NDLI: A Baseline Category Logit Model for Assessing Competing Strains of Rhizobium Bacteria

Content Provider	Springer Nature Link
Author	Brophy, C. Connolly, J. Fagerli, I. L. Duodu, S. Svenning, M. M.
Copyright Year	2011
Abstract	In this paper we describe novel methodology for evaluating competition among strains of Rhizobium bacteria which can be found naturally occurring in or can be introduced into soil. Rhizobia can occupy nodules on the roots of legume plants allowing the plant to ‘fix’ atmospheric nitrogen. Our model defines competitive outcomes for a community (the multinomial count of nodules occupied by each strain at the end of a time period) relative to the past state of the community (the proportion of each strain present at the beginning of the time period) and incorporates this prior information in the analysis. Our approach for assessing competition provides an analogy to multivariate methods for continuous responses in competition studies and an alternative to univariate methods for discrete responses that respects the multivariate nature of the data. It can also handle zero values in the multinomial response providing an alternative to compositional data analysis methods, which traditionally have not been able to facilitate zero values. The proposed experimental design is based on the simplex design and the model is an extension of multinomial baseline category logit models that includes multiple offsets and random terms to allow for correlation among clustered responses. Supplemental materials for this article are available from the journal website.
Starting Page	409
Ending Page	421
Page Count	13
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	16
Issue Number	3
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-03-29
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Competition with discrete response Compositional data analysis Discrete multivariate analysis Random effects Simplex design Zero values Biostatistics Agriculture Statistics for Life Sciences, Medicine, Health Sciences Environmental Monitoring/Analysis
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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