[Cox proportional hazards regression][1] is a very popular, semi-parametric method for survival analysis.

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Calculating Ratio of Hazard ratios

I'm trying to calculate if there has been a change in risk over time, during 10 years of follow-up, for young adults to develop depression. I've successfully calculated the hazard ratio for the two ...
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Spearman's rho vs Cox regression

I'm searching the predictors associated survival among 12 children with a disease named hemophagoctic syndrome treated only specific treatment.Our statisician used spearman's rho test but the journal ...
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22 views

how come the KM survival estimates per variable group look so weird yet we can use the variable in a cox model?

I'm trying to follow the vignette ggRandomForests. They describe an attempt to explain cirrhosis survival by several variables. The KM survival estimates for the variable ...
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loan prepayment

I'm modeling loan prepayment using survival analysis (in R). Should I use calendar dates, where the loans appear and then some mature, etc., or should I use the time past the inception of a loan, ...
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23 views

Difference between Cox regression and logistic regression; question about correlation assessment

What is the difference between Cox regression and a logistic regression? I'm writing my own thesis and I have to choose between these two. Do I have to assess the covariance between the variables I ...
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23 views

Crowdsourcing price computation for new task

I have historical data for crowdsourcing micro tasks(Task : jobtype (classification of jobs(String)), location of job , price of the job, completion time(start date - final date)). These tasks are ...
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Interpreting a Cox regression model when one predictor is log-transformed

In my model I am considering the rate of hospital re-admission (outcome) and my covariates are non-log transformed while my main variable of interest - direct cost of home rehabilitation - is ln ...
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20 views

collinearity in conditional logistic regression: glm vs coxph

I am fitting some conditional logistic regression models to wildlife radio telemetry data using a 1:1 paired design, specifically where habitat features at a single telemetry point are compared to ...
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26 views

Relation of pooled logistic regression to time dependent Cox regression analysis

I found on this paper (D'Agostino, et al. 1990) that pooled logistic regression is close to the time dependent covariate Cox regression analysis. I would like to be able to reproduce estimates ...
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22 views

Compute I-squared in individual patient data meta-analysis

I am working on an individual patient data meta-analysis, using a Cox proportional hazard model, with and without taking into account study identification, in Stata. A reviewer asked me to provide ...
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12 views

Non-parametric estimation of competing risks model with unobserved heterogenity

I've been searching for a while if there's an R package that allows to do non-parametric estimation of a competing risks model with unobserved heterogenity/frailty. ...
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11 views

If the fitted hazard ratio from a Cox model is approximately 1, does that mean the covariate is not significant?

Does a hazard ratio nearly 1 indicate that the covariate's effect on survival time is 0? If so would the corresponding p-value routinely indicate statistical insignificance? In other words, can a ...
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38 views

Determine if a time-dependent Cox model is appropriate

Before the description, here are my questions (1) Is the set-up of my time-dependent data correct? (2) Are the ways I run my Cox proportional hazard model with a time-dependent variable/ non time-...
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21 views

Checking assumptions of Cox proportional hazards model in R

I'm using the survival package to build Cox-ph models. What are ways to check the model's assumptions using this package? I've found a couple of sites, such as ...
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20 views

Lee (1983) sample selection correction with accelerated failure time model (in Stata)

I am trying to replicate the selection control used by Henderson et al. (2006), which is derived from Lee (1983). Henderson et al study CEOs over time and try to control for the likelihood that a CEO ...
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1answer
40 views

Designing a prognostic model from a randomized controlled trial

I want to develop a prognostic model from outcome data of patients treated in a randomized controlled trial where patients received radiotherapy in one arm and radiotherapy and concurrent chemotherapy ...
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3 views

Extracting coefficients from frailty survival model with sparse=T [migrated]

I am fitting a survival model in R with time-dependent covariates and using frailty.gaussian() for some of the variables. An example call is ...
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16 views

What to do if my -log(-log(S(t|x))) kaplan-meier survival function violates PH assumption?

I've already performed survdiff() on my survival curves to find that there is a difference in time-to-germination between my 3 treatments. As far as I'm aware, I will need to run coxph() to be able to ...
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29 views

Interpreting coxph output with cumulative time dependent covariate

Hoping for some help in interpreting the coxph output in R using the survival package. I am very new to R, but have successfully ...
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18 views

Analyzing event occurrences in panel data

I have a dataset with over around 50 firms over 10 years, 8 time varying firm level characteristics as predictor and as response, technologies that they adopted each year. For the response variable, ...
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Hazard model for three-tiered-response dependent variable

My time-series dataset is composed of measurements for a number of independent variables and one dependent variable. The dependent variable accepts 3 responses: weak reaction, strong reaction, or no ...
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Deviance residuals in Cox Model

Based on this article: Click here, the martingale residuals is a sum of each martingale residual per subject from counting process data. So, if deviance residuals in Cox regression are defined by: $$...
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6 views

Writte the proportional hazard model with some variable as explanatory

Write a proportional hazards model with the age as a explanatory variable. How can this be done? I know the proportional hazards model or also called cox model is writen like: $h(t|X)=h_0 (t)e^{\...
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Can I use Covariate Balancing Propensity Score method to adjust for confounding in a Cox Regression model with splines?

