Improving estimation in genetic models using prior information

Statistical models used to investigate research questions in behavioral genetics often require large amounts of data. This paper introduces some key concepts of Bayesian analysis and illustrates how these methods can aid model estimation when the data does not provide enough information to reliably...

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Main Author: Espen Moen Eilertsen
Format: Article
Language:English
Published: Norsk Forening for Epidemiologi 2016-07-01
Series:Norsk Epidemiologi
Online Access:https://www.ntnu.no/ojs/index.php/norepid/article/view/2017
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author Espen Moen Eilertsen
author_facet Espen Moen Eilertsen
author_sort Espen Moen Eilertsen
collection DOAJ
description Statistical models used to investigate research questions in behavioral genetics often require large amounts of data. This paper introduces some key concepts of Bayesian analysis and illustrates how these methods can aid model estimation when the data does not provide enough information to reliably answer research questions. The use of informative prior distributions is discussed as a method of incorporating information from other sources than the data at hand. The procedure is illustrated with an ACE model decomposition of the variance of antisocial personality disorder. The data originates from the Norwegian Twin Registry, and includes adult twins assessed with the Structured Interview for DSM Personality (SIDP-IV). Inclusion of prior information lead to a shift with respect to conclusions about the presence of shared environmental effects compared to a traditional analysis. Small and medium sized studies should consider use of prior information to aid estimation of population parameters.
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spelling doaj.art-25e06012b2cf4246abebb0a4f00803192022-12-22T03:15:47ZengNorsk Forening for EpidemiologiNorsk Epidemiologi0803-24912016-07-01261-210.5324/nje.v26i1-2.2017Improving estimation in genetic models using prior informationEspen Moen EilertsenStatistical models used to investigate research questions in behavioral genetics often require large amounts of data. This paper introduces some key concepts of Bayesian analysis and illustrates how these methods can aid model estimation when the data does not provide enough information to reliably answer research questions. The use of informative prior distributions is discussed as a method of incorporating information from other sources than the data at hand. The procedure is illustrated with an ACE model decomposition of the variance of antisocial personality disorder. The data originates from the Norwegian Twin Registry, and includes adult twins assessed with the Structured Interview for DSM Personality (SIDP-IV). Inclusion of prior information lead to a shift with respect to conclusions about the presence of shared environmental effects compared to a traditional analysis. Small and medium sized studies should consider use of prior information to aid estimation of population parameters.https://www.ntnu.no/ojs/index.php/norepid/article/view/2017
spellingShingle Espen Moen Eilertsen
Improving estimation in genetic models using prior information
Norsk Epidemiologi
title Improving estimation in genetic models using prior information
title_full Improving estimation in genetic models using prior information
title_fullStr Improving estimation in genetic models using prior information
title_full_unstemmed Improving estimation in genetic models using prior information
title_short Improving estimation in genetic models using prior information
title_sort improving estimation in genetic models using prior information
url https://www.ntnu.no/ojs/index.php/norepid/article/view/2017
work_keys_str_mv AT espenmoeneilertsen improvingestimationingeneticmodelsusingpriorinformation