Considerations on jury size and composition using lower probabilities

The use of lower probabilities is considered for inferences in basic jury scenarios to study aspects of the size of juries and their composition if society consists of subpopulations. The use of lower probability seems natural in law, as it leads to robust inference in the sense of providing a defendant with the benefit of the doubt. The method presented in this paper focusses on how representative a jury is for the whole population, using a novel concept of a second ’imaginary’ jury together with exchangeability assumptions. It has the advantage that there is an explicit absence of any assumption with regard to guilt of a defendant. Although the concept of a jury in law is central in the presentation, the novel approach and the conclusions of this paper hold for representative decision making processes in many fields, and it also provides a new perspective to stratified sampling.     

AFDC/TANF Exits and Re-entries for Families Raising Children with Educational Disabilities

Having a child with a disability is considered a barrier to self-sufficiency among welfare recipients. This study examines the impact of children's educational disability on single-mother families' welfare exits and re-entries for a cohort of children in a metropolitan region in Missouri, who were born between 1982 and 1994, and received AFDC/TANF at least once from 1990 through 2008 (N=4,928). A semiparametric proportional hazards model for recurrent events is used to analyze the relationship between a child's educational disability and family welfare exit and re-entry. Results show that families with children with disabilities (the disability group) are less likely to exit and more likely to re-enter the welfare system than families with children without disabilities (the nondisability group). After the 1996 welfare reform, the welfare exit rate increases more for the disability group than for the nondisability group, while the welfare re-entry rate decreases less for the disability group than for the nondisability group.     

Biased Bootstrap Methods for Reducing the Effects of Contamination

Contamination of a sampled distribution, for example by a heavy-tailed distribution, can degrade the performance of a statistical estimator. We suggest a general approach to alleviating this problem, using a version of the weighted bootstrap. The idea is to 'tilt' away from the contaminated distribution by a given (but arbitrary) amount, in a direction that minimizes a measure of the new distribution's dispersion. This theoretical proposal has a simple empirical version, which results in each data value being assigned a weight according to an assessment of its influence on dispersion. Importantly, distance can be measured directly in terms of the likely level of contamination, without reference to an empirical measure of scale. This makes the procedure particularly attractive for use in multivariate problems. It has several forms, depending on the definitions taken for dispersion and for distance between distributions. Examples of dispersion measures include variance and generalizations based on high order moments. Practicable measures of the distance between distributions may be based on power divergence, which includes Hellinger and Kullback–Leibler distances. The resulting location estimator has a smooth, redescending influence curve and appears to avoid computational difficulties that are typically associated with redescending estimators. Its breakdown point can be located at any desired value ε∈ (0, ½) simply by 'trimming' to a known distance (depending only on ε and the choice of distance measure) from the empirical distribution. The estimator has an affine equivariant multivariate form. Further, the general method is applicable to a range of statistical problems, including regression.     

Widowhood and Well‐being in Europe: The Role of National and Regional Context

Researchers have documented that widows have lower levels of subjective well‐being than married individuals, but we still know little about how the regional and national contexts affect the impact of widowhood on well‐being. Building on social capital theory and using data from 5 rounds of the European Social Survey (N= 119,292 people, 206 regions, 23 countries), the authors tested how marital status composition at the national and regional levels affects the well‐being of widows. Widows fare worse in countries with high proportions of married people and in regions and countries with high proportions of widowed persons. The proportion of married individuals at the regional level does not affect their well‐being. These results are in line with the greedy marriage hypothesis, but varying effects at regional and national levels suggest that the standard explanation for this phenomenon, lack of individual social support, is not valid. This study demonstrates the importance of multiple contextual embeddedness.     

Can ranking techniques elicit robust values?

This paper reports two experiments which examine the use of ranking methods to elicit ‘certainty equivalent’ values. It investigates whether such methods are able to eliminate the disparities between choice and value which constitute the ‘preference reversal phenomenon’ and which thereby pose serious problems for both theory and policy application. The results show that ranking methods are vulnerable to distorting effects of their own, but that when such effects are controlled for, the preference reversal phenomenon, previously so strong and striking, is very considerably attenuated.