Survival analysis is concerned with modelling the time before subjects change state, typically time until death or failure. One key feature of such data is that they can be censored, that is, some subjects will not have changed state before the study ends.

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Implementing random forest to predict the success rate and time of completion

I have a large dataset with more than 120 columns for which I'm trying to classify whether the order will be successful or not. There are two parameters that I need figure out. One is the probability ...
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37 views

Why is the derivative not zero?

I am working with survival models and I am using R's coxph function to learn the Cox proportional hazard model. To try it out, I am using the standard veteran dataset (obtainable by loading the ...
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5 views

Power analysis for spatially structured variables in survival analysis

I am working with colleagues on an analysis of survival in a chronic neurological disease. There are several well known factors that influence survival. We have data from a good register which ...
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28 views

Are this two definitions of survival equivalent

Let $\lambda_i(t)$ denote hazard of the $i$-th individual at time $t$ and let $\lambda(t)=\frac{\sum_{i=1}^n S_i(t) \lambda_i(t)}{\sum_{i=1}^n S_i(t)}$ be the weighted average of individual hazards. ...
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Non-independent variables (covariates) in survival analysis

I want to perform survival analysis, and compare at which of 3 spatial scales habitat variables affect the most nest survival. I thought to perform analysis separately for each spatial scale and ...
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23 views

Censoring “Death” in Time-To-Recovery Analysis

I am performing time-to-recovery analysis comparing 2 groups. In both groups, a few subjects died from the disease under consideration (instead of recovering). Is it appropriate to consider the deaths ...
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6 views

KM plots with PFS > OS

I'm plotting KM curves for OS and PFS for the same population. There is not much difference between the groups, ie. most of the "events" for PFS are actually death, not progression but there are a few ...
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8 views

Cox model with known measurement error

I am trying to perform a univariate Cox PH survival analysis in R. My covariate was generated from another analysis, meaning that I have a 95% CI range (between 0 and 1) for the values. Right now, I ...
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13 views

developing a prediction model for HIV outcome in cox regression using cross validation/GCV

During the application of cross-validation in sufficient large dataset (say 6000), is there a recommended ratio to split the data in to learning/training and testing/validation data set? I have seen ...
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21 views

Type one right censored data [duplicate]

Does anyone have any idea about how to simulate censored data in R? For example, generate a sample of 200 with 30% of that Type 1 right censored, based on Weibull distribution. (30% of 200 = 60).
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Survival analysis with cures when it is known that for some subjects the event (death) will never occur

Say we have the following set up. At time t=0 there are N infected patients. There is a treatment which, if taken until t=T, cures 100%. However, some patients will be cured before t=T while others ...
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1answer
18 views

Calibration and validation of an accelerated failure time model on new data

I have an existing AFT (accelerated failure time) model which I'm using on a new dataset, with the obvious intent of testing whether the model predicts the new data well. A first step is to look at ...
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22 views

AUC of Survival ROC smaller than 0.5

If we obtain an AUC < 0.5 analysing a binary response variable (0/1) with a marker, this means the negative values of marker is associated to the value 1 of the response. We could use the trick to ...
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2answers
22 views

Competing hazards for event that makes the event of interest more likely

Suppose I'm Netflix. I'm using survival analysis methods (kaplan-meier curves) to study when my customers decide to cancel their subscription. However, I've noticed that customers that experience ...
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21 views

What is the R code for a 2 one-sided equivalence log-rank test? [closed]

I am trying to perform an equivalence test (alpha = 0.1, beta = 0.8, equivalence interval = 0.85-1.25) for two samples of survival data. Is there a code in R in the Survival package or any other ...
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1answer
20 views

how to deal with unavailable survival data

I'm writing a retrospective study presenting an overall survival analysis comparing two groups of patients. I implement a Cox regression model with some covariates and then present the results in ...
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29 views

simulate censored data (right censored) using R statistics [duplicate]

I want to generate right censored data, but I want to be able to pass in a parameter to a function to dictate that a certain percentage of the data will be censored. I have found this R-package: ...
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1answer
32 views

Hazard estimate of 'muhaz' function?

library(muhaz) nsam = 5000 time <- rexp(nsam,4) cause0 = rbinom(nsam,1,.75) haz = muhaz(time,cause0) plot(haz) I simulated failure time data which is ...
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18 views

How do I solve for Weibull parameters given a failure function's pmf and cdf values?

I am trying to find the parameters for a Weibull distribution to model data I have on retention for my company's subscription packages. The data I have is the failure and survival rates from month to ...
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14 views

Within-sibling-pair survival model

I'm modeling a time-to-event outcome (death) in a setting where the key independent variable (education) is measured for each member of a sibling pair. If I were simply interested in determining ...
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27 views

Survival probability for a case-control study

I have a case-control study in which 21 patients with a certain clinical outcome and 20 patients without that clinical outcome were (retrospectively) selected from a larger group of patients who were ...
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15 views

Very puzzling - naming the endpoint of survival analysis

A question that should be straightforward for statisticians but is puzzling me to the point I am nervous. I am doing a PhD in Epidemiology and am going to use Cox regression. The predictor is a ...
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33 views

Model for survival analysis with time varying predictors (panel data) and delayed effects

I collected behavioral data of more than 150 people, monthly, over two years. So for each of them I have 24 repeated measures over time. It occurs that after some months some of them get infected by ...
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19 views

data requirements for survival analysis

I recently study customer churn on trade data of customers with survival analysis,but I have some questions. Q1:Is there any assumption on the data? I mean if the data should be regularly(just like ...
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1answer
25 views

