Learn More
We consider the problem of modeling point-level spatial count data with a large number of zeros. We develop a model that is compatible with scientific assumptions about the underlying data generating process. We utilize a two-stage spatial generalized linear mixed model framework for the counts, modeling incidence, resulting in 0-1 outcomes, and prevalence,(More)
Optimal experimental design procedures, utilizing criteria such as D-optimality, are useful for producing experimental designs for quantitative responses, often under nonstandard conditions such as constrained design spaces. However, these methods require a priori knowledge of the exact form of the response function, an often unrealistic assumption.(More)
1. Introduction. In the past few years we have been actively involved in redesigning our first level highly enrolled courses in statistics, including a) statistical literacy, b) introductory statistics, c) biostatistics, and d) engineering statistics. In each restructured course we have transferred responsibility for learning to the students, and provided(More)
OBJECTIVE The timely acknowledgement of critical patient clinical reports is vital for the delivery of safe patient care. With current EHR systems, critical reports reside on different screens. This leads to treatment delays and inefficient work flows. As a remedy, the R.A.P.I.D. (Root Aggregated Prioritized Information Display) system represents all data(More)
The motivation for engaging in peer review of teaching vacillates between providing opportunities to improve teaching and evaluating teaching performance. We strive to find ways to maximize the benefits of peer review of teaching because this activity provides a valuable opportunity for peer collaboration and curricular coordination within a program. This(More)
Finding the global optimum(s) of a non-convex function is of great importance in numerous applications in science and engineering where the function takes the form of an expensive computer code and its inputs are the independent variables. For this type of problem, Jones et al. [12] proposed the idea of expected improvement (EI) and embedded it in an(More)
Split-plot experiments are appropriate when some factors are more difficult and/or expensive to change than others. They require two levels of randomization resulting in a non-independent error structure. The design of such experiments has garnered much recent attention, including work on exact D-optimal split-plot designs. However, many of these procedures(More)