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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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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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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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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33 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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1answer
17 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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5answers
108 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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3 views

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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2answers
27 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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18 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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43 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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26 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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14 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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26 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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38 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
49 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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0answers
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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17 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
33 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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16 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
76 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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22 views

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 ...
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65 views

It it possible in R to specify a regression formula for the hazard rate for a survival analysis model?

I am currently trying to fit a survival analysis model which has the following survival function: $S(t) = \lambda_i e^{-\lambda_i t}$ but with $\lambda_i = e^{\beta_0 +\beta_1 log(1+X_i)}$ where ...
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1answer
50 views

Objective test for proportionality assumption in Cox Regression Model (SAS)?

I was trying to fit Cox Regression (aka Proportional Hazard) model on some cancer data (N=2288). I got the following output from SAS proc phreg: ...
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1answer
34 views

Logrank test for trend (proportional hazards)

How one can create a logrank test for trend and does it differ from normal logrank test? Any suggestions or literature? Maybe some R examples and functions?
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53 views

Why are these MLE estimates biased?

I estimate the parameters of survival data with censoring which is simulated from Weibull distribution. The mean time to event was set to 10 by choosing the combinations of shape and scale ...
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1answer
50 views

What’s wrong with this way of fitting time-dependent coefficients in a Cox regression?

I have a Cox proportional hazards model. Judging by Schoenfeld residual vs. time plots and corresponding tests for zero slope, there is clear violation of the PH assumption for several of the ...
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34 views

survival packages in R that allow for time dependent covariates

Which survival packages in R explicitly allow for time dependent covariates? By explicitly, I mean that the package allows its models to accept a survival object with the form ...
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27 views

Is there a way to customize my likelihood function for logit models using speedglm/biglm/glm packages?

My goal is to fit a custom logistic regression/survival analysis function using the optim/maxBFGS functions in R and literally ...
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50 views

How does one derive the survival function from an accelerated time failure model in R?

I'm currently working with accelerated time failure models. However, when I fit a model using survreg in R, the predict function ...
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27 views

What kind of analysis gives you the statement "If you DONT reach X amount by time T, then your chances go down by P percentage?

I am trying to model growth for data I have regarding downloads of applications. I would like to make a statement, if you "DONT reach X amount of downloads by time T, then your chances of reaching 15 ...
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1answer
29 views

Survfit function in R to score a new dataset

I have built a cox proportional hazards model in the R survival package. I want to score new data set using this model. I thought the survfit function would doing this using survfit(original model, ...
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49 views

how to use ggplot2 make recursive partitioning survival tree [closed]

can everyone tell me how to use ggplot2 make recursive partitioning survival tree? I know " party " package can make a plot in R, however the plot is not looking good, and all the plots in the rest ...
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33 views

survreg Ran out of iterations and did not converge

Survival data with censoring were generated by monte carlo method in R. Patients survival data was assumed to follow a weibull distribution. Parameters were extracted by fitting a parametric model to ...
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13 views

Preliminary crosstabs in survival analysis?

I am new in survival analysis. I have been taught that you analyze using survival because you have a special dataset: one with censored data. And that if I work only with not censored data, I can have ...
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27 views

Combining two separate Cox PH models into one model?

I have two Cox proportional hazards models (in R), using same outcomes and predictors, one for $n_m$ males and one for $n_f$ females. Is it possible to combine them into one equivalent model over all ...
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26 views

Complete interpretation of Cox regression output in R

I need help with complete interpretation of this output(below). Can someone explain all (almost all) estimators in this output: what they mean and what is the substantive interpretation. In ...
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9 views

Assistance with hazard ratios

I want to compare car accident deaths in two groups of people aged 18-24 (lets use this as the reference) and 24-30 after a certain law was changed using a Cox hazard model using SPSS version 22. I ...
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1answer
71 views

How to translate R to SQL for a Cox Proportional Hazards model?

I have built a cox model in R using the coxph function in the survival package, and now I need to replicate the model in SQL for scoring. From my understanding, the model has the form described on ...
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2answers
57 views

High Censoring Rate in Survival Analysis; Much higher survival time among censored patients

I am trying to understand censoring in survival analysis and wondering about how to tell when standard use of censoring breaks down. In one case, the number of censored patients is fairly high (low ...
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55 views

Survival Analysis in R with Grouped Data

I'm just getting started with survival analysis and I'm having trouble finding something in R that will do what I'm looking for. Most of the packages use survival ...
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1answer
62 views

How to generate survival data with time dependent covariates using R

I want to generate survival time from a Cox proportional hazards model that contains time dependent covariate. The model is $h(t|X_i) =h_0(t) \exp(\gamma X_i + \alpha m_{i}(t))$ where $X_i$ is ...
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19 views

how does sd of empirical log survival function and empirical log survival function

a sample of size 100 from an exponential distribution with parameter lambda 1. In this case, I believe that standard deviation of the empirical log survival function is ...
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13 views

Applying Cox proportional hazards model to new data to get absolute risk (Framingham risk score)

I'm trying to apply one of the Framingham cardiovascular event risk scores to a new dataset in order to get absolute risk. D'Agostino 2013 "Cardiovascular Disease Risk Assessment: Insights from ...
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9 views

Addition of time before commencement of radiotherapy to Cox Model

I have a dataset from a clinical trial for which all cancer patients received radiotherapy, but at different times following surgical removal of their tumour. So more simply, I have a variable, time ...
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1answer
67 views

Conditional expected lifetime in survival analysis

I want to do survival analysis with the Colon Cancer data in survival package: ...
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49 views

Survival Analysis why does probability drop to zero

I'm really new to stats and R and I suspect I'm missing something obvious. I have a set of memberships all who start after a point in time (six months ago). I have done my query to estimate the ...
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36 views

What's the best way to calculate survival time using outputs from random survival forest

I have built a random survival forest using R package randomForestSRC. The OOB error rate is around 10%. I was wondering whether anyone had some experience in utilizing the outputs from this model ...
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2answers
78 views

Survival analysis in R with left-truncated data

I am doing a survival analysis in R with the survival package. I think I am working with left-truncated data, but I'm not entirely sure how to handle it. I have a ...
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0answers
71 views

Predicting conditional expected lifetime by Cox model in R

I'm using a Cox proportional hazards model, estimate the hazard rate for Levamisole relative to 5-FU, adjusting for Age and Sex. ...
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13 views

estimate conditional time-to-event for recurring event history model

I have a sample of individuals for whom I have measured the time at which they display a particular behavior. This behavior is recurrent (it is not fatal). I have modeled these events with ...