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Article
Mathematics, Interdisciplinary Applications
Prabhashi W. Withana Gamage et al.
Summary: The proportional hazards model is widely used for analyzing lifetime data in epidemiological studies. This paper proposes a novel unified PH model that can handle censored outcomes and left truncated data, and develops an expectation-maximization algorithm for model fitting.
LIFETIME DATA ANALYSIS
(2023)
Article
Mathematical & Computational Biology
Michael J. Crowther et al.
Summary: In this article, a general parametric AFT model is proposed, with restricted cubic splines used to model the baseline for greater flexibility. The model is extended to accommodate time-dependent acceleration factors, allowing for delayed entry and time-dependent covariates. Simulation evaluations show substantial improvements compared to standard parametric AFT models. Analytical and simulation results also demonstrate the collapsibility of AFT models, indicating their suitability for causal inference. The methods are illustrated using a dataset of breast cancer patients, and efficient, user-friendly software packages in Stata and R are provided.
Article
Statistics & Probability
Shahedul A. Khan et al.
Summary: Two common problems encountered in survival analysis are recurrent event data analysis and joint modeling, for which the proportional hazards (PH) family provides an attractive modeling paradigm. When the PH assumption fails, an accelerated failure time (AFT) model can be considered for joint modeling. The proposed methodology involves computational algorithms for statistical inference and a software package to fit these models, demonstrated using simulated and real data.
COMPUTATIONAL STATISTICS
(2022)
Article
Health Care Sciences & Services
Abdisalam Hassan Muse et al.
Summary: Survival analysis is a crucial statistical technique that examines the time it takes for an event to happen. This study focuses on Bayesian inference for the generalized log-logistic proportional hazard model and its application to right-censored healthcare data sets. The research found that the proposed model performs well and can be beneficial in analyzing various types of survival data.
JOURNAL OF HEALTHCARE ENGINEERING
(2022)
Article
Public, Environmental & Occupational Health
Joseph Waogodo Cabore et al.
Summary: COVID-19 has impacted the African region significantly. Through a comprehensive model, it is estimated that the number of infections in the region from Jan 2020 to Dec 2021 was 505.6 million, with only 1.4% reported. Deaths are estimated at 439,500, with 35.3% related to COVID-19. By the end of 2022, infections are predicted to remain high, but deaths will decrease significantly.
LANCET GLOBAL HEALTH
(2022)
Article
Mathematics, Applied
Abdisalam Hassan Muse et al.
Summary: The purpose of this study is to propose a novel, general, tractable, fully parametric class for hazard-based and odds-based models of survival regression for the analysis of censored lifetime data, named as the Amoud class (AM) of models. This class is broad enough to cover a number of widely used models, including the proportional hazard model, the general hazard model, the proportional odds model, the general odds model, the accelerated hazards model, the accelerated odds model, and the accelerated failure time model, as well as combinations of these. This study demonstrates the utility of the proposed model by applying it to a right-censored lifetime dataset with crossing survival curves.
Article
Mathematics, Interdisciplinary Applications
Adam Braima S. Mastor et al.
Summary: A novel version of the exponential Weibull distribution, known as the extended exponential Weibull (ExEW) distribution, is developed and examined using the Lehmann alternative II (LAII) generating technique. The basic mathematical properties of the new distribution are derived, and the maximum likelihood estimation (MLE) technique is used to estimate the unknown parameters. The performance of the estimators is further assessed using Monte Carlo simulation, and the applicability of the new distribution is demonstrated using two real-world data sets.
Article
Statistics & Probability
Fatima-Zahra Jaouimaa et al.
Summary: This article discusses a parametric modelling approach for survival data, where covariates can enter the model through multiple distributional parameters. The authors extend the model to handle multivariate survival data by introducing random effects and estimate the model using an h-likelihood approach. The results of the study demonstrate that the proposed modelling approach is flexible, robust, and performs well in both simulation studies and real data applications.
STATISTICAL MODELLING
(2022)
Article
Engineering, Multidisciplinary
Abdisalam Hassan Muse et al.
Summary: The paper introduces several commonly used distributions for modeling survival data, including the log-normal, log-logistic, and Weibull distributions. The authors propose a more flexible parametric model, the generalized log-logistic distribution, which can accommodate both monotone and non-monotone failure rate functions. They formulate an accelerated failure time model based on this distribution and demonstrate parameter estimation using Bayesian and frequentist approaches. The proposed model is evaluated through extensive simulation studies and the analysis of real-life survival data, showing its effectiveness in modeling survival data with various hazard rate shapes.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Mathematics
Gabriela M. Rodrigues et al.
