm using like below: ...
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14 views

Multivariate survival analysis and multiple comparisons in R using survival package

I'm studying how different light cycles and feeding regiments affect survival times in different species and would like to compute pairwise comparisons between the survival curves of 12 different ...
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1answer
56 views

Survival analysis with biased coins

Suppose I have five biased coins $c1, c2, c3, c4$ and $c5$ each with different probabilities of getting heads. Pr. heads for coin $c1=0.5$ Pr. heads for coin $c2=0.8$ Pr. heads for coin $c3=0.6$ Pr....
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cureregr: post-estimation problem predicting hazards

What is the problem: I am using the post-estimation 'predict' command to estimate the hazard rates for individuals after running a cure model (cureregr) and I get the following error message: Maximum ...
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magnitude of covariates in user churn/survival analysis

Hi experts out there! I’m trying to use survival analysis for my user churn prediction. In General, I can get % of survival rate (X axis) as time goes by (Y axis) from survival analysis for one of ...
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2answers
32 views

How to properly do a Survival analysis - Question about start times

I have a monthly report that lists transactional errors made by facilities all over the country. Each row is a single error and the columns represent descriptive information about each error (ID, ...