Behavior Genetics

, Volume 43, Issue 5, pp 415–426 | Cite as

Heritability and the Equal Environments Assumption: Evidence from Multiple Samples of Misclassified Twins

  • Dalton ConleyEmail author
  • Emily Rauscher
  • Christopher Dawes
  • Patrik K. E. Magnusson
  • Mark L. Siegal
Original Research


Classically derived estimates of heritability from twin models have been plagued by the possibility of genetic-environmental covariance. Survey questions that attempt to measure directly the extent to which more genetically similar kin (such as monozygotic twins) also share more similar environmental conditions represent poor attempts to gauge a complex underlying phenomenon of GE-covariance. The present study exploits a natural experiment to address this issue: Self-misperception of twin zygosity in the National Longitudinal Survey of Adolescent Health (Add Health). Such twins were reared under one “environmental regime of similarity” while genetically belonging to another group, reversing the typical GE-covariance and allowing bounded estimates of heritability for a range of outcomes. In addition, we examine twins who were initially misclassified by survey assignment—a stricter standard—in three datasets: Add Health, the Minnesota Twin Family Study and the Child and Adolescent Twin Study in Sweden. Results are similar across approaches and datasets and largely support the validity of the equal environments assumption.


Equal environments Twin misclassification Heritability ACE model 



This research uses data from Add Health, a Program Project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by Grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website ( No direct support was received from Grant P01-HD31921 for this analysis. This research was funded by the National Science Foundation’s Alan T. Waterman Award, SES-0540543.

Supplementary material

10519_2013_9602_MOESM1_ESM.docx (22 kb)
Supplementary material 1 (DOCX 23 kb)


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Dalton Conley
    • 1
    Email author
  • Emily Rauscher
    • 2
  • Christopher Dawes
    • 3
  • Patrik K. E. Magnusson
    • 4
  • Mark L. Siegal
    • 5
  1. 1.Department of SociologyNew York University & NBERNew YorkUSA
  2. 2.Department of SociologyUniversity of KansasLawrenceUSA
  3. 3.Wilf Family Department of PoliticsNew York UniversityNew YorkUSA
  4. 4.Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
  5. 5.Department of Biology, Center for Genomics and Systems BiologyNew York UniversityNew YorkUSA

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