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Cited by 273

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Determining zygosity in the Vietnam Era Twin Registry: an approach using questionnaires

Eisen, S., Neuman, R., Goldberg, J., Rice, J., True, W.·1989·Clinical Genetics

Abstract

The Vietnam Era Twin Registry (VETR) is a registry of 7375 American male veteran twin pairs born between 1939 and 1955 who served in the armed forces of the United States between 1964 and 1975. Optimal use of registry data requires the determination of zygosity. Two approaches are available: analysis of blood genetic marker systems and responses of twins to questions about sibling similarity. Zygosity for the VETR was determined using the questionnaire technique supplemented with blood group typing data abstracted from military records. After comparing four alternative zygosity assignment methods, a logistic regression technique which uses discriminating variables based on race was selected. The approach is similar to that described by Magnus et al. (1983) in their study of Norwegian twins, suggesting that questionnaire responses are independent of nationality and reinforcing the reliability of the questionnaire method for zygosity ascertainment.

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Metadata

Authors
Eisen, S., Neuman, R., Goldberg, J., Rice, J., & True, W.
Venue
Clinical Genetics
Publisher
Wiley
Published
1989-06
Volume
35
Issue
6
Pages
423-432
ISSN
  • 0009-9163 (ISSN-L)
  • 1399-0004
OpenAlex
W2129497655
Cited by
273
References
0
FWCI
2.75
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Determining zygosity in the Vietnam Era Twin Registry: an approach using questionnaires. https://app.cochat.ai/papers/10.1111/j.1399-0004.1989.tb02967.x
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Eisen, S., Neuman, R., Goldberg, J., Rice, J., & True, W. (1989). Determining zygosity in the Vietnam Era Twin Registry: an approach using questionnaires. Clinical Genetics. https://doi.org/10.1111/j.1399-0004.1989.tb02967.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.