Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Stress at work and psychological and immunological parameters in a group of Norwegian female bank employees

This study concerned the immunological correlates of stress and work. Self reported stress, emotional state, ego-strength, and defensiveness were examined in relation to measures of cellular immunity (T-cell response to Con A and number of T4 and T8 cells) and humoral immunity (concentrations of immunoglobulins and complement components in plasma) in a group of 96 Norwegian female bank employees. The analyses showed that workload, the stress factor with the highest group mean, was associated with number of T-cells, while strain due to body posture during work was related to concentrations of IgM and C3. Further, depression was significantly correlated with IgM concentration and T-cell number, and anxiety with C3 concentration. T-cell activity was the immunological parameter most consistently associated with psychological well-being, showing positive correlations with defensiveness and ego-strength and negative correlations with anxiety and depression. In conclusion, T-cell number and concentrations of IgM and C3 were sensitive to both work-related stress experience and emotional distress. Coping abilities, indicated by the MMPI Ego-strength scale and emotional distress, were reflected in T-cell activity; insufficient coping was associated with low T-cell activity.     

Mapping Gender and Migration in Sociological Scholarship: Is It Segregation or Integration?

A review of the sociological research about gender and migration shows the substantial ways in which gender fundamentally organizes the social relations and structures influencing the causes and consequences of migration. Yet, although a significant sociological research has emerged on gender and migration in the last three decades, studies are not evenly distributed across the discipline. In this article, we map the recent intellectual history of gender and migration in the field of sociology and then systematically assess the extent to which studies on engendering migration have appeared in four widely read journals of sociology (American Journal of Sociology, American Sociological Review, Demography, and Social Forces). We follow with a discussion of these studies, and in our conclusions, we consider how future gender and migration scholarship in sociology might evolve more equitably.     

Prehistoric landscapes of the sonoran desert Hohokam

The Hohokam of southern Arizona are noted for greater duration of settlement than other major agricultural traditions in the archaeological record of the southwestern United States, including the Anasazi and Mogollon. The 40,000 square mile area inhabited by the Hohokam is marked by low elevation desert basins, but encompasses a range of topographic and climatic variability that shaped opportunities for prehistoric farming technologies. Irrigation from rivers was frequently associated with the longterm persistence of individual sites, while floodwater farming along ephemeral drainages was more often correlated with continuous occupation of hydrologically favored zones. Renewal of fields by waterborne nutrients and efficient practices in the use of natural resources countered the limited mobility options afforded by the Hohokam environment.In spite of a restrictive agricultural setting and an essentially static suite of productive technologies over many centuries, relationships among population, settlement, and landuse were redefined in evolving social and economic configurations. An example from the Tucson Basin illustrates differentiated patterns of settlement and agriculture arising in conjunction with increased levels of population and territorial integration in the late prehistoric period. Community organization among interrelated settlements incorporated a diversity of topographic zones and agricultural technologies in this high-risk context for prehistoric cultivators.     

Betrayal and repetition: Understanding aggression in sexually abused girls

Betrayal by a significant object is seen as primary in causing behavioral and emotional disturbances in incest victims, leading to a pervasive identification with the aggressor and disturbances in object relations development. Identification with the aggressor is understood not as a uniform defense mobilized against a specific affect but as a complex compromise formation which defends against anxiety, while also providing libidinal, aggressive and superego gratifications. Far from simply attempting to overcome the past, identifications thus preserve affects that have become pleasurable and self-defining. Two case studies of adolescent girls illustrate how treatment can help victims recognize and begin to forego the sadomasochistic pleasure derived from these identifications, a relinquishment necessary for true mastery.     

Mining the Data: Analyzing the Economic Implications of Mining for Nonmetropolitan Regions

Extractive industries such as logging and mining are generally expected to bring significant economic benefits to rural regions, but a growing number of findings have now challenged that common expectation. Still, it is not clear whether the findings of less–than–desirable economic outcomes are isolated or representative. In this article, we assemble literally all of the relevant quantitative findings on mining that we have been able to identify in published and/or technical literature from the United States. In the interest of rigor, we limit the assessment to cases in which strictly nonmetropolitan mining regions are compared against other nonmetropolitan regions and/or against those regions’ own experiences over time. Overall, 301 findings meet the criteria for inclusion. Contrary to the long–established assumptions, but consistent with more recent critiques, roughly half of all published findings indicate negative economic outcomes in mining communities, with the remaining findings being split roughly evenly between favorable and neutral/indeterminate ones. Positive findings are more likely to be associated with incomes than with poverty or (especially) unemployment rates, and they are more likely to come from the western United States, where much of the mining involves relatively large, new coal strip mines. Over half of all positive findings come from the years prior to 1982. In virtually all other categories, the plurality or majority of findings have been negative. When the patterns of findings are subjected to one–sample means tests, the only way to produce a significantly positive outcome is by combining all neutral/indeterminate findings with the positive ones, while focusing exclusively on incomes; by contrast, in the case of poverty or unemployment rates—as well as for the overall body of findings—the results are consistently and significantly negative, whether the neutral/indeterminate findings are combined with negative ones or omitted from the equations altogether. Until or unless future studies produce dramatically different findings, there appears to be no scientific basis for accepting the widespread, “obvious” assumption that mining will lead to economic improvement.     

The 10% Flat Tax: Tithing and the Definition of Income

Developing a fair and widely accepted income definition presents one of the greatest challenges to tax reform. To arrive at a definition separate from the federal tax code, we surveyed 1200 Latter‐day Saints about their practice of tithing. Tithing is similar to a flat tax with no deductions, where individuals voluntarily contribute 10% of self‐defined income to the church. The results of our survey indicate that most respondents operate on a cash realization basis, which excludes savings and does not allow any deductions. Respondents' income concepts generally do not coincide with current tax laws or economists' views of comprehensive income.     

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.