0
votes
0answers
19 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
0answers
17 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
47 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
63 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
72 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
20 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
60 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
56 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
87 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
122 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 ...
0
votes
0answers
73 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
62 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
110 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
40 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
91 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 ...
3
votes
1answer
295 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
68 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
80 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
147 views

Making a cumulative incidence plot in R

Background I have a survival object in R called km. ...
2
votes
0answers
129 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
154 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
81 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
23 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
356 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
38 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
176 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
161 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
96 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
236 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 ...
4
votes
0answers
88 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
48 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 ...
1
vote
0answers
144 views

Parametric modelling of customer lifetime value using survival (Cox) analysis

I have half a year long data of purchases in e-commerce site (100K purchases by 60K customers). In simplest A/B testing framework random customers got a discount on the next purchase after order ...
0
votes
0answers
65 views

Meta analysis of summary data or model of raw data?

I have data of the following form: Sample MeasureZZ Time Event S1 M1 t1 e1 .... I have calculated the influence of ZZ on survival by ...
0
votes
0answers
97 views

Calculate variance of survival estimate generated from 'baseline' of coxph

Short version: calculate variance of estimator of survival for a new subject (new covariates) where the coefficients for the covariates have been calculated from existing data. Sorry this is so long, ...
3
votes
1answer
1k views

How to estimate baseline hazard function in Cox Model with R

I need to estimate baseline hazard function $\lambda_0(t)$ in a time dependent Cox model $\lambda(t) = \lambda_0(t) \exp(Z(t)'\beta)$ While I took Survival course, I remember that the direct ...
0
votes
0answers
45 views

Cross-validation in gamma frailty model

Does anyone know how to do cross-validation in a gamma frailty model in R? I am using the survival package, which uses the ...
3
votes
1answer
218 views

Estimate Survival Function from hazard function — an inconsistent result between basehaz and survfit function

I am trying to caculate survival function in a time dependent covariates Cox model from its baseline hazard function. However, my program gives a different result compared with ...
0
votes
1answer
73 views

Competing risk data

I want to simulate survival time for two competitive events using R. Consider that there are no censored data, and the survival time for each event has exponential ...
1
vote
0answers
145 views

Using R, how can I plot survival curves of Cox PH model with time-varying covariates?

I've been following the R code from page 74 of this link to plot a survival curve given a set of independent variable values. Note that the author uses ...
3
votes
2answers
538 views

coxph ran out of iterations and did not converge

Yes, I have checked that previous answers to "Ran out of iterations..." questions do not solve my problem. I have fault data on Firefox, 899 faults and 1395 (estimated) censored faults. The ...
2
votes
0answers
119 views

Fitting survival/hazard model to probability of default

I will very grateful with some help on the following problem: I need to forecast probability of default for portfolio of retail loans, depending on several factors, that can be divided into three ...
0
votes
0answers
108 views

Path Analysis from cookie data using Survival Analysis?

I have a data analysis task where I need to assign value to various advertisement exposures that lead to an online purchase. The various types of exposures are recorded in sequence but there is no ...
2
votes
0answers
85 views

Feed forward neural networks for the analysis of censored survival data, how should I implement it in R?

Recently, I have read an article which name is “Feed forward neural networks for the analysis of censored survival data: A partial logistic regression approach”. Without a math background, I catch ...
2
votes
0answers
150 views

Applying Kaplan-Meier survival function estimate to get expected number of events

I have the Kaplan-Meier estimate for the survival function which I obtained using R's survival package: ...
3
votes
1answer
409 views

How to simulate a Cox proportional hazards model with change point and code it in R

I have a model that has the following characteristics: The covariate $X$ follows a $Be(1/3)$. If $X=0$, survival time $Y$ follows an $E=Exponential (1)$. If $X=1$, survival time $Y$ is generated as ...
0
votes
1answer
124 views

Survival analysis with ridge regression in R give same results with different random seeds

I am doing survival analysis using ridge regression. I'm using this R command: coxph(Surv(time, status) ~ ridge(x1, x2, x3), data=DATA) As far as I know, ...
0
votes
0answers
102 views

survSplit at different times for each individual

I am doing a follow-up study in which I follow patients with liver cirrhosis who initially abstain from alcohol. My outcome is time to death, and I am using Cox regression. Some patients resume ...
2
votes
1answer
96 views

Illness-death multistate survival model

I am attempting to use and illness-death multi-state scenario to model a time-dependent covariate in a competing risks analysis following Beyersmann et al. 2012 (Competing Risks and Multi-state Models ...
2
votes
1answer
291 views

Competing risk survival analysis with time-dependent covariates

Can anyone recommend an R package that handles left-truncation, right censoring, AND time-dependent covariates? I have a data set that consists of distance-to-event data rather than time-to-event as ...
1
vote
1answer
86 views

Plotting the gap between two times

I have a (large) dataset where I know, for each observation, the departure and the arrival time of a worker (between 0 and 24, in decimal) : ...