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geomorph: an r package for the collection and analysis of geometric morphometric shape data
Summary 1. Many ecological and evolutionary studies seek to explain patterns of shape variation and its covariation with other variables. Geometric morphometrics is often used for this purpose, whereExpand
Geometric morphometrics: Ten years of progress following the ‘revolution’
TLDR
This paper briefly update the discussion in that paper and summarize the advances in the ten years since the paper by Rohlf and Marcus (1993) and speculate on future directions in morphometric analysis. Expand
A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data.
  • D. Adams
  • Biology, Medicine
  • Systematic biology
  • 1 September 2014
TLDR
A generalization of the K statistic of Blomberg et al. that is useful for quantifying and evaluating phylogenetic signal in highly dimensional multivariate data is described and the utility of the new approach is illustrated by evaluating the strength of phylogenetics signal for head shape in a lineage of Plethodon salamanders. Expand
RESAMPLING TESTS FOR META‐ANALYSIS OF ECOLOGICAL DATA
TLDR
Re- sampling methods should be incorporated in meta-analysis studies, to ensure proper evaluation of main effects in ecological studies, and confidence limits based on bootstrapping methods were found to be wider than standard confidence limits, implying that resampling estimates are more conservative. Expand
A METHOD FOR ASSESSING PHYLOGENETIC LEAST SQUARES MODELS FOR SHAPE AND OTHER HIGH‐DIMENSIONAL MULTIVARIATE DATA
  • D. Adams
  • Biology, Medicine
  • Evolution; international journal of organic…
  • 1 September 2014
TLDR
The new procedure provides a useful means of assessing trait covariation across a set of taxa related by a phylogeny, enabling macroevolutionary biologists to test hypotheses of adaptation, and phenotypic change in high‐dimensional datasets. Expand
A field comes of age: geometric morphometrics in the 21 st century
TLDR
This review describes the Procrustes paradigm and the current methodological toolkit of geometric morphometrics, and highlights some of the theoretical advances that have occurred over the past ten years since the prior review (Adams et al., 2004). Expand
RRPP: An r package for fitting linear models to high‐dimensional data using residual randomization
The ability to analyse multidimensional traits and other multivariate data has become a requisite skill for evolutionary biologists and ecologists over the last few decades. This reality isExpand
A method for analysis of phenotypic change for phenotypes described by high-dimensional data
TLDR
It is demonstrated that using more phenotypic variables can increase effect sizes, and allow for stronger inferences, as well as eliminating variables potentially reduces effect sizes for comparative analyses, yet test statistics require more observations than variables. Expand
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