2
|
Cai C, Mei S, Zhong W. Configuration of intrusion prevention systems based on a legal user: the case for using intrusion prevention systems instead of intrusion detection systems. INFORMATION TECHNOLOGY & MANAGEMENT 2018. [DOI: 10.1007/s10799-018-0291-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
3
|
Xiong C, Luo J, Chen L, Gao F, Liu J, Wang G, Bateman R, Morris JC. Estimating diagnostic accuracy for clustered ordinal diagnostic groups in the three-class case-Application to the early diagnosis of Alzheimer disease. Stat Methods Med Res 2018; 27:701-714. [PMID: 29182052 PMCID: PMC5841923 DOI: 10.1177/0962280217742539] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Many medical diagnostic studies involve three ordinal diagnostic populations in which the diagnostic accuracy can be summarized by the volume or partial volume under the receiver operating characteristic surface for a diagnostic marker. When the diagnostic populations are clustered, e.g. by families, we propose to model the diagnostic marker by a general linear mixed model that takes into account of the correlation on the diagnostic marker from members of the same clusters. This model then facilitates the maximum likelihood estimation and statistical inferences of the diagnostic accuracy for the diagnostic marker. This approach naturally allows the incorporation of covariates as well as missing data when some clusters do not have subjects on all diagnostic groups in the estimation of, and the subsequent inferences on the diagnostic accuracy. We further study the performance of the proposed methods in a large simulation study with clustered data. Finally, we apply the proposed methodology to the data of several biomarkers collected by the Dominantly Inherited Alzheimer Network, an international family-clustered registry to study autosomal dominant Alzheimer disease which is a rare form of Alzheimer disease caused by mutations in any of the three genes including the amyloid precursor protein, presenilin 1 and presenilin 2. We estimate the accuracy of several cerebrospinal fluid and neuroimaging biomarkers in differentiating three diagnostic and genetic populations: normal non-mutation carriers, asymptomatic mutation carriers, and symptomatic mutation carriers.
Collapse
Affiliation(s)
- Chengjie Xiong
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, U.S.A
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Jingqin Luo
- Division of Public health, Department of Surgery, Washington University in St. Louis, St. Louis, MO, U.S.A
- Biostatistics Core, Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Ling Chen
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Feng Gao
- Division of Public health, Department of Surgery, Washington University in St. Louis, St. Louis, MO, U.S.A
- Biostatistics Core, Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Jingxia Liu
- Division of Public health, Department of Surgery, Washington University in St. Louis, St. Louis, MO, U.S.A
- Biostatistics Core, Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Guoqiao Wang
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, U.S.A
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - Randall Bateman
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, U.S.A
| | - John C. Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, U.S.A
- Departments of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, U.S.A
| |
Collapse
|