Behavior Genetics

, Volume 14, Issue 4, pp 325–343 | Cite as

Adjustment of twin data for the effects of age and sex

  • Matt McGue
  • Thomas J. BouchardJr.
Article

Abstract

For most psychological, physiological, and medical variables there are substantial age and sex effects. In assessing twin similarity for these variables, one can either fail to adjust for the effects of age and sex, adjust for these effects using normative data, or use information in the twin sample to define an age-sex adjustment. It is shown that failing to correct for age and sex effects when they exist will result in overestimation of the twin intraclass correlation. Using normative data to define an age-sex adjustment will also result in overestimation of the twin intraclass correlation, although the magnitude of this overestimation is slight for moderate-sized normative samples and virtually nonexistent for large normative samples. Using a twin-based age-sex adjustment will lead to an underestimation of the twin intraclass correlation, but this underestimation can be corrected for through proper specification of the degrees of freedom for the between-pairs mean square. Illustration of the effects of age-sex adjustment are provided as well as the results of a computer simulation comparison of the various approaches. It is concluded that, even with moderately sized samples, the effects of age and sex can best be adjusted for through a twin-based approach.

Key Words

twin data analysis intraclass correlation age-sex effects heritability 

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References

  1. Birron, J. E., and Schaie, K. W. (1977).Handbook of the Psychology of Aging, Van Norstrand Reinhold, New York.Google Scholar
  2. Bouchard, T. J., Heston, L., Eckert, E., Keyes, M., and Resnick, S. (1981). In Gedda, L., Parisi, P., and Nance, W. E. (eds.),Twin Research 3: Intelligence Personality, Development, Alan R. Liss, New York.Google Scholar
  3. Finch, C. E., and Hayflick, L. (1977).Handbook of the Biology of Aging, Van Norstrand Reinhold, New York.Google Scholar
  4. Fisher, R. A. (1921). On the probable error of a coefficient of correlation deduced from a small sample.Metron 1:1–32.Google Scholar
  5. Garai, J. E., and Scheinfeld, A. (1968). Sex differences in mental and behavioral traits.Genet. Psychol. Monogr. 77:169–299.Google Scholar
  6. Haggard, E. A. (1958).Intraclass Correlation and the Analysis of Variance, Dryden, New York.Google Scholar
  7. Hyde, J. S. (1981). How large are cognitive gender differences: A meta analysis using ω2 and d.Am. Psychol. 36:892–901.Google Scholar
  8. IMSL Inc. (1979).IMSL Library Reference Manual Edition 7, IMSL Inc., Houston, Tex.Google Scholar
  9. Maccoby, E., and Jacklin, C. N. (1974).The Psychology of Sex Differences, Stanford University Press, Stanford, Calif.Google Scholar
  10. Wilson, J. R., and Vandenberg, S. G. (1978). Sex differences in cognition: Evidence from the Hawaii Family Study. In McGill, T. E., Dewsbury, D. A., and Sachs, B. D. (eds.),Sex and Behavior, Plenum Press, New York, pp. 317–355.Google Scholar
  11. Wilson, J. R., DeFries, J. C., McClearn, G. E., Vandenberg, S. G., Johnson, R. C., Mi, M. P., and Rashad, M. N. (1975). Cognitive abilities: Use of family data as a control to assess sex and age differences in two ethnic groups.Int. J. Aging Hum. Devel. 6:261–276.Google Scholar

Copyright information

© Plenum Publishing Corporation 1984

Authors and Affiliations

  • Matt McGue
    • 1
  • Thomas J. BouchardJr.
    • 2
  1. 1.Division of BiostatisticsWashington University School of MedicineSt. Louis
  2. 2.Department of PsychologyUniversity of MinnesotaMinneapolis

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