1
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1answer
40 views

Conditional expected lifetime in survival analysis

I want to do survival analysis with the Colon Cancer data in survival package: ...
3
votes
0answers
41 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 ...
1
vote
1answer
41 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 ...
0
votes
0answers
46 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. ...
0
votes
0answers
36 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 ...
2
votes
0answers
26 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 ...
0
votes
0answers
26 views

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- ...
1
vote
0answers
50 views

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. ...
2
votes
0answers
36 views

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: ...
0
votes
1answer
34 views

Survival analyses for complicated models

I've just began looking into survival analyses, and I'm having some difficulty interpreting the results. I have a model linear regression model where time ~ x1 * x2 * x3... x9, this model seems to ...
1
vote
0answers
22 views

unique spline for different groups in a linear model (and no spline at all for one group)

I have a problem that has puzzled me for a long time. It involves linear models and spline functions. I need to model "time since diagnosis" when some individuals never had a diagnosis. I use Poisson ...
2
votes
1answer
47 views

Interval censoring

I ran an interval censor survival curve with R, JMP and SAS. They both gave me identical graphs, but the tables differed a bit. This is the table JMP gave me. ...
1
vote
1answer
110 views

p-value zero in hypothesis testing for survival curves

I have done survival analysis. I used Kaplan-Meir to do the survival analysis. Description of data: My data set is large and data table has close 120,000 records of survival information belong to 6 ...
0
votes
0answers
19 views

How to have a captured response table for a 2-year prediction base Cox model in R?

My study is about "Churn Risk Evaluation of College Students". I decided to use R software, already had a result for the survival probability of an old data (all the students already left or ...
1
vote
0answers
15 views

How to check out an appropriate survival model?

Maybe this question is too general, but I think it's worthy to post to clarify me some standard procedures in survival analysis. As we know, there are a list of method and models like parametric (exp, ...
1
vote
0answers
45 views

Is there an R function to do a survival analysis with right censoring + nested + crossed factors

I have this dataset to model, but I'm not sure how to do it. I want to model the surviving probability of different populations of two species depending on a treatment applied. Populations should ...
1
vote
1answer
50 views

Variance-covariance matrix of survival model

Suppose I have a survival model like this: ...
1
vote
0answers
40 views

How to predict cumulative hazard in survival analysis?

Suppose I have a survival model like this: ...
0
votes
0answers
151 views

Using a Decision Tree Algorithm such as C4.5 to understand population Partition

I have multivariate data about a certain population with more than 1000 attributes per exemplar. Some of the variables are basic demographics attributes including: gender, age, race, ethnicity, ...
0
votes
0answers
42 views

Time-scale in cox porportinal hazards model with multiple time-dependent variables

I'm doing survival analysis and I have three time-dependent variables, with different time scales each. I've already done univariate analysis and I want to proceed with multivariate analysis. My ...
0
votes
1answer
47 views

R Interpret coefficient from Survreg(dist=“gaussian”)

I was wondering if anyone could help me on how to interpret the coefficient from an analysis I have carried out in R (survival package). The data is right ...
0
votes
0answers
133 views

Predict probability of failure in R using survreg

I am fitting a weibull model as follows: s <- Surv(DFBR[,"Time"],DFBR[,"Censor"]) wei <- survreg(s~ Group+ UsefulLife, data = DFBR, dist="weibull") How ...
4
votes
1answer
86 views

How would you visualize the difference between Cox/Weibull regression?

I'm trying to figure a way of properly displaying the difference\resemblance between various regression values on the same data set, using cox ph, weibull regression and log-normal regression. ...
1
vote
0answers
148 views

Confidence interval for the restricted mean in survival analysis

What is the recommended way of calculating confidence intervals for the restricted mean in survival analysis? Here are some example data, taken from the paper Chris Barker (2009), The Mean, Median, ...
0
votes
0answers
24 views

Two-state model with transient states for panel data

I need to analyse unbalanced panel data where the variable of interest is a dummy with two non-absorbing states (i.e. switch from 0 to 1 and 1 to 0 is possible at any time period). The goal is to ...
1
vote
0answers
86 views

How to use Cox proportional hazards model in interval-censored data with time-dependent variables?

The question is self-explanatory. I have survival data (n=156) which, in about half of the observations, is right-censored or interval-censored. I'm am using R to do the analysis and I know I can use ...
0
votes
1answer
96 views

Survfit function for gbm cox model

I just fitted a boosted regression coxph model: cox=gbm(Surv(periods, event) ~ grade + fico_range_low + revol_util + dti, data=notes) However, I want to obtain ...
1
vote
1answer
160 views

How to calculate Prob > chi2 in R to test model fit of conditional logistic regression

I used the clogit function (from the survival package) to run a conditional logistic regression in R with a big dataset of 1:M matched pairs with n=300368964 and number of events= 39995. ...
2
votes
1answer
268 views

Why do coxph() and survreg(, dist=“exponential”) NOT return the same coefficient (except for expected opposite sign) in R?

