Research Papers:
3.
Byron C. Wallace, Issa J. Dahabreh, Thomas A. Trikalinos, Joseph Lau, Paul Trow, Christopher H. Schmid
Abstract: Since R was first launched, it has managed to gain the support of an ever-increasing percentage of academic and professional statisticians. However, the spread of its use among novice and occasional users of statistics have not progressed at the same pace, which can be attributed partially to the lack of a graphical user interface (GUI). Nevertheless, this situation has changed in the last years and there is currently several projects that have added GUIs to R. This article discusses briefly the history of GUIs for data analysis and then introduces the papers submitted to an special issue of the Journal of Statistical Software on GUIs for R.
4.
http://www.r-bloggers.com/a-big-list-of-the-things-r-can-do/
1.
Complex Survey Data Analysis: A Comparison of SAS, SPSS and STATA (Asian Journal of Mathematics & Statistics)
Complex Survey Data Analysis: A Comparison of SAS, SPSS and STATA (Asian Journal of Mathematics & Statistics)
G.M. Oyeyemi, A.A. Adewara and R.A. Adeyemi
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Abstract: We compared three statistical packages (SAS, SPSS and STATA) in analyzing complex survey data in the context of multiple regression analysis using concrete examples from two national healthcare database (MEPS and NDHS). The three packages are found to be efficient and flexible in analyzing complex survey data, but SAS in some cases seems to over estimate the variances of the sample statistics. Adjustment for stratification (incorporating stratification) is very important in complex survey analysis, especially if the stratification variable is endogenous.
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2.
The American Statistician: Statistical Computing Software Reviews (Jstor.org)
The American Statistician: Statistical Computing Software Reviews (Jstor.org)
Stable URL : http://www.jstor.org/stable/30037298
Closing the Gap between Methodologists and End-Users: R as a Computational Back-End:
Byron C. Wallace, Issa J. Dahabreh, Thomas A. Trikalinos, Joseph Lau, Paul Trow, Christopher H. Schmid
(Journal of statistical software)
Abstract: Since R was first launched, it has managed to gain the support of an ever-increasing percentage of academic and professional statisticians. However, the spread of its use among novice and occasional users of statistics have not progressed at the same pace, which can be attributed partially to the lack of a graphical user interface (GUI). Nevertheless, this situation has changed in the last years and there is currently several projects that have added GUIs to R. This article discusses briefly the history of GUIs for data analysis and then introduces the papers submitted to an special issue of the Journal of Statistical Software on GUIs for R.
Link:
4.
A big list of the things R can do:
http://www.r-bloggers.com/a-big-list-of-the-things-r-can-do/
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