Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression

Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters and their uncertainty estimates depend upon the underlying error variance structure in the model. Typically, a priori the researcher would not know if the error variances are homoscedastic (i.e., constant across dose) or if they are heteroscedastic (i.e., the variance is a function of dose). Motivated by this concern, in this paper we introduce an estimation procedure based on preliminary test which selects an appropriate estimation procedure accounting for the underlying error variance structure. Since outliers and influential observations are common in toxicological data, the proposed methodology uses M-estimators. The asymptotic properties of the preliminary test estimator are investigated; in particular its asymptotic covariance matrix is derived. The performance of the proposed estimator is compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using a data set obtained from the National Toxicology Program.     

Expressing Gambling-Related Cognitive Biases in Motor Behaviour: Rolling Dice to Win Prizes

Cognitive perspectives on gambling propose that biased thinking plays a significant role in sustaining gambling participation and, in vulnerable individuals, gambling problems. One prominent set of cognitive biases include illusions of control involving beliefs that it is possible to influence random gaming events. Sociologists have reported that (some) gamblers believe that it is possible to throw dice in different ways to achieve gaming outcomes (e.g., ‘dice-setting’ in craps). However, experimental demonstrations of these phenomena are lacking. Here, we asked regular gamblers to roll a computer-simulated, but fair, 6 sided die for monetary prizes. Gamblers allowed the die to roll for longer when attempting to win higher value bets, and when attempting to hit high winning numbers. This behaviour was exaggerated in gamblers motivated to keep gambling following the experience of almost-winning in gambling games. These results suggest that gambling cognitive biases find expression in the motor behaviour of rolling dice for monetary prizes, possibly reflecting embodied substrates.     

A modified LGB method for detecting significant effects based on a half-normal probability plot

In analyzing data from unreplicated factorial designs, the half-normal probability plot is commonly used to screen for the ‘vital few’ effects. Recently, many formal methods have been proposed to overcome the subjectivity of this plot. Lawson (1998) (hereafter denoted as LGB) suggested a hybrid method based on the half-normal probability plot, which is a blend of Lenth (1989) and Loh (1992) method. The method consists of fitting a simple least squares line to the inliers, which are determined by the Lenth method. The effects exceeding the prediction limits based on the fitted line are candidates for the vital few effects. To improve the accuracy of partitioning the effects into inliers and outliers, we propose a modified LGB method (hereafter denoted as the Mod_LGB method), in which more outliers can be classified by using both the Carling’s modification of the box plot (Carling, 2000) and Lenth method. If no outlier exists or there is a wide range in the inliers as determined by the Lenth method, more outliers can be found by the Carling method. A simulation study is conducted in unreplicated $2^4$ designs with the number of active effects ranging from 1 to 6 to compare the efficiency of the Lenth method, original LGB methods, and the proposed modified version of the LGB method.     

How publics’ active and passive communicative behaviors affect their tornado responses: An integration of STOPS and SMCC

During imminent threat crises, such as natural disasters, publics have minutes to decide how to respond after receiving a warning. This study advances understanding of publics’ crisis communicative and noncommunicative behaviors in the context of tornadoes through combining and extending two theories: the social-mediated crisis communication (SMCC) model and the situational theory of problem solving (STOPS). Findings from a survey of Southeast U.S. residents (n = 1,585) indicate that STOPS is internally consistent and accurate at measuring its intended outcomes of communicative action in problem solving. However, the STOPS measures do not have a significant relationship with the desirable outcome for imminent threat crisis communication: individuals following government’s protective action guidance about tornadoes. In comparison, the expanded SMCC model predicts individuals’ self-reported compliance. Finally, variables from the SMCC model and tornado-specific variables were integrated into the STOPS model to explain individuals’ communicative engagement. Implications for theory and public relations practice are discussed.     

