Cited by 704Geochemistry and Geologic MappingAdvanced Statistical Methods and ModelsStatistical Methods and Applications

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Compositional Data Analysis: Theory and Applications

V. Pawlowsky Glahn, Antonella Buccianti·2011·Wiley eBooks

DOI 10.1002/9781119976462

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Abstract

It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science.

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Background
A survey on pre-processing techniques: Relevant issues in the context of environmental data mining
Gibert, K., Sànchez–Marrè, M., & Izquierdo, J. (2016) · AI Communications · doi:10.3233/aic-160710 · Cited by 77
“Finally, compositional data are sets of s strictly positive real variables with constant sum Z > 0 [181].”
Aitchison’s Compositional Data Analysis 40 Years on: A Reappraisal
Greenacre, M. J., Grunsky, E., Bacon‐Shone, J., Erb, I., & Quinn, T. P. (2023) · Statistical Science · doi:10.1214/22-sts880 · Cited by 98
“Several books have been published that present developments in the theory and practice of CoDA based on logratios [66, 67, 40, 24].”
Background
Potentially toxic elements in soils of Campania region (Southern Italy): Combining raw and compositional data
Zuzolo, D., Cicchella, D., Lima, A., et al. (2020) · Journal of Geochemical Exploration · doi:10.1016/j.gexplo.2020.106524 · Cited by 74
Some practical aspects of predicting texture data in digital soil mapping
Amirian‐Chakan, A., Minasny, B., Taghizadeh‐Mehrjardi, R., Akbarifazli, R., Darvishpasand, Z., & Khordehbin, S. (2019) · Soil and Tillage Research · doi:10.1016/j.still.2019.06.006 · Cited by 75
Mapping of Fe mineralization-associated geochemical signatures using logratio transformed stream sediment geochemical data in eastern Tianshan, China
Wang, W., Zhao, J., & Cheng, Q. (2013) · Journal of Geochemical Exploration · doi:10.1016/j.gexplo.2013.11.008 · Cited by 73
Common trends in elements? Within- and between-tree variations of wood-chemistry measured by X-ray fluorescence — A dendrochemical study
Scharnweber, T., Hevia, A., Buras, A., van der Maaten, E., & Wilmking, M. (2016) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2016.05.182 · Cited by 72
A kriging approach based on Aitchison geometry for the characterization of particle-size curves in heterogeneous aquifers
Menafoglio, A., Guadagnini, A., & Secchi, P. (2014) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-014-0849-8 · Cited by 72
“We use two viewpoints to interpret these types of data: (a) a Functional Data Analysis [FDA, Ramsay and Silverman (2005)] and (b) a Compositional Data Analysis [CoDa, Aitchison (1982); Aitchison (1986); Pawlowsky-Glahn and Buccianti (2011)] approach.”
Method
Spatial analysis of compositional data: A historical review
Pawlowsky‐Glahn, V., & Egozcue, J. J. (2015) · Journal of Geochemical Exploration · doi:10.1016/j.gexplo.2015.12.010 · Cited by 72
Self-citation
Clustering transformed compositional data using K -means, with applications in gene expression and bicycle sharing system data
Godichon‐Baggioni, A., Maugis-Rabusseau, C., & Rau, A. (2018) · Journal of Applied Statistics · doi:10.1080/02664763.2018.1454894 · Cited by 70
“…the relative proportions of a whole and can be represented in the simplex of d parts: Such data are a common phenomenon in several research domains, including evolutionary ecology [1,6], geochemistry [10,31], economics [15,26], and genomic surveys [20]; see [32] for more examples of applications.”
Background
Geometallurgical Modeling at Olympic Dam Mine, South Australia
Boisvert, J. B., Rossi, M. E., Ehrig, K. J., et al. (2013) · Mathematical Geosciences · doi:10.1007/s11004-013-9462-5 · Cited by 71
“A good review of best practice for compositional data modeling techniques is provided by Pawlowsky-Glahn and Buccianti (2011).”
Method
Graphical statistics to explore the natural and anthropogenic processes influencing the inorganic quality of drinking water, ground water and surface water
Flem, B., Reimann, C., Fabian, K., et al. (2017) · Applied Geochemistry · doi:10.1016/j.apgeochem.2017.09.006 · Cited by 70
Interpretation of Na–Cl–Br Systematics in Sedimentary Basin Brines: Comparison of Concentration, Element Ratio, and Isometric Log-ratio Approaches
Engle, M. A., & Rowan, E. L. (2012) · Mathematical Geosciences · doi:10.1007/s11004-012-9436-z · Cited by 68
Aurora: A Generalized Retrieval Framework for Exoplanetary Transmission Spectra
Welbanks, L., & Madhusudhan, N. (2021) · The Astrophysical Journal · doi:10.3847/1538-4357/abee94 · Cited by 60
Applications and Comparison of Dimensionality Reduction Methods for Microbiome Data
Armstrong, G., Rahman, G., Martino, C., McDonald, D. T., González, A., Mishne, G., & Knight, R. D. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.821861 · Cited by 70
“…such as the additive log-ratio (ALR), centered log-ratio (CLR), and isometric log-ratio (ILR) can convert abundance data to the space of real numbers such that analysis and interpretation are less skewed by false positives (Aitchison and Greenacre, 2002; Pawlowsky-Glahn and Buccianti, 2011).”
Background
Assessing multiscale visual appearance characteristics of neighbourhoods using geographically weighted principal component analysis in Shenzhen, China
