Dimensions Of Well-Being And Their Measurement: The Spf-Il Scale

What are the dimensions of well-being? That is, what universal goals need to be realized by individuals in order to enhance their well-being? Social production function (SPF) theory asserts that the universal goals affection, behavioral confirmation, status, comfort and stimulation are the relevant dimensions of subjective well-being. Realization of these substantive goals and the perspective on opportunities to realize these goals in the future contributes to the affective and cognitive component of well-being. The theoretical elaboration of this theory has been published elsewhere. This paper provides a measurement instrument for the dimensions of well-being. To measure levels of affection, behavioral confirmation, status, comfort and stimulation and empirically validate the dimensions of well-being, the SPF-IL scale was developed. This paper presents findings from a pilot study (n=145), the main study (n=1094), a test–retest examination (n=163), and a validation study (n=725). The measurement model was tested by means of structural equation modeling. Confirmatory factor analysis supported the dimensional structure of well-being indicating construct validity. The overall fit of the model was sufficient, in spite of the somewhat problematic measurement of status, and the test–retest study showed an acceptable level of stability. As for the content validity of the dimensions and their measurement, various sub-studies showed that the SPF-IL scale is a valid instrument, doing at least as well as popular measures of overall well-being but also specifying its dimensions.     

Reclassifying causes of death to study the epidemiological transition in The Netherlands, 1875–1992

This article describes a method for reclassifying causes of death in the Netherlands for the period 1875–1992. Two criteria should be met to obtain a useful classification to study the epidemiological transition. First, the categories should be nosologically continuous over the period under study and second, there should be enough detail in causes which are important in the context of the epidemiological transition viz. communicable diseases, non-communicable diseases and external causes of death. A method developed by Vallin and Meslé (1988), which involves ‘dual correspondence tables’ and ‘fundamental associations’, was used to create nosologically continuous categories. These categories were tested for statistical continuity during the transition years of one ICD-revision to the next, using ordinary least squares regression analysis. The reclassification procedure resulted in a nested classification consisting of three levels of refinement of causes of death: 27 causes, 1875–1992; 65 causes, 1901–1992; and 92 causes, 1931–1992. On the basis of this classification, 43% of all deaths in 1875–79 and 98% of all deaths in 1992 could be allocated to either communicable diseases, non-communicable diseases or external causes.     

A Flexible Evaluative Framework for Order Picking Systems

This paper develops a novel framework to evaluate the integral performance of order picking systems with different combinations of storage and order picking policies. The warehousing literature on order picking mostly considers minimizing either elapsed time or distance as the sole objective, whereas warehouse managers in a supply chain have to look beyond single‐dimensional performance and consider trade‐offs among different criteria. Thus managers still need a unified and efficient framework to select a portfolio of appropriate order picking policies from a multi‐criteria and contextual perspective. Our framework—combining data envelopment analysis, ranking and selection, and multiple comparisons—provides an efficient methodology to simultaneously analyze several interrelated problems in order picking systems with multiple performance attributes, such as service levels and operational costs. We demonstrate our approach through comprehensive evaluations of order picking policies in three low‐level, picker‐to‐parts rectangular warehouses facing demand variations.     

Identifying Technology Spillovers and Product Market Rivalry

The impact of R&D on growth through spillovers has been a major topic of economic research over the last thirty years. A central problem in the literature is that firm performance is affected by two countervailing “spillovers” : a positive effect from technology (knowledge) spillovers and a negative business stealing effects from product market rivals. We develop a general framework incorporating these two types of spillovers and implement this model using measures of a firm's position in technology space and productmarket space. Using panel data on U.S. firms, we show that technology spillovers quantitatively dominate, so that the gross social returns to R&D are at least twice as high as the private returns. We identify the causal effect of R&D spillovers by using changes in federal and state tax incentives for R&D. We also find that smaller firms generate lower social returns to R&D because they operate more in technological niches. Finally, we detail the desirable properties of an ideal spillover measure and how existing approaches, including our new Mahalanobis measure, compare to these criteria.     

Small sample study on estimators of life distributions and of mean survival times using randomly censored data

Whereas large-sample properties of the estimators of survival distributions using censored data have been studied by many authors, exact results for small samples have been difficult to obtain. In this paper we obtain the exact expression for the ath moment (a > 0) of the Bayes estimator of survival distribution using the censored data under proportional hazard model. Using the exact expression we compute the exact mean, variance and MSE of the Bayes estimator. Also two estimators ofthe mean survival time based on the Kaplan-Meier estimator and the Bayes estimator are compared for small samples under proportional hazards.     

Statistical Certification of Software Systems

Common software release procedures based on statistical techniques try to optimize the trade-off between further testing costs and costs due to remaining errors. We propose new software release procedures where the aim is to certify with a certain confidence level that the software does not contain errors. The underlying model is a discrete time model similar to the geometric Moranda model. The decisions are based on a mix of classical and Bayesian approaches to sequential testing and do not require any assumption on the initial number of errors.     

On the almost sure convergence for sums of negatively superadditive dependent random vectors in Hilbert spaces and its application

Abstract

This paper develops almost sure convergence for sums of negatively superadditive dependent random vectors in Hilbert spaces, we obtain Chung type SLLN and the Jaite type SLLN for sequences of negatively superadditive dependent random vectors in Hilbert spaces. Rate of convergence is studied through considering almost sure convergence to 0 of tail series. As an application, the almost sure convergence of degenerate von Mises-statistics is investigated.