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Full-Text Articles in Physical Sciences and Mathematics
Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott
Tennis Anyone? Teaching Experimental Design By Designing And Executing A Tennis Ball Experiment, Laura Pyott
Mathematics Faculty Publications
Understanding the abstract principles of statistical experimental design can challenge undergraduate students, especially when learned in a lecture setting. This article presents a concrete and easily replicated example of experimental design principles in action through a hands-on learning activity for students enrolled in an experimental design course. The activity, conducted during five 50-min classes, requires the students to work as a team to design and execute a simple and safe factorial experiment and collect and analyze the data. During three in-class design meetings, the students design and plan all aspects of the experiment, including choosing the response variable and factors, …
Evaluation Of Multiple Interventions Using A Stepped Wedge Design, Vivian H. Lyons, Lingyu Li, James Hughes, Ali Rowhani-Rahbar
Evaluation Of Multiple Interventions Using A Stepped Wedge Design, Vivian H. Lyons, Lingyu Li, James Hughes, Ali Rowhani-Rahbar
UW Biostatistics Working Paper Series
Background: Stepped wedge cluster randomized trials are a class of unidirectional crossover studies that have historically been limited to evaluating a single intervention. This design is especially suitable for pragmatic trials where the study feasibility can be improved with a phased introduction of the intervention. We examined variations of stepped wedge designs that would support evaluation of multiple interventions. Methods: We propose four different design variants for implementing a stepped wedge trial with two interventions: concurrent design, supplementation, replacement, and factorial designs. Analyses were conducted comparing the precision of the estimated intervention effects for the different designs. Results: Concurrent, …
High-Dimensional Repeated Measures, Martin Happ, Solomon W. Harrar, Arne C. Bathke
High-Dimensional Repeated Measures, Martin Happ, Solomon W. Harrar, Arne C. Bathke
Statistics Faculty Publications
Recently, new tests for main and simple treatment effects, time effects, and treatment by time interactions in possibly high-dimensional multigroup repeated-measures designs with unequal covariance matrices have been proposed. Technical details for using more than one between-subject and more than one within-subject factor are presented in this article. Furthermore, application to electroencephalography (EEG) data of a neurological study with two whole-plot factors (diagnosis and sex) and two subplot factors (variable and region) is shown with the R package HRM (high-dimensional repeated measures).
Application Of Factorial Design In The Analysis Of Factors Influencing Textile Dye Adsorption On Activated Carbon, Eid A. Alkhatib, Penny A. Snetsinger, Ahmad Alanazi, Sarah Aanonsen
Application Of Factorial Design In The Analysis Of Factors Influencing Textile Dye Adsorption On Activated Carbon, Eid A. Alkhatib, Penny A. Snetsinger, Ahmad Alanazi, Sarah Aanonsen
Chemistry & Physics Faculty Publications
In this study, the use of factorial design software is applied to evaluate efficiently factors influencing the adsorption capacity of activated carbon in treating textile dyes. Activated carbon is usually used to treat wastewater effluents from textile industries in order to remove textile dyes before discharge into the environment. Most treatment facilities, particularly large industrial or wastewater treatment facilities use continuous flow reactors or packed columns to treat the dye. Due to the limited residence time in these types of reactors, adsorption equilibrium is not necessarily reached, and the absorption rate becomes an important factor in this treatment process. Other …
On Adaptive Testing In Orthogonal Saturated Designs, Daniel T. Voss, Weizhen Wang
On Adaptive Testing In Orthogonal Saturated Designs, Daniel T. Voss, Weizhen Wang
Mathematics and Statistics Faculty Publications
Adaptive, size-a step-down tests are provided for the analysis of orthogonal saturated designs. The tests work effectively under effect sparsity, and include as special cases the individual nonadaptive tests of Berk and Picard (1991) and the simultaneous nonadaptive tests of Voss (1988). The approach is similar to that used by Wang and Voss (2003) to construct adaptive confidence intervals, but testing is simpler because one can use the same denominator for all statistics. Step-down tests also have a clear power advantage over simultaneous confidence intervals and analogous single-step tests, as is demonstrated theoretically and assessed via simulation.
On Adaptive Estimation In Orthogonal Saturated Designs, Weizhen Wang, Daniel T. Voss
On Adaptive Estimation In Orthogonal Saturated Designs, Weizhen Wang, Daniel T. Voss
Mathematics and Statistics Faculty Publications
A simple method is provided to construct a general class of individual and simultaneous confidence intervals for the effects in orthogonal saturated designs. These intervals use the data adaptively, maintain the confidence levels sharply at 1 - α at the least favorable parameter configuration, work effectively under effect sparsity, and include the intervals by Wang and Voss (2001) as a special case.
Control Of Error Rates In Adaptive Analysis Of Orthogonal Saturated Designs, Weizhen Wang, Daniel T. Voss
Control Of Error Rates In Adaptive Analysis Of Orthogonal Saturated Designs, Weizhen Wang, Daniel T. Voss
Mathematics and Statistics Faculty Publications
Individual and simultaneous confidence intervals using the data adaptively are constructed for the effects in orthogonal saturated designs under the assumption of effect sparsity. The minimum coverage probabilities of the intervals are equal to the nominal level 1 - α.