Multivariate Analysis

By Michael V. Boland, Robert F. Murphy. 1998

One of the goals of Current Protocols is to provide information from the very basic level to the very advanced. This unit is an excellent example of providing explanation and application for a complex area. Building upon several other units on data analysis, it provides a detailed explanation of how multivariate analytical techniques are applied to flow cytometry data. The unit deals with the covariance matrix, principal component analysis, and cluster analysis and provides sources for software as well as example data files. This material will be particularly valuable to the graduate student trying to obtain a good understanding of statistical methods in flow cytometry, as well as to the experienced investigator who uses these tools on a regular basis without really understanding how they operate. Keywords: principal components analysis; cluster analysis; FCS file format One of the goals of Current Protocols is to provide information from the very basic level to the very advanced

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Citations in the corpus

On the Schoenberg Transformations in Data Analysis: Theory and Illustrations (2010, background): “The dispersion tr( B ( a )) is minimum when a is the uniform distribution, a standard choice in classical MDS (see e.g. Mardia et al. 1979).”
Subcellular location prediction of apoptosis proteins (2002, unknown): “Among these three, however, the jackknife test is deemed as the most effective and objective one (see Chou and Zhang 21 for a comprehensive discussion about this, and Mardia et al. 41 for the mathematical principle).”
Statistical Representation of Distribution System Loads Using Gaussian Mixture Model (2010, background): “The algorithm was terminated when the relative difference of log-likelihood values [17] in two consecutive iterations is below a threshold.”
High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality (2000, background): “Good references on some of these issues include [41, 51, 66]; I use these often in teaching.”
Socio-economic Distance and Spatial Patterns in Unemployment Journal of Applied Econometrics 17 (2002, methodology): “[20] provide a detailed description of this method.”
Spatial Ability: A Neglected Dimension In Talent Searches For Intellectually Precocious Youth (2007, methodology): “…and least favorite high school course, leisure activities, undergraduate majors, and anticipated occupations) were categorized to examine the validity of spatial ability using the group membership approach (Humphreys et al., 1993; Rulon, Tiedmen, Tatsuoka, & Langmuie, 1967; Tatsuoka, 1988).”
Partial Distance Correlation with Methods for Dissimilarities (2013, unknown): “Mardia, Kent and Bibby [19] summarize the result in Theorem 14.2.1, and provide a proof.”
Assessment of the effect of PET calculation method on the Standardized Precipitation Evapotranspiration Index (SPEI) (2020, background): “See Johnson and Wichern (2002) for more details.”
Differences in Scholastic Achievement of Public, Private Government-Dependent, and Private Independent Schools (2008, unknown): “This procedure results in a measurement model of the next level of the students (see Hox, 2002).”
Dismantling the Mantel tests (2011, unknown): “Key-words: landscape ecology, landscape genetics, phylogeography, geographic epidemiology, spatial structure, isolation by distance, isolation by resistance, autocorrelation, type I error,Loa loa”
CCA: An R Package to Extend Canonical Correlation Analysis (2008, unknown): “It is well known (Mardia et al. 1979) that: Proposition 2.1.”