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Twin Concordance for a Binary Trait. I. Statistical Models Illustrated With Data on Drinking Status

Published online by Cambridge University Press:  01 August 2014

Murray C. Hannah
Affiliation:
Department of Medicine, University of Melbourne, Royal Melbourne Hospital, Victoria, Australia
John L. Hopper
Affiliation:
Department of Medicine, University of Melbourne, Royal Melbourne Hospital, Victoria, Australia
John D. Mathews*
Affiliation:
Department of Medicine, University of Melbourne, Royal Melbourne Hospital, Victoria, Australia
*
University of Melbourne, Department of Medicine, Royal Melbourne Hospital, Victoria 3050, Australia

Abstract

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A flexible method based on maximum likelihood theory is introduced for the analysis of binary response data in twins. The method allows for explanatory variables such as age and sex, is free of the untestable distributional assumption of bivariate normality of liability, and makes more efficient use of the data available. The method is illustrated with preliminary data on drinking status in adult twins. Although there is some bias in the ascertainment of male dizygous twins, the results suggest that monozygous twins are more concordant than dizygous twins for drinking status.

Type
Research Article
Copyright
Copyright © The International Society for Twin Studies 1983

References

REFERENCES

1.Baker, RJ, Nelder, JA (1978): “The GLIM System. Release 3.” Oxford: Numerical Algorithms Group.Google Scholar
2.Box, GEP, Cox, DR (1964): An analysis of transformations. J Royal Stat Soc, Series B. 26:211252.Google Scholar
3.Cox, DR (1970): “Analysis of Binary Data.” London: Methuen, pp 14–29, 61–72, 87100.Google Scholar
4.Cox, DR, Hinkley, DV (1974): “Theoretical Statistics.” London: Chapman and Hall, pp 279363.CrossRefGoogle Scholar
5.Kaplan, B, Elston, RC (1972): A subroutine package for maximum likelihood estimation (MAXLIK). Chapel Hill: University of North Carolina, Institute of Statistics Mimeo Series No. 823.Google Scholar
6.Kaprio, J, Sarna, S, Koskenvico, M (1981): Multivariate logit analysis of concordance ratios for qualitative traits in twin studies. Acta Genet Med Gemellol 30:267274.Google Scholar
7.Karlin, S (1979): Comments on statistical methodology in medical genetics. In Sing, CF, Skolnick, M (eds): “Genetic Analysis of Common Diseases: Applications to Predictive Factors in Coronary Disease.” New York: Alan R. Liss, pp 497520.Google Scholar
8.Kendall, M, Stuart, A (1977): “The Advanced Theory of Statistics.” Vol. 1. London: Griffin, pp 243262.Google Scholar
9.Hopper, JL, Mathews, JD (1982): Extensions to multivariate normal models for pedigree analysis. Ann Hum Genet 46:373383.CrossRefGoogle ScholarPubMed
10.Landis, JR, Koch, GG (1977): A one-way components of variance model for categorical data. Biometrics 33:671679.CrossRefGoogle Scholar
11.Smith, C (1974): Concordance in twins: Methods and interpretation. Am J Hum Genet 26:454466.Google Scholar