Perceptions of the Benefits and Challenges of Purchasing Local Foods in the Iowa Hotel Industry

The purpose of this study was to explore hotel industry decision makers\u27 perceptions of benefits and challenges of purchasing locally produced foods in a Midwestern state. The Theory of Planned Behavior provided the theoretical framework for this study. Interviews were conducted with four full service and limited service hotels in Iowa. Mailed questionnaires were sent to 209 full service and limited service hotels in five Iowa counties which had active local food initiatives. Results showed that Perceived Behavior Control influenced decision makers\u27 Behavioral Intention, while there were not statistically significant influences of Attitudes and Subjective Norms on Behavioral Intention. Purchasing local foods were perceived as beneficial to the businesses, but decision makers experienced challenges such as, lack of information, budget constraints, inconsistent quality, and lack of established refund policies when purchasing local foods. This study provided insights into the needs of the hotel industry and addressing those needs will open new markets for local food producers

Food safety policies and procedures for student-led food events at colleges and universities in the United States

Many college students host student-led food events at colleges and universities (CUs) in the United States (U.S.), but research has shown that a lack of food safety knowledge among college students may result in unsafe food handling practices. While CUs in the U.S. may have food safety policies and procedures in place to ensure safe food handling practices for student-led food events during these events, there have been no research studies exploring their current food safety policies and procedures. This study is therefore aimed at exploring current food safety policies and procedures for student-led events at CUs in the U.S., and assessing similarities and differences in existing food safety policies and procedures for such events. The participants (n=231)were obtained by merging two sample clusters of land-grant universities: 120 land-grant CUs from a list provided by the United States Department of Agriculture-National Institute of Food and Agriculture and 190 CUs from a list of the Association of Public and Land-grant Universities. After eliminating redundancies in universities, a web-based questionnaire was emailed to 231 personnel responsible for overseeing student-led events at CUs in the U.S. Of the 86 questionnaires returned, 75 (32.5%) completed responses were usable with respect to results. Participants were knowledgeable about food safety practices/risks (9.25 ñ 0.29 out of ten possible points). Of the 75 participating CUs, 55 (73.3%) indicated that they sanctioned student-led food events and 40 (72.7%) had food safety policies and procedures in place. Statistical significant differences (p\u3c0.05) and practical significance (Cohen’s d ≥ 0.70) in attitudes towards food safety policies and procedures were identified by the number of registered student organizations at CUs during the 2016-2017 academic year. A content analysis was conducted to identify common and variable aspects in food safety policies and procedures for student-led food events presented on the 40 CU websites that had indicated in-place food safety and policies. As seen through the results, guidelines for proper food handling and adequate cooking were commonly presented on CU websites, whereas those for reliable food procurement sources and food safety related to contaminated equipment were not. While food safety policies were often presented on CU websites, procedures for addressing foodborne illness incidents or allegations were not. The results of this study provide knowledge about current food safety policies and procedures for student-led CU food events and describe similarities and differences among these policies and procedures. This study will provide guidance for the future development of a food safety policy and procedures template that can be used by CUs as a checklist for food safety preparedness of student-led food events

Efficient Case-Cohort Design using Balanced Sampling

A case-cohort design is a two-phase sampling design frequently used to analyze censored survival data in a cost-effective way, where a subcohort is usually selected using simple random sampling or stratified simple random sampling. In this paper, we propose an efficient sampling procedure based on balanced sampling when selecting a subcohort in a case-cohort design. A sample selected via a balanced sampling procedure automatically calibrates auxiliary variables. When fitting a Cox model, calibrating sampling weights has been shown to lead to more efficient estimators of the regression coefficients (Breslow et al., 2009a, b). The reduced variabilities over its counterpart with a simple random sampling are shown via extensive simulation experiments. The proposed design and estimation procedure are also illustrated with the well-known National Wilms Tumor Study dataset

Statistical methods for case-control and case-cohort studies with possibly correlated failure time data

