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Open Access DOI:10.23937/2469-5831/1510021
Dejian Lai, Ahmed A Arif, Haiyun Xu and George L Delclos
Article Type: Original Research article | First Published: April 29, 2019
Statistical classification analysis has been widely used in many fields. In this article, we applied and compared three different classification procedures: Logistic regression, Fisher''s linear discriminant function and the second order Bahadur representation to two datasets from two surveys on asthma among healthcare professional in Texas. The first dataset contained 102 subjects and the second dataset 2963. The concordance of the classification from the three statistical procedures with possi...
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Open Access DOI:10.23937/2469-5831/1510020
An Approximation of a Longitudinal Stochastic Model
Khalid A Salah
Article Type: Research Article | First Published: March 25, 2019
We propose to approximate a model for repeated measures that incorporated random effects, correlated stochastic process and measurements error. The stochastic process used in this paper is the Integrated Ornstein-Uhlenbeck (IOU) process. We consider a Bayesian approach which is motivated by the complexity of the model, thus, we propose to approximate the IOU stochastic process into a continuous spatial model that constructed by convolving a very simple and independent, process with a kernel func...
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Open Access DOI:10.23937/2469-5831/1510019
Xiaoyong Wu, Jayesh P Rai, Guohua Yan, Srivastava DK and Shesh N Rai
Article Type: RESEARCH ARTICLE | First Published: March 04, 2019
Assessing the performance of diagnostic tests for repeated binary measurements is very important in clinical trials and diagnostic medicine. The gastric-emptying studies involve 4-hourly measurements of emptying. Empirical results suggest that the gastric emptying results over time are correlated and therefore failure to consider the correlation in statistical measures may not produce satisfactory assessments. If these measurements are highly correlated/associated, early gastric emptying can be ...
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Volume 5
Issue 1
Issue 1