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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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Help with cox regression (survival analysis)

I had a few questions about analyzing my data via cox regression. Relatively simple data: the effects of rainfall amount and frequency on survival of tadpoles in small ponds. Not too sure if this is ...
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Predicting whether house is sold: regression or classification

I am new to machine learning (I am currently following the Udemy course machine learning from A-Z). Basically, I would like to reproduce the following analysis (https://www.datasciencecentral.com/...
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Cox Model with time-varying covariates in mlr

I am using the mlr package in R to perform survival analysis. mlr includes the Cox Proportional Hazards Model (function coxph from library survival) as one of its integrated learners. As I understand ...
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Minimum sample size to trust univariate cox regression

I have performed a univariate Cox proportional hazards regression for an admittedly miniscule group of 25 samples, and consequently received a certain p-value (significant) and an associated ...
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Survival analysis of identical items in lifelines

I am doing survival analysis of hardware (more precisely, hard disk drives) and wanna predict HDD expected lifetime from its specs. I have a dataset of drives, where for each drive its lifetime in the ...
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How to model change in independent variable for Cox Proportional Hazards Model?

I'm interested in calculating a time to event model (Cox Proportional Hazards Model) and one of my independent variables has multiple measurements. I'm planning on using a time varying covariate for ...
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Interpretation of Cox Hazard Model with quadratic term

I am having trouble finding information on how to interpret coxph model hazard ratios with a quadratic term. Some of my variables are continuous count data, whereas others are continuous percentages. ...
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Survical model: get time-dependent survival estimates with nested random effect and repeated measurements

In an ecological experiment I have recorded survival of individuals in response to two different food items (treatment). Individuals belong to different families (random term) and are measured at 5 ...
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Cox regression with two events

We have a status variable with three events: 0) Censored 1) Relapse 2) Death We want to examine if two different types of medicine have a different risk on either death or relapse. How can we compare ...
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Extremely huge Hazard Ratios from Cox regression

We made a cox regression and ended up with huge HR for some of our variables. One of them (which was an interaction) gave us a HR=2747,093. Our dataset consists of only 74 observations. What is wrong?
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Using Mean Cumulative Function (Nelson-Aalen) to assess drug efficacy

I have a large medical retrospective longitudinal dataset of electronic health records. An individual is identified by an ID. A medical event or drug prescription event is identified using a code and ...
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How to control for severe medical cases using survival analysis and Cox regression?

I have a longitudinal medical record dataset. My cohort is made up of patients with a particular disease. There are no members of this cohort without this disease. Disease indications are denoted by a ...
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Bayesian approach for exponential and Cox proportional hazard model in R

I have difficulty understanding and applying the Bayesian approach to survival analysis. I assume that data follow exponential life time likelihood and that failure rate lambda can be expressed in ...
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Time dependent variable in survival analysis using Cox regression

Trying to determine how to analyse a time dependent variable (rainfall) in a survival analysis. Two rows of example data for animal A and animal B as below: Each value next to the animal represents ...
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Cox proportional hazards model, problem with correlated predictors or overfitting?

I have a question concerning a Cox proportional hazard model (in R) on which I would love to get your opinion and feed back! I think that there is a problem, however I would like to be sure and ...
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Violation of the proportional hazard assumption, interaction with time. Am I taking the correct steps?

I will try to keep my question as short as possible. For my thesis I am researching if a risk score can predict graft failure in a cohort of $596$ patients over the course of $10$ years. (The ...
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How to validate(with sample-split data) and calibrate Cox model with time-dependent covaraites?

I am building 2 cox models: Without time-dependent covariates With time-dependent covariates. 1.The first model (without time-dependent variables) as specified below in R works fine and I have no ...
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Time dependent variable (daily rainfall) in a cox survival analysis

I'm trying to analyse the effect of rainfall (a time dependent variable) on animal survival. In order for an animal to be measured as 'survived' in my study it needs to be found for a minimal period ...
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Changing the baseline hazard ratio at each event in a PWP Cox model

I am performing a PWP (conditional) recurrent cox regression analysis over medical records. For each individual, events are indicated by dates in their medical record. It is, therefore very easy to ...
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Different starting survival/hazard in Kaplan-Meier/Cox-regression

I couldn't find an existing answer to this yet. If there is, please share the link. I wondered if there is a problem with Kaplan-Meier analyses or cox-regressions when already at the beginning of ...
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Calculation of propensity score using cox regression analysis

I want to assess the association of a treatment with survival time in patients. The background information of patients like age and severity differ between the treatment group and non-treatment group. ...
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1answer
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How to interpret CoxPH survival regression

I have a time to event data. Where 20% of the events are observed, so, 80% of the events are censored. Using this data I developed a CoxPH model using python ...
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Linear predictor from coefficients of Cox PH model

I need to calculate the linear predictor of a Cox PH model by hand. I can get continuous and binary variables to match the output of predict.coxph (specifying 'lp') but I can't seem to figure out how ...
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Compare hazard ratios in case-control setup

quick disclaimer: first time poster; i have searched through the forums extensively but please bear with me if this is a silly question or point me towards the solution if it has been answered before. ...
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How to estimate the hazard function?

