Results 1 to 10 of about 18,981 (120)

Simulation of generalized Gamma distribution with maximum likelihood estimation and expectation-maximization algorithm on right censored data type 1 [PDF]

Decision Science Letters, 2021
The Generalized Gamma distribution is very suitable for modeling data with various forms of hazard (risk) functions, which makes the Generalized Gamma distribution useful in survival analysis.
Kurniasari, Dian, Warsono, Warsono, Indryani, Nourma, Usman, Mustofa, Hadi, Sutopo   +4 more
doaj   +1 more source

Statistical methodologies for evaluation of the rate of persistence of Ebola virus in semen of male survivors in Sierra Leone

PLoS ONE, 2022
The 2013–2016 Ebola virus (EBOV) outbreak in West Africa was the largest and most complex outbreak ever, with a total number of cases and deaths higher than in all previous EBOV outbreaks combined.
Ndema Habib, Michael D. Hughes, Nathalie Broutet, Anna Thorson, Philippe Gaillard, Sihem Landoulsi, Suzanne L. R. McDonald, Pierre Formenty   +7 more
doaj   +3 more sources

Bayesian Spatial Split-Population Survival Model with Applications to Democratic Regime Failure and Civil War Recurrence

Mathematics, 2023
The underlying risk factors associated with the duration and termination of biological, sociological, economic, or political processes often exhibit spatial clustering.
Minnie M. Joo, Brandon Bolte, Nguyen Huynh, Bumba Mukherjee   +3 more
doaj   +1 more source

Handling Censoring and Censored Data in Survival Analysis: A Standalone Systematic Literature Review

International Journal of Mathematics and Mathematical Sciences, 2021
The study recognized the worth of understanding the how’s of handling censoring and censored data in survival analysis and the potential biases it might cause if researchers fail to identify and handle the concepts with utmost care.
Anthony Joe Turkson, Francis Ayiah-Mensah, Vivian Nimoh   +2 more
doaj   +1 more source

Survival Analysis and Hazard of Log Logistic Distribution on Type I Censored Data Parametrically

Contemporary Mathematics and Applications (ConMathA), 2023
Survival Analysis is a research method that examines the survival time of individuals or experimental units in relation to events such as death, disease, recovery, or other experiences.
Ardi Kurniawan, Ruth Hosana, Ni Wayan Widya Septia Sari   +2 more
doaj   +1 more source

Interval shrinkage estimation of two-parameter exponential distribution with random censored data [PDF]

Journal of Mahani Mathematical Research
The use of the two-parameter exponential distribution model in fitting survival and reliability analysis data in the presence of censored random data has recently attracted the attention of a large number of authors.
Ali Soori, Parviz Nasiri, Mehdi Jabbari Nooghabi, Farshin Hormozinejad, Mohammadreza Ghalani   +4 more
doaj   +1 more source

Quantile Regression in Survival Analysis: Comparing Check-Based Modeling and the Minimum Distance Approach

Journal of Biostatistics and Epidemiology, 2023
Introduction: Quantile regression is a valuable alternative for survival data analysis, enabling flexible evaluations of covariate effects on survival outcomes with intuitive interpretations. It offers practical computation and reliability.
Fereshteh Mokhtarpour, Mostafa Hosseini, Akram Yazdani, Mehdi Yaseri   +3 more
doaj   +1 more source

Exploring the Effects of Early Censoring and Analysis of Clinical Trial Survival Data on Effectiveness and Cost-effectiveness Estimation through a Case Study in Advanced Breast Cancer

Medical Decision Making, 2018
Interim analyses of clinical trial data are frequently used to provide evidence to obtain marketing authorization for new drugs. However, results from such analyses may not reflect true estimates of relative effectiveness when trial follow-up is complete.
Bagust, Adrian, Beale, Sophie J
openaire   +3 more sources

Estimating the Individual Treatment Effect on Survival Time Based on Prior Knowledge and Counterfactual Prediction

Entropy, 2022
The estimation of the Individual Treatment Effect (ITE) on survival time is an important research topic in clinics-based causal inference. Various representation learning methods have been proposed to deal with its three key problems, i.e., reducing ...
Yijie Zhao, Hao Zhou, Jin Gu, Hao Ye
doaj   +1 more source

Examining Selected Theoretical Distributions of Life Expectancy to Analyse Customer Loyalty Durability. The Case of a European Retail Bank

Acta Universitatis Lodziensis. Folia Oeconomica, 2020
One of the key elements related to calculating Customer Lifetime Value is to estimate the duration of a client’s relationship with a bank in the future. This can be done using survival analysis.
Dominik Kubacki, Robert Kubacki
doaj   +1 more source