ReviewDevelopment genes and evolution2016
Measurement error in geometric morphometrics.
Review in Development genes and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
84 citing papers in PubMed.
- Bony labyrinth taxonomic identification and long-term evolution of livestock in the Southwest and Central Asia.Royal Society open science · 2026Article
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- Skeleton-based morphometric analysis of small yellow croaker (Larimichthys polyactis) in the Southern Yellow Sea and East China Sea.Journal of fish biology · 2026Article
- Virtual reconstruction and analysis of the face of DFN3-150 Paradolichopithecus aff. arvernensis specimen from Dafnero, Greece.Scientific reports · 2026Article
- Two-group interlandmark distance analysis for skeletal sex estimation using resampling and posterior probability contour plots.International journal of legal medicine · 2026Article
- Morphometric Assessment of Pelvic Asymmetry in Domestic Cats and Dogs.Animals : an open access journal from MDPI · 2026Article
- Effect of tooth agenesis on facial soft tissue profile.Scientific reports · 2026Article
- Comparative analysis of a manual and an automated 3D landmark digitization method of the torso in adolescents with idiopathic scoliosis.Scientific reports · 2026Article
- "Visiting scientist effect"? Exploring the impact of time-lags in the digitization of 2D landmark data.Anatomical record (Hoboken, N.J. : 2007) · 2025Article
- Article
- Wing Shape Fluctuating Asymmetry in Flies: Insights into Environmental and Public Health Risk.Animals : an open access journal from MDPI · 2025Article
- Temporal Effects of Preservation on the Shape and Size of Yellow Perch: Implications for Morphological Analyses.Ecology and evolution · 2025Article
- Tales of a Super Butterfly: Is Vanessa carye a Truly Migrant Species? Unraveling Migration Using Morphological and Genomics Approaches.Molecular biology and evolution · 2025Article
- ECR-MobileNet: An Imbalanced Largemouth Bass Parameter Prediction Model with Adaptive Contrastive Regression and Dependency-Graph Pruning.Animals : an open access journal from MDPI · 2025Article
- Shell characterization of the youngest valid species of the European Eocene genus Neochelys (Pleurodira, Podocnemididae): The Spanish Bartonian Neochelys salmanticensis.Anatomical record (Hoboken, N.J. : 2007) · 2025Article
- Inter- and intra-observer variation in phytolith morphometry.Annals of botany · 2025Article
- The Influence of Aquaculture and a Natural Environmental Gradient on Shell Landmark Variation of the Mediterranean Mussel (Mytilus galloprovincialis Lamarck, 1819) From the Eastern Adriatic Sea.Journal of morphology · 2025Article
- Intraspecific Variation in Wings of Eufriesea violacea (Blanchard, 1840) (Hymenoptera, Apidae, Euglossina) from a Highly Fragmented Landscape in Western Paraná State, Brazil.Neotropical entomology · 2025Article
- Geometric morphometrics approach for classifying children's nutritional status on out of sample data.Scientific reports · 2025Article
- Article
24 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Geometric morphometrics-a set of methods for the statistical analysis of shape once saluted as a revolutionary advancement in the analysis of morphology -is now mature and routinely used in ecology and evolution. However, a factor often disregarded in empirical studies is the presence and the extent of measurement error. This is potentially a very serious issue because random measurement error can inflate the amount of variance and, since many statistical analyses are based on the amount of "explained" relative to "residual" variance, can result in loss of statistical power. On the other hand, systematic bias can affect statistical analyses by biasing the results (i.e. variation due to bias is incorporated in the analysis and treated as biologically-meaningful variation). Here, I briefly review common sources of error in geometric morphometrics. I then review the most commonly used methods to measure and account for both random and non-random measurement error, providing a worked example using a real dataset.
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