Economic impact report for proposed regulations, coil coating segment of machinery and mechanical products point source category /

"December 10, 1980."

Radiological emergency response operations course (category IV) for radiological emergency response teams.

Mode of access: Internet.

Coloramatrix : a thermally controlled liquid crystal alphanumeric display /

"June, 1971."

American National Standard N43.10 : safe design and use of panoramic, wet source storage gamma irradiators (category IV).

Item 245.

Voluntary products standards : an index based on hazard category /

Mode of access: Internet.

C-130BL category I performance test and qualitative stability and control evaluation /

"February 1961."

Elem. dropouts by grade, gender and racial/ethnic category and dropout rates for ...

Description based on 1991-1992; title from caption.

On a category of transformation groups in three and four dimens...

Thesis (doctoral)--

American National Standard N433.1 : safe design and use of self-contained, dry source storage gamma irradiators (category I).

Issued July 1978.

Nonstationary brand variables in category management: A cointegration perspective

Category-management models serve to assist in the development of plans for pricing and promotions of individual brands. Techniques to solve the models can have problems of accuracy and interpretability because they are susceptible to spurious regression problems due to nonstationary time-series data. Improperly stated nonstationary systems can reduce the accuracy of the forecasts and undermine the interpretation of the results. This is problematic because recent studies indicate that sales are often a nonstationary time-series. Newly developed correction techniques can account for nonstationarity by incorporating error-correction terms into the model when using a Bayesian Vector Error-Correction Model. The benefit of using such a technique is that shocks to control variates can be separated into permanent and temporary effects and allow cointegration of series for analysis purposes. Analysis of a brand data set indicates that this is important even at the brand level. Thus, additional information is generated that allows a decision maker to examine controllable variables in terms of whether they influence sales over a short or long duration. Only products that are nonstationary in sales volume can be manipulated for long-term profit gain, and promotions must be cointegrated with brand sales volume. The brand data set is used to explore the capabilities and interpretation of cointegration.

Locating cosmopolitanism - Between humanist ideal and grounded social category

The emerging interdisciplinary body of cosmopolitanism research has established a promising field of theoretical endeavour by bringing into focus questions concerning globalization, nationalism, population movements, cultural values and identity. Yet, despite its potential importance, what characterizes recent cosmopolitanism research is an idealist sentiment that considerably marginalizes the significance of the structures of nation-state and citizenship, while leaving unspecified the empirical sociological dimensions of cosmopolitanism itself. Our critique aims at making cosmopolitanism a more productive analytical tool. We argue for a cosmopolitanism that consists of conceptually and empirically identifiable values and outlooks. While there has been some progress made in this direction in the recent literature on cosmopolitanism, most writing still considers cosmopolitanism as something so delicate that it cannot be measured. Furthermore, in order to appreciate the full currency of the concept, we argue that researchers must not only agree on some common determinants of cosmopolitanism and cosmopolitan dispositions, but also ground their analyses of cosmopolitanism in the context of enduring nation-state structures.

From complexity to category: Responding to diagnostic uncertainties of autistic spectrum disorders

Objective: Recent data from Education Queensland has identified rising numbers of children receiving diagnoses of autistic spectrum disorder (ASD). Faced with funding diagnostic pressures, in clinical situations that are complex and inherently uncertain, it is possible that specialists err on the side of a positive diagnosis. This study examines the extent to which possible overinclusion of ASD diagnosis may exist in the presence of uncertainty and factors potentially related to this practice in Queensland. Methods: Using anonymous self-report, all Queensland child psychiatrists and paediatricians who see paediatric patients with development/behavioural problems were surveyed and asked whether they had ever specified an ASD diagnosis in the presence of diagnostic uncertainty. Using logistic regression, elicited responses to the diagnostic uncertainty questions were related to other clinical- and practice-related characteristics. Results: Overall, 58% of surveyed psychiatrists and paediatricians indicated that, in the face of diagnostic uncertainty, they had erred on the side of providing an ASD diagnosis for educational ascertainment and 36% of clinicians had provided an autism diagnosis for Carer's Allowance when Centrelink diagnostic specifications had not been met. Conclusion: In the absence of definitive biological markers, ASD remains a behavioural diagnosis that is often complex and uncertain. In response to systems that demand a categorical diagnostic response, specialists are providing ASD diagnoses, even when uncertain. The motivation for this practice appears to be a clinical risk/benefit analysis of what will achieve the best outcomes for children. It is likely that these practices will continue unless systems change eligibility to funding based on functional impairment rather than medical diagnostic categories.

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.