期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2020
页码：201-220
DOI：10.2436/20.8080.02.100
出版社：SORT- Statistics and Operations Research Transactions
摘要：Compositional data analysis is concerned with the relative importance of positive variables, expressed through their log-ratios. The literature has proposed a range of manners to compute log-ratios, some of whose interrelationships have never been reported when used as explanatory variables in regression models. This article shows their similarities and differences in interpretation based on the notion that one log-ratio has to be interpreted keeping all others constant. The article shows that centred, additive, pivot, balance and pairwise log-ratios lead to simple reparametrizations of the same model which can be combined to provide useful tests and comparable effect size estimates.
关键词：compositional regression models;CoDa;composition as explanatory;centred log-ratios;pivot coordinates;pairwise log-ratios;additive log-ratios;effect size
