Results 321 to 330 of about 24,504,658 (383)
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Journal of Neurosurgery, 2001
OBJECT The extent of tumor resection that should be undertaken in patients with glioblastoma multiforme (GBM) remains controversial. The purpose of this study was to identify significant independent predictors of survival in these patients and to ...
M. Lacroix +13 more
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OBJECT The extent of tumor resection that should be undertaken in patients with glioblastoma multiforme (GBM) remains controversial. The purpose of this study was to identify significant independent predictors of survival in these patients and to ...
M. Lacroix +13 more
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Nonlinear multivariate analysis
Evaluation News, 1990Reports (1-4 double-spaced typewritten pages) should describe tools, products, andlor services found useful by practicing evaluators. Reports should also include the context of use and sufficient informationfor interested readers to contact the user directly for more detailed information, that is, name, address, and telephone number.
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Analysis of Incomplete Multivariate Data
, 1997Introduction Assumptions EM and Inference by Data Augmentation Methods for Normal Data More on the Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data Further Topics Appendices References ...
J. Schafer
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Multivariate Analysis of Variance
Journal of Marketing Research, 1987Introduction to Multivariate Analysis of Variance Omnibus MANOVA Tests Analyzing and Interpreting Significant MANOVAs Causal Models Underlying MANOVA Analyses Complex Designs Overview of Computer Programs for ...
D. D. V. Morgan +2 more
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Regression Analysis and Multivariate Analysis
Seminars in Reproductive Medicine, 1996Proper evaluation of data does not necessarily require the use of advanced statistical methods; however, such advanced tools offer the researcher the freedom to evaluate more complex hypotheses. This overview of regression analysis and multivariate statistics describes general concepts. Basic definitions and conventions are reviewed.
David L. Olive, Antoni J. Duleba
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Multivariate Data and Multivariate Analysis
2005Multivariate data arise when researchers record the values of several random variables on a number of subjects or objects or perhaps one of a variety of other things (we will use the general term “units”) in which they are interested, leading to a vector-valued or multidimensional observation for each.
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, 2014
Preface 1. Introduction and data types 2. Using Canoco 5 3. Experimental design 4. Basics of gradient analysis 5. Permutation tests and variation partitioning 6. Similarity measures and similarity-based methods 7. Classification methods 8.
P. Šmilauer, J. Lepš
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Preface 1. Introduction and data types 2. Using Canoco 5 3. Experimental design 4. Basics of gradient analysis 5. Permutation tests and variation partitioning 6. Similarity measures and similarity-based methods 7. Classification methods 8.
P. Šmilauer, J. Lepš
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Xenobiotica; the fate of foreign compounds in biological systems, 1999
(1999). 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica: Vol. 29, No. 11, pp. 1181-1189.
J. Nicholson, J. Lindon, E. Holmes
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(1999). 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica: Vol. 29, No. 11, pp. 1181-1189.
J. Nicholson, J. Lindon, E. Holmes
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Multivariate Analysis in Twins
Acta geneticae medicae et gemellologiae, 1970We present the results of a noncentral χ2 test applied to 63 like-sexed twin pairs.We have separated the pairs into two groups: 30 serologically identical and 33 serologically nonidentical pairs for nine sera of the blood groups ABO, MN, and Rh.The probabilities of monozygosity of the serologically identical pairs, calculated by the method of Maynard ...
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Multivariate Statistical Analysis
Psychophysiology, 1973ABSTRACTGeneral multivariate statistical theory and three statistical models (multi‐variate analysis of variance, canonical correlation analysis, and factor analysis) are described. Numerical examples, mathematical notes, an annotated bibliography, and references to computer programs are presented.
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