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.     

Factors of regional poverty reduction in Colombia: Do institutional conditions matter?

Colombia has a unique history, which has been heavily conditioned by armed conflict lasting more than 50 years. This study examines the institutional conditions for success and failure in reducing poverty in Colombian departments by considering changes that took place between 2003 and 2014. Fuzzy‐set qualitative comparative analysis identifies the changes in regional conditions that reduce poverty over time. The pathways for poverty reduction are multidimensional, and many involve changes in institutional attributes such as government transparency, absence of violence, and electoral turnout. The framework developed in this paper can be used to monitor necessary and sufficient pathways in regional clusters.     

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.     

Forecasting interest rates: a comparative assessment of some second-generation nonlinear models

Modeling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary methods such as ARMA and VAR, but only with moderate success. We examine here three methods, which account for several specific features of the real world asset prices such as nonstationarity and nonlinearity. Our three candidate methods are based, respectively, on a combined wavelet artificial neural network (WANN) analysis, a mixed spectrum (MS) analysis and nonlinear ARMA models with Fourier coefficients (FNLARMA). These models are applied to weekly data on interest rates in India and their forecasting performance is evaluated vis-à-vis three GARCH models [GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)] as well as the random walk model. Both the WANN and MS methods show marked improvement over other benchmark models, and may thus hold out several potentials for real world modeling and forecasting of financial data.     

Properties of systems with two exchangeable Pareto components

The life lengths of the units in a system can be modelled by a bivariate distribution. In this paper, we suppose that the joint distribution of the units is a symmetric bivariate Pareto (Lomax) distribution. For this model, we obtain basic reliability properties for series and parallel systems. J. M. Ruiz Partially Supported by Ministerio de Ciencia y Tecnologia under grant BFM2003-02947 and Fundacion Seneca under grant 00698/PI/04.     

An echelon inventory-based single-stage cost function for a two-station tandem system

We propose an alternative cost-accounting function for inventory control problems on a make-to-stock setting. Our proposal is based on observing that the traditional holding and backlog parameters introduce some odd short term distortions on the inventory state space. Our single-stage cost function accounts for echelon inventories and possesses a pair of cost parameters for each echelon inventory variable, depending on whether it is positive or negative. With the modified cost-accounting function, we study a twostation tandem system producing a single product, and investigate how it compares with the performances obtained with the usual single-stage cost function. The results available so far show that the optimal policies approach a multi-echelon base stock structure for each machine. Also, the service levels achieved are better under the modified function without increasing the levels of finished goods inventory.     

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.     

Quality of College Life (QCL) of Students: Further Validation of a Measure of Well-being

This paper reports a study designed to further validate a measure of quality of college life (QCL) of university students (Sirgy, Grzeskowiak, Rahtz, Soc Indic Res 80(2), 343–360, 2007). Two studies were conducted: a replication study and an extension study. The replication study involved surveys of 10 different college campuses in different countries. The results of the replication study provided additional nomological (predictive) validation support of the measure based on a theoretical model mapping out the antecedents and consequences of satisfaction with college life. With respect to the extension study, the focus was to further test the nomological validity of the QCL measure by arguing and empirically demonstrating that the consequence of QCL is life satisfaction. The extension study involved a survey of three college campuses in different countries. The results were also supportive of the nomological validity of the QCL measure.     

Back pack injuries in Indian school children: risk factors and clinical presentations

The use of backpack increased substantially among the school children. Studies have shown that carrying a backpack cause to develop different symptoms of musculoskeletal disorders among the carrier of the backpack. In India there are fewer studies available in literature which explains the musculoskeletal discomfort among the school children. This study aimed at to find out the prevalence of different musculoskeletal problems among the school children. In a retrospective study data were collected for twenty two students. The main diagnostic criteria were pressure mark (redness or swelling) over neck and shoulder corresponding to the straps of the backpack, stooping posture while carrying the back pack, pain or stiffness in the neck, upper back and shoulders predominantly while carrying the back pack and absence of these symptoms during school holidays. Results revealed that pain in the upper back (40%), neck (27%) and shoulder (20%) were most prevalent body regions followed by forearm and wrist pain (7%) and low back (6%). Results further revealed that all the students participated in this study have a pressure mark over shoulder. 54.55% of the children were diagnosed with myofascial pain and rest with thoracic outlet syndrome.     

A program to support the construction and evaluation of resilience indicators

The main objective of this work is to propose a method and a tool to support the development of indicators able to inform an organization about the state of its resilience through a cyclical process of identifying its resilience factors, proposing resilience indicators, assessing its organizational resilience followed by assessing and improving the resilience indicators. The research uses concepts from complex adaptive systems and from resilience engineering to establish an initial set of indicators able to assess elements that contribute to organizational resilience, and structures them temporarily as a hierarchy. A software application to support indicator definition and structuring, questionnaire generation, and result assessment activities was built to assist in speeding up the experiment-adjust cycle. Prototype indicators were instantiated with helicopter operating companies in mind, and were reviewed by a domain expert.