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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Cross-validating a survival model with right censoring?

Is it sensible and possible to cross-validate a survival model? Does it depend on whether there is censoring? If not, why? If the answer depends on the model, then answer for common survival models ...
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Is calculating r2 appropriate for cox mixed effect models?

I'm looking at the effects of inbreeding on survival in a captive animal species. I'm trying to clearly distinguish the effects of inbreeding from other possible random genetic factors on survival. ...
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Getting the 1 and 3 years overall and progression-free survival (OS&PFS) and their p values in SPSS

I have a cohort of 300 subject divided into two groups (e.g. chemo y/n). The Median follow-up is 18 months (range 1-87). There were 45 deaths so median survival was not reached. I have compared ...
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10 views

Fitting Cox Regression / Proportional Hazard Model with x time interaction term in R

I am asking this in the context of wanting to diagnose for violation of proportional hazard assumption and its correction. (Schemper 1992) On p.179 of Hosmer, Lemeshow and May, it says that we can ...
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24 views

Specifying the LHS for a proportional-hazards survival regression

This is a basic question to understand how datasets for survival analysis are constructed. I understand the terms in the model, given by this equation: (P.41, G. Brostrom, "Event History Analysis ...
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9 views

Time dependent covariate SPSS

I am attempting a time dependent covariate analysis using SPSS but end up running into some difficulties. This is the first time I am trying it using SPSS so would appreciate some advise or direction. ...
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34 views
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Ignore strata in external validation of stratified Cox prop hazards model?

I've fit a stratified Cox proportional hazards model to some survival data, where I've stratified by a potential confounder which is the batch the data comes from (there are three batches). Now, I'd ...
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1answer
46 views

Survival analysis where P(event) < 1

Suppose you are interested in analyzing time to event data for a sample of patients. You are interested in the time elapsed until a patient contracts an illness. However, a majority of patients will ...
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1answer
27 views

Calculating probabilities using cox regression [duplicate]

I have done a multivariate Cox regression in R. The model fits to my data very well. Now, I would like to use my model and predict the survival probabilities of new observations. I am unclear how to ...
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32 views

Plotting the effect of a variable estimated by a regression model fit

Plotting the effect of a variable estimated by a regression model fit is quite interesting. However, I have some questions regarding this subject. Here is some example code: ...
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plotting stratified KM curve in R--want one stratum per plot so the final plot looks like a plot matrix [migrated]

I have a cohort data set and am trying to show the difference in survival patterns of 4 related diseases across eras (say I have 6 decades of data and want to stratify by each decade). How could I ...
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19 views

The Definition of “Approach infinity at rate n”?

In p.62 of the textbook, "Statistical Models and Methods for Lifetime Data" second edition, (Jerald F. Lawless, Wiley, 2003) it states "An added requirement is that the sequence of fixed ...
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Perform logrank test only with survival probabilities

So I have survival probabilities for 2 groups at years 1, 3, 5, 10,15. Is there way to detect significant differnece between all of them as a whole or even between each pair? I don't have the ...
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2answers
40 views

Estimating expected lifetime from hazard ratio and estimated base hazard function

Apologies if this is a basic question, I am not very familiar with survival analysis ... I have trained a gradient boosted Cox proportional hazards model in R, and have been able to obtain reasonable ...
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33 views

Weighted Kaplan-Meier Curve Log Rank Test

I need to compare two weighted KM curves created by using the svykm function from the survey package. I am unable to find any ...
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1answer
41 views

AFT model with time varying independent variables

I am a newbie in survival analysis and I would like to pose some simple questions, after reading numerous posts regarding how to perform survival analysis in R. So, what I would like to know is: Can ...
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1answer
89 views

model selection through shrinkage (Lasso) using glmnet

I would like to use model selection through shrinkage (Lasso) using glmnet. After trying the example of the glmnet manual and tried the procedure with my data. ...
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1answer
75 views

Impute missing values using aregImpute

I have a data frame with 61 columns. Some data is missing. I read in Steyerberg's book about aregImpute in Hmisc. I used it with ...
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20 views

Expected survival time: comparisons when measurements are an average over other measurements?

Set up We have a few types of interventions. For each intervention, a failure occurs randomly at some time $t$ after start for each subject. We take $n$ measurements of $t$ using $n$ subjects, and ...
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25 views

Joint Models vs the 'usual' time-dependent Cox regression for time-varying predictors

I've got a methodological question, and no data set attached. Suppose I aim to fit a proportional hazards model (Cox) for survival data. I have multiple observations for each individual (data in long ...
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1answer
44 views

Time-dependent covariate in extended Cox model

In Cox's PHM, $$ \lambda(t;\mathbb{x}) = \lambda_0(t) \exp(\beta^T \mathbb{x})~, $$ it is well known that the effect of a time - independent covariate on the survivor function is to raise it to a ...
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1answer
75 views

How to evaluate the goodness of fit for survial functions

I am a newcomer to survival analysis, although I have some knowledge in classification and regression. For regression, we have MSE and R square statistics. But how we can say that survival model A ...
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1answer
40 views

Simulate time to event times based on an existing subset of data

I have to task to predict data volume to be processed for a study that currently has 40 patients, but will have 100 patients eventually. Since most of the data is generated during the treatment phase, ...
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23 views

Best way to examine mortality tables?

I have a set of tables containing mortality rates (hazard rates) and I want to see how well these values reflect the influence of the covariates (age, sex, issue year, etc.). I also have actual ...
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1answer
46 views

plotting “log relative hazard” against continuous covariate: what are knots when using cph

I try to get into in Cox Regression and read the example chapter from Steyerberg's book. Afterwards I tried to plot log relative hazards against continuous variables using the rms package: ...
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2answers
47 views

Log-rank / Cox analysis with very unequal sized groups: alternative calculations of p-value?

