Zero-inflated generalized extreme value regression model for binary response data and application in health study

Diop, Aba; Dème, El Hadji; Diop, Aliou

doi:10.1080/00949655.2022.2089673

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…Previous research has also explored the application of non-standard link functions on zero-inflated models. Diop et al [ 15 ] proposed a modification to ZIP that involved the use of the quantile function of the Generalized Extreme Value (GEV) distribution as a link function for zero-inflated data with rare events. The approach was proposed to curb the drawbacks of logistic regression when dealing with imbalanced data, where the probability of a rare event is underestimated.…”

Section: Introductionmentioning

confidence: 99%

Improving performance of hurdle models using rare-event weighted logistic regression: an application to maternal mortality data

Awuor Okello,

Otieno Omondi,

Odhiambo

2023

R. Soc. open sci.

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In this paper, performance of hurdle models in rare events data is improved by modifying their binary component. The rare-event weighted logistic regression model is adopted in place of logistic regression to deal with class imbalance due to rare events. Poisson Hurdle Rare Event Weighted Logistic Regression (REWLR) and Negative Binomial Hurdle (NBH) REWLR are developed as two-part models which use the REWLR model to estimate the probability of a positive count and a Poisson or NB zero-truncated count model to estimate non-zero counts. This research aimed to develop and assess the performance of the Poisson and Negative Binomial (NB) Hurdle Rare Event Weighted Logistic Regression (REWLR) models, applied to simulated data with various degrees of zero inflation and to Nairobi county’s maternal mortality data. The study data on maternal mortality were pulled from JPHES. The data contain the number of maternal deaths, which is the outcome variable, and other obstetric and demographic factors recorded in MNCH facilities in Nairobi between October 2021 and January 2022. The models were also fit and evaluated based on simulated data with varying degrees of zero inflation. The obtained results are numerically validated and then discussed from both the mathematical and the maternal mortality perspective. Numerical simulations are also presented to give a more complete representation of the model dynamics. Results obtained suggest that NB Hurdle REWLR is the best performing model for zero inflated count data due to rare events.

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Section: Introductionmentioning

confidence: 99%

Improving performance of hurdle models using rare-event weighted logistic regression: an application to maternal mortality data

Awuor Okello,

Otieno Omondi,

Odhiambo

2023

R. Soc. open sci.

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A Bimodal Exponential Regression Model for Analyzing Dengue Fever Case Rates in the Federal District of Brazil

da Costa,

Lima,

Cordeiro

2024

Mathematics

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Dengue fever remains a significant epidemiological challenge globally, particularly in Brazil, where recurring outbreaks strain healthcare systems. Traditional statistical models often struggle to accurately capture the complexities of dengue case distributions, especially when data exhibit bimodal patterns. This study introduces a novel bimodal regression model based on the log-generalized odd log-logistic exponential distribution, offering enhanced flexibility and precision for analyzing epidemiological data. By effectively addressing multimodal distributions, the proposed model overcomes the limitations of unimodal models, making it well suited for public health applications. Through regression analysis of dengue case data from the Federal District of Brazil during the epidemiological weeks of 2022, the model demonstrates its capacity to improve the fit of the disease rate. The model’s parameters are estimated using maximum likelihood estimation, and Monte Carlo simulations validate their accuracy. Additionally, local influence measures and residual analysis ensure the proposed model’s goodness-of-fit. While this innovative regression model offers substantial advantages, its effectiveness depends on the availability of high-quality data, and further validation is necessary to confirm its applicability across diverse diseases and regions with varying epidemiological characteristics.

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Zero-inflated generalized extreme value regression model for binary response data and application in health study

Cited by 2 publications

References 27 publications

Improving performance of hurdle models using rare-event weighted logistic regression: an application to maternal mortality data

Improving performance of hurdle models using rare-event weighted logistic regression: an application to maternal mortality data

A Bimodal Exponential Regression Model for Analyzing Dengue Fever Case Rates in the Federal District of Brazil

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