I model the survival data with a piece wise constant exponential distribution at time t. Let R be the total number of the population at time t, and D be the number of deaths observed at time t+dt. So, ...
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Statistical test on Proportional Hazards Assumption

Usually the scaled Schoenfield residuals and related test (e.g. cox.zph) are used to show that the proportional hazards assumption is not violated. I would like to show that the proportional hazards ...
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1answer
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How to interpret hazard ratios of Cox output?

I'm really struggling to understand how to interpret my R outputs in terms of hazards ratios. I have ran a Cox proportional hazard regression to compare survival between 2 treatment groups (neutron ...
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log transform fixed PH in Cox model - how?

I have survival data to which I am fitting a Cox model with a continuous predictor. The cumulative martingale residual method (supremum test) of Lin, Wei and Ying suggested that both proportional ...
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When doing Cox regression, what should we take as event duration for censored data, and how should we divide the data into training and testing sets?

I am starting out with survival analysis, and am confused about some things specifically in Cox regression. I have not found a tutorial that explains these things clearly, that's why I'm posting this ...
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R equivalent of SAS PHREG: HAZARDRATIO

I am trying to find the equivalent of the SAS PROC PHREG: HAZARDRATIO command in R. Specifically, I want to evaluate the effect of a drug vs. placebo for different values of BMI. My SAS code is: <...
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Interpreting outputs in R coxph model

This is a follow-up question to the one posted here. I have run a proportional hazards model in R using the coxph function. The model includes 3 covariates: ...
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Concordance index

Let A and B be two models for survival time prediction, which achieve concordance indices of 0.5+a and 0.5-a respectively for 0 < a < 0.5. Is the performance of model B equivalent to A's ...
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1answer
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Survival Analysis in Hockey - Usage of coxph and survfit

I'm investigating the difference between Regular Season and the Playoffs in hockey using Survival Analysis in R. My dataset has the variable time_diff, which is ...
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Determining pairwise differences in Cox proportional hazards model

I am running an analysis looking at mortality data (of fruit flies) in an experiment containing four different juvenile treatment conditions. Individual flies were placed into separate containers, ...
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Survival analysis problems using Cox regression in R

I downloaded gene expression data from TCGA and analysis Cox-regression. I want to know hazard ratio under the gene expression data 3780.797 5272.794 32251.525 24584.968 4423.347 4378.428 14925....
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How to estimate changepoint from Cox survival model with time-varying effects?

I'm wondering the best way to model the duration of time to a changepoint in survival within a known-fate, continuous time survival model (as well as estimate survival rate before and after the ...
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1answer
25 views

Predicting survival time from log-hazard

I have estimated a Weibull regression model in BUGS/JAGS which gives me the log-hazard as a function of intercept (baseline hazard) and covariate effects. The intercept is estimated as -9.826 and one ...
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How to calculate total failures in an AG-model, when the survival prob. are calculated?

I have fitted an Andersen-Gill model to a dataset which contains customers of a large car dealer. Between 2000 and 2017, a customers bought at least 1 car and at most 5 cars. They enter the study at ...
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Crossed and multi-nested factors in GLM/Cox mixed models

In the fig. below there is a graphic summary of the experiment that I’m designing. I will have two factors (i) time that lobster egg clutches are exposed to the air (air-exposure), three levels of ...
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1answer
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Cox proportional hazards model and dummy variables

I have some doubts while doing this question. I tried out parts (a) - (c) and am quite confused by (d). Would appreciate if someone can help to check my work to see if I have done it correctly, ...
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What is the Cox Partial Likelihood the partial likelihood of?

In linear regression, the likelihood works as follows: Suppose that $Y \mid X, \beta \sim \mathcal{N}(\beta^T X, 1)$. Then the likelihood of $\beta$ given a datum $(x, y)$ is $L(\beta; x, y) = \...
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developing and assessing a prediction Cox model using lasso

I wonder if anyone can comment on if the following modelling strategy is valid please? I have a 200 patient survival data set (actually 2 data sets: 40 events and 160 events) and 100,000 ish candidate ...
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1answer
47 views

How to calculate expected risk from fitted Cox PH model in R?

I'd like to calculate expected risk (cumulative incidences), which are derived from fitted Cox PH model using R packages. I have the fitted Cox PH model like as follows: [Variables] Dataset: 10,...
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Cohort Study Sample Size and Multiple Comparisons

I'm designing an epidemiological retrospective cohort study with a large number of exposures and outcomes, and I'm trying to figure out how many subjects I'll need in order to run all my analyses. The ...
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1answer
25 views

How do we maximise power for observational proportional hazards model?

This question relates to the optimal study design when looking at survival to event based on observational data (i.e. the precise time of event will be unobserved but we can observe status at times ...
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What is the equivalent of cross-validation for a fitted Cox Proportional Hazards model?

I am studying the effects of customer interaction on the probability that the customer will adopt a recommendation we make to them. For example, we might send out a first email, then a follow-up email ...
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1answer
37 views

Piecewise survival analysis?

I am trying to analyze time-to-event data (time to completion of a task). Looking at the KM curves, there is a distinct behavioral change around 12 months. This makes sense, because at 12 months there ...
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Partial least square cox regression interpretation

I am new to PLSR cox regression. I want to understand the output of these two models. Here is the R code that produced the output below: ...
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1answer
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Exponentially distributed X in cox regression

I am trying to build a multivariate cox model with several predictors in order to show that my biologic marker (X1 measured in patient blood) has an independent effect on mortality. With X2, X3 ... Xn ...