If I understand correctly, the coefficient of a covariate X under a Weibull accelerated failure time (AFT) model is related to the ...
1
vote
0answers
119 views

How to use Turnbull's nonparametric estimator for interval-censored data in R

I am doing Survival Analysis with interval-censored data and I want to apply Turnbull's nonparametric estimator to the analysis of the covariates (suggested by Turnbull (1976)). I want to know if ...
2
votes
1answer
118 views

Comparison of CPH, accelerated failure time model or neural networks for survival analysis

I am new to survival analysis and I've recently learned that there are different ways to do it given a certain goal. I am interested in actual implementation and appropriateness of these methods. I ...
1
vote
1answer
208 views

how does Cox proportional hazards model deal with time-dependent variables

When considering time dependent data in survival analysis, you have multiple start-stop times for an individual subject with measurements for the covariates. If each season has a different size (for ...
1
vote
0answers
43 views

Decision to add all predictive variables in Kaplan-Meier and Cox PH

In R's survival and rms packages, Kaplan-Meier (Surv and ...
2
votes
1answer
123 views

What is the parameterization of exponential distribution for survival in Stata?

I'm new to data analysis so this is kind of a simple question. I would like to understand why I cannot reproduce a survival curve generated by a fitted exponential model from Stata. I use the ...
4
votes
1answer
501 views

R neural network model with target vector as output containing survival predictions

Overview I want to simulate the survival prediction using neural networks described in this paper entitled "Application of Artificial Neural Network-Based Survival Analysis on Two Breast Cancer ...
1
vote
1answer
98 views

Interpretation of survival risk predictions generated from R's predictSurvProb

I am starting to learn R and its power for giving survival predictions. Abstract I use the predictSurvProb function from the ...
0
votes
0answers
146 views

Using the calibrate function in rms package for Cox model: use 'hare' method or 'KM'?

I'm creating a calibration plot for my breast cancer prognostic Cox model, which doesn't include any fancy transformations, using the calibrate() function in the ...
0
votes
1answer
308 views

Making a cumulative incidence plot in R

Background I have a survival object in R called km. ...
2
votes
0answers
211 views

How to simplify coxme survival models?

I have some questions about specifying a coxme (mixed-effects Cox proportional hazards) model in R and then simplifying it after reading the ...
2
votes
1answer
180 views

Obtaining R pec survival patient risk percentage

Introduction I have a 300,000-row cancer dataset with around 60 variables (cancer stage, year of diagnosis, radiation therapy, histology, etc.) with a time variable ("number of months survived") and ...
1
vote
1answer
110 views

Coefficients from a penalized Cox PH

I'm using the R package Penalized (0.9-42) on a Cox PH model. I'm using L2 (Ridge) on the grounds that I don't want to shrink my coefficients to 0. I don't understand why when I ask for: ...
0
votes
0answers
27 views

Mean residual life with censored observations and covariant eps

I have a time variable ( time of claim settlement after occurrence ) that may be censored ( claim still open at the moment of observation) and some additional covariates ( line of business, claim ...
0
votes
1answer
675 views

Risk table for a Kaplan Meier plot in R

I need to make a Kaplan Meier plot with a risk table beneath it. Otherwise stated, I need a table of the number of subjects at risk at different time points aligned below the figure. I found a website ...
1
vote
0answers
51 views

Survival analysis cycle time dependent variable

I've a survival analysis study going on and I'm having trouble with dealing with time-dependent variables. To deal with time-dependent variables I have to create intervals when the variable changes. ...
2
votes
1answer
307 views

Predicting absolute risk using cox regression

I am trying to use R to predict the absolute risk of developing adverse events in a cohort, and to compare that with the observed outcome. Should I use survreg or ...
2
votes
1answer
218 views

How do I use the “survival” package and “Surv” function in R with left-truncated data?

I am trying to run survival analysis using the Surv and survfit functions from the survival ...
1
vote
0answers
114 views

obtaining Standard Errors in maximum likelihood estimation

I am trying to obtain the standard errors of my maximum likelihood model, I am having trouble to fix the error message: ...
5
votes
1answer
360 views

Generating survival times for a piecewise constant hazard model with two change points

When there are two change points in a piecewise constant hazard model then the density function becomes some triangle exponential distribution. In this situation I can't generate the survival time ...
5
votes
0answers
109 views

Structure of data and function call for recurrent event data with time-dependent variables

I'm attempting to estimate the effect of 2 drugs (drug1, drug2) on the likelihood of a patient falling (...
0
votes
0answers
55 views

Survival Analysis — Probability Definition and Distribution application

edit: I think really the crux of my question is more meta, really how should I think of survival data and how do I know what kind of distribution I should fit into it? Are there any resources on how ...