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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Would Innovations from Survival Analysis not have happened without Actuaries? [on hold]

Were insurance actuaries responsible for the entire development of survival analysis? This reminds me how innovations in statistical methods are kept secret by HFTers
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17 views

using non-cancerous patients to predict survival time from cancer?

I have data that consists of lab test results for patients, cancer dates for those who got cancer, and time till death/censor from that cancer. This cancer is both rare (most of the patients never get ...
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How to statistically make inferences about how close are repeated events to each other?

I have data about patient hospital readmission within one year after surgery. About two thirds of patients were readmitted, and the number of readmissions for those readmitted vary from 1 to 8 times. ...
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16 views

survival analysis: time to event

I am trying to fit a model for a loan portfolio which have been acquired over several years, each of the loan has one of the several term periods (different performance window) over which the loan ...
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9 views

Distribution for modelling return times with inflated zeros

I have data on people's return times which I wanted to fit a distribution to using maximum likelihood estimation. I was planning on using a Weibull or Gamma but there are a high number of return ...
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24 views

Smooth hazard function at given knots in R

Is there a way to obtain a smooth estimate of the hazard function at specific x coordinates in R? My problem is related to functional data analysis where I have a number of hazard function estimates (...
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1answer
18 views

fit GLM for weibull family

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 ...
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5 views

Interpreting Accelerated Failure Time Coefficients

I feel like this may be a stupid question, so please excuse it if it is--I'm still learning. I have an analysis I'm running using parametric survival analysis, specifically an accelerated failure ...
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20 views

Fitting Weibull PH model to Weibull mixture cure model

I generated a mixture cure model with Weibull distributed survival times (Weibull mixture cure model) . This is my baseline survival function conditional on the Bernoulli distributed covariate $X_i$ : ...
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24 views

Classification(Machine Learning) or Survival Analysis

I am working on building prediction model for disk failures (time taken to occur a disk failure and what parameters could strongly affect disk failures). I am bit confused on- What data ...
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1answer
12 views

Recurrent event survival model set-up

I'm trying to model customer reorders using a survival model using R's survival package and am having a hard time figuring out if I'm setting up the data correctly ...
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1answer
23 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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3answers
39 views

Benefit of smoothing survival function

Can someone explain the benefits of smoothing the survival function (or equivalently the empirical c.d.f.)? Smoothing leaves out some peaks that might be important. Would one still want to smooth the ...
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Interpreting random survival forest mortality

I'm trying to follow random survival forests. The ensemble mortality for $x_i$ is estimated by $ M_{e,i}=\sum_{j=1}^nH_e(T_j|x_i)$. Which means - sum over all death/...
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7 views

How do I assess goodness of fit when I don't have a model, only results of it?

I'm trying to assess goodness of fit for survival. I am using output of a parametric model for survival. I have the the survival at each year from time 0 to time 70 months. This model was created ...
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1answer
29 views

right or interval censored survival curve for survival within a survey period

I was hoping somebody could help with a relatively easy survival analysis question. I have survey data of an animal populaton and I want to create a survival curve for a specific year. So, I have ...
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2answers
46 views

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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1answer
32 views

Estimating a rate of failure/survival using only right censored data?

I am trying to estimate the probability $q$ that a household with certain known covariates will move to a new home in the following year, by estimating an event rate $\lambda$ dependending on some ...
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1answer
28 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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1answer
26 views

Algorithm for ordered curves clustering

I am looking for some statistical solution to the problem of testing the similarity of curves. I am working with multiply time series (sort of survival curves). The curves are calculated as a separate ...
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14 views

alternatives to survival analysis or other methods of tackling

Assume "I would like to take a trip with my bicycle but a component in it has a probability distribution of failing depending on the number of kilometers. Given that I want to come back also, what is ...
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75 views

What distribution could simulate “realistic” human survival times?

I want to simulate more or less realistic survival times for humans. I want to use a basic distribution$^*$ to do so. What distribution and what parameters would, to some extent, resemble the survival ...
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1answer
93 views

Survival analysis for patients that have been subjected to multiple treatments

I have data for patients that were subjected to either one treatment or multiple treatments at various points in time and I need to analyse their survival times after treatments. This of course means ...
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1answer
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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29 views

A time-series analysis problem

I am trying to run an analysis where I am looking at the time it takes for a building lot to go from having submitted its first construction job application to having earned its first construction ...
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1answer
20 views

Accounting for interval censoring JAGS model of binary mortality data

I have data on tree mortality, based on two observations of a tree in time. All trees are alive at the beginning of the interval. The length of the re-measurement interval, ...
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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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1answer
40 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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1answer
51 views

How to calculate the probability of death between two discrete time periods using survival curves

I was hoping somebody could help, I am trying to work out the probability of death between two time points on a survival curve. i.e. I have my survival curve as follows (this is an example Kaplan-...
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1answer
34 views

Interpret hazard ratio that has huge value

I run a coxph model in R using survival package. Here's the output ...
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1answer
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

Determining reference groups in coxph

When I run a univariate cox regression test using the survival package in R, assuming that my categorical variable-factor has ...
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23 views

What is the meaning of p-value in survreg output?

I am trying to understand the output from the survreg{survival} function when fitting a parametric model to two groups of data. I consulted the help documentation, but didn't find it very helpful. I ...
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25 views

In R, why is the survdiff function returning the p value = 0?

I want to obtain the pvalue of the three curves that are plotted. Here is the code that does a survdiff: ...
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1answer
29 views

Need help understand likelihood in survival analysis

I really appreciate it if you could help me understand the likelihood in a survival model with a time varying covariate. To be more clear, let's first start with a survival analysis with fixed ...
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31 views

Dealing with survival analysis data - reliability

I am totally new on Survival Analysis and my data is tricking me. I have, in excel, a list of failure's records informing date and hour of ocurrence, what failed/broke on that equipment and the cause ...
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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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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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1answer
56 views

What's the difference between univariate and multivariate cox regression?

I'm dealing with oncology patients so it would be nice to know whether to use univariate or multivariate cox regression. I have some books on survival analysis but they don't elaborate the academic ...
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23 views

If my null is rejected when using survdiff(), it means that there is a difference in survival curves for at least one pair of treatments

I am trying to run a survival analysis on my germination data and have been using (McNair et al. 2012, How to analyse seed germination data using statistical time-to-event analysis: non-parametric ...
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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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31 views

What imputation methods can be used for missing not at random covariate values in a survival analysis?

I'm new to survival analysis and trying to understand how to use it properly. My dataset is a time series dataset where most dependent variable values are available, 2 dependent variable values are ...
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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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10 views

Method for analyzing interactions of periodical exposures (drug x drug interaction and likelihood of adverse events)

I am interested in studying drug usage interactions (drug x drug) and its relation to adverse events. I would appreciate help with choosing the right model/method for this type of analysis. The data ...
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22 views

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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8 views

What do the parameters of “frailty” function of R package “survival” mean

What do the methods "aic" and "df" mean in R package survival's function "frailty"? I can guess that aic somehow uses Akaike's information criterion (thus the name, duh), but how does it differ from ...
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1answer
31 views

Cox model for recurrent events (with estimation of residuals / of an individual effect)

Consider some individuals that are followed during a period $T = 1$ (the same for all individuals). The individual indexed by $i$ have $n_i \ge 0$ events, at times $t_{i1}, t_{i2}, \dots, t_{in_i}$. ...