Journal of Clinical Trials
Open Access
ISSN: 2167-0870
ISSN: 2167-0870
Jingjing Yin, Hani Samawi and Yi Hao
ScientificTracks Abstracts-Workshop: J Clin Trials
In medical diagnostics, the ROC curve is the graph of sensitivity against 1-specificity as the diagnostic threshold runs through
all possible values. The ROC curve and its associated summary indices are very useful for the purpose of evaluating the
discriminatory ability of biomarkers/diagnostic tests with continuous measurements. Among all summary indices, the area under
the ROC curve (AUC) is the most popular diagnostic accuracy index and it has been extensively used by many researchers for
biomarker evaluation and selection. Sometimes, taking the actual measurements of a biomarker is very difficult and expensive
while ranking them without actual measurements can be easy. In such cases, ranked set sampling which based on order statistics
would give more accurate estimation than simple random sampling, since ranked set samples are more likely to span the full range
of population (thus is more representative). In this study, Gaussian kernel is utilized to obtain a nonparametric estimate of AUC.
Intensive simulations are carried out to compare the proposed method using ranked set samples with the one using simple random
samples and the proposed method out performs universally with much smaller mean squared errors (MSE). A real data set is
analyzed for illustrating the proposed method.
Jingjing Yin received her Bachelor degree in Public Health Administration from Sichuan University in China. She obtained PhD in Biostatistics at University at
Buffalo. Simultaneously, she was a Teaching Assistant for one Undergraduate Course and two Graduate Courses and then she became a Research Assistant
working as a Biostatistician at Buffalo VA Medical Center and Statistical Consulting Laboratory at University at Buffalo. Immediately after completion of her PhD
degree, she joined the Department of Biostatistics at Georgia Southern University. She has 10 publications and serves as the Associate Editor of Biometrics &
Biostatistics International Journal.