Results 311 to 320 of about 24,504,658 (383)
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Statistics in Medicine, 2003
AbstractMeta‐analysis is now a standard statistical tool for assessing the overall strength and interesting features of a relationship, on the basis of multiple independent studies. There is, however, recent acknowledgement of the fact that in many applications responses are rarely uniquely determined.
Nam, In-Sun+2 more
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AbstractMeta‐analysis is now a standard statistical tool for assessing the overall strength and interesting features of a relationship, on the basis of multiple independent studies. There is, however, recent acknowledgement of the fact that in many applications responses are rarely uniquely determined.
Nam, In-Sun+2 more
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Some distance properties of latent root and vector methods used in multivariate analysis
, 1966SUMMARY This paper is concerned with the representation of a multivariate sample of size n as points P1, P2, ..., PI in a Euclidean space. The interpretation of the distance A(Pi, Pj) between the ith andjth members of the sample is discussed for some ...
J. Gower
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, 1972
Chapter 1: Introduction Chapter 2: Examining Your Data Chapter 3: Factor Analysis Chapter 4: Regression Chapter 5: Multiple Discriminant Analysis Chapter 6: Manova Chapter 7: Conjoint Analysis Chapter 8: Cluster Analysis Chapter 9: MDS Chapter 10 ...
J. Hair
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Chapter 1: Introduction Chapter 2: Examining Your Data Chapter 3: Factor Analysis Chapter 4: Regression Chapter 5: Multiple Discriminant Analysis Chapter 6: Manova Chapter 7: Conjoint Analysis Chapter 8: Cluster Analysis Chapter 9: MDS Chapter 10 ...
J. Hair
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Multivariate Statistical Analysis
2014The Encyclopedia: - represents the first comprehensive reference work on scientific and other scholarly research on the quality of life - covers the subject of quality-of-life from a multi disciplinary perspective - includes the behavioral and social sciences as well as health and healthcare Encyclopedia's Keywords: Happiness - Health - Patient ...
MAGGINO, FILOMENA, M. Fattore
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, 1986
A new multivariate analysis technique, developed to relate community composition to known variation in the environment, is described. The technique is an extension of correspondence analysis (reciprocal averaging), a popular ordination technique that ...
C. Braak
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A new multivariate analysis technique, developed to relate community composition to known variation in the environment, is described. The technique is an extension of correspondence analysis (reciprocal averaging), a popular ordination technique that ...
C. Braak
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Applied Regression Analysis and Other Multivariate Methods
, 19781. CONCEPTS AND EXAMPLES OF RESEARCH. Concepts. Examples. Concluding Remarks. References. 2. CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS. Classification of Variables. Overlapping of Classification Schemes. Choice of Analysis. References.
Subhash C. Sharma+2 more
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An Introduction to Multivariate Statistical Analysis
, 1959Preface to the Third Edition.Preface to the Second Edition.Preface to the First Edition.1. Introduction.2. The Multivariate Normal Distribution.3. Estimation of the Mean Vector and the Covariance Matrix.4. The Distributions and Uses of Sample Correlation
W. G. Madow, T. Anderson
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FITTING MULTIVARIATE MODELS TO COMMUNITY DATA: A COMMENT ON DISTANCE‐BASED REDUNDANCY ANALYSIS
, 2001Nonparametric multivariate analysis of ecological data using permutation tests has two main challenges: (1) to partition the variability in the data according to a complex design or model, as is often required in ecological experiments, and (2) to base ...
B. McArdle, Marti J. Anderson
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Elliptical multivariate analysis
Journal of Econometrics, 1989We investigate the interpretation and the asymptotic properties of the well-known statistics \({\hat \theta}\) derived in multivariate analysis, when the parent distribution of the observations is not necessarily normal but belongs to the wider class of elliptical distributions (including the normal).
Bernard M.S. van Praag+1 more
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Multivariate analysis in community ecology
, 1984Preface 1. Introduction 2. Sampling methods 3. Direct gradient analysis 4. Ordination 5. Classification 6. Applications 7. Conclusion Appendix References Index.
H. Gauch
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