What Do Grandmothers Think about Self‐esteem? American and Taiwanese Folk Theories Revisited

The study investigates European American and Taiwanese grandmothers’ folk theories of childrearing and self‐esteem, building on an earlier comparison of mothers from the same families. Adopting methods that privilege local meanings, we bring grandmothers’ voices into the conversation about childrearing, thereby contributing to a deeper understanding of intergenerational nuances in folk theories. In each cultural case, 16 grandmothers of 3‐year‐olds participated in in‐depth interviews that were customized according to local communicative norms. Although self‐esteem emerged as a central organizing concept in the folk theories of European American mothers, grandmothers spoke in two voices, either echoing their daughters or invoking a counter‐discourse of wariness towards self‐esteem. By contrast, Taiwanese mothers and grandmothers resembled one another—but differed from their American counterparts—in treating self‐esteem as peripheral in childrearing. Results contribute to the growing consensus that self‐esteem is a culture‐specific childrearing goal and suggest that the European American tendency to valorize self‐esteem varies by generation.     

Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.     

Semi-parametric estimation of ROC curves based on binomial regression modelling

This paper presents a method of estimating a receiver operating characteristic (ROC) curve when the underlying diagnostic variable X is continuous and fully observed. The new method is based on modelling the probability of response given X , rather than the distribution of X given response. The method offers advantages in modelling flexibility and computational simplicity. The resulting ROC curve estimates are semi-parametric and can, in principle, take an infinite variety of shapes. Moreover, model selection can be based on standard methods within the binomial regression framework. Statistical accuracy of the curve estimate is provided by a simply implemented bootstrap approach.     

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.     

Modelling data from single-photon emission computerized tomography

The completely random character of radioactive disintegration provides the basis of a strong justification for a Poisson linear model for single-photon emission computed tomography data, which can be used to produce reconstructions of isotope densities, whether by maximum likelihood or Bayesian methods. However, such a model requires the construction of a matrix of weights, which represent the mean rates of arrival at each detector of photons originating from each point within the body space. Two methods of constructing these weights are discussed, and reconstructions resulting from phantom and real data are presented.