Side-by-side statistical analyses in R, SAS, SPSS
Have you ever needed to do a type of statistical analysis you haven’t done in a while (or perhaps ever), and weren’t quite sure how to get started in R? In this situation, my usual starting point is to find an example of a similar analysis someone else has done, and then adapt it to my own data set (with regular reference to the help pages).
Each page includes one or more examples of the type of analysis in question. (For example: “We wish to study the influence of age, gender and exercise on whether or not someone has a heart attack. Again, we have a binary response variable, whether or not a heart attack occurs.”) Also provided is all the code in R to download the data and conduct the analysis…
Have you ever needed to do a type of statistical analysis you haven’t done in a while (or perhaps ever), and weren’t quite sure how to get started in R? In this situation, my usual starting point is to find an example of a similar analysis someone else has done, and then adapt it to my own data set (with regular reference to the help pages).
Each page includes one or more examples of the type of analysis in question. (For example: “We wish to study the influence of age, gender and exercise on whether or not someone has a heart attack. Again, we have a binary response variable, whether or not a heart attack occurs.”) Also provided is all the code in R to download the data and conduct the analysis.
Better yet, if you’re already familiar with how to do the analysis in another system such as SAS or SPSS, the code for many of the same examples is also available for those systems. If you’re a SAS user (for example) looking at the code for Probit Regression side-by-side in SAS and then in R is a great way of using your SAS knowledge to learn R.
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