State estimation for nonlinear state-space transmission models of tuberculosis

Given the high prevalence of tuberculosis (TB) and the mortality rate associated with the disease, numerous models, such as the Gammaitoni and Nucci (GN) model, were developed to model the risk of transmission. These models typically rely on a quanta generation rate as a measurement of infectivity. Since the quanta generation rate cannot be measured directly, the unique contribution of this work is to develop state estimators to estimate the quanta generation rate from available measurements. To estimate the quanta generation rate, the GN model is adapted into an augmented single-room GN model and a simplified two-room GN model. Both models are shown to be observable, i.e., it is theoretically possible to estimate the quanta generation rate given available measurements. Kalman filters are used to estimate the quanta generation rate. First, a continuous-time extended Kalman filter is used for both adapted models using a simulation and measurement sampling rate of 60 s. Accurate quanta generate rate estimates are achieved in both cases. A more realistic scenario is also considered with a measurement sampling rate of one day. For these estimates, a hybrid extended Kalman filter (HEKF) is used. Accurate quanta generation rate estimates are achieved for the more realistic scenario. Future work could potentially use the HEKFs, the adapted models, and real-time measurements in a control system feedback loop to reduce the transmission of TB in confined spaces such as hospitals.     

A Note on Interpersonal and Communication Skills for IS Professionals: Evidence of Positive Influence

A recent article by Byrd and Turner (2001) reported that interpersonal skills on the part of information systems personnel had a negative influence on the success of systems as measured by competitive advantage. Several reasons were forwarded to account for this unexpected result, including lack of richness in the measure of these skills, the use of strategic success measures, the true complexity of interpersonal relations within an organization, and the sample of CIOs who may have a bias in favor of technical skills. We address these concerns by incorporating a set of communication skills into the interpersonal skills set, sampling users for a different set of stakeholders, and employing a more complex model based on theories of expectation. The results indicate that the impacts of interpersonal skills on system success is not a simple function of the perceived level of the IS staff's skill proficiency but is also determined by the understood expectations of skill requirements.     

Factor structure of the Mini-Maternal Behavior Q-Sort and associations with infant attachment: Informing precision in research and intervention

We examined the factor structure of parental sensitivity to infants as assessed by the Mini-Maternal Behavior Q-Sort (Mini-MBQS), a 25-item short-form of the original 90-item MBQS. We aimed to: (1) identify latent factors of the Mini-MBQS; and (2) validate each factor by testing associations with infant attachment classifications. Data on parent-infant dyads (n = 313; 222 mothers with 281 children, 29 fathers with 32 children) were drawn from a three-generation Australian cohort study. Exploratory Factor Analysis and Exploratory Structural Equation Modelling examined the structure of the Mini-MBQS. Two latent Mini-MBQS factors were identified, requiring 8 of 25 original items: (1) Attention and Responsiveness and (2) Contingency in Interactions. Infants with insecure attachment classifications had parents with lower sensitivity across both factors relative to infants classified secure. In particular, infants with resistant attachment classifications had parents with notably low Contingency in Interactions scores. Infants with disorganised attachment classifications had parents with the lowest relative sensitivity across both factors, and in these dyads Attention and Responsiveness scores were especially low. Results provide an empirically derived factor structure for the Mini-MBQS. Two subscales, each with significant infant attachment associations, may improve precision in clinical intervention and research translation.     

Sensitivity analyses for the principal ignorability assumption using multiple imputation

In the context of clinical trials, there is interest in the treatment effect for subpopulations of patients defined by intercurrent events, namely disease-related events occurring after treatment initiation that affect either the interpretation or the existence of endpoints. With the principal stratum strategy, the ICH E9(R1) guideline introduces a formal framework in drug development for defining treatment effects in such subpopulations. Statistical estimation of the treatment effect can be performed based on the principal ignorability assumption using multiple imputation approaches. Principal ignorability is a conditional independence assumption that cannot be directly verified; therefore, it is crucial to evaluate the robustness of results to deviations from this assumption. As a sensitivity analysis, we propose a joint model that multiply imputes the principal stratum membership and the outcome variable while allowing different levels of violation of the principal ignorability assumption. We illustrate with a simulation study that the joint imputation model-based approaches are superior to naive subpopulation analyses. Motivated by an oncology clinical trial, we implement the sensitivity analysis on a time-to-event outcome to assess the treatment effect in the subpopulation of patients who discontinued due to adverse events using a synthetic dataset. Finally, we explore the potential usage and provide interpretation of such analyses in clinical settings, as well as possible extension of such models in more general cases.     

A Transaction‐Efficiency Analysis of an Internet Retailing Supply Chain in the Music CD Industry*

The emergence of the Internet may have fundamentally altered the mechanisms underlying information exchanges between sellers and end consumers. However, little attention has been given to the impact these mechanisms have on the efficiency of supply chain operations. This paper begins to address this deficiency in the literature by evaluating supply chain transaction efficiency effects from Internet purchases by consumers. It develops and empirically tests a theoretical framework examining the role Internet purchases have in establishing transaction‐efficiency levels in product exchanges involving sellers, placed at different supply chain echelons, and consumers. The theoretical framework integrates the transaction‐cost and internet economics, inter‐organizational information systems, and supply chain management literatures. Empirical testing, via structural equation modeling, is based on archival data in the Internet music CD market. The results show that Internet‐mediated purchases by consumers allow for greater transaction efficiencies when inventory ownership is postponed farther upstream in the supply chain and supply chain echelons are disintermediated. The results also indicate that channel structure configuration, defined by the supply chains' Internet retailing echelon, moderates these transaction efficiency effects.