Dynamic sampling plans in on-line control charts

Three simple dynamic sampling plans for detecting the change point are investigated in the discrete-time case. The first is a two-rate sampling CUSUM procedure. The second is a two-rate sampling Shiryayev-Roberts procedure. The third is a periodic sequential testing procedure. Two problems are discussed. First, simple design methods are provided for practical use. Second, a comparison between the three plans is made in the continuous-time case, which shows that by properly choosing the design parameters, the three plans can be made equally efficient in certain senses.     

Estimation of the MSE matrix of the stein estimator

Uniformly minimum-variance unbiased (UMVU) estimators of the total risk and the mean-squared-error (MSE) matrix of the Stein estimator for the multivariate normal mean with unknown covariance matrix are proposed. The estimated MSE matrix is helpful in identifying the components which contribute most to the total risk. It also contains information about the performance of the shrinkage estimator with respect to other quadratic loss functions.     

Effect of equicorrelation in detecting a spurious observation

This note examines the effect of equicorrelation of the observations on Grubbs' (1950) procedure of detecting an outlier in a sample of n independent observations. It is shown that the procedure is robust, in fact the significance level remains unchanged.     

Akaike Information Criterion for Selecting Variables in the Nested Error Regression Model

The Akaike Information Criterion (AIC) is developed for selecting the variables of the nested error regression model where an unobservable random effect is present. Using the idea of decomposing the likelihood into two parts of “within” and “between” analysis of variance, we derive the AIC when the number of groups is large and the ratio of the variances of the random effects and the random errors is an unknown parameter. The proposed AIC is compared, using simulation, with Mallows' C _p , Akaike's AIC, and Sugiura's exact AIC. Based on the rates of selecting the true model, it is shown that the proposed AIC performs better.     

Segmentation,alignment and statistical analysis of biosignals with application to disease classification

We present a novel methodology for a comprehensive statistical analysis of approximately periodic biosignal data. There are two main challenges in such analysis: (1) the automatic extraction (segmentation) of cycles from long, cyclostationary biosignals and (2) the subsequent statistical analysis, which in many cases involves the separation of temporal and amplitude variabilities. The proposed framework provides a principled approach for statistical analysis of such signals, which in turn allows for an efficient cycle segmentation algorithm. This is achieved using a convenient representation of functions called the square-root velocity function (SRVF). The segmented cycles, represented by SRVFs, are temporally aligned using the notion of the Karcher mean, which in turn allows for more efficient statistical summaries of signals. We show the strengths of this method through various disease classification experiments. In the case of myocardial infarction detection and localization, we show that our method compares favorably to methods described in the current literature.     

Understanding vaccine knowledge,attitudes, and decision-making through college student interviews

Abstract

Objective: We aimed to explore knowledge, attitudes, and beliefs about vaccines required for college-entry and vaccine-related behaviors among college students. Participants: Thirty-three full-time undergraduate students, ≥ 18 years old, enrolled at public (2) and private (3) colleges and universities in metropolitan Philadelphia in fall 2016. Methods: We conducted semistructured interviews, which were double-coded with 5,015 comments overall and 99.3% intercoder reliability (κ?=?0.779) using NVivo 11 software. Results: Six key themes emerged: (1) low knowledge about vaccines and requirements; (2) mixed attitudes about required vs. recommended vaccines; (3) high trust in medical professionals; (4) low perceived risk for vaccine-preventable disease outbreaks; (5) substantial parental influence on students’ decision-making; and (6) low utilization of Student Health Services. Conclusions: This study revealed lack of knowledge about and low prioritization of vaccination despite overall positive attitudes towards vaccines. Prematriculation education of college students is critical to increasing vaccine knowledge and use.     

The impact of forest to urban land conversion on streamflow, total nitrogen, total phosphorus, and total organic carbon inputs to the converse reservoir, Southern Alabama, USA

High total organic carbon (TOC) concentrations in Converse Reservoir, a water source for Mobile, Alabama, have concerned water treatment officials due to the potential for disinfection byproduct (DBP) formation. TOC reacts with chlorine during drinking water treatment to form DBPs. This study evaluated how increased urbanization can alter watershed-derived total nitrogen (TN), total phosphorus (TP) and TOC inputs to the Converse Reservoir. Converse Watershed, on the urban fringe of Mobile, is projected to undergo urbanization increasing watershed urban land from 3% in 1992 to 22% urban land by 2020. A pre-urbanization scenario using 1992 land cover was coupled with 2020 projections of land use. The Loading Simulation Program C++ watershed model was used to evaluate changes in nutrient concentrations (mg L^?1) and loads (kg) to Converse Reservoir. Urban and suburban growth of 52 km² simulated from 1991 to 2005 (15 year) caused overall TN and TP loads to increase by 109 and 62%, respectively. Simulated urban growth generally increased monthly flows by 15%, but resulted in lower streamflows (2.9%) during drought months. Results indicate that post-urbanization median TN and TP concentrations were 59 and 66% higher than corresponding pre-urbanization concentrations, whereas TOC concentrations were 16% lower. An increase in urban flow caused TOC loads to increase by 26%, despite lower post-urbanization TOC concentrations.     

Evidence for a curvilinear relationship between abusive supervision and creativity in South Korea

Applying activation theory, this study examined the possibility of a curvilinear relationship between abusive supervision and employee creativity. Using survey responses of 203 subordinate–supervisor dyads in South Korea, hierarchical regression analyses demonstrated a curvilinear (inverted U-shaped) relationship between a supervisor's abusive behaviors and an employee's creative performance. Specifically, employees exhibited more creativity when abusive supervision was at a moderate level rather than at very low or very high levels. Implications for theory and practice are discussed.     

Properties of the mixed regression estimator when disturbances are not necessarily normal

Small-disturbance approximations for the bias vector and mean squared error matrix of the mixed regression estimator for the coefficients in a linear regression model are derived and efficiency with respect to least squares estimator is examined.