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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Similar assumptions for log-rank and Cox model. Request for article reference
I understand that the Score function for a Cox model with a single binary predictor with a regression constant equal to zero equals the statistics for the log-rank test (a simple rewrite of the math). ...
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What are the differences between PS-match and adjusted Cox regression?
This is more like an extension of the following question: Propensity Score Matching with Cox Regression
I am wondering what are the differences between these:
matching patients with PS and running ...
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Multi-state Cox models: different formulas for different transitions?
I'm using coxph from Therneau et al's survival package to model a multi-state system. Transitions include:
Baseline -> ...
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Fisher Information for Cox Model
Actually, I'm working on a Statistical Genetics Article (Schaid and al,2010) in a retrospective likelihood context.
In the article, authors present some result about conditional likelihood but I can't ...
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Doing Cox univariate analyses followed by multivariable analysis on significant variables?
I have collected a dataset on a group of patients with a rare disease where not much is known. These patients can have an outcome, X, which has been seen in 50 of the 300 patients. I want to find out ...
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Differences among Cox regression, accelerated failure time regression and linear regression when using no censoring data
I would like to investigate whether social economic status (SES) would be associated with the age of onset of mental illness, after controlling some possible confounders, in the cohort of patients ...
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How to visually assess tt() suitability in coxph? [closed]
For this example, I am taking cues from the time-dependent survival vignette.
I am interested in understanding how to assess the suitability of a covariate-time interaction using ...
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How to plot hazard ratio from coxph model with tt() term [closed]
This question is related to another that I posted here:
How to visually assess tt() suitability in coxph
If we have a time-varying HR that arises from a time-dependent coefficient because we have ...
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Cox-like model: weighted sum of proportional hazards
We are trying to do inference on vaccine effectiveness (VE) during an epidemic in a risk-stratified population.
Models:
Consider the Cox model:
$$ \lambda_{ik}(t) = \lambda_0(t) \exp [\beta X_{ik}] $$
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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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Can I use age as a time varying covariate in a Cox PH?
I am studying how long a rebel group leader remains in charge of a rebel group until they are forced to step down. I have leader-year data with the following variables:
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Martingale residuals in Cox PH model for categorical variable
I understand that for continuous data, martingale residuals can be used to assess the linearity of the variable, but if it's a categorical variable (2 levels) is there any interpretation that comes ...
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Measuring Cox PH predictions
I'm running a Cox PH model in python using lifelines package.
The two performance measures this package offers is log-likelihood or concordance index.
I am aware ...
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How to aggregate confidence interval from spline into intervals correctly for Cox model?
Currently i'm estimating HR splines using mgcv::gam::coxph. My spline is nonlinear and has one turn, so i'd like to divide my spline into two sections given the turn and get conditional estimates for ...
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What test shall I use to validate the use of a certain score to predict my outcome in a survival analysis?
I validate usage of a clinical cardiovascular score to predict the risk of dementia using data from a longitudinal study. Therefore, my outcome is binary (dementia yes or not) and the independent ...
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Is it possible to perform a survival analysis in a patient population only, using their age of onset as time-to-event data?
We have data on the age of onset of a certain disease in a patient population of 1,000 cases. The average age of onset is 60 years. The data were obtained by recruiting patients who visited either of ...
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Error “system is computationally singular” when running cox.zph for a Cox Model
I have built an extended Cox Model in R, with time-dependent covariates, as described in this R vignette.
I have built the model by running the following:
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The logrank test statistic is equivalent to the score of a Cox regression. Is there an advantage of using a logrank test over a Cox regression?
I have understood the logrank test as a "safe" or "conservative" way to check for a difference between two survival curves. It is "safe" in the sense that it is a ...
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Setting a reference in Cox regression with splines and interaction
I run a Cox regression with a continuous variable age and a categorical variable sex. The model includes splines for the continuous variable and an interaction between both. I want to choose the ...
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probability that the failure is on the individual as observed
In his paper Regression Models and Life Tables, where he introduced the proportional hazard model, David Cox states that:
For the particular failure at time $t_{(i)}$, conditionally on the risk set $\...
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Concordance index in survival analysis (Gonen and Heller)
I am working on a project to externally validate a clinical prediction model. The original model coefficients were estimated using a Cox model. The model uses the baseline hazard and coefficients to ...
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How to formulate and simulate data from an accelerated failure time model?
I understand that an accelerated failure time model can be conceptualized as a cox model which includes covariates whose effects depend on actual time, so the convenient expression of the partial ...
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Survival analysis with cluster data
I am performing a survival analysis with cluster data cluster(id) using GEE in R (package:survival).
I was wondering I could correctly interpret the Robust value in the summary of the model output.
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How to create KM curves with time-dependent covariate
Some patient received an treatment as treated group and some did not as control group. In order to consider "immortal time bias", I coded the treatment as a time-dependent covariate. Could ...
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Time varying covariate is polytomous for cox proportional regression, how to deal and interpret?
I am trying to conduct a cox proportional hazard, after I checked the assumptions, it turns out that interaction exists. So, I have to put an interaction into the model. But the time varying covariate ...
