Monday, January 31, 2011

QMD - A framework for prioritizing research ideas

This from a recent exchange with a research assistant. He's trying to decide what to do for his undergraduate honors thesis, and I was trying to give him some sage advice. Here's the practical framework I use when deciding what research ideas to pursue:

Every research paper is a combination of three main parts: 1) a question, 2) a methodology, and 3) data. For instance, the Druckman paper [from this week's reading] asks 1) when elite framing can influence opinion using 2) an experiment where 3) college students read and discuss news articles. ...

(By the way, "data" includes any kinds of facts you'd use to build your argument, not just numbers. Surveys, content analysis, government statistics, experimental results, interviews, historical case studies, etc. are all data -- they're just analyzed differently.)

The combination of QMD that you choose largely determines how hard it will be to carry out the project, the kinds of conclusions you will be able to draw, and the threats to validity that critics can use against you. Choosing the QMD for a research project is like choosing a major in college -- in a lot of ways, all the later decisions are just details.

When you choose which Q, M, and D to use, you can either come up with something completely new, or borrow ideas from past studies. It is much, much harder to come up with new questions, methods and data than it is to borrow from past research. As a strong rule of thumb, you only want one of your three parts to be new. So if you're asking a new question, use familiar methods and easy-to-find data. (This isn't plagiarism because you're completely up front about the idea that you're building on previous work.)

Probably the easiest kind of study to pull off is a replication study, using new data with old methods and questions. For example, to deal with one of the threats to validity in Druckman et. al's study, you might do the same experiment with a representative sample of people, instead of just college students. Same question, same method, different data. This would still take work, but there aren't a lot of unknowns in the process, and anyone who believes Druckman and Nelson will probably believe your results as well. Replication studies are good for boosting ("Not only are Druckman and Nelson right about framing effects for college students -- they're right about all American adults as well!") or cutting back ("Druckman and Nelson's findings only apply to people under 30. Everyone else is much less susceptible to elite framing.") the scope of previous findings.

The next hardest is applying a new method to an old question. For example, you might ask when elite framing influences public opinion using a series of carefully timed surveys asking the same questions that Druckman et al used. Similar question, different method, similar data. This is a little harder, because you'd have to use different skills, build a new kind of argument, and deal with new threats to validity. On the plus side, different methods have different threats to validity, so if you use a new method, you can probably address some of the threats to validity that previous studies couldn't. For example, timed surveys could deal with the "recency effects" that Druckman can't do much about.

Introducing new questions is the hardest of all, for at least three reasons. First, you have to convince people that your question is worth asking. This is harder than it sounds. In my experience, people like to think they already understand the world pretty well, so they will resist the notion that you've found a blind spot in their worldview. Second, you have to be able to convince people that you're the first one to ask the question. Third, you have to build an entirely new line of evidence to defend your reasoning. With a one-semester deadline, I'd advise against trying to introduce a new question, just because it's so hard to do.

Anyway, that might be more than you want to know, but it's the way I decide what research projects to take on. QMD is my framework for figuring out what topics are in the overlap of "interesting" and "doable."


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