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.     

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.     

Negotiating Gendered Subjectivity in the Enterprise Culture: Metaphor and Entrepreneurial Discourses

An enterprise culture is one in which ‘certain enterprising qualities — such as self reliance, personal responsibility, boldness and a willingness to take risks in the pursuit of goals — are regarded as human virtues and promoted as such’. Work is not seen as a constraint upon the individual but rather as an opportunity for self‐fulfilment. The pervasiveness of enterprise culture has led to observations that it influences aspects of social life beyond the workplace. However, the kind of self that is imagined in enterprise culture is also a male self, with female entrepreneurship measured against a male norm. In this article, then, we present evidence of metaphor as a strategy for coping with the gendered expectations embodied by life in enterprise culture. We show how metaphor is simultaneously an index of and a resource for understanding gendered subjectivities in enterprise culture.     

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.     

Gender differences and attitudes towards homosexuality

The aim of this research is two-fold. First, it examined individuals' attitudes towards homosexuals in Singapore. Second, it also investigated whether gender differences in attitudes towards homosexuals exist. Respondents comprised 365 students and data were collected through the use of questionnaires. Results generally suggested that respondents harboured negative attitudes towards homosexuals. The prevalence of such ambivalent attitudes seemed to suggest that respondents were still generally quite conservative in their attitudes towards gender roles and homosexuality. Our findings also revealed that, generally, women reported that they were more comfortable in working closely with male homosexuals while the reverse was true for men. Implications of our findings were discussed.     

Censored Kullback-Leibler Information and Goodness-of-Fit Test with Type II Censored Data

The Kulback-Leibler information has been considered for establishing goodness-of-fit test statistics, which have been shown to perform very well (Arizono & Ohta, 1989; Ebrahimi et al., 1992, etc). In this paper, we propose censored Kullback-Leibler information to generalize the discussion of the Kullback-Leibler information to the censored case. Then we establish a goodness-of-fit test statistic based on the censored Kullback-Leibler information with the type 2 censored data, and compare the test statistics with some existing test statistics for the exponential and normal distributions.