I would like to set up a series of tests on the difference in survival between two very unequal sized groups. Generally either log-rank (using the R survdiff function) or a cox regression (R coxph) ...
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Predicting dropout in an ordered process: Cox regression, autoregressive model, multilevel modeling?

I am working on a project in which I collected data about 100 people’s steps in an ordered process. All took at least one step, with some continuing up to a fourth step. Each person either drops out ...
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21 views

Simulate KM curves with assumptions in R

I am looking to simulate 2 survival curves under different assumptions on the mean / median process underlying the 2 arms. Has anyone done this in R?
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1answer
42 views

Survival analysis - sideways

I have a typical Survival analysis data-set - patients progressing through various stages of Alzheimer's Disease over 8 years of time, with some covariates, plenty of censored records. However, I'm ...
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1answer
22 views

Modeling remaining duration for prediction

Suppose we're in the business of repairing broken specialty widgets and reselling them. At each point in time, we want to predict how much cash we'll make in the next 30 days on the existing ...
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30 views

Using time to event data to predict future time to event data

Design: People get drug A and time to an event is measured. Not everyone has the event. Later, most of those people get drug B (those censored and uncensored) and again, time to event is measured. ...
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33 views

Spatial analysis separating size from location in mri

Has anyone seen, done or understand how I can go about analyzing MRI datasets that have been registered to standard (MNI) space. What I´d like to do is analyze the effect on survival of lesion volume ...
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1answer
144 views

Calculate incidence rates using poisson model: relation to hazard ratio from Cox PH model

I want to calculate incidence rates to present along hazard ratio's in order to present both relative and absolute measures of risk. I saw in other studies that such incidence rates can be calculated ...
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34 views

Standardising input parameters in coxph models

I'm trying to standardize the input variables of my coxph analysis to make outputs more easily interpretable. I've used the following function (Which was ...
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189 views

Adjust for everything you have in propensity score?

I have a methodological question, and therefore no sample dataset is attached. I'm planning to do a propensity score adjusted Cox regression that aims to examine whether a certain drug will reduce ...
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Segregation Analysis for predicting age-specific cancer risk

I am relatively new to the worlds of bioinformatics and genetics research. I have been tasked with presenting to my lab the potential value of a paper that uses Complex Segregation Analysis for a risk ...
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30 views

Use of data from ROC curve

In order to find an optimal time for initiation of treatment post surgery (oncologic patients) I created a ROC curve with death defined as event. The AUC was not significant. However, I decided to use ...
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33 views

Predict Failure time/ Weibull analysis

Suppose I want to predict how many machine are going to fail in the next three years. The data collected are in days, so we want to predict no. of fails in next 1095 days. All the machines (100 of ...
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1answer
56 views

log-rank test in R

I need to use the survdiff function to statistically compare (using log-rank test) the following survival functions: (1) Male (Sex=1) and Female (Sex=2) (2) ...
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33 views

Problems estimating CIs on the survival function, $S_{t}$, in a logit hazard model

This is a bit longish (I want to be thorough), but my actual question is a short one (in bold below). BACKGROUND: Suppose I have a conditional logistic discrete time event history model (aka logistic ...
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1answer
19 views

What happens to the variance of missing covariates in poisson models

In normal multivariate regression you can leave out covariates (assuming they aren't correlated with any covariates you leave in) and the variance of covariates left out gets subsumed into the error ...
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28 views

Survival - comparing Kaplan-Meier curve to handful of points

I am investigating the effect of genomic dysmethylation on cancer survival time, with data from multiple different cancers with very different survival curves. Normally, I would split the cases into ...
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43 views

Validating Bootstrapped Probability of Survival Results From Small Sample Size Data

Quite often in industry, due to cost and schedule constraints, decisions must be made on small sample size data. I have 4 cycles-to-failure values resulting from running samples to failure in a ...
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1answer
61 views

How to assess the proportional hazards assumption for a continous variable

I am having a problem with checking the assumptions for a continuous variable in a proportional hazards model. If a variable were a factor with many levels, then I could use the logrank test or check ...
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18 views

Is there a version of Buhlmann-Straub credibility that uses an non-fixed $\theta_i$?

Everything I've read about Buhlmann-Straub credibility assumes a fixed $\theta_i$ (the unknown parameter that $X_{ij}$, the variable of interest, depends on). Does anyone know of a version where theta ...
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20 views

Result of the summary of the proportional hazard model with frailty in R

I am trying to fit coxph a model with frailty with syntax below: ...
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1answer
34 views

If I only have access to data that records everyone in a study as having died, can I still implement survival analysis?

I am currently trying to fit a survival analysis model. After reading through several books, I have still not come across the theoretical implications of implementing survival analysis on data that ...
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21 views

Extended COX model in R [closed]

Objective: To predict time to event of a customer using R I developed a Non parametric model but as per my understanding we cannot perform predictions from these models, so I have to build a model ...
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1answer
88 views

Is it possible to construct a discrete-time multilevel hazard model in R?

I'm trying to run a discrete-time multilevel hazard analysis comparable to the model proposed by Barber et al. I am attempting to model the hazard of migrating internationally using predictors at the ...
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Would this be a problem that Survival Analysis can tackle? The problem deals with localized durations and uncensored data

I am trying to fit a model in R that doesn't have censoring. In other words, I know that each event will eventually happen. There are several experimental groups with people in each group receiving ...