First a disclaimer. I choose the title of this post to reflect how I think others view these data products. These are not, in fact, competing data products, nor are they alternatives to one another. I view these data products as complementary, each with individual strengths and weaknesses, but ultimately a powerful data analysis resource when combined. Below I briefly describe the difference between the two data products and outline the pros and cons of using each (though my ultimate recommendation is to combine the two data products for a “pros-only” data set).
Learning how to use a complex data set like the HRS can seem daunting. Fortunately, HRS provides all the information and tools necessary to get started. Below I outline 4 steps to getting started with the HRS.
On Feb. 5th, 2009 I became a registered HRS user. I was finishing my last semester in a PhD program and, as I’d spent the previous years working on a different national, longitudinal study of adult health, I felt ready to tackle this new data set with which I could pursue additional topics in aging-related research. So, I downloaded some data and started exploring. Within minutes I had questions… so, so many questions (like, what are all of these files and why are there 20-year-olds in a study of older adults!?!)… and I was stuck. In retrospect, I should have devoted much more time to studying the documentation.
Fortunately I was a grad student at the University of Michigan at the time, working in the same building as the HRS and many of its users. I was helped in my early days of using the HRS by some very friendly staff (thanks Gwen Fisher!) and faculty (thanks Philippa Clarke!). Since then I have continued to rely on the generous nature of HRS personnel and other HRS users to solve my data conundrums. I’ve also read many of the informative documents provided by the HRS to its users. I now help others who are getting started with HRS data. And you know what? They encounter the same problems I did, and have many of the same questions.
The HRS can seem formidable to new users. To be honest, I’ve been using the data for more than seven years and it still seems formidable to me at times. But this data is worth it, my friend, it’s definitely worth it. HRS data provide so many exciting opportunities for conducting studies that make significant contributions to debates, both scientific and policy, on the nature of aging in the U.S. and globally. The trick is to successfully navigate past the common user errors and data pitfalls as you journey from new user to expert user. This blog is intended to help you on your HRS journey, whether you are just getting started or have been working with the data for years.