作者: Jaclyn A. Scholl , John R. O'Leary
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摘要: SAS® users are increasingly collaborating with clinical researchers and biostatisticians who rely on R as their primary tool for statistical analyses. Having the technical flexibility to use either software when creating exploratory or publication quality graphics can be very useful in especially a team-oriented research environment. We offer some simple examples common graphs such bar graphs, histograms, scatter plots survival curves coded both R. By comparing different approaches, we demonstrate how one approach may advantageous other by needing fewer lines of code, while alternative greater there is need manipulate even smallest details graph. This paper will valuable experienced want concrete graphing tasks that accomplished simply R, hopefully not realize tools available SAS 9.2. providing methods languages authors hope readers yet “bilingual”, curious enough begin exploring non-native language, whether Finally point out many excellent print internet resources which they found own learning these equally beneficial reader well.