Maximum Value of Hotelling's T 2 Statistics Based on the Successive Differences Covariance Matrix Estimator

In statistical process control applications, the multivariate T ² control chart based on Hotelling's T ² statistic is useful for detecting the presence of special causes of variation. In particular, use of the T ² statistic based on the successive differences covariance matrix estimator has been shown to be very effective in detecting the presence of a sustained step or ramp shift in the mean vector. However, the exact distribution of this statistic is unknown. In this article, we derive the maximum value of the T ² statistic based on the successive differences covariance matrix estimator. This distributional property is crucial for calculating an approximate upper control limit of a T ² control chart based on successive differences, as described in Williams et al. (2006 Williams , J. D. , Woodall , W. H. , Birch , J. B. , Sullivan , J. H. ( 2006 ). On the distribution of T ² statistics based on successive differences . J. Qual. Technol. 38 : 217 – 229 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).     

Sample-size requirements for confidence bounds of prescribed precision on multivariate normal quantiles

The problem of setting confidence bounds on a central multivariate normal quantile is considered. It is shown that for the setting of exact confidence bounds of specified closeness to the quantile,the required minimum size of a normal sample is large and rises rapidly with the number of variates considered.     

A test for abrupt change in hazard regression models with Weibull baselines

We develop a likelihood ratio test for an abrupt change point in Weibull hazard functions with covariates, including the two-piece constant hazard as a special case. We first define the log-likelihood ratio test statistic as the supremum of the profile log-likelihood ratio process over the interval which may contain an unknown change point. Using local asymptotic normality (LAN) and empirical measure, we show that the profile log-likelihood ratio process converges weakly to a quadratic form of Gaussian processes. We determine the critical values of the test and discuss how the test can be used for model selection. We also illustrate the method using the Chronic Granulomatous Disease (CGD) data.     

Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

A pivotal characteristic of credit defaults that is ignored by most credit scoring models is the rarity of the event. The most widely used model to estimate the probability of default is the logistic regression model. Since the dependent variable represents a rare event, the logistic regression model shows relevant drawbacks, for example, underestimation of the default probability, which could be very risky for banks. In order to overcome these drawbacks, we propose the generalized extreme value regression model. In particular, in a generalized linear model (GLM) with the binary-dependent variable we suggest the quantile function of the GEV distribution as link function, so our attention is focused on the tail of the response curve for values close to one. The estimation procedure used is the maximum-likelihood method. This model accommodates skewness and it presents a generalisation of GLMs with complementary log–log link function. We analyse its performance by simulation studies. Finally, we apply the proposed model to empirical data on Italian small and medium enterprises.     

Learning in and from projects: the learning modes and a learning capability model

Abstract

The notion of ‘project delivery’ is well embedded in and across the management and organizational sciences literature – generating a narrative that reflects and recognizes the instrumental nature of projects and programmes in strategy execution. Project management, as a distinct and well-established body of research enquiry, has increasingly sought to focus our attention on the impacts of complexity, risk and uncertainty in projects; the corollary being a desideratum to strengthen our theoretical understanding of how insight and learning from projects may influence improvements to organizational efficiency. The wider literature suggests that organizational learning remains a challenging proposition, particularly in the context of organizations operating in environments of high complexity. In this paper, we enhance the conversation on organizational learning through a series of case studies, generating evidence of thirteen ‘learning modes’. The paper proposes that mature organizations tend to exhibit a greater number of learning modes and that there is a tendency to capture and socialize knowledge with a greater emphasis on the context of the learning situation rather than the learning artefact in isolation. The empirical evidence gathered in this paper forms the basis of a capability model, characterized by the thirteen modes of learning. The model intimates that learning occurs, and is more effective, when knowledge and information are enacted in practice through the learning modes which form a nucleus of the organizational learning capability. The research concludes with a 'call to action' that emphasizes the strategic importance of learning practices and routines in project oriented-organizations.     

Illustrating the Value of Critical Methodologies Through Third-sector Gender Studies: A Case for Pluralism

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - To encourage methodological pluralism in the field, this paper examines an illustrative sample of articles that apply...     

Indigenous research methodology – weaving a research interface

ABSTRACT

Indigenous research Knowledges and methodologies have existed over millennia, however it is only recently that Indigenous scholars have been able to challenge institutional Western hegemony to reclaim sovereignty in the research space. Despite the high volume of quantitative research describing Aboriginal and Torres Strait Islander health, there has been limited evaluation of the value added through incorporation of Indigenous Knowledges and methodologies. ‘Research at the interface’ has been discussed as an Indigenous research methodology for researchers to contextualise and inform their research practices, between Indigenous and Western systems of knowledge. In this article we address the significance of ‘research at the interface’ for Aboriginal and Torres Strait Islander research, as an exciting opportunity for innovation to ensure strength, self-determination and resilience for Aboriginal and Torres Strait Islander communities engaged in research. We also introduce weaving a methodology for ‘research at the interface’ as a process for conceptualising Indigenous and quantitative research methodologies at the interface.     

Sex Work in a Digital Era

In recent years, scholars have begun to investigate the role of digital technologies, namely the Internet, in facilitating growth in sexual commerce. Recent studies investigate the ways the Internet shapes the experiences of sex workers and how sex workers use the Internet to maximize profits and reduce risk exposure. Overall, scholars strategically frame sex work in a digital era in terms of affordances. In doing so, they can note the positive changes in the work experiences of these workers. However, I argue that this literature is altogether too optimistic, and in focusing primarily on the affordances of Internet‐based sex work, these scholars neglect the new dangers that emerge online. In addition, by focusing only on the online practices of escorts, these scholars paint a homogenized portrait of digital sex work and neglect the diversity of labor performed by sex workers. This literature also neglects the diversity among sex workers themselves (e.g., race, ethnicity, class, gender, age, and ability). In order to address these limitations, I make nine specific suggestions for future lines of inquiry.