Kamis Manis

In my previous article, I presented the problem of estimating a criminal's risk of recidivism, focusing on the philosophical problems of attributing a probability to an individual.  In this article I turn to the more practical problem of doing the estimation. My collaborator asked me to compare two methods and explain their assumptions, properties, pros and cons: 1) Logistic regression : This is the standard method in the field.  Researchers have designed a survey instrument that assigns each offender a score from -3 to 12.  Using data from previous offenders, they estimate the parameters of a logistic regression model and generate a predicted probability of recidivism for each score. 2) Post test probabilities : An alternative of interest to my collaborator is the idea of treating survey scores the way some tests are used in medicine, with a threshold that distinguishes positive and negative results.  Then for people who "test positive" we can compute the post...

I am collaborating with a criminologist who studies recidivism.  In the context of crime statistics, a recidivist is a convicted criminal who commits a new crime post conviction.  Statistical studies of recidivism are used in parole hearings to assess the risks of releasing a prisoner.  This application of statistics raises questions that go to the foundations of probability theory. Specifically, assessing risk for an individual is an example of a "single-case probability", a well-known problem in the philosophy of probability.  For example, we would like to be able to make a statement like, "If released, there is a 55% probability that Mr. Smith will be charged with another crime within 10 years."  But how could we estimate a probability like that, and what would it mean? I suggest we answer these questions in three steps.  The first is to choose a "reference class"; the second is to estimate the probability of recidivism in the reference class; the t...

When I was in third grade, the principal of my elementary school announced a bottle cap drive with the goal of collecting one million bottle caps.  The point, as I recall, was to demonstrate that one million is a very large number.  After a few months, we ran out of storage space, the drive was cancelled, and we had to settle for the lesson that 100,000 is a lot of bottle caps. So it is a special pleasure for me to announce that, early Sunday morning (November 1, 2015), this blog reached one million page views.  I am celebrating the occasion with a review of some of my favorite articles and, of course, some analysis of the page view statistics. Here's a screenshot of my Blogger stats page to make it official: And here are links to the 10 most read articles: Posts Entry Pageviews Are first babies more likely to be late? Feb 7, 2011, 9 comments 130446 All your Bayes are belong to us! Oct 27, 2011, 56 comments 47...