Endogeneity in Threshold Nonlinearity Tests

This article shows the conditions under which endogeneity of a regressor variable does not affect threshold nonlinearity tests. Inference on the values of the parameters derived from standard statistics is also appropriate. Simulation techniques are used to approximate the p-value of the test. Monte Carlo simulations confirm the validity of Wald tests in the presence of endogeneity in the regressors.     

Erratum

This study explores research methodology courses and their potential impact on the doctoral process in one university in Spain. Specifically, it analyses the role and usefulness of research methodologies courses for students as they prepare for their dissertation work. Data were collected using semi‐structured interviews with 11 students. Syllabi from five different doctoral programmes and 54 educational research projects conducted by students were also analysed. Contrary to prior research, our results indicate that students are motivated and interested in methodological matters. These courses are a valuable component to the doctoral programme providing general orientation to inquiry and aiding students in becoming educational researchers. Furthermore, we found that methodological pluralism was adopted and used by students in their research projects when this same pluralism was covered in their coursework. Implications for teaching research methodology courses are included.     

An ICT-Driven Hybrid Automation System for Elderly Care Support: A Rehabilitation Facility Study Case

Abstract

The demographic statistics in developed countries suggest growth in the elderly segment of the population. At the same time, other studies forecast a shortage of nurses, increasing the pressure on hospitals to provide treatment for longer periods of time. These trends suggest a need for new ways of taking care of the elderly population that support safe, comfortable, and independent living. Meanwhile, prominent advances in information and communications technology (ICT) have enabled new systems that address various needs of the elderly. This article presents a case study of a rehabilitation facility located in Tampere, Finland, that uses an automation system in which ambient assisted living (AAL) and building automation (BA) system functionalities are combined. It details a field study summarizing the needs of the users, describes functional scenarios supported by the system, and reports the results of the first usability tests suggesting acceptance of a new technology by residents and caregivers. The unique combination of ambient assisted living and building automation offers a safer and more comfortable environment for the elderly as well as helps caregivers on-site in managing their workloads.     

Marshall–Olkin q-Weibull distribution and max–min processes

In this paper, we introduce a new probability model known as Marshall–Olkin q-Weibull distribution. Various properties of the distribution and hazard rate functions are considered. The distribution is applied to model a biostatistical data. The corresponding time series models are developed to illustrate its application in times series modeling. We also develop different types of autoregressive processes with minification structure and max–min structure which can be applied to a rich variety of contexts in real life. Sample path properties are examined and generalization to higher orders are also made. The model is applied to a time series data on daily discharge of Neyyar river in Kerala, India.     

Competing Identities? Race,Ethnicity and Panethnicity Among Dominicans in the United States

In this paper we explore the racial and ethnic self-identification of Dominican immigrants in the United States. This issue is central in understanding how immigrants experience the process of incorporation into American society. We argue that as Dominican immigrants incorporate to American life, they adopt a Hispanic or Latino identity. This identity serves both as a form of racial identification within the American racial stratification system and as a form of assertive panethnic identity. This identity, however, does not supersede national identification, which remains the anchoring identity.     

Single cycle policies for the one-warehouse N-retailer inventory/distribution system

We address a multi-echelon inventory system with one-warehouse and N  -retailers. The demand at each retailer is assumed to be known and satisfied by the warehouse. Shortages are not allowed and lead times are negligible. Costs at each facility consist of a fixed charge per order and a holding cost. The goal is to determine single-cycle policies which minimize the average cost per unit time, that is, the sum of the average holding and setup costs per unit time at the retailers and at the warehouse. We propose a O(NlogN)$\mathrm{O}(N\log N)$ heuristic procedure to compute efficient single-cycle policies. This heuristic is compared with other approaches proposed by Schwarz, Graves and Schwarz and Muckstadt and Roundy. We carry out a computational study to test the effectiveness of the heuristic and to compare the performance of the different procedures. From the computational results, it is shown that the new heuristic provides, on average, better single-cycle policies than those given by the Muckstadt and Roundy method.     

