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Impairment of Continuous Insulin Delivery Therapy and Analysis from Graeco-Latin Square Design Model

Journal of Biosciences and Medicines 2016年第8期4卷 40-51页

作者： norou diawara Ayodeji Demuren Eric Gyuricsko Department of Mathematics and Statistics Old Dominion University Norfolk VA USA Department of Mechanical and Aerospace Engineering Old Dominion University Norfolk VA USA Department of Pediatrics Eastern Virginia Medical School Norfolk VA USA

The desire to deliver measured amount of insulin continuously to patients with type I diabetes, for glycemic control, has attracted a lot of attention. Continuous subcutaneous insulin infusion has seen some success in recent years. However, occlusion of insulin delivery may prevent the patient from receiving the prescribed dosage, with adverse consequence. An in vitro study of insulin delivery is performed, using different insulin pumps, insulin analogs and operating conditions. The aim is to identify incidences of occlusion due to bubble formation in the infusion line. A detailed statistical analysis was performed on the data collected to determine any significant differences and deviations in insulin delivery rates that might be due to factors such as: pump type, the set basal flow rate, insulin type, vibration, and possible insulin occlusion due to air bubble formation within the infusion line. Our findings from the Graeco-Latin Square design model show that there are statistical differences due to the devices, and statistical identifiable clusters are used to distinguish the devices. Such hierarchical models used to describe the analyses, include the flow rate, the pump types, and the activity level.

关键词： Graeco-Latin Square Design Insulin Delivery Model Based Cluster Analysis Occlusion

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The Use of Item Response Theory in Survey Methodology: Application in Seat Belt Data

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American Journal of Operations Research 2018年第1期8卷 17-32页

作者： Mark K. Ledbetter norou diawara Bryan E. Porter Mathematics and Statistics Department Old Dominion University Norfolk VA USA Department of Psychology Old Dominion University Norfolk VA USA

Problem: Several approaches to analyze survey data have been proposed in the literature. One method that is not popular in survey research methodology is the use of item response theory (IRT). Since accurate methods to make prediction behaviors are based upon observed data, the design model must overcome computation challenges, but also consideration towards calibration and proficiency estimation. The IRT model deems to be offered those latter options. We review that model and apply it to an observational survey data. We then compare the findings with the more popular weighted logistic regression. Method: Apply IRT model to the observed data from 136 sites within the Commonwealth of Virginia over five years collected in a two stage systematic stratified proportional to size sampling plan. Results: A relationship within data is found and is confirmed using the weighted logistic regression model selection. Practical Application: The IRT method may allow simplicity and better fit in the prediction within complex methodology: the model provides tools for survey analysis.

关键词： Item Response Theory Logistic Regression Sampling Weight

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