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Questions tagged [survival]

Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.

1 vote
0 answers
7 views

I’m fitting a survival model with a multi-level factor (HistologyClass) and binary treatment variables (Radiotherapy, Chemotherapy). I do not want the full HistologyClass * Treatment interaction, ...
Kavalali's user avatar
  • 473
3 votes
1 answer
24 views

I am using Ordinal Semiparametric Regression (Frank Harrell's rms package) to model overall survival in patients with brain tumor. My training data is from the SEER database (covering years 2004 to ...
Çağan Kaplan's user avatar
2 votes
0 answers
26 views

I have recently become interested in Markov State Transition Models for the analysis of clinical trials with composite endpoints, such as the Markov Longitudinal Ordinal Model described in Frank ...
underflow's user avatar
  • 355
7 votes
1 answer
256 views

Let's consider the below example as a life table for survival analysis: At time 124, we have censored patinet, lost to follow up. Generally, I have noticed that we don't get from the software ...
AgnieszkaTomczyk's user avatar
2 votes
1 answer
34 views

I am working with Neural Network violating Proportional Hazard survival model. This model directly incorporates the proportional hazard into its architecture. I have applied this model in UnempDur ...
coderoid's user avatar
  • 275
2 votes
1 answer
45 views

How do these two differ in terms of interpretation? When should one be used over the other? ...
esss123's user avatar
  • 21
0 votes
0 answers
19 views

I have done 5 fold cross validation to create 5 fold: three for training data, one for validation and one for test data. I want to perform Kaplan-Meier method in this data. I have computed 10 unique ...
coderoid's user avatar
  • 275
4 votes
1 answer
200 views

I commonly work with cancer data that is on the patient-lesion level, as patients with metastases often have multiple treated lesions. While looking at patient survival is easy, I get a bit stuck with ...
scott9's user avatar
  • 135
1 vote
0 answers
22 views

I am trying to understand the Cox PH assumption when using a Cause-Specific Hazard Model. I have a dataset of 5,000 observations, split 50/50 between treatment and placebo. There is a main event of ...
Iasios's user avatar
  • 11
3 votes
1 answer
44 views

I came across the article from Bender et al.(2005) and attempted to put this into R code to simulate survival times based on an empirical baseline hazard from existing data. I compute survival times ...
peer's user avatar
  • 43
8 votes
2 answers
356 views

I am comparing two survival prediction models for CNS tumor patients, and my main concern is temporal drift in histology definitions rather than ordinary overfitting. My development dataset is SEER (...
Kavalali's user avatar
  • 473
2 votes
1 answer
49 views

(Maybe the follow-up of this post: Running Cox PH model with time-dependent variables using large data) I used Case-Cohort subsampling to fit the Cox proportional hazard model with time-dependent ...
JH Park's user avatar
  • 45
5 votes
1 answer
105 views

In one of my dissertation chapters, I am using survival analysis to assess time to next birth following calf loss in a wild dolphin population to address costs to female fitness. My question is about ...
Meredith-Mac's user avatar
1 vote
0 answers
28 views

I computed a survival AFT model with lognormal distribution and derived a nomogram for predicting mortality in a cohort of patients and I would like to extract the predicted mortality at different ...
Claudio Laudani's user avatar
0 votes
0 answers
34 views

This is a follow-up question from this post: The difference in VIF between frailty model and standard Cox model with robust estimator In my case, I chose to use a frailty model due to high VIF in the ...
doraemon's user avatar
  • 530

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