Literature DB >> 10844712

Community-based studies of Alzheimer's disease: statistical challenges in design and analysis.

L A Beckett1.   

Abstract

Alzheimer's disease is a chronic disease, primarily of the elderly, characterized by progressive dementia and eventual death. Community-based studies will likely provide a better representation of the spectrum of disease than will studies drawn solely from clinical sources, because an unknown and possibly substantial fraction of the cases do not come to the attention of the medical care system, or are diagnosed only very late in the disease. Community-based studies will provide not only more accurate estimates of prevalence and incidence, but also more directly comparable unaffected people for studies of risk factors for onset and progression. Such studies are likely to consist of a census component where relatively inexpensive but useful auxiliary information is collected and a probability sample from the census, with the detailed and costly clinical diagnosis of Alzheimer's disease restricted to the sample. The statistician faces challenges both in designing a sample that meets multiple objectives efficiently and in analysing data from the resulting complex survey designs. Copyright 2000 John Wiley & Sons, Ltd.

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Year:  2000        PMID: 10844712     DOI: 10.1002/(sici)1097-0258(20000615/30)19:11/12<1469::aid-sim439>3.0.co;2-j

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  4 in total

1.  Maximizing power to track Alzheimer's disease and MCI progression by LDA-based weighting of longitudinal ventricular surface features.

Authors:  Boris A Gutman; Xue Hua; Priya Rajagopalan; Yi-Yu Chou; Yalin Wang; Igor Yanovsky; Arthur W Toga; Clifford R Jack; Michael W Weiner; Paul M Thompson
Journal:  Neuroimage       Date:  2013-01-04       Impact factor: 6.556

2.  Empowering imaging biomarkers of Alzheimer's disease.

Authors:  Boris A Gutman; Yalin Wang; Igor Yanovsky; Xue Hua; Arthur W Toga; Clifford R Jack; Michael W Weiner; Paul M Thompson
Journal:  Neurobiol Aging       Date:  2014-08-27       Impact factor: 4.673

3.  Limitations of clinical trial sample size estimate by subtraction of two measurements.

Authors:  Kewei Chen; Xiaojuan Guo; Rong Pan; Chengjie Xiong; Danielle J Harvey; Yinghua Chen; Li Yao; Yi Su; Eric M Reiman
Journal:  Stat Med       Date:  2021-11-01       Impact factor: 2.373

4.  Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury.

Authors:  James H Cole; Amy Jolly; Sara de Simoni; Niall Bourke; Maneesh C Patel; Gregory Scott; David J Sharp
Journal:  Brain       Date:  2018-03-01       Impact factor: 13.501

  4 in total

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