Modelling the Survival of Western Honey Bee <i>Apis mellifera</i> and the African Stingless Bee <i>Meliponula ferruginea</i> Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

Isiaho, Patience and Salifu, Daisy and Mwalili, Samuel and Tonnang, Henri E. Z. (2024) Modelling the Survival of Western Honey Bee <i>Apis mellifera</i> and the African Stingless Bee <i>Meliponula ferruginea</i> Using Semiparametric Marginal Proportional Hazards Mixture Cure Model. Journal of Data Analysis and Information Processing, 12 (01). pp. 24-39. ISSN 2327-7211

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Abstract

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

Item Type: Article
Subjects: Open Research Librarians > Multidisciplinary
Depositing User: Unnamed user with email support@open.researchlibrarians.com
Date Deposited: 05 Feb 2024 07:01
Last Modified: 05 Feb 2024 07:01
URI: http://stm.e4journal.com/id/eprint/2467

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