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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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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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Differences between logistic regression parameter estimates and Cox-proportional hazard parameters

We have been working on a survival analysis. We are examining tree seedling survival over a decade with annual to biannual census intervals. We have been using the package coxme in R for a mixed ...
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How to simplify coxme survival models?

I have some questions about specifying a coxme (mixed-effects Cox proportional hazards) model in R and then simplifying it after reading the ...
David Gibbs's user avatar
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Is missing outcome in survival analysis a problem?

I would like to look at survival in time to event data. So individuals either have an event, or are censored. My problem is the sensitivity for detecting an event differs between arms. I.e. in the ...
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How to better understand when to use Weibull AFT versus Cox Model for Failure Data

I am struggling to understand when I should consider using a Cox regression model versus using a Weibull AFT model to predict the end of life of mechanical components. I have tried to apply the Cox ...
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Modelling recurrent events using Cox regression (in R)

I would appreciate a sanity check of whether I am using Cox PH regression in R correctly to analyse recurrent events. My work has used the instructions proposed in "Modelling recurrent events: a ...
Anthony Nash's user avatar
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Interpretation of scaled Schoenfeld residual for time dependent coefficient

https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf I've been following the vignette on implementing time dependent coefficient in addressing non proportional hazards in a cox ...
Michael Luu's user avatar
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Modelling transition times parametrically in multi-state models (in R)

I've been trying to understand multi-state modelling (MSM) for my use case, which is a simple illness-death model. For a standard 2-state survival analysis I often use parametric models of the time-to-...
Stuart Lacy's user avatar
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Handling Informative Censoring in Survival Analysis

In a survival study with informative censoring (for example, studying the effects of cigarettes on mortality and smokers are more likely to be Lost to Follow Up). This causes the censored data to be ...
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Approximating cox model with time varying covariates using poisson

How do you reformat a dataset in order to perform a cox regression with time-varying covariates as a poisson regression. I'm trying to run a survival analysis regression in python with time varying ...
Luke's user avatar
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Median survival time for stratified Cox model

I have a dataset of 30,000 patients who are matched by surgical procedure. My main exposure of interest is if the patient got regional anesthesia during surgery or did not. I have 27 different ...
Catherine Bulka's user avatar
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550 views

How can I compare parametric and semiparametric survival models?

On a given dataset, I am running a semiprametric Cox proportional hazards model, together with a series of parametric models (Weibul, gamma, lognormal, exponential, etc.). How can I know which is ...
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Cox interactions and co-linearity

I am interested in developing a model to predict survival based on a few predictors: age, sex, and two lab values, albumin and globulin. I have approximately 14,000 deaths in the data. I initially ...
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2k views

Propensity score and Cox regression

I have a retrospective dataset of patients treated with a certain drug (treatment, $n=46$) or with placebo (control $n=96$). The stored variables are age, sex, stage of disease. I want to assess the ...
Andrea's user avatar
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Interpretation of interaction term in Cox PH model when centering LP on mean values of predictors

Let's say I have a Cox PH model for predicting the risk of dying, that in a simplified form looks something like this: ...
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Interpretation AFT, Cox PH and discrete-time hazard model

I am struggling with the interpretation of the AFT model, Cox proportional hazard model and discrete-time hazard model. My question is: Can the coefficients in discrete-time hazard model also be ...
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Cox proportional hazards with time-dependent covariates: predict in R

I would like to use the predict function (or something similar) in R to generate expected values from a Cox proportional hazards model with time-dependent covariates. The model takes the form ...
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Proportional hazards assumption for cox regression - global test or graphical assessment

I have run a cox regression with only a treatment in mind so far and have then tested the proportional hazards assumption along with a graphical assessment using the log-log survival plot. My global ...
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Analyzing uncensored time-to-event data with no risk of events after a certain period

I'm trying to investigate several independents on a dataset with time-to-event data for a treatment. I'm measuring time-to-treatment effect (where treatment effect is a binary parameter). Treatment ...
Erik A's user avatar
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interpretation of cox HR under non-proportional hazard

When the true hazard ratio $\lambda(t)$ is time varying as shown below, I used a standard cox regression to get a hazard ratio. If the hazard ratio of $\lambda=0.78$, how can this value be interpreted?...
Mary's user avatar
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How to manually calculate concordance for a coxPH model

I am struggling to work out how the concordance statistic of a coxPH model is derived. I have built a coxPH model on a small dataset (4 observations). The resultant model is given below: ...
Alex's user avatar
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Kaplan-Meier estimates with missing data on non-survivors

As a hobby application, I want to estimate a Kaplan-Meier curve for "survival" of football referees, i.e., for how long they stick to this activity. I have data for when they started and, if ...
Christoph Hanck's user avatar
3 votes
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Approach to a complex survival analysis

Hello and thanks for reading! I'm a student who has unfortunately 'designed' quite a complicated experiment which I'm struggling to analyse statistically. I do like statistics but my experience is ...
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Cox regression: age covariate within age group strata

I am using Cox regression to calculate the hazard ratio between two treatment groups, in which (as usual) age is one of the confounding variables. The effect of age is strong and markedly nonlinear. ...
Knackiedoo's user avatar
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Concordance index in survival and rms packages

I would like to compute concordance index to validate Cox model. From the following post concordance rms I know that I can use rms package and ...
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One covariable in multivariate Cox regression model shows infinite upper confidence interval value

I perform a multivariate Cox analysis using 'survival' package in R ...
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How can the Cox proportional hazard model be formatted into a generalized linear model?

