Multivariate Statistical Methods

By W. Wilson. 2005

1,497 citations recorded by the source corpus.

Subfields: General Materials Science, Sociology and Political Science, Water Science and Technology

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Citations in the corpus

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging (2015, neutral): “It should be noted that in the low dimensional high sample size setting confidence intervals associated with the Hotelling T 2 - statistic Morrison (1967) provide such a mechanism.”
Outcomes of a Longitudinal Administration of the Persistence in Engineering Survey (2010, methodology): “Likewise, the primary assumption underlying repeated-measures designs is the variance-covariance assumption of circularity (Marcoulides and Hershberger, 1997).”
ECG to identify individuals (2005, methodology): “A stepwise canonical correlation that used the Wilkes’ lambda as a divergence measure provided the feature selection [14].”
Antecedents and Consequences of Online Social Interactions (2007, background): “Statistical tests to determine if the covariance matrices were equal (Morrison, 1990) were conducted for the first three venues (e-mail lists, Web site bulletin boards, and Usenet newsgroups) and the remaining three venues (real-time online chat rooms, Web-based chat rooms, and MUDs).”
Multiple Hypothesis Testing in Microarray Experiments (2003, methodology): “…of these methods to the twodimensional testing problem where several hypotheses are tested simultaneously for each of thousands of genes [see Gabriel (1975), Krishnaiah and Reising (1985), Morrison (1990), and Westfall and Young (1993) for background on multivariate multiple testing methods].”
Collaborative Leadership Effects on School Improvement: Integrating Unidirectional- and Reciprocal-Effects Models (2010, methodology): “The adequacy of each model can be determined through the comparison of several model-fit criteria (see Marcoulides & Hershberger, 1997), as well as the size and significance of the standardized path coefficients.”
SUCCESSFUL STRATEGIES FOR TEACHING MULTIVARIATE STATISTICS (2006, background): “It then provides an overview of the primary multivariate statistical techniques, discusses examining your data to ensure its accuracy and completeness, and then focuses on in depth, hands on coverage of the major techniques.”
Combining Pattern Classifiers: Methods and Algorithms (2005, background): “Other texts, such as those of Morrison (1976), Dillon and Goldstein (1984), and Jackson (1991), might be more accessible.”
Elevational gradients in species richness and endemism of selected plant groups in the central Bolivian Andes (2000, methodology): “Altitudinal zonation was tested with an analysis of deviance (Karson 1982; McCullogh & Nelder 1983; Austin 1985) following the method proposed by Shipley & Keddy (1987).”
Evaluation of image analysis techniques for quantifying aggregate shape characteristics (2007, neutral): “, [9,21]).”
Measuring Residents’ Attitudes toward Sustainable Tourism: A Reexamination of the Sustainable Tourism Attitude Scale (2011, methodology): “An RMSEA value less than .06 and an SRMR value less than .08 have served as rule of thumb of acceptable fit (Hu and Bentler 1999; Joreskog and Sorbom 1993; Marcoulides and Hershberger 1997).”
The Organizational Culture Profile Revisited and Revised: An Australian Perspective (2005, methodology): “The assumption of multivariate normality was assessed by examining the skewness and kurtosis of all variables in the variance-covariance matrix as recommended by Marcoulides and Hershberger (1997).”
Probabilistic Prediction for Monthly Streamflow through Coupling Stepwise Cluster Analysis and Quantile Regression Methods (2016, methodology): “The development of SCA is based on the theory of multivariate analysis of variance (Morrison 1967; Cooley and Lohnes 1971; Overall and Klett 1972; Wang et al. 2013).”
A correlation among safety leadership, safety climate and safety performance (2008, background): “CCA seeks to identify and quantify the interrelationships among sets of multiple criterion variables and multiple predictor variables (Hair et al., 1998; Johnson & Wichern, 2002; Morrison, 1990; Stevens, 1992).”
Metabolomics: a global biochemical approach to drug response and disease. (2008, background): “Although excellent texts exist (80, 81), readers might be best served by following up this topic either with local experts in informatics (including those conducting studies outside of metabolomics, such as investigators involved in microarray analysis) and/or with the authors of relevant publicatio”