title: How can I "think OOP" when using R?
body: <p>I am a statistics graduate student who works a lot with R.  I am familiar with OOP in other programming contexts.  I even see its use in various statistical packages that define new classes for storing data.  </p>
  
  <p>At this stage in my graduate career, I am usually coding some algorithm for some class assignment--something that takes in raw data and gives some kind of output.  I would like to make it easier to reuse code, and establish good coding habits, especially before I move on to more involved research.  Please offer some advice on how to "think OOP" when doing statistical programming in R.</p>