Questions tagged [survival]

Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.

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54
votes
8answers
22k views

How to tell the probability of failure if there were no failures?

I was wondering if there is a way to tell the probability of something failing (a product) if we have 100,000 products in the field for 1 year and with no failures? What is the probability that one of ...
34
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3answers
26k views

What distribution does my data follow?

Let us say that I have 1000 components and I have been collecting data on how many times these log a failure and each time they logged a failure, I am also keeping track of how long it took my team to ...
49
votes
5answers
47k views

Prediction in Cox regression

I am doing a multivariate Cox regression, I have my significant independent variables and beta values. The model fits to my data very well. Now, I would like to use my model and predict the survival ...
12
votes
1answer
9k views

ML estimate of exponential distribution (with censored data)

In Survival Analysis, you assume the survival time of a r.v. $X_i$ to be exponentially distributed. Considering now that I have $x_1,\dots,x_n$ "outcomes" of i.i.d r.v.'s $X_i$. Only some proportion ...
10
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2answers
24k views

How to do ROC-analysis in R with a Cox model

I've created a few Cox regression models and I would like to see how well these models perform and I thought that perhaps a ROC-curve or a c-statistic might be useful similar to this articles use: J. ...
19
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3answers
17k views

Time dependent coefficients in R - how to do it?

Update: Sorry for another update but I've found some possible solutions with fractional polynomials and the competing risk-package that I need some help with. The problem I can't find an easy way to ...
7
votes
1answer
16k views

Test Cox proportional hazard assumption (Bad Schoenfeld residuals)

Using R I generated a Cox model looking like this ...
42
votes
14answers
10k views

References for survival analysis

I am looking for a good book/tutorial to learn about survival analysis. I am also interested in references on doing survival analysis in R.
14
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3answers
17k views

How to create a toy survival (time to event) data with right censoring

I wish to create a toy survival (time to event) data which is right censored and follows some distribution with proportional hazards and constant baseline hazard. I created the data as follows, but I ...
10
votes
4answers
11k views

Discrete-Time Event History (Survival) Model in R

I'm trying to fit a discrete-time model in R, but I'm not sure how to do it. I've read that you can organize the dependent variable in different rows, one for each time-observation, and the use the <...
3
votes
2answers
800 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 ...
29
votes
3answers
23k views

Imputation before or after splitting into train and test?

I have a data set with N ~ 5000 and about 1/2 missing on at least one important variable. The main analytic method will be Cox proportional hazards. I plan to use multiple imputation. I will also be ...
23
votes
4answers
29k views

Intuition for cumulative hazard function (survival analysis)

I'm trying to get intuition for each of the main functions in actuarial science (specifically for the Cox Proportional Hazards Model). Here's what I have so far: $f(x)$: starting at the start time, ...
13
votes
2answers
7k 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 ...
20
votes
2answers
81k views

How do I interpret Exp(B) in Cox regression?

I'm a medical student trying to understand statistics(!) - so please be gentle! ;) I'm writing an essay containing a fair amount of statistical analysis including survival analysis (Kaplan-Meier, Log-...
14
votes
2answers
5k views

Layman's explanation of censoring in survival analysis

I have read about what censoring is and how it needs to be accounted for in survival analysis but I would like to hear a less mathematical definition of it and a more intuitive definition (pictures ...
17
votes
2answers
9k views

Survival Model for Predicting Churn - Time-varying predictors?

I am looking to build a predictive model for predicting churn and looking to use a discrete time survival model fitted to a person-period training dataset (one row for each customer and discrete ...
18
votes
1answer
2k views

Why are p-values often higher in a Cox proportional hazard model than in logistic regression?

I've been learning about the Cox proportional hazard model. I have a lot of experience fitting logistic regression models, and so to build intuition I've been comparing models fit using ...
12
votes
1answer
865 views

Modelling when the dependent variable has a "cut-off"

Apologies in advance if any of the terminology I use is incorrect. I'd welcome any correction. If what I describe as a "cut-off" goes by a different name, let me know and I can update the question. ...
6
votes
1answer
3k views

Relative importance of variables in Cox regression

I've understood that relative importance of predictors is a tricky question. Suggested methods range from very complex models to very simple variable transformations. I've understood that the ...
4
votes
2answers
15k views

How to conduct conditional Cox regression for matched case-control study?

I am attempting to find a program that will let me conduct Cox regression on my matched case-control dataset. Please assist. p.s. I have STATA, SPSS, and MedCalc
9
votes
2answers
4k views

Understanding Hazard Function Values Exceeding 1

I keep running into problems in understanding hazard rates. I know, for example, that in a strict sense a hazard rate is not a probability and it is continually mentioned that because of this the ...
9
votes
3answers
6k views

fit GLM for weibull family [closed]

I am trying to fit generalized linear model for weibull family, but when I try it in R, it gives an error. I know that weibull does not fit in exponential family, but I have read some research ...
8
votes
1answer
228 views

proportional hazards model with fixed interval censoring = cloglog GLM with fixed effect of time?

Consider a survival analysis with time-constant coefficients, interval-censored, where the observation intervals are consistent across all individuals (e.g. each individual is observed at the end of ...
6
votes
2answers
859 views

Cox Regression when survival doesn't go to 0?

