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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cox frailty model in R

I run a cox frailty model(model 1) in R, by adding new co-variate to model(model 2) The ACI decreases that show the new model is better than model 1, but the variance of random effect of model 2 is ...
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Non-monotone Survival Function?

I was given the task of plotting the graph of a survival function with the following details defined. hazardrate (lambda) = λ(t) = 0.2 (1 + sin(tπ/12)) the underlying process is exponential I am ...
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Is this approach the right one in Cox with time-dependent covariates in R?

first of all I would like to thank you for reading my post. Then let me describe my situation: I'm trying to develop a Cox model with time-dependent covariates. I have a dataset of patients with ...
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What's the benefit of carrying out a survival analysis vs LM/ANOVA

I work in a lab where group members sometimes individually carry out an experiment of the following form: pairs are bred at some definite time the pairs are grouped by in experimental treatments (i.e....
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How to produce a nomogram for a conditional survival model?

Conditional survival is the survival probability after already surviving a predefined time period. The formula used for conditional survival (CS) was: CS(x|y) = S(x + y)/S(x), where S(x) represents ...
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How to account for dependencies in survival analysis of PS-matched cohorts with replacement?

I work on data from a cohort study (n = 3100). We want to compare outcomes of individuals with a special condition (n = 300) and their matched controls. I estimated propensity scores and used genetic ...
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Decision making with respect to utility function

I am currently working on a small project targeted towards predicting survival times (red, green functions) of certain engine parts. The ultimate goal is to decide what part would be the best choice ...
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Estimating age group specific hazard ratios from cohort data with left and right censoring

Background on the data: I have a dataset from a cohort of hundreds of thousands of individuals. Variables of interest included are: age at start of follow-up, disease endpoints, age at endpoint or ...
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Calculating hazard using Cox regression

I'm using the Cox regression model in lifelines (python) to try and predict what the probability of a patient surviving X days is given several variables. Do to some very silly restrictions on the ...
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Exposure onset unknown in time to event analyses

If I want to model the time to an event (cancer) in a group of patients exposed to e.g. a cancerous substance. I now have some people where I do not know if they were already exposed to the substance ...
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How to calculate the number of events at a time T from a Cox proportional hazards model and/or a Kaplan Meier survival estimate?

Given survival curves, S(t) where t is months as a customer, how do I calculate the number of events (i.e. customer churns) at a given time t? Intuitively, to find number of events at time t, I ...
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Assuming identical base hazards up to a multiplicative constant, what is the probability that event A will happen before event B?

Let's say I'm a retailer with a finite supply of widgets. Both men and women visit my shop. There are more men who visit my shop than women, but women are more likely to buy a widget. I'm assuming ...
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How to interpret left and right censoring

I am fully aware that question regrading left and right censoring has been asked before. I will however post my own question, as I believe that its focus differs significantly. Here goes: I have a ...
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Multiple comparisons problem in survival analysis

I would like to determine which variables have impact on the survival of patients suffering from a disease. It requires performing e.g. log-rank tests. The question is what about the multiple ...
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Choosing strata in stratified log-rank test

Let's say I would like to see which factors affect the survival of patients suffering from cancer. And let's assume I have two variables: chemo ($0$ - if a patient is not treated with chemotherapy or ...
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Estimating survival curve purely based on observed events under a given time period

Suppose you wish to estimate the survival curve (i.e. probability of surviving until a given age) of the human population by observing the ages of those humans passing away under a small observation ...
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Violation of Proportional Hazards Assumption by a Continuous Variable

I'm constructing a multivariable Cox model and I am trying to assess whether the assumption of proportional hazards is valid using scaled Schoenfeld residuals (using ...
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Scaled Shoenfeld Residuals

When constructing a multi-variable Cox model, is it necessary to check the proportional hazard assumption for each covariate individually by first fitting a univariable model and checking the ...
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Survival Analysis - log-rank test

I'm comparing the survival curves of two treatment groups. For the most part of the time period, the two curves are similar with largely overlapping confidence intervals. This is true until a later ...
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Where can I get longitudinal data of the COVID-19 cases? [closed]

Where can I download a full dataset of the SARS-CoV-2 pandemics containing time information for each individual (date of infection, date of death, age, gender, weight, censoring information...) It's ...
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How to analyze clinical outcomes after propensity matching

Suppose I have two propensity matched groups whose covariates are balanced. How do I analyze clinical outcomes between the groups. I would be interested in overall survival, one year survival, and ...
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Python lifelines: How to do a survival analysis on panel data?

I have panel data on companies and I'm interested in how several DVs and covariates impact the time until a company gets funded. My data (pandas Dataframe) looks something like that: ...
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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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How to extract cumulative hazards from mixed-effect survival models?

I'm struggling to extract cumulative hazards from mixed-effect Cox models in R. I managed to extract survivals for each random level separately, but is there a way to obtain overall survivals ...
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Survfit function in R for Cox model and predicted conditional survival

I'm wondering how survfit in R estimates predicted survival conditional on having survived to a particular time/age. Specifically, I have a Cox proportional hazards model for mortality (saved as ...
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Issues with switching between discrete and continuous time in a linear mixed model

I'm confused why switching from discrete time to continuous time is not more of an issue. While talking about animal survival data from day 1, day 2, & day 3 in an exposure experiment, the ...
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JointLCMM “the leading minor of order 1 is not positive definite” error

I am using JointLCMM to model trajectories of a dynamic risk variable while controlling for competing events (censorship, event-type1, event-type2). My code is written as ...
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How to compute variance of Cox model coefficient estimate using Fisher information?

