Literature DB >> 18647295

Analysis of twin data using SAS.

Rui Feng1, Gongfu Zhou, Meizhuo Zhang, Heping Zhang.   

Abstract

SUMMARY: Twin studies are essential for assessing disease inheritance. Data generated from twin studies are traditionally analyzed using specialized computational programs. For many researchers, especially those who are new to twin studies, understanding and using those specialized computational programs can be a daunting task. Given that SAS (Statistical Analysis Software) is the most popular software for statistical analysis, we suggest that the use of SAS procedures for twin data may be a helpful alternative and demonstrate that we can obtain similar results from SAS to those produced by specialized computational programs. This numerical validation is practically useful, because a natural concern with general statistical software is whether it can deal with data that are generated from special study designs such as twin studies and if it can test a particular hypothesis. We concluded through our extensive simulation that SAS procedures can be used easily as a very convenient alternative to specialized programs for twin data analysis.

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Year:  2008        PMID: 18647295      PMCID: PMC2700843          DOI: 10.1111/j.1541-0420.2008.01098.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  20 in total

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Journal:  Twin Res       Date:  2003-10

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Journal:  Behav Genet       Date:  2004-01       Impact factor: 2.805

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5.  Fitting genetic models with LISREL: hypothesis testing.

Authors:  M C Neale; A C Heath; J K Hewitt; L J Eaves; D W Fulker
Journal:  Behav Genet       Date:  1989-01       Impact factor: 2.805

6.  The estimation of genetic variance from twin data.

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9.  Tree-based risk factor analysis of preterm delivery and small-for-gestational-age birth.

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10.  Genetic and environmental influences on migraine: a twin study across six countries.

Authors:  Elles J Mulder; Caroline Van Baal; David Gaist; Mikko Kallela; Jaakko Kaprio; Dan A Svensson; Dale R Nyholt; Nicholas G Martin; Alex J MacGregor; Lynn F Cherkas; Dorret I Boomsma; Aarno Palotie
Journal:  Twin Res       Date:  2003-10
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  20 in total

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3.  The latent class twin method.

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Journal:  Biometrics       Date:  2016-01-11       Impact factor: 2.571

4.  Friends and social contexts as unshared environments: a discordant sibling analysis of obesity- and health-related behaviors in young adolescents.

Authors:  S-J Salvy; D M Feda; L H Epstein; J N Roemmich
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5.  Fast eQTL Analysis for Twin Studies.

Authors:  Zhaoyu Yin; Kai Xia; Wonil Chung; Patrick F Sullivan; Fei Zou
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6.  A flexible and robust method for assessing conditional association and conditional concordance.

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7.  FSEM: Functional Structural Equation Models for Twin Functional Data.

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8.  Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data.

Authors:  Yimei Li; John H Gilmore; Dinggang Shen; Martin Styner; Weili Lin; Hongtu Zhu
Journal:  Neuroimage       Date:  2013-01-26       Impact factor: 6.556

9.  Estimating fetal and maternal genetic contributions to premature birth from multiparous pregnancy histories of twins using MCMC and maximum-likelihood approaches.

Authors:  Timothy P York; Jerome F Strauss; Michael C Neale; Lindon J Eaves
Journal:  Twin Res Hum Genet       Date:  2009-08       Impact factor: 1.587

10.  Genetic Factors Contribute to Risk for Neonatal Respiratory Distress Syndrome among Moderately Preterm, Late Preterm, and Term Infants.

Authors:  Carol L Shen; Qunyuan Zhang; Julia Meyer Hudson; F Sessions Cole; Jennifer A Wambach
Journal:  J Pediatr       Date:  2016-02-28       Impact factor: 4.406

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