Summary: This study examines the factors that increase the risk of death in hospitalized patients with COVID-19 using the odd log-logistic regression model and provides new mathematical properties of this distribution. The simulation results demonstrate the consistency of the estimates and suggest that the proposed model is efficient in identifying the determinant variables for individual survival.
Article
Mathematics
Abdisalam Hassan Muse et al.
Summary: In this study, a general hazard regression model is proposed for censored lifetime data with covariates. This model includes well-known sub-classes such as the accelerated failure time model and the proportional hazard model. By separating the covariate's effect into a relative hazard ratio and a time-scale change, the model is more adaptive and can provide more accurate survival forecasts. The nested structure of the models offers a tool for identifying the most appropriate model for a given dataset.
Article
Mathematics, Interdisciplinary Applications
Elisangela C. Biazatti et al.
Summary: Motivated by the growing popularity of the beta prime distribution, this study presents a more flexible generalized distribution to fit symmetrical or asymmetrical and bimodal data, as well as non-monotonic failure rate. The Weibull-beta prime distribution is defined and its structural properties are examined. Maximum likelihood estimation is used to estimate the parameters, and a new regression model is proposed. Simulations demonstrate the consistency of the estimators, and the application to censored COVID-19 data confirms the adequacy of the models.
Article
Health Care Sciences & Services
Haro Aida et al.
Summary: Survival analysis is a statistical method used to infer event occurrence time, with the accelerated failure time model being an alternative to the proportional hazards model. The study considers a cure model with frailty for uncured patients, proposing an estimation algorithm that accounts for individual heterogeneities.
Article
Statistics & Probability
Md Ashraf-Ul-Alam et al.
Summary: The study investigates the flexibility of the generalized Topp-Leone-Weibull (GTL-W) distribution as an accelerated failure time model in fitting censored survival data under the Bayesian setting, utilizing Bayesian model selection criteria for model comparison and selection.
AUSTRIAN JOURNAL OF STATISTICS
(2021)
Article
Mathematical & Computational Biology
Danilo Alvares et al.
Summary: Survival analysis is a crucial field in medical and biological sciences, with Bayesian methods gaining popularity as a flexible and powerful alternative to frequentist approaches. This article reviews popular Bayesian survival models and provides implementations using BUGS syntax for each model, along with discussions on reference to other Bayesian R-packages.
STATISTICS IN MEDICINE
(2021)
Review
Biochemistry & Molecular Biology
Pedro Rafael D. Marinho et al.
Summary: The article contributes by reporting general statistics and predictions on the COVID-19 pandemic in Brazil, highlighting the rapid growth and high lethality rate. It also provides insights on the expected increase or decrease of new cases and deaths, aiming to assist managers and researchers in making informed decisions.
CYTOKINE & GROWTH FACTOR REVIEWS
(2021)
Article
Primary Health Care
Gayathri Thiruvengadam et al.
Summary: This study identified factors affecting the length of hospital stay for COVID-19 patients using a Cox proportional hazard model, such as abnormalities in oxygen saturation, neutrophil-lymphocyte ratio, and levels of D-dimer. Patients with more than 2 chronic diseases had significantly longer hospital stays compared to those without comorbidities.
JOURNAL OF PRIMARY CARE AND COMMUNITY HEALTH
(2021)
Article
Statistics & Probability
Kevin Burke et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
(2020)
Article
Statistics & Probability
Kevin Burke et al.
SCANDINAVIAN JOURNAL OF STATISTICS
(2020)
Review
Infectious Diseases
Jing Yang et al.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2020)
Article
Mathematical & Computational Biology
Defen Peng et al.
STATISTICS IN MEDICINE
(2020)
Article
Pharmacology & Pharmacy
Andrea Giacomelli et al.
PHARMACOLOGICAL RESEARCH
(2020)
Article
Multidisciplinary Sciences
Shishi Wu et al.
Article
Mathematics, Interdisciplinary Applications
Sanjoy K. Sinha
LIFETIME DATA ANALYSIS
(2019)
Article
Health Care Sciences & Services
Francisco J. Rubio et al.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2019)
Article
Statistics & Probability
Tiago V. F. Santana et al.
JOURNAL OF STATISTICAL THEORY AND PRACTICE
(2019)
Article
Health Care Sciences & Services
Zhen Zhang et al.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2018)
Article
Mathematics, Interdisciplinary Applications
Shahedul A. Khan
LIFETIME DATA ANALYSIS
(2018)
Article
Mathematical & Computational Biology
Peter C. Austin
STATISTICS IN MEDICINE
(2012)
Article
Statistics & Probability
P. Economou et al.
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2007)
Article
Mathematical & Computational Biology
R Bender et al.
STATISTICS IN MEDICINE
(2005)
