A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.     

ON THE INDEPENDENCE OF THE SAMPLE MEAN AND TRANSLATION-INVARIANT STATISTICS FOR MATRIX NORMAL DISTRIBUTIONS

We present an explicit characterization of the joint dependency structure of an n×p matrix normal random matrix such that the p-dimensional sample mean vector is independent of all translation invariant statistics.     

QUESTION WORDING AND PARTISANSHIP: CHANGE AND CONTINUITY IN PARTY LOYALTIES DURING THE 1992 ELECTION CAMPAIGN

Gallup macropartisanship varies more over time than aggregatemeasures of partisanship employing the standard Michigan SurveyResearch Center (SRC) party identification measure, but previousanalyses do not provide direct evidence about why Gallup macropartisanshipis more variable. Although these differences could result fromthe short-term focus of the Gallup party affiliation question,aggregate-level analyses cannot test the effects of questionwording directly. Between March and October 1992, we conducteda series of question-wording experiments, employing six statewidecomputer-assisted telephone interview (CATI) surveys of Michiganadults, including a four-wave panel study. Our analyses stronglysuggest that the Gallup measure responds more to short-termpolitical conditions and clearly demonstrate that the Gallupmeasure is less stable over time. These individual-level resultshelp explain why Gallup macropartisanship varies more over timethan aggregate measures of partisanship employing the standardSRC measure and raise questions about the degree to which onecan generalize from analyses using the Gallup data to the researchliterature on party identification.     

Age Cohort, Ancestry, and Immigrant Generation Influences in Family Relations and Psychological Well-Being among Black Caribbean Family Members

Immigration is contributing to the U.S. population becoming increasingly ethnically diverse. This article examines the role of family relations and well-being among different generations of Black Caribbean immigrants. Family disruptions, such as migration, can have complex effects on the support networks and emotional well-being of family members. Data from a recently completed national study of American Blacks in the United States, however, reveal significant similarities across ancestry and immigrant status in family contact, solidarity and well-being. It is concluded that intrafamilial relations may serve to overcome barriers of geographical distance in providing comparable levels of contact, solidarity, and well-being for both U.S.-born and immigrant Black Caribbean family members of different generations. Because of the increasing numbers of immigrant elders, these sources of family support will become increasingly more important in bridging the gaps between government resources and needed assistance in an aging society.     

Case study in the Bayesian analysis of a cost‐effectiveness trial in the evaluation of health care technologies: Depression

We present a case study based on a depression study that will illustrate the use of Bayesian statistics in the economic evaluation of cost‐effectiveness data, demonstrate the benefits of the Bayesian approach (whilst honestly recognizing any deficiencies) with respect to frequentist methods, and provide details of using the methods, including computer code where appropriate. Copyright © 2003 John Wiley & Sons, Ltd.     

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.     

"Her" Marriage after the Revolutions

Recent social changes have made husbands' emotional investments and wives' perceptions of equity in the division of housework crucial for women's marital happiness. But wives are also happiest in their marriages when they share a strong normative commitment to lifelong marriage with their husbands and when their husbands take the lead in breadwinning. Thus our research suggests that elements of the new and the old promote marital happiness among contemporary wives.     

Communicating Global Activism

Many observers doubt the capacity of digital media to change the political game. The rise of a transnational activism that is aimed beyond states and directly at corporations, trade and development regimes offers a fruitful area for understanding how communication practices can help create a new politics. The Internet is implicated in the new global activism far beyond merely reducing the costs of communication, or transcending the geographical and temporal barriers associated with other communication media. Various uses of the Internet and digital media facilitate the loosely structured networks, the weak identity ties, and the patterns of issue and demonstration organizing that define a new global protest politics. Analysis of various cases shows how digital network configurations can facilitate: permanent campaigns; the growth of broad networks despite relatively weak social identity and ideology ties; transformation of individual member organizations and whole networks; and the capacity to communicate messages from desktops to television screens. The same qualities that make these communication-based politics durable also make them vulnerable to problems of control, decision-making and collective identity.