We have Cox proportional hazards model: $$ \lambda(t,x) = \lambda_0(t)exp(\boldsymbol \beta'\boldsymbol x),$$ where $\boldsymbol \beta$ and $\boldsymbol x$ are vectors. To make it simple, lets say ...
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Is it logic to perform a time to event analysis (survival) when the event will always occurr?

My question is regarding a hypothesis of a medication X that decreases viral shedding. I know that even for the placebo patients viral shedding will occur but of course later. Is it logic to perform a ...
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Why does Survival curve sum up to 100% when less than 50% experience event? R

This question is identical to one I have asked at stackoverflow. I have been suggested that it was better suited to post here. http://stackoverflow.com/questions/60757904/why-does-survival-curve-sum-...
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How to deal with a single biomarker measurement that is time dependent

Information: We measured about 50 biomarkers derived from 100 patients. There is only one time point at which the sample is collected. The samples were stored in the refrigerator until we analysed ...
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Should I use logistic regression prior to Cox regression?

So I've got a dataset of patients suffering from the disease, which consists of different types of data such as age, education level, blood test etc. And I want to investigate the influence of these ...
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How to simulate from a step (simple function) hazard function?

I have a step hazard function $h(t)$ (a simple function that jumps at specific times and it is constant between those jumps). Something like: How can I simulate survival times from this hazard ...
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rms/R: How to apply survSplit on two time-depedent covariates, one being a discrete covariate transformed with restricted cubic splines?

I am doing a survival analysis of time p$os.neck to death p$mors using a Cox Regression. Please, find my data sample ...
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Predicting if an event will or won't occur in a fixed time period

Hypothetically, I have sales data from a shoe store. The store would like a model, which can predict if a customer will purchase a given product (always the same product, thankfully!) within a 1-month ...
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Is Cox Proportional-Hazards model appropriate for discrete time points

I'm dealing with medical data and I'd like to determine the dropout rates at about 10 different time points. Further I'd like to see the effect of various covariates on the dropout rates. Would a Cox ...
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Predict event probabilities and visit times in cox regression with gap time approach

I run a cox model on my data looking at times between gym visits. I want to predict the probability of a customer visiting the gym at a specific point in time and also the number of visits in a given ...
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survfit and kalbfleisch-prentice method

To estimate the Kalbfleisch-Prentice survival probabilities with survfit, I noticed that these do NOT correspond to the ones that result from exp(-H). However, for the default S en H probabilities ...
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Strange Standard Error from Survreg (R)

By changing one datapoint from 4 to 2 the standard error goes from 0.24 to 9.19. Also other small changes in data results in unrealistic estimates of the standard error. The code below illustrates how ...
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Stepwise regression for left-censored using NADA - R

I'm working with environmental data which are left-censored and I found the R package NADA which seems to do the job. After fitting a complete model, using the cenreg function,I'd like to do a ...
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How to interpret time-dependent covariate in Cox regression with SPSS?

I'm struggling to find information on how to interpret time-covariate interaction and the main effect of the covariate when both the main effect and interaction are statistically significant. Can I ...
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Interpreting and Simplifying Cox PH Results

In my model I am considering the rate of account closures and my covariate is the interest rate for the account holder. My HR is .4073 and I understand that increasing the interest rate offered to ...
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weird outlier in a cox regression model

I'm using normal deviate residual to identify outliers, and I'm confused that my plot seems to suggest that there are unreasonably a lot of outliers...? Has anyone seen something like this? ...
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Difference between Schoenfeld global test and covariate specific Schoenfeld Individual test in R

In R package 'survival', I am not able to understand the difference between Global Schoenfeld test and Individual Schoenfeld test and teh corresponding p-values. I have clinical data with three ...
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Cox regression with fully factorial experimental design

I am currently trying to evaluate data from a study we performed using a Cox regression (from survival analysis). First off, let me apologize for probably using wrong words in some places - I am not ...
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Jointlcmm error when trying to use competing risks

I am still attempting to use jointLCMM to model trajectories of a risk variable while controlling for data missing not at random due to survival events. I am trying to control for multiple events ...
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How to know event in kaplan Meier?

Below is the Kaplan-Meier curve for analysis of minutes from hospital admission to patient being setup in an ICU bed. For this analysis, what’s the event? What’s the time origin? Describe what the ...
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Kalbfleisch Prentice survival calculation for Cox PH model

A method to estimate survival probabilities for a Cox PH model comes from Kalbfleisch and Prentice. It is explained in their 2002 book on page 114. They present a formula for the likelihood in terms ...
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Survival Analysis results are counter intuitive, where am I going wrong?

I am using Survival Analysis to analyse a data set, but i'm having a bit of trouble. The data consists of everyone who has/has not been terminated from employment within a 4 year period. The aim of ...
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Problems with informative censoring in survival analysis/failure time analysis

I recently began self-studying certain topics in survival analysis and just became acquainted with the concepts of 'informative' and 'non-informative' censoring. To illustrate the gaps in my current ...

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