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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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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29 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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Extended COX model in R [on hold]

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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44 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 ...
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How can I plot “intcox” interval cox proportional survival curve?

I'm doing survival analysis. I read intcox package manual but it doesn't provide R code for plotting survival curve. Anyone knows how to plot it? ...
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1answer
57 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
40 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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22 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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46 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
37 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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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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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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44 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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How to compare a Cox model with a neural network model [duplicate]

I am trying to compare a Cox model with ANN in R, but I have some problems: The result of package coxph is a hazard rate, but the result of package ...
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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
23 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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45 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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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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1answer
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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24 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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23 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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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
70 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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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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49 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
46 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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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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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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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
57 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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48 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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1answer
29 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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1answer
53 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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61 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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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 ...
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48 views

Survival Analysis—Equal follow up time

My question is whether my data are a survival analysis problem. I have 3 groups (2 interventions and 1 control). The 200 patients are all followed up for 6 months only. The follow-up is done by ...
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1answer
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How to analyze survival data with possible temporal dependencies

I want to analyze some survival data. I have measurements of a biomarker (real-valued variable) before a first treatment, after that first treatment, and then after a second treatment (different to ...
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49 views

How to simulate survival times using true base line hazard function

I want to simulate survival times from the model $\lambda(t|X_1,X_2) = \lambda_0(t) \exp(\gamma_1X_1+\gamma_2X_2)$ where covariates are given by $X_1\sim$Binomial(1,0.5), $X_2\sim$Uniform(0,1), the ...
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Showing $ λ_V(x) \leq min\{λ_1(x),\cdots,λ_n(x)\}$ Hazard function

Suppose $X_1, \cdots, X_n$ are independent, nonnegative continuous functions, each $X_i$ has hazard function $\lambda_i(x)$. If $V=\max\{X_1, \cdots, X_n\}$, I need to show that ...
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36 views

Testing significance for pairwise Kaplan-Meier survival analysis between groups and pooled data

I've been working on putting together a survival analysis using Kaplan-Meier and the logrank test. I am doing the testing in R with survdiff(). Each plot has multiple groups/curves, and I've been ...
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32 views

Hazard model with time varying covariates

I am trying to build a discrete time event model. The event occurs once in 20 years period of time. Most of the example i saw use only covariates which are same over period of time. e.g. sex,race etc. ...
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Include interaction in multiple imputation - r

I'm doing some imputation models of time until recurrence of tuberculosis (Cox model). This model should include an interaction between the time and the outcome of the previous episode of disease (0- ...
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Error in adding interaction in Cox model?

I'm doing a survival analysis and after plotting the Schoenfeld residuals and test the significance of the correlation of residuals with time, I've decided to incorporate a interaction in the model. ...
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Correlation Matrix in an Event History Analysis - 11 years - 25 Variables

I'm currently writing my thesis, and I received feedback from my professor that i need to show the correlations between all variables during the time span of my research. N: 291 Years: 11 (2000 - ...
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Simulate censored data cox model

I would like to simulate interval-censored data in a Cox model. In the R package intcox I found the following code: ...
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Validation - correctly compare and validated imputation models

I've seen a lot of interesting questions here about multiple imputation and also great answers that helped me a lot to impute my data. I've used Predictive Mean Matching, EMB and I would like to use ...
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How to estimate the point of divergence between two continuous time survival curves?

In this experiment we collect $N$ samples and each sample yields a pair of survival curves. The two survival curves are hypothesized to be identical up until time $t$ and diverge thereafter. What ...
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How was this deviance formula for Cox Proportional Hazard derived?

The gbm package in R documents the following deviance formula for CoxPH models http://gradientboostedmodels.googlecode.com/git/gbm/inst/doc/gbm.pdf $-2 \sum w_i \delta_i (f(x_i) - \log(R_i / w_i)$, ...
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predicting manufacturing survival time

My task is to improve widget quality from a high volume manufacturing process. The survival data is 99% right censored, since most products do not fail, and rapid analysis long before failure is ...