TY - JOUR
T1 - Closed form prediction intervals applied for disease counts
AU - Wang, Hsiuying
PY - 2010/5
Y1 - 2010/5
N2 - The prediction interval is an important tool in medical applications for predicting the number of times a disease will occur in a population. The performance of the existing prediction intervals, however, is unsatisfactory when the true proportion is near a boundary. Since the true proportion can be very small in real applications, in this article, we propose improved prediction intervals with better coverage probability than the existing methods. Their predictive distributions are compared in terms of the Kullback-Leibler distance and the intervals are compared using a hearing screening medical example.
AB - The prediction interval is an important tool in medical applications for predicting the number of times a disease will occur in a population. The performance of the existing prediction intervals, however, is unsatisfactory when the true proportion is near a boundary. Since the true proportion can be very small in real applications, in this article, we propose improved prediction intervals with better coverage probability than the existing methods. Their predictive distributions are compared in terms of the Kullback-Leibler distance and the intervals are compared using a hearing screening medical example.
KW - Binomial distribution
KW - Coverage probability
KW - Prediction interval
KW - Predictive distribution
UR - http://www.scopus.com/inward/record.url?scp=78649406534&partnerID=8YFLogxK
U2 - 10.1198/tast.2010.09125
DO - 10.1198/tast.2010.09125
M3 - Article
AN - SCOPUS:78649406534
SN - 0003-1305
VL - 64
SP - 250
EP - 256
JO - American Statistician
JF - American Statistician
IS - 3
ER -