For any students (or faculty, for that matter) contemplating a summer research project, Andrew Gelman (Columbia--Poli Sci) offers quite helpful, quick advice on how to approach writing up a research paper (here).
Always-provocative lawblogger Vivia Chen's recent post "Too good for Big Law" has drawn a fair bit of attention. She notes work by our very own Bill Henderson (using data from the NLJ) suggesting that associate to partner odds -- that is, the ratio of Biglaw associates hired from a particular law school to Biglaw partners from the same school -- for many elite / T14 schools are lower than those for lower-tier places.
Bill responded with his usual meticulousness at the Legal Whiteboard, offering the "statistician edition" of the Careerist post. After a suitable discussion of the potential caveats, he does a nice job of rounding up a range of possible explanations for this finding. At Above the Law, David Lat casts his vote for "Selection Effects," "Inter-Generational Privilege," and "A Better Plan B" as the most likely drivers among among BH's explanations. And Bruce MacEwen at Adam Smith Esq. lays out the data in all its glory, and has some thoughtful ruminations on why we might not want to take the results too seriously, and why (and how) we might. There's also an exposition at TaxProfBlog. For its part, the NLJ offers an interactive chart that puts some of their data in visual form (including tuition for the schools in question).
Of course, I just couldn't help myself from digging into the data a little. All of the commenters above make the point that, for this comparison to work, the numbers cannot be changing much from year to year; for example, at one point Henderson says "I analyzed this same data four years ago and got essentially the same results." So I found the same NLJ data from 2010, and did a little comparison.
The vertical axis correspond to the (2011) percentages listed at Bruce M's post; the horizontal one is the same numbers for 2010. (My UH number is a bit different from his, but the others are spot-on). Red "Xs" are the "Top 14" law schools, while black dots are the rest; I labeled a few of the outliers. The data are noisy: the simple (Pearson) correlation between the two years is 0.32. But the correlation is driven almost entirely by the difference between elite and non-elite schools: the correlation among non-elite schools only is 0.06, while that among elite schools only is a paltry 0.02. Moreover, the aggregate differences between Top 14 and non-Top 14 schools are large, averaging 17.2% vs. 28% in 2010 and 15.9% vs. 40.5% in 2011.
So, while the data are noisy, the larger pattern still holds: More elite schools have consistently lower "partner yield rates" than do less elite, tier-one schools. While this doesn't begin to get at the various reasons why this might be happening, it does lend some support to the idea that there's something here worth looking into.
Over at Concurring Opinions, Dave Hoffman's (Temple) fascinating post features a simple graphic that speaks, quite literally, for itself and potentially implies a lot for how first year civil procedure is traditionally structured and presented. Well worth a look.
Although I cannot personally vouch for this particular course (Harvard, Stats 110--Probability, Fall 2011, with Prof. Joe Blitzstein), others can (and do so gushingly). What I can heartily endorse, however, is disseminating the entire course via iTunes (and free of charge).
The good folks at Princeton University (specifically, at the Firestone Library) have put together a nice portal that includes quite helpful online tutorials designed for folks seeking to becoming more familiar with Stata basics. The graphics facilitate "learning by doing." Indeed, and as often the case, the tailored tutorials are far more user-friendly than the typical product user guides and reference material.
Although the immediate target audience for Richard J. Ball (Haverford) and Norm Medeiros' (Haverford) paper, Teaching Students to Document Their Empirical Research, includes advanced undergraduates, this helpful paper will benefit all those engaged in teaching empirical methodology as well as their students. If this is what is expected from undergraduate students engaged in empirical studies, we should expect at least as much from law students. The abstract follows.
"This paper describes a protocol we have developed for teaching undergraduates to document the statistical analysis they do for empirical research projects in such a way that their results are completely reproducible and verifiable. The protocol is guided by the principle that the documentation prepared to accompany an empirical research project should be sufficient to allow an independent researcher to replicate easily and exactly every step of the data management and analysis that generated the results reported in the study. We hope that requiring students to follow this protocol will not only teach them how to document their research appropriately, but also instill in them the belief that it is an important professional responsibility to do so."
I couldn't help noting that among the nine law school Deans that Brian Leiter characterizes as "transformative" during the past decade, at least two (Syverud and Van Zandt) were expressly noted for building a "strong empirical studies presence." The tally goes to three (of nine) if one construes (as one objectively should) the description of Hurd's decanal tenure at Illinois ("cutting edge of interdisciplinary work in multiple areas") as a clear--albeit indirect--reference to her efforts to enhance that faculty's capacity for empirical legal research. As Brian's post correctly notes, the actual number of plausibly "transformative" Deans exceeds (but surely includes) the nine highlighted. I also strongly suspect that the correlation between the list of transformative Deans and a law school's capacity for serious empirical work is both positive and robust.
Once folks finish spring semester grading, those with time and interest might want to explore UCLA's wonderfully rich online treasure-trove of helpful, practical stats resources (here), which include classes, seminars, etc. (here). Not only are the resources organized topically, but but specific statistical packages as well.
