Stata vs. SPSS, act 1

My colleagues here often ask me why I don't like to use SPSS*. I have a hard time explaining to them why I use Stata**, a package not widely used at this institution and not supported by our statistical support people. Fortunately for me, sociologist and short-fiction blogger Jeremy Freese concisely articulates what I've been unable to explain:

At first I worked with SPSS, which I found bewildering because it seemed designed to encourage users to do things in cumbersome and self-defeating way. Then, one bright day, I discovered Stata 5, and after like a forty-some-hour manuals-and-keyboarding-binge, all was bliss.

My experience is similar. I learned a number of neat SPSS programming tricks at ICPSR where I worked with one of the smartest people I've ever met. However, the more SPSS code that I wrote, the more frustrated I got with the packages limitation. As Jeremy writes, it forces you to do things in a cumbersome, repetitive way. SPSS doesn't do arrays well; it's loops are clunky; and the processing is slow. My mentor at ICPSR showed me how to use a powerful text-editor to eliminate some of the tedium in writing tedious code. But, I was convinced there must be more! I found SAS to be a better tool for these sorts of tasks. However, the learning curve on SAS was way too steep. I invested about the same amount of time trying to pick up SAS and Stata. The difference: at the end of these couple of days, I could use Stata to accomplish necessary tasks. As for SAS, I had to keep asking people for help.

* Leaving alone for a moment the fact that technically I'm an ethnographer and mutter my way through most regression tables.

** We also will leave aside the incredible price differential between these programs. Stata has an affordable price-point for student's or others with an academic affiliation. SAS and Stata seem to be pricing themselves to outfits with deep pockets.