Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio

Utilização de modelo hierárquico Bayesiano para estudar a relação alométrica entre o peso placentário e peso ao nascer

Abstract

Objectives:

to propose the use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio, including possible confounders.

Methods:

data from 26 singleton pregnancies with gestational age at birth between 37 and 42 weeks were analyzed. The placentas were collected immediately after delivery and stored under refrigeration until the time of analysis, which occurred within up to 12 hours. Maternal data were collected from medical records. A Bayesian hierarchical model was proposed and Markov chain Monte Carlo simulation methods were used to obtain samples from distribution a posteriori.

Results:

the model developed showed a reasonable fit, even allowing for the incorporation of variables and a priori information on the parameters used.

Conclusions:

new variables can be added to the modelfrom the available code, allowing many possibilities for data analysis and indicating the potential for use in research on the subject.

Key words:
Birth weight; Placenta; Data interpretation; statistics