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Full-Text Articles in Medicine and Health Sciences
Lyme Disease And Youtube™: A Cross-Sectional Study Of Video Contents, Corey H. Basch, Lindsay A. Mullican, Kwanza D. Boone, Jingjing Yin, Alyssa Berdnik, Marina E. Eremeeva, Isaac Chun-Hai Fung
Lyme Disease And Youtube™: A Cross-Sectional Study Of Video Contents, Corey H. Basch, Lindsay A. Mullican, Kwanza D. Boone, Jingjing Yin, Alyssa Berdnik, Marina E. Eremeeva, Isaac Chun-Hai Fung
Environmental Health Sciences Faculty Publications
Objectives: Lyme disease is the most common tick-borne disease. People seek health information on Lyme disease from YouTubeTM videos. In this study, we investigated if the contents of Lyme disease-related YouTubeTM videos varied by their sources.
Methods: Most viewed English YouTubeTM videos (n = 100) were identified and manually coded for contents and sources.
Results: Within the sample, 40 videos were consumer-generated, 31 were internet-based news, 16 were professional, and 13 were TV news. Compared with consumer-generated videos, TV news videos were more likely to mention celebrities (odds ratio [OR], 10.57; 95% confidence interval [CI], 2.13–52.58), prevention of Lyme disease …
Using The Roc Curve To Measure Association And Evaluate Prediction Accuracy For A Binary Outcome, Jingjing Yin, Robert L. Vogel
Using The Roc Curve To Measure Association And Evaluate Prediction Accuracy For A Binary Outcome, Jingjing Yin, Robert L. Vogel
Biostatistics Faculty Publications
This review article addresses the ROC curve and its advantage over the odds ratio to measure the association between a continuous variable and a binary outcome. A simple parametric model under the normality assumption and the method of Box-Cox transformation for non-normal data are discussed. Applications of the binormal model and the Box-Cox transformation under both univariate and multivariate inference are illustrated by a comprehensive data analysis tutorial. Finally, a summary and recommendations are given as to the usage of the binormal ROC curve.
Using Ranked Auxiliary Covariate As A More Efficient Sampling Design For Ancova Model: Analysis Of A Psychological Intervention To Buttress Resilience, Rajai Jabrah, Hani Samawi, Robert Vogel, Haresh Rochani, Daniel Linder
Using Ranked Auxiliary Covariate As A More Efficient Sampling Design For Ancova Model: Analysis Of A Psychological Intervention To Buttress Resilience, Rajai Jabrah, Hani Samawi, Robert Vogel, Haresh Rochani, Daniel Linder
Biostatistics Faculty Publications
Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis …