Literature DB >> 15193174

Implications of absence of measurement invariance for detecting sex limitation and genotype by environment interaction.

Gitta H Lubke1, Conor V Dolan, Michael C Neale.   

Abstract

Using univariate sum scores in genetic studies of twin data is common practice. This practice precludes an investigation of the measurement model relating the individual items to an underlying factor. Absence of measurement invariance across a grouping variable such as gender or environmental exposure refers to group differences with respect to the measurement model. It is shown that a decomposition of a sum score into genetic and environmental variance components leads to path coefficients of the additive genetic factor that are biased differentially across groups if individual items are non-invariant. The arising group differences in path coefficients are identical to what is known as "scalar sex limitation" when gender is the grouping variable, or as "gene by environment interaction" when environmental exposure is the grouping variable. In both cases the interpretation would be in terms of a group-specific effect size of the genetic factor. This interpretation may be incorrect if individual items are non-invariant.

Mesh:

Year:  2004        PMID: 15193174     DOI: 10.1375/136905204774200578

Source DB:  PubMed          Journal:  Twin Res        ISSN: 1369-0523


  14 in total

Review 1.  Multivariate genetic analysis of sex limitation and G x E interaction.

Authors:  Michael C Neale; Espen Røysamb; Kristen Jacobson
Journal:  Twin Res Hum Genet       Date:  2006-08       Impact factor: 1.587

2.  Group differences in the heritability of items and test scores.

Authors:  Jelte M Wicherts; Wendy Johnson
Journal:  Proc Biol Sci       Date:  2009-04-29       Impact factor: 5.349

3.  Sum Scores in Twin Growth Curve Models: Practicality Versus Bias.

Authors:  Justin M Luningham; Daniel B McArtor; Meike Bartels; Dorret I Boomsma; Gitta H Lubke
Journal:  Behav Genet       Date:  2017-08-05       Impact factor: 2.805

4.  Heritability across the distribution: an application of quantile regression.

Authors:  Jessica A R Logan; Stephen A Petrill; Sara A Hart; Christopher Schatschneider; Lee A Thompson; Kirby Deater-Deckard; Laura S DeThorne; Christopher Bartlett
Journal:  Behav Genet       Date:  2011-08-30       Impact factor: 2.805

5.  Genetic and environmental influences on the junior temperament and character inventory in a preadolescent twin sample.

Authors:  Joshua D Isen; Laura A Baker; Adrian Raine; Serena Bezdjian
Journal:  Behav Genet       Date:  2008-11-29       Impact factor: 2.805

6.  An integrated phenomic approach to multivariate allelic association.

Authors:  Sarah Elizabeth Medland; Michael Churton Neale
Journal:  Eur J Hum Genet       Date:  2009-08-26       Impact factor: 4.246

7.  Variance decomposition using an IRT measurement model.

Authors:  Stéphanie M van den Berg; Cees A W Glas; Dorret I Boomsma
Journal:  Behav Genet       Date:  2007-05-30       Impact factor: 2.805

8.  Assessment of generalized anxiety disorder diagnostic criteria in the National Comorbidity Survey and Virginia Adult Twin Study of Psychiatric and Substance Use Disorders.

Authors:  Thomas S Kubarych; Steven H Aggen; John M Hettema; Kenneth S Kendler; Michael C Neale
Journal:  Psychol Assess       Date:  2008-09

9.  Psychiatric Resilience and Alcohol Resistance: A Twin Study of Genetic Correlation and Sex Differences.

Authors:  Christina M Sheerin; Daniel Bustamante; Kaitlin E Bountress; Shannon E Cusack; Steven H Aggen; Kenneth S Kendler; Ananda B Amstadter
Journal:  Behav Genet       Date:  2021-04-24       Impact factor: 2.805

10.  Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies.

Authors:  Sophie van der Sluis; Matthijs Verhage; Danielle Posthuma; Conor V Dolan
Journal:  PLoS One       Date:  2010-11-10       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.