diary of a doctoral student

# Research directions, first cut

I talked about my research interests at last night’s department meeting. Made me realize how little I know about what I want to study. Anyway, first step is to finish bulk of coursework and pass comps. In parallel though I’d like to figure out what to do for my dissertation. Right now I’m leaning towards comparing fully Bayesian hierarchical linear models to MLE with Empirical Bayesian.

Here’s the preso I gave.

diary of a doctoral student

# Six tools for research in educational statistics

In this months’ Journal of Educational and Behavioral Statistics, Howard Wainer* identifies six necessary tools that researchers in educational and behavior statistics should master:

• Bayesian methods. “Bayesian methods allow us to do easily what would be hard otherwise.” Sounds like I am on the right track.
• Causal inference. It’s not enough to chant “correlation is not causation.” You need to read and understand Rubin.
• Missing data. That’s not exactly a tool, is it? It’s a problem that afflicts all researchers working with educational and behavioral data. Wainer says, “Dealing with missing data is, quite simply, the most important practical problem facing researchers.”
• Picturing data. “A graph of data is the best way to find something that you were not looking for.” Resources: Tufte, Flowing Data.
• Writing clear prose. I think it’s funny he should bring this up, because to make this list more clear, he should have made each bullet point parallel (e.g., “Use Bayesian methods,” “Understand causal inference,” “Handle missing data,” “Explore data visually,” “Write clear prose.”) In other words, I agree with him on the importance of writing clear prose.
• A deep understanding of Type I (false negative) and Type II (false positive) errors. Specifically, statistical researchers need to pay as much attention to Type II errors as to Type I.

* Wainer, H. (2010). 14 Conversations about three things. Journal of Educational and Behavioral Statistics 35(1).

diary of a doctoral student

# Finding the right thing to work on

How do you find a dissertation topic? It’s got to be something that interests you, or you won’t feel intrinsically motivated to work on it. It’s got to be something that fits somehow into your discipline, or your department faculty won’t approve it. It’s got to be important, in some way or another, so that it’s worthy of a dissertation.

In Working hard is overrated, Caterina Fake says:

Much more important than working hard is knowing how to find the right thing to work on. Paying attention to what is going on in the world. Seeing patterns. Seeing things as they are rather than how you want them to be. Being able to read what people want. Putting yourself in the right place where information is flowing freely and interesting new juxtapositions can be seen.

And where do you find free-flowing information with interesting new juxtapositions? On the web, of course. That’s why I’m blogging again.