Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

Exposure Reconstruction for the TCDD-Exposed NIOSH Cohort Using a Concentration- and Age-Dependent Model of Elimination

Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.     

Happiness has traitlike and statelike properties: A reply to Veenhoven

Veenhoven (1994) contrasted hypotheses of whether happiness is a trait or state, concluding that it is a state variable. This article critiques the conceptual foundation of Veenhoven's paper, and examines technical deficiencies in his review of evidence. Based on previous findings and new analyses, we conclude that happiness has both traitlike and statelike properties, but that individual differences in happiness endure despite its situational reactivity, and explain greater variance than situational effects.     

Evaluation: Stakeholder-focused Criteria

Identifying and selecting suitable criteria is an important consideration in evaluating the performance of public sector organizations. Which criteria are chosen, and how they are weighted, will depend largely on the perspective being taken; different stakeholders (for example, clients, providers or commissioners) are likely to emphasize different criteria. In this paper a number of criteria are identified and an argument is developed to indicate which criteria are likely to be valued by various stakeholders. Furthermore, a number of approaches and mechanisms for evaluation are identified and the links between these, the criteria appropriate to them and the various stakeholders are made explicit. Finally, the issue of politics and the distribution of power between the stakeholders is addressed with a call for greater explicitness in using and balancing criteria (for example, as between professionals and the intended beneficiaries of services). In this way, while recognizing the inherent political nature of performance evaluation, the planning and implementation of services may be improved by a more mutually informed approach to evaluation.     

Interpersonal dependency of preferences

Standard decision theoretic models disregard the phenomenon of interpersonal dependency of preferences. In this paper it is argued that interpersonal dependency of preferences is a serious challenge for standard utility theory. First we sketch the more philosophical aspects of the problem and then, using a simple, formal model for the two-person case, we show that interpersonal dependency of preferences generally results in indeterminacy of preferences (resp. of subjective utility).     

Recent trends in the process of stratification

Using the 14 annual cross-sections from the General Social Survey, we specify a "basic model" of attainment and describe the year-by-year fluctuations in its parameters. The results are partially consistent with theories describing the gradual growth of universalistic patterns of stratification and mobility. Under a linear model of educational achievement, we find that the direct effects of race are weakening and the returns to class-based advantages are declining in tandem. The contours of the socioeconomic "gender gap" are also changing in important ways, with the male intercept declining at a rapid pace and the female term registering small and insignificant year-by-year gains. At the same time, the returns to experience and schooling are increasing for men, whereas the corresponding returns for women have remained stable over the 15-year period. This pattern of interaction effects implies that the size of the gender gap varies over time and across different population groups.     

Basic aspects of evolution strategies

Evolution strategies (ESs) are a special class of probabilistic, direct, global optimization methods. They are similar to genetic algorithms but work in continuous spaces and have the additional capability of self-adapting their major strategy parameters. This paper presents the most important features of ESs, namely their self-adaptation, as well as their robustness and potential for parallelization which they share with other evolutionary algorithms.Besides the early (1 + 1)-ES and its underlying theoretical results, the modern ( + )-ES and (, )-ES are presented with special emphasis on the self-adaptation of strategy parameters, a mechanism which enables the algorithm to evolve not only the object variables but also the characteristics of the probability distributions of normally distributed mutations. The self-adaptation property of the algorithm is also illustrated by an experimental example.The robustness of ESs is demonstrated for noisy fitness evaluations and by its application to discrete optimization problems, namely the travelling salesman problem (TSP).Finally, the paper concludes by summarizing existing work and general possibilities regarding the parallelization of evolution strategies and evolutionary algorithms in general.