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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Modelling Length of Hospital Stay, Poisson Regression or Survival 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 ...
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10 views

Recurrent time-to-event?

I am working on a research paper looking at hospital readmissions after surgery and I have data for about 200 patients. I have the readmission dates for the first year after initial hospital discharge ...
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9 views

Constrained regression for binary dependent variable

I would like to discuss the methodology of the following case: I have a data for several patients over several years for 5 factors describing the health of a particular patient. Every factor consists ...
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10 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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13 views

Interpretation of coefficients in Cox model with time varying covariates and coefficients

I have a data set on survival times for individuals that may or may not develop a disease during the course of the study. Disease status is a time varying covariate, since individuals may become ...
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16 views

Variance-Covariance matrix of Weibull Distribution for right-censored data

The probability distribution function, cumulative distribution function and survival function of Weibull distribution are given by respectively, \begin{equation} f(t;\alpha, \beta)= ...
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Weibull Distribution v/s Beta Distribution

I've recently fallen in love with the Weibull Distribution and have gotten a reason to see if there's a mapping of this distribution to an interval (0,1). After plotting the Beta Distribution against ...
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16 views

Survival time tie-handling using aareg in R's survival package

I have noticed in the CRAN documentation for the survival package that survival time tie-handling is discussed extensively for Cox-PH regression (allowing for ...
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1answer
38 views

Optimal Cutpoint for Predicted Results from Kaplan Meier and Cox Regression

Is there anyway to get the optimal cutpoint for predicted survival probabilities of the aforementioned survival analysis approaches? Something like the optimal cutpoint from ...
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1answer
23 views

Can coxph be used for categorical data?

I'm doing some survival analysis and I got the idea to change a binary variable into three-category variable by sub-dividing one category of the binary variable into two new categories. Here's a ...
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14 views

What extend does in summary.survfit

I want to extract survival probability from summary.survfit at a specified time for different patients groups. However, for some groups, there is no subject left at the end of the specified time. I ...
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1answer
59 views

predict from a Cox model with beta coefficients

I fitted a Cox PH model in R with the survival package and the coxph function. I get the beta estimates from this model. How can I use these coefficients to ...
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1answer
33 views

Recurrent event analysis

I want to model patient visits. My assumptions are: Patients visit the hospital until they stop visiting at all. I don't know if their last visit was the last one. Patients visit at certain ...
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11 views

Equal Precisision confidence band not getting sufficient coverage [closed]

I'm looking at confidence bands for the survival function of right-censored data. In particular the Hall-Wellner band and the equal precision band (by Nair). Using the km.ci R package I did a ...
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12 views

C-index of a fitted cox model in validation data set

I know that c-index of a cox model can be obtained using survival::survConcordance. Below is an example, ...
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1answer
22 views

How to get Cox p-value for 20,000 genes?

If you run the following code, you will have a data frame real.dat which has 1063 samples for 20531 genes. There are 2 extra columns named ...
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12 views

How to structure data for repeated measures Cox model in R?

I am looking the relationship between a patient's lab values (measured at baseline and post-treatment) and their survival. The lab values are measuring the concentration of the same protein, they are ...
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1answer
24 views

Forecasting survival probability using Cox Regression

I'm able to obtain predicted survival probabilities of cox regression using either survfit.coxph or predictSurvProb from ...
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11 views

How to generate survival data using R [duplicate]

I want to simulate a sample of size 200, using right-censoring. T follows exponentioal(1) and c follows uniform(0.5,b). choose b so we have 20% of data are right-censored. Thank you
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14 views

The effect of prognostic factors on the power in survival analysis

I was curious to know if there exists closed form equations for calculating the power in survival analysis, using either Cox-regression or the log-rank test, when their is an important prognostic ...
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1answer
18 views

Version of Mann-Whitney U test, for right-censored data

Is there an equivalent of the Mann-Whitney U test, but for right-censored data? I have right-censored numerical data from two different groups. The mean for one group is higher than the other. I'd ...
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1answer
39 views

Multivariable survival analysis: adding another variable lowers the p value?

When I was performing the Cox survival analysis on my data, I tried to look at the predictive value of different variables to survival. For example, here I have two variables: 'size' and 'surface'. ...
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1answer
16 views

Unobserved heterogeneity in Cox model

I have some questions about the Cox model and unobserved heterogeneity. I work on a sample of firms divided in two categories: cooperatives and corporations. I want to test the influence of some ...
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1answer
39 views

What kind of model should I use for churn risk prediction?

I have a data set containing many client's id, and its behavior characteristics measured each month before churn or censored. Data looks like: id || lifetime period || folow-up time before churn of ...
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1answer
42 views

R: How can I use global average as baseline?

Using Cox regression I'm trying to find the difference in churnrate for different demographic properties for a dataset with millions of records. The data is similar to below: user zip time ...
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1answer
121 views

How to make calibration plot for survival data without binning data?

