Literature DB >> 28573732

Error in geometric morphometric data collection: Combining data from multiple sources.

Chris Robinson1, Claire E Terhune2.   

Abstract

OBJECTIVES: This study compares two- and three-dimensional morphometric data to determine the extent to which intra- and interobserver and intermethod error influence the outcomes of statistical analyses.
MATERIALS AND METHODS: Data were collected five times for each method and observer on 14 anthropoid crania using calipers, a MicroScribe, and 3D models created from NextEngine and microCT scans. ANOVA models were used to examine variance in the linear data at the level of genus, species, specimen, observer, method, and trial. Three-dimensional data were analyzed using geometric morphometric methods; principal components analysis was employed to examine how trials of all specimens were distributed in morphospace and Procrustes distances among trials were calculated and used to generate UPGMA trees to explore whether all trials of the same individual grouped together regardless of observer or method.
RESULTS: Most variance in the linear data was at the genus level, with greater variance at the observer than method levels. In the 3D data, interobserver and intermethod error were similar to intraspecific distances among Callicebus cupreus individuals, with interobserver error being higher than intermethod error. Generally, taxa separate well in morphospace, with different trials of the same specimen typically grouping together. However, trials of individuals in the same species overlapped substantially with one another.
CONCLUSION: Researchers should be cautious when compiling data from multiple methods and/or observers, especially if analyses are focused on intraspecific variation or closely related species, as in these cases, patterns among individuals may be obscured by interobserver and intermethod error. Conducting interobserver and intermethod reliability assessments prior to the collection of data is recommended.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  3D scanning; MicroScribe digitizer; data archiving and sharing; geometric morphometrics; measurement error

Mesh:

Year:  2017        PMID: 28573732     DOI: 10.1002/ajpa.23257

Source DB:  PubMed          Journal:  Am J Phys Anthropol        ISSN: 0002-9483            Impact factor:   2.868


  17 in total

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