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

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...

Full description

Bibliographic Details
Main Authors: Fidel Ernesto Castro Morales, Anna Cecília Queiroz de Medeiros
Format: Article
Language:English
Published: Instituto Materno Infantil de Pernambuco 2016-03-01
Series:Revista Brasileira de Saúde Materno Infantil
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-38292016000100067&lng=en&tlng=en
id doaj-47ec18524904489f86218735f273ec54
record_format Article
spelling doaj-47ec18524904489f86218735f273ec542020-11-25T00:04:55ZengInstituto Materno Infantil de PernambucoRevista Brasileira de Saúde Materno Infantil1806-93042016-03-01161677010.1590/1806-93042016000100008S1519-38292016000100067Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratioFidel Ernesto Castro MoralesAnna Cecília Queiroz de MedeirosAbstract 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.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-38292016000100067&lng=en&tlng=enPeso ao nascerPlacentaAnálise estatística de dados
collection DOAJ
language English
format Article
sources DOAJ
author Fidel Ernesto Castro Morales
Anna Cecília Queiroz de Medeiros
spellingShingle Fidel Ernesto Castro Morales
Anna Cecília Queiroz de Medeiros
Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
Revista Brasileira de Saúde Materno Infantil
Peso ao nascer
Placenta
Análise estatística de dados
author_facet Fidel Ernesto Castro Morales
Anna Cecília Queiroz de Medeiros
author_sort Fidel Ernesto Castro Morales
title Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
title_short Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
title_full Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
title_fullStr Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
title_full_unstemmed Use of a Bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
title_sort use of a bayesian hierarchical model to study the allometric scaling of the fetoplacental weight ratio
publisher Instituto Materno Infantil de Pernambuco
series Revista Brasileira de Saúde Materno Infantil
issn 1806-9304
publishDate 2016-03-01
description 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.
topic Peso ao nascer
Placenta
Análise estatística de dados
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1519-38292016000100067&lng=en&tlng=en
work_keys_str_mv AT fidelernestocastromorales useofabayesianhierarchicalmodeltostudytheallometricscalingofthefetoplacentalweightratio
AT annaceciliaqueirozdemedeiros useofabayesianhierarchicalmodeltostudytheallometricscalingofthefetoplacentalweightratio
_version_ 1725427265276215296