A task I often help with is getting survey data prepped for data analysis. Typically a client has distributed a written survey via Qualtrics or SurveyMonkey, and has downloaded the survey results to Excel as an xls, xlsx, or csv.

Before importing that data into Stata, SAS, or R, [read that post here] there are a few steps you should do first. In this short tutorial post, I'll walk you through those steps. I highly recommend reading through this post in full before touching your data. Get an overview of what you'll need to do and then read through again to let the gears turn on how you'll need to clean your own data.

Feel free to post any questions in the comments! 

​Let's get started.

Do you want to model trajectories by calculating transition probabilities? You can do this in Stata with just a little extension of your longitudinal data analysis skills.

We'll be using xttrans (built in to Stata) or xttrans2 (a module you can download). 

Your data will need to be in LONG format. To reshape from wide to long, use: 

Where stub is the stubname of your variable, i is the variable that uniquely identifies observations in your data set, and j is the time variable. 

Trying to figure out how to model a categorical predictor in your regression? 

Done this code a million times but can never remember the syntax for the class statement? 

Want to generate exponentiated estimates and confidence intervals?

We'll give examples for binary, 3 levels, 4 levels, and stratified.

​Short post today on how to use the MEAN function in SAS 9.4. Let's get started.

It seems like every time I need to calculate a mean variable in SAS, I find myself looking up which CALL functions deal with missing values in this way, and which in that way. 

For example, blood pressure readings are often taken 3 times, and then we average those 3 readings together for a mean value. In some code I ran earlier this morning, I kept getting negative values in my "avg_bp" variable. What's up with that?