Is it appropriate to use cox regression to study a process that doesn't result in the survival function going to 0 when time = infinity? Cox regression is interested in hazard ratios, and it makes no ...
3
votes
1answer
318 views

Derivation of survival copula

$$ \begin{align}F(x,y) &= P(X\leq x, Y\leq y) \\ &= C(F(x), F(y)) \end{align}$$ The copula of a bivariate distribution is equal to its CDF, $C(u,v) = F(x,y)$. The density of the data's CDF ...
2
votes
2answers
521 views

Survival Analysis, Cox Regression in randomized trial vs. observational study and propensity score matching

In randomized clinical trials in the efficacy part, often survival analysis is used to analyze the time-to-event data. Since it is randomized (if randomization was done properly) one can assume that ...
1
vote
1answer
60 views

Estimating survival curves from Cox regression results

I can understand that it is possible to estimate survival curves directly from the results of a Cox regression. The way it can be done, mathematically, is furthermore very nicely explained in this ...
0
votes
1answer
79 views

Is it possible and how to predict individual survival curve after Cox regression?

Taking the veteran dataset of a two-treatment, randomized trial for lung cancer in the R package survival as an example, where <...
30
votes
2answers
18k views

In survival analysis, why do we use semi-parametric models (Cox proportional hazards) instead of fully parametric models?

I've been studying the Cox Proportional Hazards model, and this question is glossed over in most texts. Cox proposed fitting the coefficients of the Hazard function using a partial likelihood ...
10
votes
2answers
10k views

Precisely how does R's coxph() handle repeated measures?

Context I'm attempting to understand how R's coxph() accepts and handles repeated entries for subjects (or patient/customer if you prefer). Some call this Long format, others call it 'repeated ...
21
votes
4answers
11k views

Survival analysis: continuous vs discrete time

I am confused about how to decide whether to treat time as continuous or discrete in survival analysis. Specifically, I want to use survival analysis to identify child- and household-level variables ...
17
votes
4answers
5k views

Intuition behind the hazard rate

I am confused about the equation that serves as the definition of the hazard rate. I get the idea of what the hazard rate is, but I just don't see how the equation expresses that intuition. If $x$ is ...
15
votes
1answer
3k views

How to generate predicted survivor curves from frailty models (using R coxph)?

I want to compute predicted survivor function for a Cox proportional hazards model with frailty terms [using survival package]. It appears that when frailty terms are in the model, the predicted ...
15
votes
2answers
28k views

How to estimate baseline hazard function in Cox Model with R

I need to estimate baseline hazard function $\lambda_0(t)$ in a time dependent Cox model $\lambda(t) = \lambda_0(t) \exp(Z(t)'\beta)$ While I took Survival course, I remember that the direct ...
7
votes
2answers
7k views

What is a "good fit" Brier score and Harrell's C Index

This is a question I originally posted on r-help but it is more suited here. I will post the question and the answer I received from Dr. Winsemius and would be most grateful for any additional answers ...
11
votes
3answers
9k views

Priors for log-normal models

I am trying to determine what the most appropriate non-informative priors are for the two parameters of a log-normal distribution (for an accelerated failure time model). I had been working with a ...
10
votes
3answers
10k 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, ...
8
votes
1answer
3k views

Variable selection with LASSO

I am trying to fit a predictive gene-based model in survival analysis. My question is: Can I use LASSO as a variable selection method, and then run a multivariate Cox regression to get the ...
7
votes
1answer
3k views

Expected survival time for Weibull proportional hazards model with R's predict.survreg

The predictions for a Weibull proportional hazards model from R's predict.survreg() are not the expected survival times. Please help me understand this behaviour. ...
8
votes
2answers
24k views

How to interpret the output for calculating concordance index (c-index)?

I have posted a "similar" question in another thread. But I think that question is not specific/concrete enough to get the answer I expected. I know that, in survival analysis, the concordance index (...
5
votes
1answer
3k views

Time to event with no censoring - use survival or normal regression?

I have some time to event data, but the population is only those who had the event (specifically, my cohort is all kidney tx recipients who were readmitted within one year of discharge for a specific ...
2
votes
2answers
10k views

Risk table for a Kaplan Meier plot in R

I need to make a Kaplan Meier plot with an at-risk or risk-set table beneath it. Otherwise stated, I need a table of the number of subjects at risk at different time points aligned below the figure. ...
9
votes
2answers
5k views

Interval censored Cox proportional hazards model in R

Given interval censored survival times, how do I perform an interval censored Cox PH model in R? An rseek search turns up the package ...
5
votes
1answer
1k views

Interpretation of Weibull Accelerated Failure Time Model Output

In this case study I have to assume a baseline Weibull distribution, and I'm fitting an Accelerated Failure Time model, which will be interpreted by me later on regarding both hazard ratio and ...
2
votes
2answers
503 views

Violated non-proportional hazards - Cox regression model of time-dependent covariable

I have been reading a lot on Cross Validated for a while now, but this is my first post here. Thanks for all the help I've received! I am currently working on a project where we are trying to estimate ...
8
votes
3answers
4k 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: ...
3
votes
1answer
2k views

What is a hazard rate?

What is the definition of a hazard rate? What is a hazard function? I thought it was the probability that a unit does not survive the time period conditional on being alive, but I see hazard rates ...
1
vote
1answer
138 views

Dealing with left-, right- and interval-censoring and left- and right-truncation

I have a survival data set with left-, right- and interval-censoring and left- and right-truncation. Now I want to fit a Cox proportional hazard and an AFT model to these data. What is the best way to ...
16
votes
3answers
9k views

How can machine learning models (GBM, NN etc.) be used for survival analysis?

I know that traditional statistical models like Cox Proportional Hazards regression & some Kaplan-Meier models can be used to predict days till next occurrence of an event say failure etc. i.e ...

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