A balancing act in urban social-ecology: human appreciation,ponds and dragonflies

Green spaces in cities provide cultural ecosystems services (CES) such as nature connection, wildlife interaction and aesthetic appreciation which can improve aspects of human well-being. Recognising these benefits, researchers are now examining the complex relationship between humans and nature in urban social-ecology. Most studies investigate people’s appreciation and valuation of different green space features and their contribution to urban biodiversity. Recommendations arising from such studies are best practices to achieve a balance between landscape aesthetic and ecological objectives, but many knowledge gaps still exist. In a social-ecological project in Greater London, appreciation of ponds and dragonflies in urban green spaces, and the environmental factors determining dragonfly diversity were investigated. We found ponds and their appearance were valued by people as enhancing their green space experience. The preference for wild-looking ponds was moderate. Dragonflies were enjoyed for their colour and high visibility, especially by those who had basic dragonfly knowledge. Species richness of dragonflies was positively associated with habitat heterogeneity in and around a pond. However, people were unable to relate a heterogeneous pond to more dragonfly species. For the first time, some factors that influence the human appreciation-ponds-dragonflies (HPD) relationship in an urban context are revealed. To fully realise the CES potential of ponds and dragonflies in Greater London, a HPD framework is proposed. The framework underpins strategies that foster cultural sustainability for ponds and dragonfly conservation.     

A direct procedure for monitoring the coefficient of variation using a variable sample size scheme

A variable sample size (VSS) scheme directly monitoring the coefficient of variation (CV), instead of monitoring the transformed statistics, is proposed. Optimal chart parameters are computed based on two criteria: (i) minimizing the out-of-control ARL (ARL₁) and (ii) minimizing the out-of-control ASS (ASS₁). Then the performances are compared between these two criteria. The advantages of the proposed chart over the VSS chart based on the transformed statistics in the existing literature are: the former (i) provides an easier alternative as no transformation is involved and (ii) requires less number of observations to detect a shift when ASS₁ is minimized.     

Farmers' Contribution to Agricultural Social Capital: Evidence from Southern Spain

Social capital is the whole set of shared norms, values, attitudes, and beliefs that promote cooperation among individuals within the community and that has proved to be a key factor in explaining development processes. This article aims to provide an analytically reliable notion of social capital within the farming sector and a methodological tool for empirically measuring how social capital is accumulated at the farmer level. The theoretical framework proposed is based on the multidimensionality of the complex concept of social capital. Thus, to develop a comprehensive index for social capital, we identify three dimensions of the concept, structural, relational, and cognitive social capital, each one also comprising several subdimensions. This integrative approach permits creation of a composite indicator of the agricultural social capital accumulated at the farmer level, further identifying socioeconomic factors that influence its accumulation at that level. We empirically apply this methodological approach to farmers in Andalusia in southern Spain as a case study. This research provides an interesting starting point for informing policymakers about social capital and helping them implement the necessary programs to facilitate sustainable development in the agricultural sector.     

Individual and situational correlates of motivation for skills upgrading: an empirical study

The present research examines the tenability of a number of factors thought to precede an individual's motivation for skills upgrading. Because motivation for skills upgrading is instrumental to training success and is highly malleable, knowing the factors that precede motivation for skills upgrading would help managers and policy makers a great deal in formulating strategies to raise the competitiveness of the workforce. We derive several testable hypotheses from the existing literature and empirically verify the selected antecedents of motivation for skills upgrading. Results based on responses from 413 employees suggest that an individual's attitude towards skills upgrading, self-efficacy, usefulness of skills upgrading, health condition and long-term orientation are positively related to motivation for skills upgrading. Implications for policy makers, managers and researchers are discussed.     

On second-order improved estimation of a gamma scale parameter

This paper concludes our comprehensive study on point estimation of model parameters of a gamma distribution from a second-order decision theoretic point of view. It should be noted that efficient estimation of gamma model parameters for samples ‘not large’ is a challenging task since the exact sampling distributions of the maximum likelihood estimators and its variants are not known. Estimation of a gamma scale parameter has received less attention from the earlier researchers compared to shape parameter estimation. What we have observed here is that improved estimation of the shape parameter does not necessarily lead to improved scale estimation if a natural moment condition (which is also the maximum likelihood restriction) is satisfied. Therefore, this work deals with the gamma scale parameter estimation as a separate new problem, not as a by-product of the shape parameter estimation, and studies several estimators in terms of second-order risk.