Spatial Sampling Design for a Demographic and Health Survey

The recent advances in global position systems (GPS), geographic information systems (GIS), and remote sensing (RS) can be exploited for spatial sampling design for demographic and health surveys. These technologies are particularly useful when a sampling frame is unavailable and/or location (of household) is important for data collection (e.g., location of residence might greatly impact exposure to ambient air pollution among members of a population). Building on these technologies, this article presents a methodology of spatial sampling adopted for the respiratory health and demographic survey conducted in Delhi and its environs from January through April 2004. The overall goal of the survey was to select households that adequately represented exposure to ambient air pollution. The proposed methodology involved constructing a sampling frame of residential areas and the simulation of weighted random points within residential areas. The simulated locations were navigated with the aid of GPS to identify households at these locations and to acquire residents’ consent to participate in the survey; a total of 1,576 households at the 2,000 simulated locations were found suitable and participated in the survey. The average ambient air pollution at the sample sites was not significantly different from the average air pollution observed in the study area, which demonstrates the robustness of the proposed sampling method.     

An Empirical,Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications

Multivariate simulations of a set of random variables are often needed for risk analysis. Given a historical data set, the goal is to develop simulations that reproduce the dependence structure in that data set so that the risk of potentially correlated factors can be evaluated. A nonparametric, copula‐based simulation approach is developed and exemplified. It can be applied to multiple variables or to spatial fields with arbitrary dependence structures and marginal densities. The nonparametric simulator uses logspline density estimation in the univariate setting, together with a sampling strategy to reproduce dependence across variables or spatial instances, through a nonparametric numerical approximation of the underlying copula function. The multivariate data vectors are assumed to be independent and identically distributed. A synthetic example is provided to illustrate the method, followed by an application to the risk of livestock losses in Mongolia.     

A new product growth model with a dynamic market potential

Traditional new product diffusion models have assumed a constant market potential over the planning horizon for forecasting product adoptions. This assumption is conceptually unsound and is likely to yield either theoretically unacceptable parameter estimates of the model or poor demand forecasts. This paper presents a dynamic growth model which relaxes this assumption. Model illustrations, limitations and further extensions are included.     

Open review of science publications

Publication of scientific research in print is traditionally peer reviewed anonymously prior to publication, which is a time-tested process but has serious limitations. The advent of the Internet permits postpublication open review online after minimal review by the editors or the author-selected reviewers, which can be quick, that permits the authors to revise the content. Most meritorious articles published online may be selected for publication in print as annual or biennial collections.     

Generalized Verbal Behavior Increases Following a Speaker Immersion Intervention

A goal of behavior-analytic interventions is to produce behavior that is maintained under naturalistic conditions. In this experiment, we studied the effects of a speaker immersion protocol (SIP) on the number of speaker responses (tacts and mands) emitted by 3 preschool students under naturalistic, not directly targeted, conditions. During the SIP, the researchers provided 100 daily opportunities for the participants to emit mands using the target mand form by contriving establishing operations (EOs) throughout the school day. The effects of the intervention were evaluated using a multiple-probe design by measuring target mands during EO probe sessions and the number of mands and tacts emitted during noninstructional-setting probe sessions. The researchers found that the SIP produced increases in both targeted and generalized verbal behavior.Electronic supplementary materialThe online version of this article (10.1007/s40616-020-00133-2) contains supplementary material, which is available to authorized users.     

A Comparison of the Predictive Validity of Procedures for Analyzing Binary Data

Some approaches for analyzing binary data are briefly described and compared. The results of two empirical investigations in the context of assessing consumer preferences and a simulation study yield some interesting findings. The article concludes with some directions for future research in this area.     

Union presence and executive compensation: An exploratory study

While executive compensation has historically attracted considerable attention and controversy, this issue is becoming increasingly more contentious as organizations attempt to cut labor costs through reengineering and downsizing. Unions, governments, and workers are becoming critical of seemingly excessive executive compensation while employees are asked to make concessions. In fact, many labor organizations are specif-ically targeting executive compensation for criticisms: Witness their web sites tracking executive pay and numerous press releases and public statements. However, do unions, through their presence in a firm, affect executive compensation? While there is con-siderable research on the determinants and correlates of executive compensation, the literature is silent on the role of unions. We investigate the distinctive effects of union presence with data on a sample of Canadianbased metalmining firms. The differences between union and nonunion firms, as well as the unique effects of union presence, are analyzed and future research suggested.     

Predicting System Usage from Intention and Past Use: Scale Issues in the Predictors

The objective of this study is to provide insights into how the predictive power for computer‐recorded system usage can be improved. Based on 386 responses from actual users of an information system, we examine the predictive power for system usage according to the scales of the predictors used, namely, intention and past use. First, we show that the predictive power of intention can be significantly improved with the choice of an appropriate measure. However, even the desirable intention measure failed to explain two‐thirds of the variance in system usage. Second, the results show that past use as measured by computer‐recorded log data can significantly enhance our ability to predict system usage. Finally, when both intention and past use are controlled for, the explained variance in system usage is shown to vary widely from 20% to 73%, depending on the predictors' scales. Overall, our findings suggest that an accurate prediction of system usage requires a more rigorous approach than that often applied in information systems research.