Survival analysis / cox-regression of periodically recurring events

I am trying to analyse the influence of temperature on flowering dates of certain plants using survival analysis. I have data from several measuring stations that measure daily mean temperature and ...
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16 views

Survival analysis with a parametric model for recurrent events and time-dependent covariates

The question is whether I should have posted my question from math stackexchange here: ...
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1answer
62 views

Parametric vs non-parametric time series modeling

Hi I have a large data set of objects, each containing a set of the same attributes. The attributes are measured quantities like height, width, etc. The data is arranged in a time series so that the ...
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16 views

Best method to analyse longitudinal recurrent count data

I want to analyze count data, more specifically number of prescriptions over 10 years. My first idea was to use the GEE Poisson. However, after reading some papers about recurrent history analysis I ...
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1answer
27 views

Survival regression variance estimates

I would like help understanding why a survival regression with no censored data-points does not give the same variance estimates as a linear model (see code below). I think it must be something to do ...
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1answer
49 views

Calculating force of mortality from life table

The force of mortality at age $x+t$, given survival to $x+t$ is given by $\mu_{x+t}$ $=-\frac{d}{dt}[ln({}_{t}p_{x})]$ Given a life table I know how to calculate ${}_{t}p_{x}$, but then how can I ...
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1answer
57 views

Get survival rates from a cox regression in R

I am fairly new to survival analysis and am playing around in R. I have a fairly simple cox model ...
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185 views

How to simulate censored data

I'm wondering how can I simulate a sample of n Weibull distribution lifetimes that include Type I right-censored observations. For instance lets have the n = 3, shape = 3, scale = 1 and the censoring ...
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2answers
85 views

Weibull Survival Model in R

If I run a Weibull survival model in R with the code survreg(Surv(t,delta)~expalatory variables, dist="w") how do I interpret the output of the model? That is, ...
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22 views

Parameter estimates from extended cox model using the coxph() function from the survival package in R

I want to understand how the parameters from a Cox Model using the coxph() function from the survival package in R are estimated. I am following a book by Rizopoulos [1]. In the book the partial log ...
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1answer
49 views

Calculating constant hazards in exponential survival distributions in R using survreg()

In an ecological seed removal experiment, we have seed removal data from 720 seed plates with 25 seeds each. For each plate, we know the number of "surviving" seeds at several times ti until the end ...
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1answer
30 views

Risk ratios in a Cox hazard model

I'm reading a paper which gives "Risk ratios from Cox hazard models with time-varying covariates". Time-varying covariates just means that, for example if $X_i$ is a covariate for person $i$ then it ...
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38 views

Time varying coefficient in cox model

I have a model for survival after an injury that is borderline passing the Schoenfeld test for the proportional hazards assumption (cox.zph() in R). However, ...
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1answer
30 views

Survival analysis

I have a data set in which I have the date of joining of employees, age, and the date of leaving , also i have the dataset with current employees,so should I combine these two datasets or should I ...
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41 views

Predictive model for Turnover - Correlation or Survival Analysis

Question 1 - I a working on developing a model to predict employee turnover. The variables that I have are age, tenure, job satisfaction, role clarity etc. Through research papers I have found the ...
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1answer
38 views

Cox Regression: Testing for effect in subgroup

I'm using a cox proportional hazard model in R to see if a treatment variable (treatment or placebo) has effect on the survivaltime of patients. I intend to test this for each of my grouping variables ...
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2answers
56 views

Cox Regression: Testing for effect in subgroup

I'm using a cox proportional hazard model in R to see if a treatment variable (treatment or placebo) has effect on the survivaltime of patients. I intend to test this for each of my grouping variables ...
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1answer
52 views

Finding the Maximum Likelihood Estimate in R [closed]

How do I estimate the parameters through MLE for a Likelihood function like. Note that the function has 2 multiply signs and there is a integration term in the second one.
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1answer
68 views

Multiple Imputations and Survival Analysis

I’m new to using multiple imputations and I would like an opinion on using it with survival analysis in R. I am using MICE on an entire dataset. For one of my independent variables I decided to ...
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20 views

In suvival analysis, How to derive risk score from hazard function (or survival function)?

I am learning the random survival forest model which output is cumulative hazard function. In the paper[1], they used the interval of cumulative hazard function as risk score. I simulated on Weibull ...
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1answer
42 views

Estimating median survival times from Kaplan-Meier plot inspection

I've gone through the various questions relating to Kaplan-Meier plots and survival estimates, but I haven't really been able to find anything to help with this specific scenario. Sometimes, when ...
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22 views

Predict Kaplan-Meier Curve from Hazard Ratios

For illustration purposes I want to plot some potential hazard ratios, based on a known proportional hazard model. For example, plot the known curve, then plot what the curve may look like with HR's ...
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14 views

How to fit cox ph model in R to pre aggregated data

What I mean is suppose instead of individual observations one has only grouped data like this: Month,Age,Height,NoOfObseravtions,DeathRate 1,20-25,5.5-6.0,100,1% 1,20-25,5.5-6.0,150,1.20% ...
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44 views

How to compute median time from survfit and penalized cox

I'm new to the survival package in R. I used the survfit function to calculate the median survival times for the new data after fitting Cox model with (coxph) to my training data. But when I check ...
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1answer
61 views

Cox-Proportional hazards model with panel (longitude ) data

I am working with panel data with incomplete case: and the goal is to predict the probability of 1 at each time for each case. I am trying to use the cox-ph model for this analysis because like ...
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Does fitting Cox-model with strata and strata-covariate interaction differ from fitting two Cox models?

In Regression Modeling Strategies by Harell there is a section (S. 19.1.7) discussing Cox models including an interaction between a covariate whose main effect on survival we want to estimate as well ...