Visualization for Large‐scale Gaussian Updates

In geostatistics and also in other applications in science and engineering, it is now common to perform updates on Gaussian process models with many thousands or even millions of components. These large‐scale inferences involve modelling, representational and computational challenges. We describe a visualization tool for large‐scale Gaussian updates, the ‘medal plot’. The medal plot shows the updated uncertainty at each observation location and also summarizes the sharing of information across observations, as a proxy for the sharing of information across the state vector (or latent process). As such, it reflects characteristics of both the observations and the statistical model. We illustrate with an application to assess mass trends in the Antarctic Ice Sheet, for which there are strong constraints from the observations and the physics.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Functional Partial Linear Single‐index Model

This paper deals with the problem of predicting the real‐valued response variable using explanatory variables containing both multivariate random variable and random curve. The proposed functional partial linear single‐index model treats the multivariate random variable as linear part and the random curve as functional single‐index part, respectively. To estimate the non‐parametric link function, the functional single‐index and the parameters in the linear part, a two‐stage estimation procedure is proposed. Compared with existing semi‐parametric methods, the proposed approach requires no initial estimation and iteration. Asymptotical properties are established for both the parameters in the linear part and the functional single‐index. The convergence rate for the non‐parametric link function is also given. In addition, asymptotical normality of the error variance is obtained that facilitates the construction of confidence region and hypothesis testing for the unknown parameter. Numerical experiments including simulation studies and a real‐data analysis are conducted to evaluate the empirical performance of the proposed method.     

Developing and testing a satisfaction survey for nursing home residents: the Ohio Experience

Input from consumers has become an important part of quality improvement in long-term care and for consumer decision-making. This paper documents the development of the Ohio Nursing Home Resident Satisfaction Survey (ONHRSS) through a partnership of state government, research, and industry experts. The instrument was tested and refined through two waves of data--a pretest phase and later with statewide data. Exploratory and confirmatory analyses with statewide data identified eight primary factors along with an underlying, secondary Global Satisfaction factor. Reliability of the domains ranged from .69 to .95. Recommendations for further refinement and testing of the instrument are discussed along with policy and practice implications.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

An autecological interpretation of the firm and its environment

Explaining the survival and failure of firms is an important issue for researchers and managers of firms in society. Ecological approaches to the study of firms have existed for over 100 years, and have been increasingly popular during the past 40 years, especially since the pioneering works of Hannan and Freeman on one hand, and Aldrich on the other. This paper, in keeping with recent developments elsewhere in mainstream ecology outlines and positions the theoretical and philosophical foundations of an alternative ecological approach, autecology, that has not yet been formulated for the study of firms. The autecological approach affords the individual firm more autonomy in creating its own future evolutionary trajectory. The idea of an ecological complex is developed to provide clear focus on what is central to the application of autecology to the study of firms. The paper also considers several emergent research opportunities that highlight the potential value of employing an autecological approach to the study of firms.     

Factors Preventing Gridlock in Chilean Couples’ Relationships Based on the Discourse of Couples Therapists and Highly Adjusted Couples

The term gridlock describes the occurrence of rigid patterns in couples’ conflict. This study aimed to describe strategies of conflict resolution and gridlock prevention from the perspectives of couples and couple therapists. Participants were couple therapists and highly adjusted couples scored by the dyadic adjustment scale (DAS), distributed according to traditional and non‐traditional position in life and duration of relationships. Conflict gridlock scenarios were used to create video stimulus that were presented to participants. A qualitative methodology was used to analyse couples’ and therapists’ commentaries on the scenarios. Results showed differences in preventing conflict gridlock among sub‐groups of couples. Long‐term traditional couples focused on loyalty to a common project and value sacrificing to a higher good; long‐term non‐traditional couples prioritised caring and validating the bond in the relationship. Short‐term traditional couples focused on mutual love and the relief of hurt while short‐term non‐traditional couples supported the value of equity.