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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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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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Multivariate Behavioral Research, 1981
Analysis of multivariate aptitude-treatment-interaction data is discussed. Various global hypotheses and the associated follow-up descriptions are considered and compared. Analysis procedures are illustrated using data from a science education study to describe the interaction between student reading ability and the time allowed in an individualized ...
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Analysis of multivariate aptitude-treatment-interaction data is discussed. Various global hypotheses and the associated follow-up descriptions are considered and compared. Analysis procedures are illustrated using data from a science education study to describe the interaction between student reading ability and the time allowed in an individualized ...
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Multivariate analysis using ‘and’ and ‘or’
Mathematical Social Sciences, 1984Extensions from binary to continuous variables are considered of mathematical operators for connectives (''and'', ''or'', ''exclusive or'', etc). Using concepts from fuzzy set theory it is illustrated how such extensions can be used in statistical modelling of interactions in multivariate analysis.
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An Inequality with Application to Multivariate Analysis [PDF]
Biometrika, 1975 An inequality for the trace of the product of two symmetric matrices can be used to simplify the proofs of a number of results in multivariate analysis. This is illustrated on two problems: estimating the parameters of a multivariate normal population, and estimating a system of linear functional relationships between the mean vectors of k multivariate
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Multivariate Survival Analysis
Theory of Probability & Its Applications, 1993The author considers problems arising in multivariate survival analysis. It is shown that concepts of history and future of one-dimensional time lead to definitions of multidimensional measures of risk, iterated measures of hazard rate, and a representation of multidimensional survival time.
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2016
Starting with Wishart distribution, a multivariate generalization of the chi-square distribution, estimation, and inferential issues is discussed for one-sample, two-sample, and multisample problems. An introduction is given to multivariate linear model which covers multivariate versions of analysis of variance, analysis of covariance, and regression ...
P.K. Bhattacharya, Prabir Burman
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Starting with Wishart distribution, a multivariate generalization of the chi-square distribution, estimation, and inferential issues is discussed for one-sample, two-sample, and multisample problems. An introduction is given to multivariate linear model which covers multivariate versions of analysis of variance, analysis of covariance, and regression ...
P.K. Bhattacharya, Prabir Burman
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The multivariate analysis of variance
1980In this chapter the consideration of procedures based on normal distribution theory will be extended to the analysis of data arising from designed experiments. We shall find that the calculation of a multivariate analysis of variance (MANOVA) is essentially similar to the calculation of a univariate analysis of variance (ANOVA). However, the testing of
Chris Chatfield, Alexander J. Collins
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