gosset: An R package for analysis and synthesis of ranking data in agricultural experimentation
Kauê de Sousa,
David Brown,
Jonathan Steinke,
Jacob van Etten
Affiliations
Kauê de Sousa
Department of Agricultural Sciences, Inland Norway University of Applied Sciences, 2318 Hamar, Norway; Digital Inclusion, Bioversity International, Parc Scientifique Agropolis II, 34397, Montpellier Cedex 5, France; Corresponding author at: Digital Inclusion, Bioversity International, Parc Scientifique Agropolis II, 34397, Montpellier Cedex 5, France.
David Brown
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708 PB, Wageningen, The Netherlands; Digital Inclusion, Bioversity International, 30501, Turrialba, Costa Rica; College of Agriculture and Life Sciences, Cornell University, 14853 Ithaca, NY, United States of America
Jonathan Steinke
Digital Inclusion, Bioversity International, Parc Scientifique Agropolis II, 34397, Montpellier Cedex 5, France; Thaer Institute of Agricultural and Horticultural Sciences, Humboldt University Berlin, Unter den Linden 6, 10099 Berlin, Germany
Jacob van Etten
Digital Inclusion, Bioversity International, Parc Scientifique Agropolis II, 34397, Montpellier Cedex 5, France
To derive insights from data, researchers working on agricultural experiments need appropriate data management and analysis tools. To ensure that workflows are reproducible and can be applied on a routine basis, programmatic tools are needed. Such tools are increasingly necessary for rank-based data, a type of data that is generated in on-farm experimentation and data synthesis exercises, among others. To address this need, we developed the R package gosset, which provides functionality for rank-based data and models. The gosset package facilitates data preparation, modeling and results presentation stages. It introduces novel functions not available in existing R packages for analyzing ranking data. This paper demonstrates the package functionality using the case study of a decentralized on-farm trial of common bean (Phaseolus vulgaris L.) varieties in Nicaragua.
