Logistic Regression in Rare Events Data

We study rare events data, binary dependent variables with dozensto thousands of times fewer ones (events, such as wars, vetoes,cases of political activism, or epidemiological infections)than zeros ("nonevents"). In many literatures, these variableshave proven difficult to explain and predict, a problem thatseems to have at least two sources. First, popular statisticalprocedures, such as logistic regression, can sharply underestimatethe probability of rare events. We recommend corrections thatoutperform existing methods and change the estimates of absoluteand relative risks by as much as some estimated effects reportedin the literature. Second, commonly used data collection strategiesare grossly inefficient for rare events data. The fear of collectingdata with too few events has led to data collections with hugenumbers of observations but relatively few, and poorly measured,explanatory variables, such as in international conflict datawith more than a quarter-million dyads, only a few of whichare at war. As it turns out, more efficient sampling designsexist for making valid inferences, such as sampling all availableevents (e.g., wars) and a tiny fraction of nonevents (peace).This enables scholars to save as much as 99% of their (nonfixed)data collection costs or to collect much more meaningful explanatoryvariables. We provide methods that link these two results, enablingboth types of corrections to work simultaneously, and softwarethat implements the methods developed.     

Use of the MMPI-2 and the Inwald personality inventory to identify the personality characteristics of dropouts from a state police academy

The MMPI-2 and the Inwald Personality Inventory were employed to investigate the personality characteristics of dropouts from a state police academy. A traditional model of training borrowed from military models was used at the academy rather than a police generated model. Sensitive and independent individuals, more compatible with modern community policing methods may have rejected police work as a result of the experience. 15 academy completers and 9 dropouts were used in the sample. Analyses of the scales of the MMPI-2 and the Inwald Personality Inventory identified variables upon which the two groups differed. The hypothesis that more sensitive, empathic and independent individuals were leaving the academy appeared to be supported.     

A cure for the Blues: resolving nonprofit Blue Cross conversions

This Article analyzes the issues involved in converting nonprofit Blue Cross organizations to for-profit status. These issues have arisen in the context of litigation regarding the "reorganization" of Blue Cross and Blue Shield of Missouri ("BCBSMo"). BCBSMo had reorganized by creating and transferring a majority of its business to a new for-profit subsidiary. Missouri consumer groups and state regulators characterized the "reorganization" as a conversion requiring BCBSMo to transfer its assets to a foundation dedicated to charitable health purposes. BCBSMo, however, denied that it had any obligation to leave behind its assets in the nonprofit sector. The BCBSMo litigation raises issues common to most conversions of nonprofit healthcare organizations, particularly conversions of nonprofit Blue Cross plans. This Article provides a road map for state regulators and the public to follow in ensuring that the public interest is fully protected in such conversions.     

Application of Law to the Childhood Obesity Epidemic

Childhood obesity is in important respects a result of legal policies that influence both dietary intake and physical activity. The law must shift focus away from individual risk factors alone and seek instead to promote situational and environmental influences that create an atmosphere conducive to health. To attain this goal, advocates should embrace a population-wide model of public health, and policymakers must critically examine the fashionable rhetoric of consumer choice.