Related Experiment Video
Updated: Jul 5, 2025
04:44
Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
Published on: June 16, 2020
19.9K
In sarcoidosis trials, time also matters
Florence Jeny1,2, Hilario Nunes3,2, Dominique Valeyre2,4
1AP-HP, Pulmonology Department, Avicenne Hospital, Bobigny, France florence.jeny@aphp.fr.
The European Respiratory Journal
|January 18, 2024
Summary
No abstract available in PubMed .
More Related Videos
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
10.7K
10:04Analysis of 18FDG PET/CT Imaging as a Tool for Studying Mycobacterium tuberculosis Infection and Treatment in Non-human Primates
Published on: September 5, 2017
18.8K
Related Concept Videos
01:18Introduction To Survival Analysis
239
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
239
01:20Comparing the Survival Analysis of Two or More Groups
195
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
195