In large cohort studies, the major effort and cost typically arise from the assembling of covariate measurements. Case-control and case-cohort study designs are widely used ones to reduce the cost and achieve the same goals in such studies, especially when the disease rate is low. In this dissertation, we consider analyzing the multivariate failure time data arising from case-control and case-cohort studies. First, we consider a case-control within cohort study with correlated failure times. A retrospective dental study was conducted to evaluate the effect of pulpal involvement on tooth survival (Caplan and Weintraub, 1997; Caplan et al., 2005). Due to the clustering of teeth, the survival times of the matched teeth within subjects could be correlated and thus the statistical methods for conventional case-control studies cannot not be directly applied. We study the marginal proportional hazards regression model for data from this type studies. Second, we consider a case-cohort study with multiple disease outcomes. A case-cohort design was implemented in the Busselton Health Study (Cullen, 1972) and it was of interest to study the relationship between serum ferritin and coronary heart disease and stroke events. Since times to coronary heart disease and stroke events observed from the same subject could be correlated, valid statistical method needs to take it into consideration. To this end, we consider marginal proportional hazards regression model. Third, we consider marginal additive hazards regression model for case-cohort studies with multiple disease outcomes. Most modern analyses of survival data focus on multiplicative models for relative risk using proportional hazards models. The additive hazards model, which model the risk differences has often been suggested as an alternative to the proportional hazards model. In each of the three cases, we propose a weighted estimating equation approach for model parameter estimation, with different types weights to enhance the efficiency. The asymptotic properties of the proposed estimators are derived and their finite sample properties are assessed via simulation studies. The proposed method are applied to the aforementioned dental study and the Busselton Health Study for illustration

Memory-Efficient Query Processing over XML Fragment Stream with Fragment Labeling

The portable/hand-held devices deployed in mobile computing environment are mostly limited in memory. To make it possible for them to locally process queries over a large volume of XML data, the data needs to be streamed in fragments of manageable size and the queries need to be processed over the stream with as little memory as possible. In this paper, we report a considerable improvement of the state-of-the-art techniques of query processing over XML fragment stream in memory efficiency. We use XML fragment labeling (XFL) as a method of representing XML fragmentation, and show that XFL is much more effective than the popular hole-filler (HF) model employed in the state-of-the-art in reducing the amount of memory required for query processing. The state-of-the-art with the HF model requires more memory as the stream size increases. With XFL, we overcome this fundamental limitation, proposing the techniques to make query processing scalable in the sense that memory requirement is not affected by the size of the stream as long as the stream is bounded. The improvement is verified through implementation and a detailed set of experiments

Marginal Hazards Regression for Retrospective Studies within Cohort with Possibly Correlated Failure Time Data

A retrospective dental study was conducted to evaluate the degree to which pulpal involvement affects tooth survival. Due to the clustering of teeth, the survival times within each subject could be correlated and thus the conventional method for the case–control studies cannot be directly applied. In this article, we propose a marginal model approach for this type of correlated case–control within cohort data. Weighted estimating equations are proposed for the estimation of the regression parameters. Different types of weights are also considered for improving the efficiency. Asymptotic properties of the proposed estimators are investigated and their finite sample properties are assessed via simulations studies. The proposed method is applied to the aforementioned dental study

Asymptotic results for fitting marginal hazard models from stratified case-cohort studies with multiple disease outcomes

In stratified case-cohort designs, samplings of case-cohort samples are conducted via a stratified random sampling based on covariate information available on the entire cohort members. In this paper, we extended the work of Kang & Cai (2009) to a generalized stratified case-cohort study design for failure time data with multiple disease outcomes. Under this study design, we developed weighted estimating procedures for model parameters in marginal multiplicative intensity models and for the cumulative baseline hazard function. The asymptotic properties of the estimators are studied using martingales, modern empirical process theory, and results for finite population sampling

Marginal additive hazards model for case-cohort studies with multiple disease outcomes: an application to the Atherosclerosis Risk in Communities (ARIC) study

In the case-cohort studies conducted within the Atherosclerosis Risk in Communities (ARIC) study, it is of interest to assess and compare the effect of high-sensitivity C-reactive protein (hs-CRP) on the increased risks of incident coronary heart disease and incident ischemic stroke. Empirical cumulative hazards functions for different levels of hs-CRP reveal an additive structure for the risks for each disease outcome. Additionally, we are interested in estimating the difference in the risk for the different hs-CRP groups. Motivated by this, we consider fitting marginal additive hazards regression models for case-cohort studies with multiple disease outcomes. We consider a weighted estimating equations approach for the estimation of model parameters. The asymptotic properties of the proposed estimators are derived and their finite-sample properties are assessed via simulation studies. The proposed method is applied to analyze the ARIC Study

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level