Abstract

As methodologists have increasingly noted, the role of psychometrics in operationalizing a construct is often overlooked when evaluating research claims (Borsboom 2006). In a related vein, others have noted that psychological research appears to move away from assessment and interpretation of a single a priori statistical model to a more nuanced comparison of models which assess the trade-off between a model’s parsimony and complexity in explaining behavior (e.g., Rodgers 2010). The genetic factor model is one such statistical model often used to estimate the relative contributions of genetic and environmental components of observed behavior in genetically informative designs (Heath, Neale, Hewitt, Eaves, & Fulker 1989; Martin & Eaves 1977; Neale & Cardon 1992). Mathematically, the genetic factor model decomposes observed phenotypic variability into additive genetic (A), common (C), and unique (E) environmental components and is, for that reason, often referred to as the ACE model.

Original languageEnglish
Title of host publicationDependent Data in Social Sciences Research
Subtitle of host publicationForms, Issues, and Methods of Analysis
EditorsWolfgang Wiedermann, Alexander von Eye, Mark Stemmler
PublisherSpringer New York LLC
Pages231-259
Number of pages29
ISBN (Print)9783319205847
DOIs
StatePublished - 2015
EventInternational Conference on Dependent Data in Social Sciences Research Forms, Issues, and Methods of Analysis, 2013 - Erlangen-Nuremberg, Germany
Duration: Dec 6 2013Dec 7 2013

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume145
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

ConferenceInternational Conference on Dependent Data in Social Sciences Research Forms, Issues, and Methods of Analysis, 2013
Country/TerritoryGermany
CityErlangen-Nuremberg
Period12/6/1312/7/13

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