|
Simulated data for survival modelling Data Set
Download: Data Folder, Data Set Description
Abstract: A variety of survival data, with carefully controlled event and censor rates, is available to allow people to develop and test new approaches to survival modelling.
|
|
Data Set Characteristics: |
Multivariate, Time-Series |
Number of Instances: |
120000 |
Area: |
Life |
Attribute Characteristics: |
Integer, Real |
Number of Attributes: |
25 |
Date Donated |
2018-12-04 |
Associated Tasks: |
Regression |
Missing Values? |
Yes |
Number of Web Hits: |
14905 |
Source:
Creators:
Ruikin Cao, Fei Gao, Dimitris Kontogouris, Pavel Kroupa, Zongchun Li, Yuxiang Wu
Department of Computing, Imperial College London, London, UK
Matt Williams & Kerlann Le Calvez
Computational Oncology Laboratory, Imperial College London, London, UK
Imperial College Healthcare NHS Trust, London, UK
Donors:
Kerlann Le Calvez & Matt Williams
Computational Oncology Laboratory, Imperial College London, London, UK
Imperial College Healthcare NHS Trust, London, UK
Data Set Information:
We generated two batches of data, where each batch consists of 20 datasets.
For the low dimensional batch, we used 5 predictive parameters, of which 2 were dummy parameters (i.e. had no impact) and three were predictive.
For the medium dimension batch, we used 25 predictors, of which 2 were dummy and 23 predictive.
In each batch, we varied the event rate from 10% to 70% and the censor rate from 0% to 70% in 20% steps, and used a set population size of 3000.
This therefore led to two batches, each of 20 datasets of 3000 subjects.
Attribute Information:
For the low dimensional batch:
x.0 & Binary: with equal probabilities
x.1 & Gaussian: μ = 50, σ = 15
x.2 & Uniform: [1,2,3,4]
x.3 & Binary: 0.6 chance of 0
x.4 & Uniform: [1,2,3]
For the medium dimension batch:
x.0 & Binary: with equal probabilities
x.1 & Gaussian: μ = 50, σ = 15
x.2 & Uniform: [1,2,3,4]
x.3 & Binary: 0.6 chance of 0
x.4 & Uniform: [1,2,3]
x.5 & Binary: 0.95 chance of 0
x.6 & Binary: 0.9 chance of 0
x.7 & Binary: 0.85 chance of 0
x.8 & Binary: 0.8 chance of 0
x.9 & Binary: 0.75 chance of 0
x.10 & Binary: 0.7 chance of 0
x.11 & Binary: 0.65 chance of 0
x.12 & Binary: 0.6 chance of 0
x.13 & Binary: 0.55 chance of 0
x.14 & Binary: 0.5 chance of 0
x.15 & Binary: 0.5 chance of 0
x.16 & Binary: 0.45 chance of 0
x.17 & Binary: 0.4 chance of 0
x.18 & Binary: 0.35 chance of 0
x.19 & Binary: 0.3 chance of 0
x.20 & Binary: 0.25 chance of 0
x.21 & Binary: 0.2 chance of 0
x.22 & Binary: 0.15 chance of 0
x.23 & Binary: 0.1 chance of 0
x.24 & Binary: 0.05 chance of 0
Relevant Papers:
A submission to Nature is in progress
Citation Request:
Please cite the associated paper when using this dataset.
|
