title: Analysis of twin data using SAS.
abstract: 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.
authors.affiliation: Department of Biostatistics, the University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.
authors.forename: Rui
authors.initials: R
authors.lastname: Feng
authors.forename: Gongfu
authors.initials: G
authors.lastname: Zhou
authors.forename: Meizhuo
authors.initials: M
authors.lastname: Zhang
authors.forename: Heping
authors.initials: H
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015340:Epidemiologic Research Design; D020022:Genetic Predisposition to Disease / Q000453:epidemiology* / Q000235:genetics*; D015233:Models, Statistical; D018570:Risk Assessment / Q000379:methods; D012984:Software; D018433:Twin Studies as Topic; D014427:Twins