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Compare two hazard ratios from two subgroups?
For example, for the smoker group, a cox regression shows that the hazard rate of alcohol use on survival is 1.41. In the non-smoker group, another cox regression shows that the hazard ratio of ...
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Simulating bias comparing linear regression with Cox Proportional Hazard model for prediction on censored data
I wanted to show how censoring biases linear regression and how that could be resolved with survival regression using simulated data. My simulation now suggests, that survival regression (I tried a ...
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Time-dependent effects: tt function using nsk () in coxph()
I am using coxph() to compare tree seedling survival data between three treatments (Large, Small, Control). However, coxzph() showed that the coefficient for the Small treatment differed with time. To ...
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Cox survival PH violated variable is part of an interaction
One of my main predictors violates the PH assumption. I've been reading different ways to deal with this for a while and have decided on an interaction with time after making a person-period file (...
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Calculating the Magnitude of Change in Hazard/Odds Ratios for Different Fractional Units of Change
I have a Logistic and Cox PH model built. My covariates are Age Since Start, Incentive and Starting Balance. All covariates are numerical. The dependent variable is whether or not the account made a ...
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How to compute the cumulative incidence function for a specific covariate in Cox regression model and Fine-Gray model?
I have generated results for Cox proportional hazards model, and Fine and Gray competing risk model, which gives me the hazard ratio and sub-distributional hazard ratio for each of the independent ...
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Cox Proportionall Hazards compared to AFT and the proportional hazards assumption
I am dealing with survival analysis in R in big population datasets with millions of rows. My first option was a cox regression
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Time-dependent area under the precision recall
How to compare the time-dependent precision recall (PR) receiver operating curve (ROC) values for two cox regression models at multiple time points?
To compare two time-dependent AUC values, I would ...
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Cox regression latex output equation explanation
After fitting a Cox model when I export the equation using
w <- latex(f, file='f.tex')
The XB contains a constant which is not one of the beta co-efficient of the predictors in the model. Is this ...
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Can you have "missing" predictors in Cox regression or are these just considered [right] censored data?
If data is extracted from electronic health records and used for survival analysis, can outcome vars be considered missing or are they just considered right censored data points?
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Backward selection for Cox model using R
I want to perform an exploratory Cox regression analysis of medical data using R. I am practicing using the pbc data from the survival function.
Would you recommend performing a backward selection ...
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NRI and IDI with differing follow-up time
I am investigating whether the addition of an interaction term between a biomarker and a comorbidity improves a multivariable cox model predicting post-discharge outcomes.
In addition to the ...
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`pspline()` terms and checking proportional hazards
I have fit a Cox model with pspline() terms for the continuous covariates. I am trying to better understand how pspline() terms ...
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Understanding and reporting Cox models with spline terms
I have fit a Cox model with pspline() terms for the continuous covariates. I am trying to have a better understanding of what happens to report my results ...
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Interpretation of the hazard ratio in a spline model on continuous exposures
I am having trouble interpreting the output from a Cox proportion hazard model with a spline term on a continuous exposure.
In the below example (pseudo-code from R...
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Dealing with non-proportional hazards in a Cox model with many variables and a large dataset
Summary: I am trying deal with non-proportional hazards in a Cox model on a large dataset. My question is whether the proportional hazards assumption really does not hold? If no, is the second model ...
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When to stratify in a predictive model and which c-statistic to use
I am trying to understand what is the most fair approach to computing the discriminative power of a set of predictors $X$ when I have an additional binary variable $Z$ that I know modifies the risk of ...
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CoxPHFitter and WeibullAFTFitter() lifelines implementation
I am trying to build a survival model to predict years of life lost; currently, I am running several different survival analysis methods to compare their results: AFT and Cox PH.
I am using the ...
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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 ...
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Survival Analysis in R: Using Categorical vs. Continuous Gene Expression with survfit() and coxph()
I'm currently performing a survival analysis based on the expression of a single gene. Here's what I'm doing:
I standardized the gene expression data using scale().
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Am I dealing with within-cluster dependence or independence? (Cox proportional hazards model/frailty model)
this is my first time asking a stats questions anywhere online. I'm a young female PhD student and quite anxious about this, so if possible, please be kind. I'll do my best to ask my questions clearly....
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Why we can apply conditional logistic regression to model the effect of air pollution?
In a book called 'Analysing Seasonal Health Data', the time series dataset - CVDdaily was expanded by 'casecross' function,
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How to calculate score residual for cox ph model?
I try to understand the "score residual" from cox ph model in R.
There is one reference site I have used for it.
Can someone help me to get the score residual manually (I mean, using formula)...
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When having non-proportional hazards, should I use stratified Cox by time or Logrank tests within periods?
My data have non-proportional hazards with clear separation. Should I handle it via stratified Cox regression or using separate Log-rank test within subsets?
I will use R only to illustrate.
I want to ...
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AIC of a weighted cox regression model (coxphw)
I have to compare three cox-regression models.
However, one of these violates the PH assumption. Stratfying the variable did not work because it is already categorical. Thus, weighted cox regression ...
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