Multivariate frailty models using survey weights with applications to twins infant mortality in Ethiopia

Kifle, Yehenew G.; Chen, Ding‐Geng; Haileyesus, Mesfin T.

doi:10.4310/22-sii738

Cited by 1 publication

(1 citation statement)

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“…In this context, it is important to note that higher frailty values for children imply greater frailty, and consequently, an expectation of a shorter time to the event of interest compared to individuals with equivalent measured covariates [20]. When employing shared frailty models, larger frailty values (z i > 1) indicate that the event is more likely to occur earlier, in contrast to clusters with smaller frailty values (z i < 1) [21].…”

Section: Shared Frailty Modelmentioning

confidence: 99%

A Shared Frailty Model for Left-Truncated and Right-Censored Under-Five Child Mortality Data in South Africa

Mulaudzi,

Kifle,

Braekers

2023

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Many African nations continue to grapple with persistently high under-five child mortality rates, particularly those situated in the Sub-Saharan region, including South Africa. A multitude of socio-economic factors are identified as key contributors to the elevated under-five child mortality in numerous African nations. This research endeavors to investigate various factors believed to be associated with child mortality by employing advanced statistical models. This study utilizes child-level survival data from South Africa, characterized by left truncation and right censoring, to fit a Cox proportional hazards model under the assumption of working independence. Additionally, a shared frailty model is applied, clustering children based on their mothers. Comparative analysis is performed between the results obtained from the shared frailty model and the Cox proportional hazards model under the assumption of working independence. Within the scope of this analysis, several factors stand out as significant contributors to under-five child mortality in the study area, including gender, birth province, birth year, birth order, and twin status. Notably, the shared frailty model demonstrates superior performance in modeling the dataset, as evidenced by a lower likelihood cross-validation score compared to the Cox proportional hazards model assuming independence. This improvement can be attributed to the shared frailty model’s ability to account for heterogeneity among mothers and the inherent association between siblings born to the same mother, ultimately enhancing the quality of the study’s conclusions.

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Section: Shared Frailty Modelmentioning

confidence: 99%