I would like to use the Covariate Balancing Propensity Score (CBPS) method to adjust for confounding because of its optimization properties. I am doing a Cox regression model on some observed ...
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33 views

Deciding Optimal Cutoff for a Prognostic Index derived from Cox Proportional Hazards

I am planning to develop a prognostic model that would identify a particular group of head neck cancer patients who will do better if chemotherapy is added to standard radiation therapy. The data for ...
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74 views

R Survival Analysis - Cox Regression and Cumulative Time Dependent Covariate

Hoping for some help related to a survival analysis using R and the survival package. I've been relying heavily on a series of blog posts done by Dayne Batten, ...
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25 views

Applicability of survival analysis (using Cox proportional hazards) to question of interest

I have started down the path of using cox PH models to try to understand which variables are driving time-to-migration (event) in my study system. My system has two groups (A,B) of animals that ...
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Effect size interpretation from Cox logit d'

Is it reasonable to use Cohen's d guidelines in the interpretation of a Cox logit d'?
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When using counting process in Cox PH survival analysis in R (survival::coxph), must I use cluster term in the model formula?

I am running Cox Proportional Hazard Model in R, package survival, function coxph(). As I have time-varying covariates, my data is defined as counting process, that is there is one separate data ...
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20 views

Computing time dependent variables in Cox regression

For a paper I’m running analyses on factors influencing the rate of adoption of a reporting practice, i.e., the dependent variable is the rate of adopting a specific sustainability reporting standard. ...
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15 views

Can you use Cox proportional hazard model for panel data?

I need to regress health variables on pollution (PM10), and I have seen that for variables such as lung cancer that take a long time to develop, papers generally use the Cox proportional hazard model. ...
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30 views

Survival model output not consistent with actual data

I am trying to learn Survival modelling using a dummy data. The code is as follows ...
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6 views

Comparing between group HR for different age strata

I was asked by a colleague if i knew how to test if between group (cases and controls) HR were higher in one age strata than in another. The design: Matched cohorts of cases (with info on debut age) ...
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15 views

Applying Cox Proportional Hazards Model on Discontinuous Variable

I am using coxph in Rstudio to apply Cox Proportional hazards model on my data. This model is easy to use on continuous variable ...
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Difficulties fitting a Cox PH model with categorical interactions to complex survey data

I'm attempting to fit a Cox proportional hazards model to a set of NHANES data; the code to load and clean the data is here, and the resulting dataset is here. The difficulty I'm having is ...
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the graph of log(-log) for Cox model on survival analysis

I'm studying Cox Regression model on Survival Analysis. While testing validity of Proportional Hazard model, I will use log(-log) graph method in SPSS. First of all, I mention which procedure I'm ...
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Simulating interaction term in Cox model

I am trying to simulate the survival data (by using Weibull distribution) that can fit the Cox model below: h(t) = ho(t). exp(beta1 * X1 + beta2 * X1 * X2) X1 and X2 are binary. I haved tried using ...
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How to derive a simultaneous confidence band for an estimated function?

I'm approximating the functional form of the Cox model by B-splines basis functions. For simplicity, assume there's only one covariate $x$, so my model takes the form \begin{eqnarray*} \lambda(t|x)&...
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Regularized cox survival model with time varying covariates and sparce matrix in R

I was wondering if there is a survival framework in R (or any other language for that matter) for doing the following: Fitting an extended (i.e., time-varying covariates) cox survival model ...
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56 views

Textbook approach to modeling non-proportional hazards in the Cox model

In Cox models with time varying coefficients, the effect of covariates on the hazard is allowed to change through time. In cases where a coefficient has a linear relationship with time, I am aware of ...
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Cox-Snell residuals for Cox model with time varying coefficient

I am using the time transform feature of the coxph function in the survival package to model the effect of a time varying ...
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1answer
29 views

Schoenfeld residual test for model with time varying coefficients?

I'm working with the survival package in R. I fit a Cox proportional hazard model (coxph) and did a scaled Schoenfeld residual test (...
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Can mediation analysis be done with Cox proportional hazards models?

I am trying to understand what types of open source software projects succeed and stay active for a long time and what types die. I want to use survival analysis because some of the projects in my ...
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1answer
36 views

Kaplan-Meier vs Cox proportional hazards survival estimates

I am conducting a 20 year longitudinal study on firm survival using a number of variable such as size, profitability, cash resource etc. What is the difference between the Kaplan Meier and Cox ...
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55 views

Modelling Length of Hospital Stay, Poisson Regression or Cox Regression Analysis

I would like to find out what people thought about the better or more widely accepted way to model hospital Length of Stay (LOS) is? LOS can be thought of as count data (number of days) with a right-...
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1answer
37 views

Possible time-dependent mediation effect in Cox regression

I'm quite new to survival analysis, but would appreciate any advice on how to deal with the following finding in my data analysis/ results interpretation. I have been using R and have used a time-...
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29 views

How to plot adjusted Kaplan-Meier Curves?

I am trying to plot adjusted Kaplan-Meier curves. I know publications like to see something graphical. But using R, I don't know how to go about adjusting for something like age, gender, income when ...
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How to use time dependent covariates with cox regression in R

I don't know how to generate time dependent covariates in R for use cox regression. I know you need to reorganize your dataset into intervals between event times. This I believe I can do with the ...
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14 views

Observed information matrix in Cox model with constant baseline hazard

I am trying to explore properties of Cox model with (parametric) constant baseline hazard function. So the hazard function for the model is $\lambda(t|Z_i) = \lambda_0(t) \exp(\beta^\mathsf{T}Z_i)$,...
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Why doesn't a Cox model with time-dependent co-variates lead to pseudoreplication?

In survival analysis, if we have a time-dependent covariate, it is recommended to split data for each individual into multiple time-periods, with start and end dates for each, such that each time ...