TITLE:
Modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model
AUTHORS:
Patience Isiaho, Daisy Salifu, Samuel Mwalili, Henri E. Z. Tonnang
KEYWORDS:
Mixture Cure Models, Clustered Survival Data, Correlation Structure, Cox-Snell Residuals, EM Algorithm, Expectation-Solution Algorithm
JOURNAL NAME:
Journal of Data Analysis and Information Processing,
Vol.12 No.1,
February
4,
2024
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.