Adjustment of twin data for the effects of age and sex

TLDR: 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.

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.