The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Analytic approaches to twin data using structural equation models
Abstract
The classical twin study is the most popular design in behavioural genetics. It has strong roots in biometrical genetic theory, which allows predictions to be made about the correlations between observed traits of identical and fraternal twins in terms of underlying genetic and environmental components. One can infer the relative importance of these 'latent' factors (model parameters) by structural equation modelling (SEM) of observed covariances of both twin types. SEM programs estimate model parameters by minimising a goodness-of-fit function between observed and predicted covariance matrices, usually by the maximum-likelihood criterion. Likelihood ratio statistics also allow the comparison of fit of different competing models. The program Mx, specifically developed to model genetically sensitive data, is now widely used in twin analyses. The flexibility of Mx allows the modelling of multivariate data to examine the genetic and environmental relations between two or more phenotypes and the modelling to categorical traits under liability-threshold models.
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Cites
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A Twin Study of Genetic Relationships Between Psychotic Symptoms
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The use of likelihood-based confidence intervals in genetic models
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Major depression and the environment: a psychiatric genetic perspective
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Cited by
Heritability of autism spectrum disorders: a meta-analysis of twin studies
Tick, B., Bolton, P., Happé, F., Rutter, M., & Rijsdijk, F. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12499 · Cited by 1,150
Self-citationVariation in the Human Immune System Is Largely Driven by Non-Heritable Influences
Brodin, P., Jojic, V., Gao, T., Bhattacharya, S., Angel, C. J. L., Furman, D., Shen-Orr, S., Dekker, C. L., Swan, G. E., Butte, A. J., et al. (2015) · Cell · doi:10.1016/j.cell.2014.12.020 · Cited by 1,065
Cole, J. H., Poudel, R. P. K., Tsagkrasoulis, D., Caan, M. W. A., Steves, C., Spector, T. D., & Montana, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.059 · Cited by 872
Wardle, J., Carnell, S., Haworth, C. M., & Plomin, R. (2008) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/87.2.398 · Cited by 770
Variability in the Heritability of Body Mass Index: A Systematic Review and Meta-Regression
Elks, C. E., den Hoed, M., Zhao, J. H., Sharp, S. J., Wareham, N. J., Loos, R. J. F., & Ong, K. K. (2012) · Frontiers in Endocrinology · doi:10.3389/fendo.2012.00029 · Cited by 694
Metadata
- Authors
- Rijsdijk, F. V.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-01-01
- Volume
- 3
- Issue
- 2
- Pages
- 119-133
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2119947818
- Cited by
- 761
- References
- 8
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- closed
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