Generalized propensity score approach to causal inference with spatial interference.

Many spatial phenomena exhibit interference, where exposures at one location may affect the response at other locations. Because interference violates the stable unit treatment value assumption, standard methods for causal inference do not apply. We propose a new causal framework to recover direct and spill-over effects in the presence of spatial interference, taking into account that exposures at nearby locations are more influential than exposures at locations further apart. Under the no unmeasured confounding assumption, we show that a generalized propensity score is sufficient to remove all measured confounding. To reduce dimensionality issues, we propose a Bayesian spline-based regression model accounting for a sufficient set of variables for the generalized propensity score. A simulation study demonstrates the accuracy and coverage properties. We apply the method to estimate the causal effect of wildland fires on air pollution in the Western United States over 2005-2018.

Copula-based robust optimal block designs.

Blocking is often used to reduce known variability in designed experiments by collecting together homogeneous experimental units. A common modeling assumption for such experiments is that responses from units within a block are dependent. Accounting for such dependencies in both the design of the experiment and the modeling of the resulting data when the response is not normally distributed can be challenging, particularly in terms of the computation required to find an optimal design. The application of copulas and marginal modeling provides a computationally efficient approach for estimating population-average treatment effects. Motivated by an experiment from materials testing, we develop and demonstrate designs with blocks of size two using copula models. Such designs are also important in applications ranging from microarray experiments to experiments on human eyes or limbs with naturally occurring blocks of size two. We present a methodology for design selection, make comparisons to existing approaches in the literature, and assess the robustness of the designs to modeling assumptions.

Smoke Sense Initiative Leverages Citizen Science to Address the Growing Wildfire-Related Public Health Problem.

Smoke Sense is a citizen science project with investigative, educational, and action-oriented objectives at the intersection of wildland fire smoke and public health. Participants engage with a smartphone application to explore current and forecast visualizations of air quality, learn about how to protect health from wildfire smoke, and record their smoke experiences, health symptoms, and behaviors taken to reduce their exposures to smoke. Through participation in the project, individuals engage in observing changes in their environment and recording changes in their health, thus facilitating progression on awareness of health effects of air pollution and adoption of desired health-promoting behaviors. Participants can also view what others are reporting. Data from the pilot season (1 August 2017 to 7 January 2018; 5,598 downloads) suggest that there is a clear demand for personally relevant data during wildfire episodes motivated by recognition of environmental hazard and the personal concern for health. However, while participants shared clear perceptions of the environmental hazard and health risks in general, they did not consistently recognize their own personal health risk. The engagement in health protective behavior was driven in response to symptoms rather than as preventive courses of action. We also observed clear differences in the adoption likelihood of various health protective behaviors attributed to barriers and perceived benefits of these actions. As users experience a greater number and severity of symptoms, the perceived benefits of taking health protective actions exceeded the costs associated with the barriers and thus increased adoption of those actions. Based on pilot season data, we summarize key insights which may improve current health risk communications in nudging individuals toward health protective behavior; there is a need to increase personal awareness of risk and compelling evidence that health protective behaviors are beneficial.

Explorer sharpness as related to margin evaluations.

Nine experienced operative dentistry faculty each used six different explorers of varying degrees of sharpness ranging from new to well-used to evaluate marginal acceptability on a device used to simulate gradations of vertical opening. In this study, the standard for the sharpest explorer point was determined to be 68 microns in diameter measured 40 microns from the tip. There was a positive correlation between the diameter of the explorer tip at 40 microns and the mean amount of opening that could be detected until the margin was declared unacceptable. Increased explorer dullness significantly handicapped even experienced graders when the explorer alone was used to evaluate visually inaccessible margins.

Fabrication of a crown to fit an existing partial denture using castable glass.

In this case report, an accepted technique was used to fabricate a crown to fit an existing removable partial denture in which castable glass was used instead of gold. The use of castable glass allowed the crown to be cast directly from a wax-acrylic pattern and eliminated the need for templates to produce accurate facial contours in porcelain. Although castable glass has limitations and cannot be used in all such situations, the material can be used in selected cases where esthetics is important.