Property Loss Estimation for Wind and Earthquake Perils

This article describes the development of a generic loss assessment methodology, which is applicable to earthquake and windstorm perils worldwide. The latest information regarding hazard estimation is first integrated with the parameters that best describe the intensity of the action of both windstorms and earthquakes on building structures, for events with defined average return periods or recurrence intervals. The subsequent evaluation of building vulnerability (damageability) under the action of both earthquake and windstorm loadings utilizes information on damage and loss from past events, along with an assessment of the key building properties (including age and quality of design and construction), to assess information about the ability of buildings to withstand such loadings and hence to assign a building type to the particular risk or portfolio of risks. This predicted damage information is then translated into risk-specific mathematical vulnerability functions, which enable numerical evaluation of the probability of building damage arising at various defined levels. By assigning cost factors to the defined damage levels, the associated computation of total loss at a given level of hazard may be achieved. This developed methodology is universal in the sense that it may be applied successfully to buildings situated in a variety of earthquake and windstorm environments, ranging from very low to extreme levels of hazard. As a loss prediction tool, it enables accurate estimation of losses from potential scenario events linked to defined return periods and, hence, can greatly assist risk assessment and planning.     

The Dutch IOR Approach to Organizational Design: An Alternative to Business Process Re-engineering?

This paper presents the current Dutchsociotechnical design approach to integralorganizational renewal in a contextual way. Both itsdesign theory and intervention processes are reviewedand some aggregated empirical evidence is presented. Next, thepaper compares the ideas developed in the Dutch approachto those presented in its American, Scandinavian, andAustralian counterparts. It is concluded that, at a meta-level, they all share the ideal ofparticipative democracy, while at the conceptual level,these distinctive approaches appear quite incompatible.Notwithstanding substantial diversity, it is presumed these approaches can be seen as localmanifestations of a single sociotechnicalparadigm.     

P-value adjustment for multiple binary endpoints

The p-value-based adjustment of individual endpoints and the global test for an overall inference are the two general approaches for the analysis of multiple endpoints. Statistical procedures developed for testing multivariate outcomes often assume that the multivariate endpoints are either independent or normally distributed. This paper presents a general approach for the analysis of multivariate binary data under the framework of generalized linear models. The generalized estimating equations (GEE) approach is applied to estimate the correlation matrix of the test statistics using the identity and exchangeable working correlation matrices with the model-based as well as robust estimators. The objectives of the approaches are the adjustment of p-values of individual endpoints to identify the affected endpoints as well as the global test of an overall effect. A Monte Carlo simulation was conducted to evaluate the overall family wise error (FWE) rates of the single-step down p-value adjustment approach from two adjustment methods to three global test statistics. The p-value adjustment approach seems to control the FWE better than the global approach Applications of the proposed methods are illustrated by analyzing a carcinogenicity experiment designed to study the dose response trend for 10 tumor sites, and a developmental toxicity experiment with three malformation types: external, visceral, and skeletal.     

Tests for symmetry about an unknown value based on the empirical distribution function

A class of Kolmogorov-Smirnov and Cramér-von Mises type statistics for testing symmetry about an unknown value is described. These statistics are not distribution-free, however, and, indeed, are not readily amenable to calculation. A linear rank statistic analog of the first component of the Cramér-von Mises type statistic is investigated. Asymptotic non-null properties of these procedures in the normal case are studied, and an efficiency comparison of the Cramér-vonMises statistic, the linear rank statistic analog, the modified Wil-coxon statistic, and the likelihood ratio test is reported.     

First Person Accounts and Sociological Explanations of Delinquency*

Cinquante‐six garçons du secondaire ont expliqué pourquoi ils avaient perpétré ou non certains actes de délinquance (combat, vandalisme, vol à l'étalage, usage de drogues). Ils ont aussi ciblé des théories sociologiques de la délinquance qui s'appliquent à leur comportement. Leurs réponses montrent que les deux types de données se recoupent beaucoup. L'effort, la théorie gánérate, les pairs, le contrôle social, les techniques de neutralisation et la prévention sont importants, mais non l'étiquetage ni l'imitation des médias. Une théorie de contingence de la délinquance est proposée. Fifty‐six high school boys were asked to explain in their own words why they had engaged in or refrained from certain delinquencies: fighting, vandalism, petty theft, truancy and drug use. They were also given the opportunity, via a checklist, to tell whether selected sociological theories applied to their behaviour. Their responses revealed considerable overlap in the two forms of data. Strain, general theory, peers, social control, techniques of neutralization and deterrence are important in varying combinations. Labelling and media imitation are not. A contingency theory of delinquency is proposed.     

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well-known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given.     

The extended enterprise-a context for manufacturing

Today's manufacturing enterprises face tremendous competitive pressures. Global competition, together with market demands for customized products delivered just in time, place tremendous pressures on manufacturers. The emerging global economy is rapidly replacing local markets. The emergence of open markets, reductions in trade barriers, and improvements in transportation and communications links have led to a situation where local competition and markets operate in the context of global standards. This open infrastructure allows manufacturers to respond to these challenges by working more closely with their suppliers and customers, and by building extended enterprises across the whole value chain. Such extended enterprises present great challenges in terms of redesigning business processes to create a competitive advantage from the linkages they include. This paper describes the manufacturing philosophies currently in vogue. Any manufacturing or related business will need to use them, albeit tailored to its own circumstances, in one form or the other, to ensure its prosperity.     

A Measure of partial association between disease and genotype for the two-parent problem

The two-parent disease-genotype association problem is studied from the point of view of a coefficient of association between the disease phenotype of the child and the disease phenotypes of the parents, in the presence of some genotypic information about the parents. This coefficient of partial association is derived, and certain tests of hypotheses are constructed. The results are shown to be useful in estimation of recurrence risks, and in understanding the nature of the association between child and parental disease phenotypes.     

Community Organization Project for the Development of Aborigines in an Area North and North-East of Alice Springs

It is recognized in the field of social work that institutionalization of any people produces certain negative and detrimental patterns of behaviour. In geriatrics present practice is away from institutionalization. The aged are encouraged to find employment or interests and to move out of institutions. Emphasis is placed upon individual flats and self-care with any supportive services that are necessary. More and more the emphasis in child care is upon foster care in ordinary homes scattered through the general community and culture to which the children belong.     

Robust F-tests for linear models

The author presents a robust F-test for comparing nested linear models. It is suggested that the approach will be attractive to practitioners because it is based on the familiar F-statistic and corresponds to the common practice of reporting F-statistics after removing obvious outliers. It is calibrated in terms of a real parameter that can be directly interpreted as the willingness of the data analyst to remove observations, and the sensitivity of the F-statistic to this parameter is easily examined. The procedure is evaluated with a simulation study where a scale mixture distribution is used to generate outliers. The procedure is also applied to some data where the occurrence of an outlier is confounded with the significance of a regression term. This provides a comparison of two competing models for the data: one removing an outlier and the other including an additional regression term instead.