Wu, C., Peng, N., Ma, X., et al. (2020) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2020.101547 · Cited by 65
Contrasting Modes and Tempos of Venom Expression Evolution in Two Snake Species
Margres, M. J., McGivern, J. J., Seavy, M. A., Wray, K. P., Facente, J., & Rokyta, D. R. (2014) · Genetics · doi:10.1534/genetics.114.172437 · Cited by 64
Exploring topsoil geochemistry from the CoDA (Compositional Data Analysis) perspective: The multi-element data archive of the Campania Region (Southern Italy)
Buccianti, A., Lima, A., Albanese, S., Cannatelli, C., Esposito, R., & Vivo, B. D. (2015) · Journal of Geochemical Exploration · doi:10.1016/j.gexplo.2015.10.006 · Cited by 62
“Consequently, with the objective of investigating thewhole covariance structure of a geochemical dataset and tentatively identifying a baseline composition (1 × D, D number of variables) able to represent frequent and potentially spatially organised processes (following the FOREGS definition), a procedure is proposed…”
MethodSelf-citation
One day you'll wake up and won't have to go to work: The impact of changes in time use on mental health following retirement
Olds, T., Burton, N. W., Sprod, J. A., Maher, C. A., Ferrar, K., Brown, W. J., van Uffelen, J. G. Z., & Dumuid, D. (2018) · PLoS ONE · doi:10.1371/journal.pone.0199605 · Cited by 64
Weighted Pivot Coordinates for Compositional Data and Their Application to Geochemical Mapping
Hron, K., Filzmoser, P., de Caritat, P., et al. (2017) · Mathematical Geosciences · doi:10.1007/s11004-017-9684-z · Cited by 62
Organic carbon stock and composition in 3.5-m core mangrove soils (Trat, Thailand)
Kida, M., Watanabe, I., Kinjo, K., Kondo, M., Yoshitake, S., Tomotsune, M., Iimura, Y., Umnouysin, S., Suchewaboripont, V., Poungparn, S., et al. (2021) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2021.149682 · Cited by 66
Source patterns and contamination level of polycyclic aromatic hydrocarbons (PAHs) in urban and rural areas of Southern Italian soils
Thiombane, M., Albanese, S., Bonito, M. D., et al. (2018) · Environmental Geochemistry and Health · doi:10.1007/s10653-018-0147-3 · Cited by 62
Factors Influencing Consumer Purchase Intentions of Organically Grown Products in Shelly Centre, Port Shepstone, South Africa
Wekeza, S. V., & Sibanda, M. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16060956 · Cited by 62
“Larger samples are more expressive than smaller samples which decrease the level of accuracy yet moderately accessible and cheap [40].”
Background
Financial performance and distress profiles. From classification according to financial ratios to compositional classification
Linares‐Mustarós, S., Coenders, G., & Vives‐Mestres, M. (2017) · Advances in Accounting · doi:10.1016/j.adiac.2017.10.003 · Cited by 61
Status, sources and contamination levels of organochlorine pesticide residues in urban and agricultural areas: a preliminary review in central–southern Italian soils
Thiombane, M., Petrik, A., Bonito, M. D., et al. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-2688-5 · Cited by 61
Drone-Borne Hyperspectral and Magnetic Data Integration: Otanmäki Fe-Ti-V Deposit in Finland
Jackisch, R., Madriz, Y., Zimmermann, R., Pirttijärvi, M., Saartenoja, A., Heincke, B. H., Salmirinne, H., Kujasalo, J.-P., Andreani, L., & Gloaguen, R. (2019) · Remote Sensing · doi:10.3390/rs11182084 · Cited by 65
Major and persistent shifts in below‐ground carbon dynamics and soil respiration following logging in tropical forests
Riutta, T., Kho, L. K., Teh, Y. A., Ewers, R. M., Majalap, N., & Malhi, Y. S. (2021) · Global Change Biology · doi:10.1111/gcb.15522 · Cited by 60
“…respiration, and the relative contribution of litter and root inputs to total necromass pool, differed between the forest types, we used linear models for compositional data (Pawlowsky-Glahn & Buccianti, 2011), in the R package ‘compositions’ (van der Boogaart et al., 2014; van der Boogaart, 2008).”
Method
Source patterns of potentially toxic elements (PTEs) and mining activity contamination level in soils of Taltal city (northern Chile)
Reyes, A., Thiombane, M., Pánico, A., et al. (2019) · Environmental Geochemistry and Health · doi:10.1007/s10653-019-00404-5 · Cited by 59
Phytochemicals in fruits of two Prunus domestica L. plum cultivars during ripening
Usenik, V., Štampar, F., & Kastelec, D. (2012) · Journal of the Science of Food and Agriculture · doi:10.1002/jsfa.5783 · Cited by 57

Authors: Glahn, V. P., & Buccianti, A.
ORCID: Antonella Buccianti
Venue: Wiley eBooks
Publisher: Wiley
Published: 2011-07-28
DOI: 10.1002/9781119976462
OpenAlex: W571770348
Cited by: 704
References: 0
Citations by year: 2026: 30 · 2025: 38 · 2024: 34 · 2023: 40 · 2022: 45 · 2021: 71 · 2020: 71 · 2019: 46 · 2018: 61 · 2017: 60 · 2016: 52 · 2015: 42 · 2014: 47 · 2013: 37 · 2012: 22
FWCI: 14.85
Type: book
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
Locations: Wiley eBooks (publishedVersion)
Florence Research (University of Florence) (submittedVersion)
Topics: Physical Sciences › Earth and Planetary Sciences › Geochemistry and Petrology › Geochemistry and Geologic Mapping
Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: compositional data analysis, spurious correlations, parts and wholes

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