Methods of Multivariate Analysis

By Eric P. Smith. 2003

1,807 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fa3aa3ab5da4aec6d8525947d78cd3414fd3b141

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Citations in the corpus

Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range (2015, methodology): “This rotation is also advocated for conventional factor analysis (Rencher 2002) and dynamic factor analysis (Holmes,Ward & Scheuerell 2014).”
On the Kaiser-Meier-Olkin’s Measure of Sampling Adequacy (2018, background): “This rule of thumb appears to have been accepted widely, although a measure of above 0.6 is acceptable (Rencher, 2002).”
Sexual dimorphism in trophic morphology and feeding behavior of wolf spiders (Araneae: Lycosidae) as a result of differences in reproductive roles (2002, methodology): “Significant differences in trophic morphology between the sexes within species were then determined by constructing contrast statements for each species (SAS Institute Inc. 1989; Rencher 1995).”
Stand scale effects of partial harvesting and clearcutting on small mammals and forest structure (2004, positive): “If the Hotelling’s T(2) test suggested differences in at least one habitat variable between overstory types, we then used univariate F-tests with a Bonferroni-adjusted critical value of a/k (Rencher, 1995) to determine which habitat variables differed significantly between overstory types.”
Selecting Representative Data Sets (2012, background): “More details about the multivariate data characteristic can be found in [77].”
Comparison of Some Statistical Methods of Probabilistic Forecasting of ENSO. (2002, methodology): “The weights can be obtained in a manner similarA to that for the canonical loadings in canonical correlation analysis (for further details see Gittins 1985; Tatsuoka 1988; Rencher 1995).”
Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs per Unit of Randomization (2003, methodology): “The variance estimator V̂′ follows the Wishart distribution with degrees of freedom J-1, and it is independent of the fixed effects estimator ̂ (Rencher, 1995, p. 104).”
An Analytic Framework for Evaluating the Validity of Concept Inventory Claims (2015, methodology): “If the factors are largely uncorrelated, then an oblique rotation will approximate the result of using an orthogonal rotation (Rencher, 2002).”
Differentially Private Bayesian Linear Regression (2019, background): “The ordinary least squares (OLS) solution is ˆ θ = (cid:0) X T X − 1 X T y [Rencher, 2003].”
Analyzing the Longitudinal K-12 Grading Histories of Entire Cohorts of Students: Grades, Data Driven Decision Making, Dropping out and Hierarchical Cluster Analysis. (2010, methodology): “…Amherst, 2010 Practical Assessment, Research & Evaluation, Vol 15, No 7 Page 4 Bowers, Grades, 3DM, Dropout, and HCA such that “clusters” of data patterns are closest to each other in a list (Anderberg, 1973; Hubert, Köhn, & Steinley, 2009; Rencher, 2002; Romesburg, 1984; Sneath & Sokal, 1973).”
Face and facework in conflict: a cross-cultural comparison of China, Germany, Japan, and the United States (2001, methodology): “T-tests of the B coefficients can be used to determine which covariate best explains the dependent variable (Rencher, 1995).”
GIVING MEANINGFUL INTERPRETATION TO ORDINATION AXES: ASSESSING LOADING SIGNIFICANCE IN PRINCIPAL COMPONENT ANALYSIS (2003, background): “The observed value is included as one possible value of the randomized distribution, hence the addition of 1 in the numerator and denominator (A. C. A. Hope 1968).”
Depth and homogeneity in regional flood frequency analysis (2008, background): “detailed description of multivariate regression analysis can be found in Rencher (2002). 5 6”
Direct and indirect effects of pollinators and seed predators to selection on plant and floral traits (2004, methodology): “Because percent fruit set, seed set per fruit, and total seed production per plant may be intercorrelated, a MANOVA was used initially to control for Type I error (Rencher 1995).”
Spatial dynamic factor analysis (2008, background): “The fourth common factor represents the grand mean as it is fairly common in factor analysis applications (see Rencher 2002 for more details).”