How far does the gender gap extend?: Decision making on state Supreme Courts in Fourth Amendment Cases, 1980–2000

The importance of women on the bench and the influence of gender on judicial decision making has garnered much scholarly attention. We examine the voting behavior of male and female justices in 718 Fourth Amendment search and seizure votes cast on state Supreme Courts between 1980 and 2000. We find that women justices, controlling for institutional, political, and legal constraints, are more likely to rule in favor of the criminal defendant than their male brethren in cases decided after 1991 but not before. We also find women justices serving with female colleagues are more inclined to render liberal votes. We conclude the influence of gender may be evident in a wider variety of cases than those dealing with women's lives but that this influence is dependent upon the existence of a critical mass of women on the state court benches.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

Innovation,accountability, and independence at three private foundations funding higher education civic engagement, 1995 to 2005

This case study looks at changes in private foundation funding for higher education civic engagement from 1995 to 2005. The focus is three large, established foundations that were U.S. national leaders in supporting this activity during these years: Carnegie, Pew, and Kellogg. Data sources include (1) in‐depth conversations with four strategically placed foundation insiders and six nationally recognized campus leaders and (2) scans of Web sites of the three foundations that document the change in funding priorities over time, plus Web sites of the main campus initiatives supported and national campus civic engagement organizations such as Campus Compact. Research findings con‐ firm and specify other studies that suggest that foundations shift their funding priorities according to their perceived role as innovators, pressures to be accountable and show clear results, and their independence as private organizations. The article concludes by raising questions about private foundations generally in relation to issues of innovativeness, accountability, and independence.     

Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467–475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters’ prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters’ prior beliefs.     

Statistical consulting

The paper and the special issue focus on the activity of statistical consulting and its varieties. This includes academic consulting, consulting to and in industry as well as statistics in public media.     

General Job Satisfaction From a Developmental Perspective: Exploring Choice—Job Matches at Two Career Stages

The authors explored predictions of general job satisfaction at early and middle adulthood and uncovered several findings about developmental processes associated with job satisfaction. Tests of life‐span career theory propositions revealed that neither choice‐job congruence nor gender added significantly to predictions of job satisfaction at 2 career stages. Earlier occupational choice and current job added to predictions of midcareer (modal age 43 years) job satisfaction, especially for men. The predictability of job satisfaction is apparently influenced by the career stage when satisfaction is appraised.