Journal ArticleDOI
A multivariate data reduction system
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A descriptive system is introduced which examines the current information about a clinical problem and identifies best predictors of the problem and the laboratory approach to the predictive diagnosis of iron deficiency is chosen.Abstract:
The problem of predictive diagnosis based on laboratory data is approached from a mathematical standpoint. A descriptive system is introduced which examines the current information about a clinical problem and identifies best predictors of the problem. Algorithms are described for the assessment of current diagnostic ability, the evaluation of new laboratory tests, and the identification of patients to study for the development of new procedures. The laboratory approach to the predictive diagnosis of iron deficiency is chosen as an example of the system.read more
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Book ChapterDOI
The Human Health Consequences of Flooding in Europe: a Review
TL;DR: A comprehensive, risk-based emergency management program of preparedness, response, and recovery has the potential to reduce the adverse health effects of floods, but there is currently inadequate evidence of the effectiveness of public health interventions.
Journal ArticleDOI
The “iron screen”: Modification of standard laboratory practice with data analysis
J. Robert Beck,Gibbons G. Cornwell,E. Elizabeth French,Frederick A. Meier,Truls Brinck-Johnsen,Howard M. Rawnsley +5 more
TL;DR: Multivariate analysis was applied to iron deficiency anemia to generate an efficient sequence of diagnostic laboratory tests and shows how clinical laboratory data can be utilized to render diagnoses of defined probability.
Journal ArticleDOI
A multivariate approach to laboratory practice.
TL;DR: In multivariate analysis the usefulness of the proposed new procedure in the predictive diagnosis scheme is determined and the best predictors already identified and confirmed are included.
References
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Journal ArticleDOI
Multivariate Data Analysis
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Journal ArticleDOI
Multivariate Data Analysis
TL;DR: This book deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material.