To make a calibration plot for survival probabilities estimated from a Cox model, one can divide the estimated risk into groups, calculate the average risk within a group, and then compare this to the ...
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1answer
16 views

Validity of PH test using Schoenfeld residuals from Cox model on parametric models

I need to use parametric models to model survival data. If the PH assumption holds, I would fit the data for my two intervention groups using a single covariate for treatment effect. I fit a Cox PH ...
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31 views

Error in R code. (buckley james estimator)

I am performing survival analysis (Buckley James estimator), using restricted cubic splines, but in R I get a blank error message and multiple warnings such as this ...
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1answer
32 views

Weibull Survival Model with Time Varying Covariates in R

I am trying to run a survival model using the Weibull approach, but the wrinkle is that I have time varying covariates. I am using the survival package in R. My call is: output <- ...
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20 views

How to predict the survival probability for test data?

Below is a snapshot of a dataset for which i am trying to find the survival probability at an id level. I identified the survival probability curve and the hazard function. Hazard function follows ...
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15 views

concordance index for binary score

Is there a kind of a concordance index for suvival data that works for binary scores? The ones I saw are for continuous scores. When there are two uncensored individuals A,B with a long ...
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1answer
38 views

time varying coefficients in cox proportional hazard model

I am trying to fit a coxph model in R. The study can be described as follows: I have a very large dataset, in counting process form, containing whether or not someone responded to a survey or not. ...
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1answer
45 views

Survival analysis Coxph coefficient is very high

I am using R survival package for survival analysis against gene expression. fit<-coxph(Surv(time,censor) ~ expression) However, I got some very high ...
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1answer
39 views

Software for survival regression with interval censoring and frailty

I'm conducting regression analysis on sleeping time data. The data is survey data and the answer possibilities are of type "less than 4 h", "5 h", "6 h", etc. so they can be thought to be interval ...
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23 views

About mean residual life $r(t)=t+10$, can we find hazard function and survival function?

Given mean residual life $r(t)=t+10$ We know that $E(T)=r(0)=0+10=10$. Can we find the hazard function $h(t)$ and survival function $S(t)$? I don't know how to do this stuff.
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Propensity Score Matching w/ 3 levels Rx

I'm trying to match consecutive patients by fitting a Propensity Score. The treatment has 3 levels (Controls, Treat_1, Treat_2). The "MatcheIt" package, is designed to work only with 2 levels ...
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1answer
21 views

Survival in time (Kaplan Meier) when start time is unknown: is it possible and what methods exist?

Is it possible to do survival analysis if one does not know the time the studied subject has already been ‘at risk’? This is question is more theoretical than practical, as in practice you would ...
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4answers
611 views

Machine learning methods which takes time-to-event into account?

My vague understanding is that machine learning methods are based on classification labels. How about a survival type of problem? That is to say, not only "have event" or "have no event", but also ...
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19 views

Survival estimation goes crazy when I move all censored times to t=0

I have a simulated dataset with 1000 observations and Weibull-distributed survival time as outcome. A certain percentage $p_1$ of these guys belong to a risk group ($Z_i=1$ for risk group, $Z_i=0$ for ...
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2answers
54 views

What is the reference point for a Cox proprtional hazard spline model?

When trying to fit a Cox model to a continuous term we have a problem interpreting the result. When fitting a linear model the hazard ratio is referenced to the mean of the predictor values, and at ...
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15 views

How do you calculate the compared populations in cox hazard ratio problems?

Take a look at the following open-access paper http://www.ncbi.nlm.nih.gov/pubmed/26506242 I've tried doing cox regression in both R and SPSS but I cannot get ...
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37 views

classification for concordance index

In this paper (and in most of the others I found), the authors want to find a continuous predictor that maximizes the concordance index. I would like to have a binary classifier instead that ...
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35 views

Cox regression with penalized package in R

Although I have visited this site several times, this is the first time I make a question, so be kind if it is not in a appropriate form. My problem is part statistical and part R. I am trying to ...
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Survival (Kaplan Meier) of signal transmission that can both fail and recover

I'm investigating the failure to transmit of a number of signals in time. In my data I often see signals transmitting for quite a long time, but after some time they gradually start failing but still ...
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43 views

Failure to converge after including and interaction between time and a covariate (in survival analysis) in R

I have fit a Cox proportional hazards model to some survival data. I then checked assumption of proportionality of hazards by checking plots of scaled Schoenfeld residuals. based on this, it ...
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29 views

Is there any way that this function can be a Weibull distribution?

I am currently working on a fatigue life analysis using an old airworthiness stanadard, Defence Standard 00-970, which was issued by the UK Minister of Defence for British designed military aircraft. ...
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1answer
19 views

Compare effect of resection extent on survival in two types of tumors

I have two groups of patients with similar, but different brain tumors (tumor type 1 and 2 for simplicity). All underwent surgery, the achieved extent of resection over a certain cutoff value should ...
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34 views

Determine if covariate is confounding in Cox proportional hazards model

I've developed a risk score that predicts patient survival. Now I want to see whether my risk score is independent of cancer stage. I've already determined that there's no interaction between the two, ...
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25 views

Missing survival probability estimates and times using R using an Anderson-Gill model for recurrent events

I am having problems with the "survfit" method to calculate survival probabilities following fitting an Anderson-Gill (AG) model for recurrent events using the "cph" method in the "rms" package. The ...
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12 views

Weibull survival scale notation and gamma function

I plotted a Weibull survival curve with scale parameter (0.171) and shape parameter (0.91) for which I now want to calculate the mean and SEM (from the variance). My question is the scale parameter ...