Abstract
Introduction: Resampling technique as a way of overcoming instability in Cox Proportional hazard model is used for measuring the risk and related standard error for the infant mortality, given socio-economic and clinical covariates for mother and children at the Kigali University Teaching Hospital in Rwanda. Methods: Bootstrap and jackknife Cox proportional hazards models was applied to N=2117 newborn data collected in 2016 at the Kigali University Teaching Hospital in Rwanda. Results: The unadjusted models revealed significance of the age of female parents, information on previous abortion, gender of a newborn, number of newborns at a time, APGAR, the weight of a newborn and the circumference of the head of a newborn. Conclusion: Statistical analysis supports two major findings: 1) parents under 20 years of age indicate a relatively higher risk of infant death, and 2) abnormality in the newborn's head and weight indicates a relatively higher risk of infant mortality. Recommendations include avoidance of pregnancy until after age 20 and clinically recommended nutrition for the mother during pregnancy to decrease the risk of infant mortality.
Highlights
Resampling technique as a way of overcoming instability in Cox Proportional hazard model is used for measuring the risk and related standard error for the infant mortality, given socio-economic and clinical covariates for mother and children at the Kigali University Teaching Hospital in Rwanda
The standard errors in Jackknife Cox Proportional Hazards Model (JCPHM) and Cox Proportional Hazards Model (CPHM) are not critically different for all covariates except for the upper levels of covariates weight, head and height where the standard error in JCPHM is more than 40 times that of CPHM
The critical difference in standard error is observed in Bootstrap Cox Proportional Hazards Model (BCPHM) for the upper levels of covariates weight, head and height, for all levels of covariate childbirth and for the covariate number where the standard error is relatively higher in BCPHM
Summary
Resampling technique as a way of overcoming instability in Cox Proportional hazard model is used for measuring the risk and related standard error for the infant mortality, given socio-economic and clinical covariates for mother and children at the Kigali University Teaching Hospital in Rwanda. The resampling in Cox proportional hazards model consists of conducting the Cox Proportional Hazards Model (CPHM) on a given number of samples obtained after applying a relevant technique of resampling. The interest in this study will be on Bootstrap Cox Proportional Hazards Model (BCPHM) and Jackknife Cox Proportional Hazards Model (JCPHM). Hamada [3] points out the aim of using the resampling technique in CPHM. The resampling allows the assessment of the stability of the CPHM. Model adequacy may be satisfied by selecting variableV on which the model is stable rather than testing the proportionality of variables
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