# Tagged Questions

[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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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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### 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: ...