Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Larry, Tang"'
Publikováno v:
PLoS ONE, Vol 17, Iss 4, p e0266350 (2022)
Item response theory (IRT) is the statistical paradigm underlying a dominant family of generative probabilistic models for test responses, used to quantify traits in individuals relative to target populations. The graded response model (GRM) is a par
Externí odkaz:
https://doaj.org/article/37db4301364f4896a1468bac38673762
Publikováno v:
Applied Cognitive Psychology. 36:1209-1218
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
J Appl Stat
In disease screening, a biomarker combination developed by combining multiple markers tends to have a higher sensitivity than an individual marker. Parametric methods for marker combination rely on the inverse of covariance matrices, which is often a
Publikováno v:
2022 IEEE High Performance Extreme Computing Conference (HPEC).
Publikováno v:
Cancer Informatics, Vol 16 (2017)
The article proposes a unified least squares method to estimate the receiver operating characteristic (ROC) parameters for continuous and ordinal diagnostic tests, such as cancer biomarkers. The method is based on a linear model framework using the e
Externí odkaz:
https://doaj.org/article/ea4f51ea43eb4cb08d57e56c8cc5b86a
Publikováno v:
Biostatistics & Epidemiology. 5:169-188
In clustered receiver operating characteristic (ROC) data each patient has several normal and abnormal observations. Within the same cluster, observations are naturally correlated. Several nonparam...
Autor:
H. Larry Tang
Publikováno v:
Journal AWWA. 113:16-18
Publikováno v:
Applied Spectroscopy. 75:747-752
Tire evidence is a form of trace evidence that is often overlooked in today's forensics, while frequently found at crime or accident scenes, usually in the form of skid marks. The pattern of the tire skid mark has been used before to link a tire or c
Publikováno v:
Biostat Epidemiol
This manuscript estimates the area under the receiver operating characteristic curve (AUC) of combined biomarkers in a high-dimensional setting. We propose a penalization approach to the inference of precision matrices in the presence of the limit of