Murder, Extramarital Affairs, and the Issue of Probative Value

A paper previously published in Law and Human Behavior by D. Davis and W. C. Follette (2002) argued that certain "profiling" characteristics commonly admitted into court have little or no probative value. They argued that this is especially likely to be true when the characteristic used as evidence (e.g., having an extramarital affair) is rather common in the population whereas the act in question (e.g., a man murdering his wife) is rare. Their analysis has prompted a strong response by Friedman and Park and by Kaye and Koehler with a rejoinder by Davis and Follette (all three follow this paper in this issue of Law and Human Behavior). This paper describes some of the nature of this controversy.     

Polydrug fatality involving metaxalone

A 29-year old female with a history of depression was found dead in a hotel room. The death scene investigation found empty pill bottles and an empty liter bottle of wine. Metaxalone, a centrally acting muscle relaxant, along with citalopram, ethanol, and chlorpheniramine were identified in the postmortem samples and quantitated by gas chromatography-mass spectrometry. The concentration of metaxalone in femoral vein blood was 39 mg/L. The heart blood concentration was 54 mg/L. Femoral vein blood concentrations of citalopram and chlorpheniramine were 0.77 mg/L and 0.04 mg/L, respectively. Ethanol levels were 0.13 g/dL in vitreous and 0.08 g/dL in heart blood. Other tissue samples were also analyzed. The authors consider the metaxalone concentrations toxic and potentially fatal. The citalopram concentrations were lower than those reported in fatal cases for this drug alone. Death was ascribed to polydrug abuse/overdose with metaxalone a major contributor. This represents the first reported case to our knowledge in which a metaxalone overdose significantly contributed to death.     

Uncertainty and Turnout

This article develops a model that simultaneously considersindividual turnout and vote choice while also accounting foruncertainty about candidates. The theoretical development ofthis model implies that the effects of uncertainty on turnoutvary with the strength of individual preferences. Applicationof the model to individual choice in the 1996 American presidentialelection confirms that decreasing uncertainty about the charactertraits of the candidates decreases the probability of abstentionfor individuals with strong preferences but increases the probabilityof abstention for individuals with weak preferences.     

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 subpopulation data in Australian forensic DNA casework

DNA profiling evidence presented in court should be accompanied by a reliable estimate of its evidential weight. In calculating such statistics, allele frequencies from commonly employed autosomal microsatellite loci are required. These allele frequencies should be collected at a level that appropriately represents the genetic diversity that exists in the population. Typically this occurs at broadly defined bio-geographic categories, such as Caucasian or Asian. Datasets are commonly administered at the jurisdictional level. This paper focuses on Australian jurisdictions and assesses whether this current practice is appropriate for Aboriginal Australian and Caucasian populations alike. In keeping with other studies we observe negligible differences between Caucasian populations within Australia when segregated geographically. However segregation of Aboriginal Australian population data along contemporary State and Territory lines appears to mask the diversity that exists within this subpopulation. For this reason datasets collated along more traditional lines may be more appropriate, particularly to distinguish the most genetically differentiated populations residing in the north of the continent.