Is the Cox proportional hazard model a generalized linear model and how is formulated?
Blake's user avatar
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971 views

Right-censored independent variable in Cox/logistic regression

I have a right-censored continuous independent variable that I want to include in a Cox regression. The variable is a physiologic test which is capped at a certain time, say 120 seconds, due to safety ...
Polar Bear's user avatar
3 votes
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82 views

How is the hazard ratio in Cox proportional hazard models affected by the case sampling?

I'm trying to conduct survival analysis using Cox proportional hazard models, looking at a biomarker for heart disease. Age is a major risk factor, so I'm modeling the age as the time scale (counting ...
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Validate predictive power of Cox proportional hazards for individual observations

Note I've edited the example to be more intuitive and closer to my real data Intro I've got data on customers purchases and with it am trying to predict which customers are more likely to make next ...
Vlados's user avatar
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Is there a way to model left truncated and interval censored data in R or SAS?

We have a study where our participant underwent some surgery at time = 0, but at various ages. Our follow-up is based only on Medicare age-eligible people, so we have to wait until they reach the age ...
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heteroskedasticity in logit/cox

I am using a logit and a cox proportional hazard model for my analysis, and the newest version of Stata. I have found that there are no tests to check for heteroskedasticity for logit/probit models, ...
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Survival analysis for matched set cohort data - Methods for absolute and relative risks?

BACKGROUND I have a matched data set with 10,000 cases and 20,000 controls. Cases are defined as such due to a diagnosis of COPD (Chronic Obstructive Pulmonary Disease - a lung disease caused by ...
Heala45's user avatar
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532 views

Simulate censored data cox model

I would like to simulate interval-censored data in a Cox model. In the R package intcox I found the following code: ...
rose's user avatar
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571 views

How to use Cox proportional hazards model in interval-censored data with time-dependent variables?

The question is self-explanatory. I have survival data (n=156) which, in about half of the observations, is right-censored or interval-censored. I'm am using R to do the analysis and I know I can use ...
JMarcelino's user avatar
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0 answers
1k views

How to interpret the frailty terms in a coxph.penal model?

I have the following coxph model: Surv(Y) ~ genotype + treatment + age + frailty(batch) + genotype:frailty(batch) ...
f1r3br4nd's user avatar
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What are the independence assumptions of Cox models with time varying covariates?

In longitudinal studies, you might be observing time-to-event endpoints with some covariate that changes as a function of time. When covariates are fixed at baseline, the only independence assumption ...
AdamO's user avatar
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3 votes
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Survival analysis - Using parameter estimates of a fully-parameterized PH model into an AFT model

I want to predict an event based on transactional data. I'm only interested in predicting either future hazard or time-to-event. My understanding is that to predict in the future I have to use a fully-...
cwarny's user avatar
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Cox Regression: handling immediate drop-outs

In an RCT with two groups, I‘m currently analyzing data using cox regression. While I‘m familiar with the concept of censoring, a rather substantial amount of participants (~32% and 35% in the groups) ...
Survival's user avatar
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2 votes
1 answer
60 views

Survival analysis with different follow-up times in exposure groups

I have been asked to help analyse some recurrent-events survival data (using an Anderson-Gill model) looking at risk of disease relapse among two different subtypes of the disease (primary covariate) ...
LucaS's user avatar
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Proportional hazard assumption: graphical approach vs subsampling

Hopefully someone can guide me on the following. I have a large dataset (> 151k firms with multiple observations per firm). My dataset looks at firm failure using counting process style and my ...
Laura Hill's user avatar
2 votes
0 answers
130 views

Time varying coefficients with splines in Cox model

I am wondering whether it is valid to fit spline interactions between time and predictor variables (either categorical or continuous) in a Cox model. I am having difficulties specifying this model, ...
user167591's user avatar
2 votes
0 answers
180 views

How to model an interaction in a propensity-score matched dataset

Suppose I am performing a propensity score matched analysis using the MatchIt package in R, following the example reported here: https://kosukeimai.github.io/...
user89547235's user avatar
2 votes
1 answer
138 views

Understanding the simulated cox ph example from mgcv for generalized additive models

I am trying to learn cox Ph for gam. I found an example code in mgcv package to generate data for cox ph gam. However I can not understand a point there. ...
user avatar
2 votes
0 answers
58 views

How do I complete a sensitivity analysis to simulate censored data?

I am currently trying to analyze the duration of the egg stage of two species of insect (factor 1; 2 levels - HA and AP) at several different temperatures (factor 2: 5 levels - 20, 23, 26, 29, 32) ...
Insect_biologist's user avatar
2 votes
0 answers
497 views

Different prediction plot from visreg versus ggplot(Predict())

The problem: I am hoping to visualise interaction effects between a continuous and a dichotomous variable from a cox proportional hazard regression. When graphing this with different packages (visreg ...
Lee's user avatar
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2 votes
0 answers
86 views

Likelihood of a censored data vs. likelihood based on IPCW weights

I was wondering if there is a relation between the classical form of the likelihood when we have censored observation : i.e Let's define $T_i = \inf(X_i,C_i)$ and $\delta_i = \mathbb{1}_{X_i \leq C_i} ...
SKOUBANI Mohammed-Amine's user avatar
2 votes
1 answer
361 views

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 ...
AdamO's user avatar
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2 votes
0 answers
312 views

Adjusting for drop-outs in survival analysis when all dropouts have time = 0 and event = 0

I have data where participants were assessed at two timepoints ; baseline and follow up. At baseline, participants were categorised based on presence of a marker (yes = 1, no = 0). At follow-up, ...
a.henrietty's user avatar
2 votes
0 answers
154 views

Step functions for non-proportional hazards

I have a stratified Cox model with covariates ("big") which violate proportional hazard assumptions: ...
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