Título:	Two-stage inference in experimental design using DEA: an application to intercropping and evidence from randomization theory.
Autoria:	GOMES, E. G. SOUZA, G. da S. e VIVALDI, L. J.
Afiliação:	Eliane Gonçalves Gomes, Embrapa-SGE; GERALDO DA SILVA E SOUZA, Embrapa-SGE; Lúcio José Vivaldi, Universidade de Brasília.
Ano de publicação:	2008
Referência:	Pesquisa Operacional, v.28, n.2, p. 339-354, mai./ago. 2008.
Conteúdo:	In this article we propose the use of Data Envelopment Analysis (DEA) measures of efficiency, under constant returns to scale and input equal to unity, in the analysis of multidimensional nonnegative responses in the design of experiments. The approach agrees with the standard Analysis of Variance (Covariance) for univariate responses and simplifies the statistical analysis in the multivariate case. The best treatments provided by the analysis optimize a combined output defined by shadow prices, which are the solutions of the DEA problem. The approach is particularly useful for the analysis of intercropping (crop mixtures) experiments. In this context we discuss two examples. To properly address the issue of correlation and non-normality of DEA measurements in different experimental plots we validate the results via Randomization Theory.
NAL Thesaurus:	experimental design intercropping
Palavras-chave:	Ensaio experimental Consórcio Análise envoltória de dados Data envelopment analysis
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado / Embrapa Unidades Centrais (AI-SEDE)