Strategic and Organizational Evolution of Spanish Firms: Towards a Holding Network Form?

The main objective of this study is to analyse the strategic and organizational evolution of large firms in a current time period and within a specific geographical context (Spain). In order to achieve this purpose, the paper combines the Chandlerian programme with processual analysis. We draw on documentary sources (annual reports, company histories, business directories and so on) and interviews. We have found that in the model of corporate development some characteristics of new organizational structures will coexist with some features of old ones. In line with previous studies our findings highlight the existence of the 'multidivisional network' but, most importantly, our findings also reflect the emergence of a new kind of organizational form that we call 'holding network'. The 'holding network' is more decentralized, both strategically and operationally, than the multidivisional form. However, its level of decentralization is less than in the N-form. Furthermore, whereas the multidivisional form is a hierarchy, the 'holding network' emphasizes the communication among people of different levels. This multilevel communication differs from that in the N-form. Apart from the horizontal communication in the same level there is vertical and horizontal communication between different levels. We conclude by emphasizing the need to explore in future empirical studies to what extent these patterns and new organizational forms should be considered as a transitory or consolidated phenomenon.     

Bayesian compartmental model for an infectious disease with dynamic states of infection

Population-level proportions of individuals that fall at different points in the spectrum [of disease severity], from asymptomatic infection to severe disease, are often difficult to observe, but estimating these quantities can provide information about the nature and severity of the disease in a particular population. Logistic and multinomial regression techniques are often applied to infectious disease modeling of large populations and are suited to identifying variables associated with a particular disease or disease state. However, they are less appropriate for estimating infection state prevalence over time because they do not naturally accommodate known disease dynamics like duration of time an individual is infectious, heterogeneity in the risk of acquiring infection, and patterns of seasonality. We propose a Bayesian compartmental model to estimate latent infection state prevalence over time that easily incorporates known disease dynamics. We demonstrate how and why a stochastic compartmental model is a better approach for determining infection state proportions than multinomial regression is by using a novel method for estimating Bayes factors for models with high-dimensional parameter spaces. We provide an example using visceral leishmaniasis in Brazil and present an empirically-adjusted reproductive number for the infection.     

Living with zombie companies: Do we know where the threat lies?

This paper shows the existence of extreme types of zombie firm, i.e. companies with negative equity that continue to do business despite having lost their entire equity. We explain how these firms are measured and how the riskier ones are defined with different determinants. Using a Spanish sample from 2010 to 2014 an index called the EZIndex is developed that includes four dimensions of the extreme zombie problem: extension, contagion, recovery signs and immediacy. The paper contributes to zombie theory on the one hand by developing a method for ranking zombie firms based on risks and changes over time, and on the other hand by using a log-linear model to detect the riskiest corporate profiles out of all these risky firms. It demonstrates significant implications that need to be considered by the competent authorities not only in terms of their impact as a whole but also in regard to the particular profile of extreme zombie firms: they are less regulated, large and located in regions with large business fabrics.     

A novel quantification of information for longitudinal data analyzed by mixed‐effects modeling

Nonlinear mixed‐effects (NLME) modeling is one of the most powerful tools for analyzing longitudinal data especially under the sparse sampling design. The determinant of the Fisher information matrix is a commonly used global metric of the information that can be provided by the data under a given model. However, in clinical studies, it is also important to measure how much information the data provide for a certain parameter of interest under the assumed model, for example, the clearance in population pharmacokinetic models. This paper proposes a new, easy‐to‐interpret information metric, the “relative information” (RI), which is designed for specific parameters of a model and takes a value between 0% and 100%. We establish the relationship between interindividual variability for a specific parameter and the variance of the associated parameter estimator, demonstrating that, under a “perfect” experiment (eg, infinite samples or/and minimum experimental error), the RI and the variance of the model parameter estimator converge, respectively, to 100% and the ratio of the interindividual variability for that parameter and the number of subjects. Extensive simulation experiments and analyses of three real datasets show that our proposed RI metric can accurately characterize the information for parameters of interest for NLME models. The new information metric can be readily used to facilitate study designs and model diagnosis.