George Mason University School of Law's Law and Economics Center is hosting a Workshop on Empirical and Experimental Methods for Law Professors on May 23-26, 2011, in Arlington, VA. Interestingly, this is the second entrant into a growing market for programs specifically addressing law professors and empirical legal scholarship. (We've previously noted similar programs jointly sponsored by Wash U/Northwestern.) A more detailed description of the GMU Workshop, as well as contact information, follow.
"The Workshop on Empirical and Experimental Methods for Law Professors is designed to teach law professors the conceptual and practical skills required to (1) understand and evaluate others’ empirical studies, and (2) design and implement their own empirical studies. Participants are not expected to have background in statistical knowledge or empirical skills prior to enrollment. Instructors have been selected in part to demonstrate the development of empirical studies in a wide-range of legal and institutional settings including: antitrust, business law, bankruptcy, class actions, contracts, criminal law and sentencing, federalism, finance, intellectual property, and securities regulation. Class sessions will provide participants opportunities to learn through faculty lectures, drawing upon data and examples for cutting edge empirical legal studies, and participating in experiments. There will be numerous opportunities for participants to discuss their own works-in-progress or project ideas with the instructors.
The Workshop will begin on Monday May 23, at 8:30 a.m. and conclude on Thursday May 26, at 12 pm. Classes on May 23, 24 and 25 will run from 8:30 am to 5pm, and include lectures, group sessions, and opportunities for participants to present their own empirical projects or “works in progress.”
Tuition for the Workshop on Empirical and Experimental Methods is $850 for the first professor from a law school and $500 for additional registrants from the same school.
Those interested in the Workshop should contact Jeff Smith directly at:
"John Keyser and I co-teach a course called “The Role of Social Science in the Law” at the Washington and Lee Law School. While John and I taught a fairly ordinary version of the course during our first time teaching the class, this year we have added simulations in which law students have to assume the roles of attorneys who are faced with using or critiquing the use of social scientific research in mock cases. Given our experiences in creating this course, I am interesting in finding out which law schools and law school professors are offering courses on empirical methods for law students. Specifically, I’m interested in courses that don’t simply teach the methods themselves, but take the additional step of using these new skills to (1) examine how judges and lawyers use/abuse social scientific research in the courtroom, or (2) examine how social scientists study judicial behavior. I’d also be interested to hear what textbook or articles the professors use, as well as any simulation materials."
Another (positive) sign of the times is the publication (by Aspen) of the Lawless, Robbennolt, & Ulen (all at Illinois) casebook: Empirical Methods in Law. A blurb notes:
"Today's legal profession demands that lawyers understand and engage in
dialogue about basic empirical research techniques. Empirical Methods in Lawteaches law students to recognize when empirical research needs to be applied
in legal practice. It provides the vocabulary with which to communicate with
scientific experts, and an awareness of the type of questions to ask about
A colleague determined to conquer R (or at least become functionally fluent) bemoaned recently R's inaccessible documentation and obtuse manuals. To be sure, the price is right (R is free open-source), but she is now looking for suggestions on helpful, basic, and more user-friendly "How-To" books for R. As this is the Holiday season I agreed to pass along her request. Suggestions (and comments) welcome.
Over at PrawfsBlawg Jonathan Simon (Berkeley), drawing on his deep reservoir of experience (as an Assoc. Dean in charge of Berkeley's Jurisprudence & Social Policy Program), comments on the challenges incident to building a coherent empirical curriculum into a leading sociolegal & policy program. As is invariably the case, Simon's interesting thoughts on the topic warrant a wide audience.
The ideal statistical software for teaching would be powerful, easy to learn and free. Stata, SPSS and SAS are powerful and relatively easy to learn, but not exactly free. R is free and very powerful, but has a long-toed learning curve (see previous discussion on software package preferences here). At one point I toyed with PSPP (an open-source knock-off of SPSS) but it is a very poor substitute and not worth anyone's time. Now I've found Gretl (The GNU Regression, Econometric and Time-Series Library). Gretl is a stand-alone open-source cross-platform package. It can directly import files from Stata 9, Excel, csv and several other formats, although the imports do not always proceed smoothly. It uses menus or scripting, and it can invoke R for more sophisticated analysis and graphing (if R is installed). The built-in routines include the expected (e.g., ols and logit) as well as time-series and some arcana (3sls). The post-estimation analyses are first rate. Gretl won't supplant Stata on my personal desktop any time soon, but it's worth considering for the classroom if you are teaching statistics to law students with Excel or Datadesk.
Information on the workshop, organized by Lee Epstein (Northwestern) and Andrew Martin (Wash U) and scheduled for June 23-25 in Chicago, is found here. A summary follows.
"The Conducting Empirical Legal Scholarship workshop is for law school faculty
interested in learning about empirical research. Leading empirical scholars Lee
Epstein and Andrew Martin will teach the workshop, which provides the formal
training necessary to design, conduct, and assess empirical studies, and to use
statistical software (Stata) to analyze and manage data. Participants need no
background or knowledge of statistics to enroll in the workshop."