Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.     

The use of statistics to examine the association between fluoride in drinking water and cancer death rates

"The basis of statistical tests of significance of association between fluoride level in drinking water and cancer death rates is discussed. Reference is made to two reported studies in each of which cancer death rates of a number of [U.S.] cities were used. It is argued that between city variation should be taken into account when performing tests of significance. In one of the two studies this was done informally; in the other between city variation was ignored."     

Applying State Space to SPC: Monitoring Multivariate Time Series

Monitoring cross-sectional and serially interdependent processes has become a new issue in statistical process control (SPC). In up-to-date SPC literature, Kalman filtering was reported to monitor univariate autocorrelated processes. This paper applies a Kalman filter or state-space method for SPC to monitoring multivariate time series. We use Aoki's approach to estimate the parameter matrices of a state-space model. Multivariate Hotelling T ² control charts are employed to monitor the residuals of the state-space. Examples of this approach are illustrated.     

Alternative Factors for Control Chart Construction

Conflicting decision signals resulting from Shewhart Mean and Variability Control Charts produce undesirable consequences. Therefore, we construct “six-sigma” control charts by alternative methods to avoid problems associated with Control Charts yielding different signals. By adjusting methods for control chart construction for dispersion charts, we produce new reference tables. The new tables provide consistent signals and appear similar and familiar to users of historical tables.     

Production as social change: Policy sociology as a public good

ABSTRACT

Burawoy described two ways sociology can aid the public, through: (1) instrumental (policy) sociology and (2) reflexive (public) sociology. This article elaborates the different assumptions of how social change occurs according to policy and public sociology (and how sociology effects social change). Policy sociology assumes social change occurs through the scientific elaboration of the best means to achieve goals. However, policy sociology largely takes the public as an object of power rather than subjects who can utilize scientific knowledge. Public sociology assumes that social change occurs through the exposure of contradictions in goals, which elaborates better goals. However, the elaboration of contradictions assumes that there is a fundamental thesis/antithesis in society. If there are multiple goals/theses, public sociology fails in at least three ways. Policy sociology, when reflexively selecting its public, provides the best way sociology can aid the public.     

A REVIEW OF BOUNDS FOR THE EFFICIENCY FACTOR OF BLOCK DESIGNS

This paper draws together bounds for the efficiency factor of block designs, starting with the papers of Conniffe & Stone (1974) and Williams & Patterson (1977). By extending the methods of Jarrett (1983), firstly to cover supercomplete block designs and then to cover resolvable designs, a set of bounds is obtained which provides the best current bounds for any block design with equal replication and equal block size, including resolvable designs and two-replicate resolvable designs as special cases. The bounds given for non-resolvable designs apply strictly only to designs which are either regular-graph (John & Mitchell, 1977) or whose duals are regular-graph. It is conjectured (John & Williams, 1982) that they are in fact global bounds. Similar qualifications apply to the bounds for resolvable designs.     

In the Mix,Yet on the Margins: The Place of Families in Urban Neighborhood and Child Development Research

In the 1990s, the most popular theoretical and empirical research issue concerning the local ecologies of families focused on the impact of family structures (e.g., household composition) and processes (e.g., child management strategies) on the relationship between urban neighborhoods and child and adolescent development. In this article, we synthesize and critically examine the decade's prevailing literature on the topic, organizing this review into three areas: (a) the research designs of quantitative and ethnographic studies of urban neighborhoods, families, and child outcomes; (b) the conceptual approaches used in these studies; and (c) the role of structural and behavioral features of family and parenting as factors that influence the relationship between urban neighborhoods and child development in ethnically and racially diverse populations. Results suggest that although family has been center stage in the neighborhood effects research question of the decade, it has remained on the margins in terms of theoretical and methodological specificity. Recommendations for future research are also offered.     

AN APPROACH TO COST—VOLUME—PROFIT ANALYSIS UNDER UNCERTAINTY*

Cost-Volume-Profit analysis is a tool of cost accountants aiding in the choice of an optimal course of action in the solution of a managerial problem. C-V-P is a limited analysis since all the needs of management in determining the optimal strategy are not fulfilled. Factors pertinent to the choice of the optimal strategy under uncertainty are variables, although traditional C-V-P treats these factors as constants. Hence, an approach to C-V-P where pertinent factors necessary for decision making are considered as variables is more desirable than traditional C-V-P. By introducing uncertainty, it is also beneficial to broaden C-V-P to fulfill the following desire of management. Should management choose a course of action based only on its own estimates of the decision parameters or is it advisable to postpone a terminal decision until additional research into the decision parameters is accomplished? Broadened C-V-P solves this problem with the aid of Bayesian Decision Theory for the choice of the optimal course of action in the face of uncertainty.