scholarly journals A Bibliometric Analysis of the 35th anniversary of the paper "The Statistical Analysis of Compositional Data" by John Aitchison (1982)

2021 ◽  
Vol 50 (2) ◽  
pp. 38-55
Author(s):  
Carolina Navarro ◽  
Silvia Gonzalez-Morcillo ◽  
Carles Mulet-Forteza ◽  
Salvador Linares-Mustaros

This study presents a comprehensive bibliometric analysis of the paper published by John Aitchison in the Journal of the Royal Statistical Society. Series B (Methodological) in 1982. Having recently reached the milestone of 35 years since its publication, this pioneering paper was the first to illustrate the use of the methodology "Compositional Data Analysis" or "CoDA". By October 2019, this paper had received over 780 citations, making it the most widely cited and influential article among those using said methodology. The bibliometric approach used in this study encompasses a wide range of techniques, including a specific analysis of the main authors and institutions to have cited Aitchison' paper. The VOSviewer software was also used for the purpose of developing network maps for said publication. Specifically, the techniques used were co-citations and bibliographic coupling. The results clearly show the significant impact the paper has had on scientific research, having been cited by authors and institutions that publish all around the world.

2021 ◽  
Vol 8 (1) ◽  
pp. 271-299
Author(s):  
Michael Greenacre

Compositional data are nonnegative data carrying relative, rather than absolute, information—these are often data with a constant-sum constraint on the sample values, for example, proportions or percentages summing to 1% or 100%, respectively. Ratios between components of a composition are important since they are unaffected by the particular set of components chosen. Logarithms of ratios (logratios) are the fundamental transformation in the ratio approach to compositional data analysis—all data thus need to be strictly positive, so that zero values present a major problem. Components that group together based on domain knowledge can be amalgamated (i.e., summed) to create new components, and this can alleviate the problem of data zeros. Once compositional data are transformed to logratios, regular univariate and multivariate statistical analysis can be performed, such as dimension reduction and clustering, as well as modeling. Alternative methodologies that come close to the ideals of the logratio approach are also considered, especially those that avoid the problem of data zeros, which is particularly acute in large bioinformatic data sets.


Author(s):  
Lisa-Marie Larisch ◽  
Emil Bojsen-Møller ◽  
Carla F. J. Nooijen ◽  
Victoria Blom ◽  
Maria Ekblom ◽  
...  

Intervention studies aiming at changing movement behavior have usually not accounted for the compositional nature of time-use data. Compositional data analysis (CoDA) has been suggested as a useful strategy for analyzing such data. The aim of this study was to examine the effects of two multi-component interventions on 24-h movement behavior (using CoDA) and on cardiorespiratory fitness among office workers; one focusing on reducing sedentariness and the other on increasing physical activity. Office workers (n = 263) were cluster randomized into one of two 6-month intervention groups, or a control group. Time spent in sedentary behavior, light-intensity, moderate and vigorous physical activity, and time in bed were assessed using accelerometers and diaries, both for 24 h in total, and for work and leisure time separately. Cardiorespiratory fitness was estimated using a sub-maximal cycle ergometer test. Intervention effects were analyzed using linear mixed models. No intervention effects were found, either for 24-h behaviors in total, or for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Despite a thorough analysis of 24-h behaviors using CoDA, no intervention effects were found, neither for behaviors in total, nor for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Although the design of the multi-component interventions was based on theoretical frameworks, and included cognitive behavioral therapy counselling, which has been proven effective in other populations, issues related to implementation of and compliance with some intervention components may have led to the observed lack of intervention effect.


mSphere ◽  
2017 ◽  
Vol 2 (5) ◽  
Author(s):  
Gaorui Bian ◽  
Gregory B. Gloor ◽  
Aihua Gong ◽  
Changsheng Jia ◽  
Wei Zhang ◽  
...  

ABSTRACT We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations. The microbiota of the aged is variously described as being more or less diverse than that of younger cohorts, but the comparison groups used and the definitions of the aged population differ between experiments. The differences are often described by null hypothesis statistical tests, which are notoriously irreproducible when dealing with large multivariate samples. We collected and examined the gut microbiota of a cross-sectional cohort of more than 1,000 very healthy Chinese individuals who spanned ages from 3 to over 100 years. The analysis of 16S rRNA gene sequencing results used a compositional data analysis paradigm coupled with measures of effect size, where ordination, differential abundance, and correlation can be explored and analyzed in a unified and reproducible framework. Our analysis showed several surprising results compared to other cohorts. First, the overall microbiota composition of the healthy aged group was similar to that of people decades younger. Second, the major differences between groups in the gut microbiota profiles were found before age 20. Third, the gut microbiota differed little between individuals from the ages of 30 to >100. Fourth, the gut microbiota of males appeared to be more variable than that of females. Taken together, the present findings suggest that the microbiota of the healthy aged in this cross-sectional study differ little from that of the healthy young in the same population, although the minor variations that do exist depend upon the comparison cohort. IMPORTANCE We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations.


2015 ◽  
Vol 319 ◽  
pp. 134-146 ◽  
Author(s):  
Catarina Guerreiro ◽  
Mário Cachão ◽  
Vera Pawlowsky-Glahn ◽  
Anabela Oliveira ◽  
Aurora Rodrigues

2000 ◽  
Vol 32 (8) ◽  
pp. 953-959 ◽  
Author(s):  
Jane M. Fry ◽  
Tim R. L. Fry ◽  
Keith R. McLaren

Geobios ◽  
2009 ◽  
Vol 42 (5) ◽  
pp. 561-579 ◽  
Author(s):  
Valentino Di Donato ◽  
Paola Esposito ◽  
Vittorio Garilli ◽  
Debora Naimo ◽  
Giuseppe Buccheri ◽  
...  

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0206013 ◽  
Author(s):  
Irene Rodríguez-Gómez ◽  
Asier Mañas ◽  
José Losa-Reyna ◽  
Leocadio Rodríguez-Mañas ◽  
Sebastien F. M. Chastin ◽  
...  

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