# avoid methodological mousetraps

New methods are key to developing new hypotheses and testing old ones. It would be difficult to imagine social sciences today without regression models, or social network analysis, or online ethnographies. Each has been developed and used to expand what we think that we know about the social world.

But social scientists, especially junior researchers, too often fail to justify their new methods. They demonstrate their creativity and document the often considerable work they put into developing their new approach. But scholars should take care that they're not just building a better mousetrap.

# zipping up r

Because I am a masochistperfectionist, I spent the better part my day making my R code more elegant. I figured out what to do with a simple loop, but wanted to write the code the right way. I always tell myself that the time I spend torturing myselfwriting the right code will help me down the line so I know how to do it next time. I will inevitably forget and spend the same four hours doing the same thing again. As a gift to my future self, I decided that I would write down what I learned because it will likely come up again (you're welcome, future Mike!).

My basic problem comes from the desire to match two lists item-by-item. Python contains a function, zip(), that does this. I want to figure out how to zip in R.

# shifting values in r

R presents more of a challenge to Stata on many fronts, one of which is basic data management.

I often find myself calculating the value of one observation given the value of an adjacent value. For example, to assess a lagged effect, I would take the value of the preceding interval. Stata makes this really easy, R not so much.

Here's what we would do in Stata:

set obs 1000
gen i = _n
gen val = round(runiform()*10)
gen lag = val[_n-1]


The last command throws the warning, (1 missing value generated) because the first observation has no lagged observation. The first 10 observations ...

# beckieball, or selecting on skill

Over the weekend, jeremy posted about beckieball, a "new sport sweeping the country." The purpose was to show how selection on characteristics affects the correlation between characteristics upon selection. This, as commenter Stuart Buck pointed out, is an example of Berkson's Paradox, though it relates to jeremy's post about height and nba.

Although he left several other exercises to the reader, I thought I would do a simpler one: recreate the code that he used to make his example. I did this a) because it was a semi-useful way to shake the cobwebs from egg nog and yuletides, and b) because I think that it will come ...

# importing text files with variable names to r

I am attempting to learn R. This is either a great thing or a terrible, terrible mistake while on the tenure clock. But, all the cool kids are doing -- so even though they might also jump off a bridge, I'm going to jump into R.

The hardest part so far is doing things that now come as second nature to me in Stata. Although R's tools are much better in the long-run, learning what types of objects different functions return and such ends up being a very high learning curve.

A while back (all posts are a while back now), I wrote a post describing how to import ...

# nesting stata macros, or hacking a hash map

Programming in Stata is relatively straightforward and this is partly because the programming syntax is both powerful and relatively straightforward. There are, however, a few minor annoyances in Stata's language including using the backtick and apostrophe to indicate local macros (i.e.,localname'). Among these shortcomings, I would argue that the lack of anything like a list in Stata's language is one of the largest.

In most langauges, you can store a list of items and refer to the item in the list by some sort of index. This is particularly helpful for iterating over the same step multiple times. Lists generally come in two flavors: lists to which you ...

# calculating simple power analyses

I am currently preparing a proposal for submission and one piece of information that the agency suggests is the power required to distinguish effects. This is obviously a perfectly reasonable piece of information to request; however, power calculations fall into that class of things that I know that I should know but I don't. It is one of those topics that every statistics book will tell you is important, but either a) glosses over the topic, or b) provides such a deep background that it is impossible to follow what the authors are talking about. Additionally, power calculations are complicated enormously by the fact that sample designs can become very ...

# matching substrings entirely within stata

At Orgtheory, Fabio asked about how to identify substrings within text fields in Stata. Although this is a seemingly simple proposal, there is one big problem, as Gabriel Rossman points out: Stata string fields can only hold 244 characters of text. As Fabio desires to use this field to analyze scientific abstracts, then 244 characters is obviously insufficient.

Gabriel Rossman has posted a solution he has called grepmerge that uses the Linux-based program grep to search for strings in files. This is a great solution, but it comes with one large caveat: it cannot be used in a native Windows environment. This is because the grep` command ...