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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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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12 views

Svm for survival analysis in r [on hold]

Is there any implemented package for survival analysis with SVM in R? I need to feed the model with both survival time and event. Thanks!
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27 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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76 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
63 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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16 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
38 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
19 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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28 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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29 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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27 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
35 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
39 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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45 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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47 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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40 views

Cox Regression Model

I have been simulating survival times, status and explanatory variables to apply in a Cox model, for a cohort of 10000 people. In this case, all the covariates were continuous and generated using a ...
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16 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
21 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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18 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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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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24 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
43 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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41 views

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 ...
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35 views

Temporal features in survival analysis

I'm modeling customer churn, experimenting with both Aalen Additive and Cox Proportional Hazards models, using the lifelines package in Python. If this were a more ...
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58 views

Survival Analysis Applied when Individuals that “Died” can still Return

I'm running an AB Test and using Survival Analysis to estimate the Return Rate to the website. Each day (in a total of 7 days) I randomly assign 100 users to group A and 100 users to group B and ...
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Why big difference between categorical and continous variable inregression analysis?

I am currently doing a survival analysis where I want to adjust for several confounders. One of my variables, which I will name MyScore is a score from 1-5. When I enter MyScore as a continuous ...
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A question about the effective sample size in life tables

I am currently studying basic methods of survival analysis and I came across this strange estimator of the effective sample size at a given interval. For the jth interval say, the estimator ...
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23 views

Relationship between OOB Error in Random Survival Forests and c-index

The error rate reported by Random Survival Forests is ( 1 - C-index ) using the OOB survival predictions, and I am trying to understand exactly what is the relationship between the C-index and the OOB ...
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367 views

What is my lambda here

The life of automobile voltage regulators has an exponential distribution with a mean life of six years. You purchase a six-year-old automobile, with a working voltage regulator and plan to own it for ...
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40 views

fitting parametric survival curves on Kaplan Meier probabilities in aggregate data

Lets suppose I have aggregate survival probabilities (NOT individual level data) from Kaplan Meier curves. I would like to curve fit different "types" of distribution like exponential, weibull, ...
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26 views

Predicting time to failure with time varying cofators

The Goal I am modeling Hospital Length of Stay. More specifically, I would like to predict the number of days until a patient is discharged given all of the patients clinical factors throughout ...
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1answer
16 views

Cutoffs to consider for survival tree

In an tree based algorithm a criterion is measured at certain cutoffs for the variable. This cutoffs are the candidate split points for that variable. How does one come up with candidate split points ...
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1answer
27 views

Left-censoring , $Y_i=\text{max}(T_i,U_i)$

In the book , Statistical Models and Methods for Lifetime Data , in Left-censoring , it is written that Can only observe $Y_i=\text{max}(T_i,U_i)$ . Where , ...
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2answers
53 views

What is the right way of computing baseline hazard rate

What is the right way of computing baseline hazard rate? To my understanding hazard rate at time t is simply #events / #AtRisk ...
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49 views

Hazard function of a gamma distribution

The system we are working on is biological, more specifically the distribution of specific events across a chromosome. This can be thought of as 1D array (the chromosome) across which points can be ...
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1answer
58 views

Intuitive meaning of the limit of the hazard rate of a gamma distribution

For a Gamma distribution with shape parameter $\alpha >1$ and scale parameter $\beta > 1$, one can show that its hazard rate function $h$ is increasing and satisfies \begin{equation} ...
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49 views

Survival Analysis Help

This is the problem i am trying to solve for a client , and would appreciate some help : 1) I am trying to predict the "time to default" (along with the associated probability for a particular loan ...
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47 views

propensity score matching and survival analysis

I am using the Matching R package to compute Average Treatment Effect within Propensity Score Matching (PSM). I have two groups: treatment and control. In ...
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26 views

Kaplan Meier estimate for data with unequal numbers in treatments

Is it possible to estimate Kaplan-Meier medians, CIs and difference with unequal sample size in treatments or do I have to do coxph? For example, in my dataset, ...
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16 views

Interpretation of non-significant parameters in significant Cox-model as prognostic factors

I want to analyze predictive factors for patient survival after surgery. I have variables that are based on investigations at the time of the surgery, known predictive factors (age, KPS) and data on ...
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40 views

Measuring effectiveness of marketing through attribution analysis [closed]

My data(dataframe in R) looks like this:The data is ordered by CustomerName and then TimeofEvent. ...
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1answer
45 views

Data collection process in survival analysis

I must apologize if this seems a very basic question. I am fairly new to survival analysis. Could some please enlighten me on how survival data is collected? I am very much aware of some of the ...
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1answer
28 views

P-value from proportional hazards regression object [closed]

I'm running some proportional hazards regression models using the survival package in r and would like to know how I can access ...
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39 views

Tail problem with hazard function

Before doing a more advanced survival analysis, I generated an exponentially distributed variable in Stata and used the following code to get a constant hazard rate graph: "sts graph, hazard" I get ...
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26 views

variance-covariance matrix in R for Weibull survival curve

A simple doubt: Can I use values from vcov(ajust) directly? Or do I need some kind of transformation? I mean, for a Weibull model, does ...
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52 views

Plotting Survival Rates For Different Cohorts

I am using Stata 13 to analyze a panel with firm level data. I am estimating a dynamic probit model via the means of xtprobit. During my research I came across Peters (2009) and a very cool graph (see ...
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1answer
33 views

Dummy variables and intercept in Cox regression

I am working with the Cox Proportional Hazards model. Where the covariates include 2 categorical variables. Assume each category has 3 levels, so I model these in terms of dummy variables. Category ...
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1answer
96 views

Cox Regression p-value

I am using R's flexsurvreg function (in the flexsurv package) to fit a AFT model to my data. This is the line of code that fits the model to the data: ...
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1answer
75 views

Comparing failure rates between 2 products with different number of deployed equipment

I have the following scenario, which I am trying to better understand. There are 2 different brands or groups of devices performing the same functionality as such: - Product/Brand 1 has 4,323 devices ...
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18 views

linearized incidence patient-year

I am writhing a manuscript were I have to report according to guidelines the linearized incidence of postoperative complications expressed as % patient-year follow-up. How one can do it in R? Thanks