Statistical Methods for Survival Data Analysis
By B. Gillespie. 2015
134 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/294afd0ef8e977ccd4bc25c5d3554dafc26fcfb4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Statistics and Probability
- Ibrahim Elbatal
- Christophe Chesneau
- Mohammed Elgarhy
- Abdulhakim A. Al-babtain
- O. Mohamed
- Junzhou Huang
- Ahmed Z. Afify
- G. Hamedani
Citations in the corpus
- Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks (2020, background): “• Parametric censored regression models: PCR models formulates the joint probability of the uncensored and censored instances as a product of death density function and survival functions, respectively [56].”
- Sine Topp-Leone-G family of distributions: Theory and applications (2020, methodology): “[47] Lee ET, Wang JW. Statistical methods for survival data analysis, 3rd edn.”
- A New Three-Parameter Exponential Distribution with Variable Shapes for the Hazard Rate: Estimation and Applications (2020, methodology): “The first set of data was studied by Lee and Wang [20], and it represents the remission times (in months) of a random sample of 128 bladder cancer patients.”