A New Approach to Handle Missing Covariate Data in Twin Research
The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate data in twin research results in reduced power to detect statistical effects, as only phenotypic and covariate data of individual twins with complete data can be used. Here we present a full information... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2016 |
Reihe/Periodikum: | Schwabe , I , Boomsma , D I , de Zeeuw , E L & van den Berg , S M 2016 , ' A New Approach to Handle Missing Covariate Data in Twin Research ' , Behavior Genetics , vol. 46 , no. 4 , pp. 583-595 . https://doi.org/10.1007/s10519-015-9771-1 |
Schlagwörter: | /dk/atira/pure/keywords/cohort_studies/netherlands_twin_register_ntr_ / name=Netherlands Twin Register (NTR) / /dk/atira/pure/sustainabledevelopmentgoals/quality_education / name=SDG 4 - Quality Education |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26844715 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://research.vu.nl/en/publications/99dee519-f7d2-4243-a211-a4b393f6b59e |