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Questions tagged [cox-model]

Cox proportional hazards regression is a semi-parametric method for survival analysis. No distributional form needs to be assumed, only that the effect of one-unit increase in a covariate is a constant multiple.

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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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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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similar risk estimates between groups but have significant interaction

I am running a cox proportional hazard model to analyze the association between air pollution and risk of mortality. In the subgroup analysis, I obtained some confusing results. For example, when ...
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How to compare two cox regression coefficient for one predictor on two different outcomes?

Here are the results of the univariate analyses by Cox regression to determine whether a variable has a differential effect on survival in the first 5 years versus the latter 5 years. But I don’t know ...
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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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Cox proportional hazard analysis with non-uniform samples; power analysis

We have a study involving 10,000 patients, 5,000 of them treated with drug A and 5,000 with drug B. We want to know if drug A is more effective than B. The median time to event (death) after treatment ...
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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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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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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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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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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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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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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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In cox regression analysis, do time dependent covariates have to persist indefinitely

I'm new to Cox regression analysis and have been following helpful advice from Therneau, Crowson and Atkinson. I have learnt that time dependent covariates persist and that their value can be changed ...
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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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proportional hazard assumption

What is the assumption we must check if Cox proportional hazard regression is used? Is my step and method to build on Cox proportional hazard model correct, or not? Can I used ln(-ln(survival))curve ...
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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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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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How do I apply weights to a Cox Regression Model in R?

I am trying to answer the question of whether service in a certain organization has an effect on age of first marriage, and am interested in using the Cox model to understand the difference in the ...
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1answer
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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
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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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How to calculate the survival function in R for a glmnet cox family?

I have a sample data of 583 type 2 diabetes patients and want to calculate the 5 year incidence probability of an event for every patient. Variables which were collected are time to an event variable ...
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Schoenfled Residua test shows proportionality hazard assumptions holds but Kaplan-Meier plots intersect

"If Kaplan-Meier plots cross each other then proportional hazard assumption does not hold". The issue I am facing is that I got the Kaplam-Meier plot(bleow). We can clearly see that it is overlapping. ...
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How to calculate treatment effect and its confidence interval for subgroups in a clinical trial using Cox regression models

Plenty of literature exists on how to interpret subgroup analyses in clinical trials. One example is in this thread. Unfortunately, I have not found any paper explaining how to perform a subgroup ...
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Hazard ratio for more than two groups

Consider the line of code below for implementing Cox model in R and finding the hazard ratio: fitcox <- coxph(Surv(Survival,Death) ~ clusters, data = data) ...
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Survival analysis with time dependent covariates and non-proportional hazards in R

I am attempting to do a survival analysis which will examine the effects of both rainfall (a time-dependant variable) and altitude on nest survival in a species of wasp found in NW Ecuador. I have ...
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Survival analysis of two dependent variables (hatching time and total life duration)

I strive to find the best approach to analyse survival data from an experiment where random samples of fish eggs (sample size 30) were put into 3 different solutions of 8 heavy metals (total 24 ...
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Interpretation of cox.zph Output with Smoothing Splines in R

In Luke Keele's paper, "Covariate Functional Form in Cox Models", Dr. Keele carries out two Grambsch and Therneau non-proportionality tests, that is, one for a model without splines and one for a ...
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R Cox Proportional Hazards (no covariate) versus Nelson Aalen estimator

As titled, is CoxPH model with no covariate the same as a Nelson Aalen estimator? As when fitting a coxph() in R, do I get the Nelson Aalen (NA) estimator instead of Kaplan Meier? Does the Breslow ...
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Check homogeneity in Cox Proportional Hazard Regression

I'm investigating the associations of a quartile variable (let's say: X, consists of 1st/2nd/3rd/4th quartiles based on categorization of a continuous variable) with survival in Cox Proportional ...
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Time Dependent Coefficient in Cox Model using R [duplicate]

I ran into a problem where I have one continuous covariate which I suspect having a time-varying coefficient. This covariate was measured only once at baseline for all subjects in the dataset with no ...
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Compare fit Cox models with clusters in R

I would like to compare the model fits of Cox proportional-hazards models with a likelihood-ratio test (or equivalent). This usually works by comparing the fit with the ...
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Survival Analysis: event & censor coding

Simple query I suspect. I've been running a cox regression in R and noticed that my time-to event and time-to-censoring models produce identical output. Is that what I should expect? That is, does it ...
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1answer
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Survival analysis for fixed time period licencing

I need to predict attrition of customers who use product that has fixed time period (1 year) licence. I have monthly feature usage data, for example the product has 5 features f1, f2, f3, f4 and f5, I ...
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Bias in parameter estimates for Cox proportional hazard model when covariates are collinear

For linear regression, if $y$ actually depends on two positively correlated covariates $x_1$ and $x_2$ (we can call it the true model), and if we only include one covariate, say $x_1$, in the ...
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R package `survival`: the estimated parameters are off

I simulated some survival data and used the R package survival's function coxph to estimate the parameters, but they are ...
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Poisson Regression vs. Exponential_Weibull vs. Cox Regression vs. Negative Binomial [closed]

Problem: I would like to predict the number of days a student continues with school using student and school level covariates (no censor data). Data includes the number of days that the student ...
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Interpreting this KM Curve

I would like someone experienced to look at my KM curve. I have categorized a continuous clinical variable into 2 groups based on its median. The Log rank test is significant (p=0.0052). I have then ...
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Cox's Proportional Hazard coefficients clarification

I'd like a clarification about the Cox proportional hazard coefficients reported on this page. For example, doesn't the hazard ratio (HR) for gender in that ...
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1answer
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What are criteria to select the variables to include in a multiple Cox regression model

I have a group over about 500 subjects and want to perform a cox-regression to find predictors of an event taking into account the time to event. I have 12 potential predicting variables that I want ...
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1answer
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Cox regression - unknowns within covariates

I have run a model for duration in treatment. Records have either exited treatment or are still in treatment. If exited, the number of days is known. If still in treatment, the number of days in ...
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Real 1 dimensional non-binary data where Cox Proportional hazards model fails

I am learning about the Cox Proportional Hazards model and understood that it is very flexible, even when the assumption of proportional hazards is not met, e.g. for additive hazards. But say we have ...
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Cox Regression Specifics: Standardizing, Log Transforming

In the statistical analysis of this paper I have some questions regarding their approach. https://academic.oup.com/ndt/article/33/6/1001/3978817 “Variables with non-normal distributions were either ...
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Shared Frailty Assumptions

Do we need to check the proportional hazards assumption when running a shared frailty model for clustered data?
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Predict hazard relative to a specific sample

I want to predict the hazard ratio and 95% confidence intervals relative to a specific sample rather than the population mean: ...
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Cross-validation of (Cox) survival model with very high censoring rate

I am currently working on survival analysis of data with very high censoring rate (~99%), and the number of events is only about 500, using R. I would like to ask in such case, whether the validate() ...
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Question regarding the Supervised Principal Components method

I'm going over Bair's and Tibshirani's Supervised PC method and looking at their R package tutorial here. In their paper, in the section titled "A Breast Cancer Example," it seems they find the most ...