Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

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.

Cox proportional hazards regression is a very popular semi-parametric method for survival analysis.

It is semi-parametric in that the baseline hazard is left unspecified, but parameters for the effects of covariates are estimated. Eliminating the possibility of misspecifying the baseline makes the beta estimates more robust.

Proportional hazards means that no matter what the baseline hazard may be at any point in time, the ceteris paribus effect of a one-unit increase in a covariate is a constant multiple of the baseline hazard.

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Prediction in Cox regression

I am doing a multivariate Cox regression, I have my significant independent variables and beta values. The model fits to my data very well. Now, I would like to use my model and predict the survival of a new observation. I am unclear how to do this…
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Does Cox Regression have an underlying Poisson distribution?

Our small team was having a discussion and got stuck. Does anyone know whether Cox regression has an underlying Poisson distribution. We had a debate that maybe Cox regression with constant time at risk will have similarities with Poisson regression…
Julie
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In survival analysis, why do we use semi-parametric models (Cox proportional hazards) instead of fully parametric models?

I've been studying the Cox Proportional Hazards model, and this question is glossed over in most texts. Cox proposed fitting the coefficients of the Hazard function using a partial likelihood method, but why not just fit the coefficients of a…
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How to interpret the output of predict.coxph?

After fitting a coxmodel it is possible to make predictions and retrieve the relative risk of new data. What I don't understand is how the relative risk is computed for an individual and what is it relative to (i.e. the average of the population)?…
user4673
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Cox baseline hazard

Let's say I have a "kidney catheter" data set. I'm trying to model a survival curve using a Cox model. If I consider a Cox model: $$h(t,Z) = h_0 \exp(b'Z),$$ I need the estimate of the baseline hazard. By using the built-in survival package R…
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How to get predictions in terms of survival time from a Cox PH model?

I want to develop a prediction model (Cox PH) for all-cause mortality in a dataset of participants of whom (almost) all have died at the end of follow-up (e.g. 1-year). Instead of predicting the absolute risk of dying at a certain timepoint, I…
Rob
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What is the "$R^2$" value given in the summary of a coxph model in R

What is the $R^2$ value given in the summary of a coxph model in R? For example, Rsquare= 0.186 (max possible= 0.991 ) I foolishly included it a manuscript as an $R^2$ value and the reviewer jumped on it saying he wasn't aware of an analogue of…
danielsbrewer
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Time dependent coefficients in R - how to do it?

Update: Sorry for another update but I've found some possible solutions with fractional polynomials and the competing risk-package that I need some help with. The problem I can't find an easy way to do a time dependent coefficient analysis is in R.…
Max Gordon
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Why are p-values often higher in a Cox proportional hazard model than in logistic regression?

I've been learning about the Cox proportional hazard model. I have a lot of experience fitting logistic regression models, and so to build intuition I've been comparing models fit using coxph from the R "survival" with logistic regression models fit…
Jonah Sinick
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Cox model vs logistic regression

Let's say we are given the following problem: Predict which clients are most likely to stop buying in our shop in next 3 months. For each client we know the month when one started to buy in our shop and additionally we have many behavioral…
Tomek Tarczynski
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How can machine learning models (GBM, NN etc.) be used for survival analysis?

I know that traditional statistical models like Cox Proportional Hazards regression & some Kaplan-Meier models can be used to predict days till next occurrence of an event say failure etc. i.e Survival analysis Questions How can regression version…
GeorgeOfTheRF
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How to estimate baseline hazard function in Cox Model with R

I need to estimate baseline hazard function $\lambda_0(t)$ in a time dependent Cox model $\lambda(t) = \lambda_0(t) \exp(Z(t)'\beta)$ While I took Survival course, I remember that the direct derivative of cumulative hazard function ($\lambda_0(t) dt…
elong
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Interpretation and validation of a Cox proportional hazards regression model using R in plain English

Can someone explain my Cox model to me in plain English? I fitted the following Cox regression model to all of my data using the cph function. My data are saved in an object called Data. The variables w, x, and y are continuous; z is a factor of…
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How to generate predicted survivor curves from frailty models (using R coxph)?

I want to compute predicted survivor function for a Cox proportional hazards model with frailty terms [using survival package]. It appears that when frailty terms are in the model, the predicted survivor function cannot be computed. ## Example…
ledzep
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What are the options in proportional hazard regression model when Schoenfeld residuals are not good?

I am doing a Cox proportional hazards regression in R using coxph, which includes many variables. The Martingale residuals look great, and the Schoenfeld residuals are great for ALMOST all of the variables. There are three variables whose Schoenfeld…
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