Journal ArticleDOI
A new method for non-parametric multivariate analysis of variance
TLDR
In this article, a non-parametric method for multivariate analysis of variance, based on sums of squared distances, is proposed. But it is not suitable for most ecological multivariate data sets.Abstract:
Hypothesis-testing methods for multivariate data are needed to make rigorous probability statements about the effects of factors and their interactions in experiments. Analysis of variance is particularly powerful for the analysis of univariate data. The traditional multivariate analogues, however, are too stringent in their assumptions for most ecological multivariate data sets. Non-parametric methods, based on permutation tests, are preferable. This paper describes a new non-parametric method for multivariate analysis of variance, after McArdle and Anderson (in press). It is given here, with several applications in ecology, to provide an alternative and perhaps more intuitive formulation for ANOVA (based on sums of squared distances) to complement the description pro- vided by McArdle and Anderson (in press) for the analysis of any linear model. It is an improvement on previous non-parametric methods because it allows a direct additive partitioning of variation for complex models. It does this while maintaining the flexibility and lack of formal assumptions of other non-parametric methods. The test- statistic is a multivariate analogue to Fisher's F-ratio and is calculated directly from any symmetric distance or dissimilarity matrix. P-values are then obtained using permutations. Some examples of the method are given for tests involving several factors, including factorial and hierarchical (nested) designs and tests of interactions.read more
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Book
Experimental Design and Data Analysis for Biologists
Gerry P. Quinn,Michael J. Keough +1 more
TL;DR: An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data is as discussed by the authors, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced.
Journal ArticleDOI
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
Kristin G. Ardlie,David S. DeLuca,Ayellet V. Segrè,Timothy J. Sullivan,Taylor Young,Ellen Gelfand,Casandra A. Trowbridge,Julian Maller,Taru Tukiainen,Monkol Lek,Lucas D. Ward,Pouya Kheradpour,Benjamin Iriarte,Yan Meng,Cameron D. Palmer,Tõnu Esko,Wendy Winckler,Joel N. Hirschhorn,Manolis Kellis,Daniel G. MacArthur,Gad Getz,Andrey A. Shabalin,Gen Li,Yi-Hui Zhou,Andrew B. Nobel,Ivan Rusyn,Fred A. Wright,Tuuli Lappalainen,Pedro G. Ferreira,Halit Ongen,Manuel A. Rivas,Alexis Battle,Sara Mostafavi,Jean Monlong,Michael Sammeth,Marta Melé,Ferran Reverter,Jakob M. Goldmann,Daphne Koller,Roderic Guigó,Mark I. McCarthy,Emmanouil T. Dermitzakis,Eric R. Gamazon,Hae Kyung Im,Anuar Konkashbaev,Dan L. Nicolae,Nancy J. Cox,Timothée Flutre,Xiaoquan Wen,Matthew Stephens,Jonathan K. Pritchard,Zhidong Tu,Bin Zhang,Tao Huang,Quan Long,Luan Lin,Jialiang Yang,Jun Zhu,Jun Liu,Amanda Brown,Bernadette Mestichelli,Denee Tidwell,Edmund Lo,Mike Salvatore,Saboor Shad,Jeffrey A. Thomas,John T. Lonsdale,Michael T. Moser,Bryan Gillard,Ellen Karasik,Kimberly Ramsey,Christopher Choi,Barbara A. Foster,John Syron,Johnell Fleming,Harold Magazine,Rick Hasz,Gary Walters,Jason Bridge,Mark Miklos,Susan L. Sullivan,Laura Barker,Heather M. Traino,Maghboeba Mosavel,Laura A. Siminoff,Dana R. Valley,Daniel C. Rohrer,Scott D. Jewell,Philip A. Branton,Leslie H. Sobin,Mary Barcus,Liqun Qi,Jeffrey McLean,Pushpa Hariharan,Ki Sung Um,Shenpei Wu,David Tabor,Charles Shive,Anna M. Smith,Stephen A. Buia,Anita H. Undale,Karna Robinson,Nancy Roche,Kimberly M. Valentino,Angela Britton,Robin Burges,Debra Bradbury,Kenneth W. Hambright,John Seleski,Greg E. Korzeniewski,Kenyon Erickson,Yvonne Marcus,Jorge Tejada,Mehran Taherian,Chunrong Lu,Margaret J. Basile,Deborah C. Mash,Simona Volpi,Jeffery P. Struewing,Gary F. Temple,Joy T. Boyer,Deborah Colantuoni,Roger Little,Susan E. Koester,Latarsha J. Carithers,Helen M. Moore,Ping Guan,Carolyn C. Compton,Sherilyn Sawyer,Joanne P. Demchok,Jimmie B. Vaught,Chana A. Rabiner,Nicole C. Lockhart +132 more
TL;DR: The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
Journal ArticleDOI
Fitting multivariate models to community data: a comment on distance‐based redundancy analysis
TL;DR: The distance-based redundancy analysis (db-RDA) as mentioned in this paper is a nonparametric multivariate analysis of ecological data using permutation tests that is used to partition the variability in the data according to a complex design or model, as is often required in ecological experiments.
Journal ArticleDOI
Microbiota Modulate Behavioral and Physiological Abnormalities Associated with Neurodevelopmental Disorders
Elaine Y. Hsiao,Sara Mcbride,Sophia Hsien,Gil Sharon,Embriette R. Hyde,Tyler McCue,Julian A. Codelli,Janet Chow,Sarah E. Reisman,Joseph F. Petrosino,Paul H. Patterson,Sarkis K. Mazmanian +11 more
TL;DR: A gut-microbiome-brain connection in a mouse model of ASD is supported and a potential probiotic therapy for GI and particular behavioral symptoms in human neurodevelopmental disorders is identified.
Journal ArticleDOI
Distance-based tests for homogeneity of multivariate dispersions.
TL;DR: In this paper, distance-based tests of homogeneity of multivariate dispersions, which can be based on any dissimilarity measure of choice, are proposed, relying on the rotational invariance of either the multivariate centroid or the spatial median to obtain measures of spread using principal coordinate axes.
References
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Statistical Principles in Experimental Design
TL;DR: In this article, the authors introduce the principles of estimation and inference: means and variance, means and variations, and means and variance of estimators and inferors, and the analysis of factorial experiments having repeated measures on the same element.
Journal ArticleDOI
Statistical Principles in Experimental Design
TL;DR: This chapter discusses design and analysis of single-Factor Experiments: Completely Randomized Design and Factorial Experiments in which Some of the Interactions are Confounded.
Journal Article
The Design and Analysis of Experiments
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Journal ArticleDOI
Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data.
TL;DR: In this article, a framework for the study of molecular variation within a single species is presented, where information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes.
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