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Analysis of Twin Data Using SAS
Author(s) -
Feng Rui,
Zhou Gongfu,
Zhang Meizhuo,
Zhang Heping
Publication year - 2009
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2008.01098.x
Subject(s) - computer science , software , inheritance (genetic algorithm) , task (project management) , statistical analysis , statistical hypothesis testing , data mining , statistical software , data science , statistics , programming language , mathematics , systems engineering , biochemistry , chemistry , engineering , gene
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.