Thing

DISCLAIMER


Welcome! The goal of this blog is to share my analysis of the free, publicly available user-reported law school applicant data from Law School Numbers. Using the data from Law School Numbers is problematic for a variety of reasons (such as users misreporting their actual information, users creating fake accounts, selection bias, etc.) and if I had access to it, I'd much rather work with the data that schools themselves have on applicants. We have what we have, though. Also, while I do have some facility with the type of statistical analysis I employ in my blog posts, I am far from being a professional statistician. I am doing this solely for the purpose of providing my analysis to interested readers, getting feedback, and generating discussion. What I am not doing is prescribing courses of action for law school applicants, or pretending to actually know what goes on behind closed doors in law school admission committees' meetings. I am, however, interested in looking at the story the numbers seem to portray, and sharing that with people with similar interests. I think I'll be able to provide a lot of interesting, and perhaps even helpful, analysis here, but at the end of the day, it is up to the individual law school applicant to put together applications and application strategies tailored to his or her own hopes and goals.

Saturday, June 1, 2013

Very basic T14 vs. Non-T14 breakdown

I have been plugging away processing the data, putting together school profiles as I get requests, and generally trying to think of the best way to approach this.  I definitely appreciate the feedback I've gotten so far, so keep it coming.

I did want to do something quick to post while I continue working, so I thought it might be interesting to take a quick look at factors as they play a role in the top 14 law schools as compared to the rest of the law schools outside the top 14.  I'm using the same Model 1 as always, in which I regress these independent variables (LSAT score, GPA, earlier month sent, URM status, non-traditional student applications, and female) on the dependent variable, which in this case is the decision result (acceptance, waitlist, or rejection). Results are below:

                                

For those who are reading this blog for the first time, those percentages given correspond to the increase in the likelihood an applicant has of either

        • Being admitted as opposed to being waitlisted/rejected
        • Being admitted/waitlisted as opposed to being rejected
So, for instance, at a T14 school, you're 26% more likely to be admitted with a 173 LSAT as opposed to a 172 LSAT, all other factors being held equal.


Seems pretty clear that the T14 schools give much bigger boosts for numbers, earlier submission (want to get squared away earlier?), and both URM and female applicants (the URM boost is much bigger than that for the non-T14).  The only group of applicants that seems to fare better outside the T14 are non-traditional applicants, who get a little boost in the non-T14 but nothing at all in the T14.

Of course, there is plenty of variation within these two categories of schools, and that's what I'm working on.  But, I figured this would be worth looking at in the meantime.

Comments, feedback, questions, and requests welcome!

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