A score test for the agronomical overlap effect in a two-way classification model

dc.creatorAquiles Darghan
dc.creatorSinha Surendra
dc.creatorJulio Monroy
dc.date2014
dc.date.accessioned2026-07-07T02:43:42Z
dc.descriptionIn some agricultural research, a treatment applied to an experimental unit may affect the response in the neighboring experimental units. This phenomenon is known as overlap. In this article, a test to evaluate this effect in the Draper and Guttman model was developed by imposing side conditions on the parameters of a two-way classification model to obtain a re-parameterized model which can be used in different neighboring patterns of experimental units, usually plants within a crop, whenever the nearest neighbor is considered a directly affected experimental unit and the two-way model is used. Three methods, namely maximum likelihood, least squares with side conditions and generalized inverse, were used to estimate the parameters of the original model in order to calculate the value of the test statistics for the null hypothesis associated with the absence of the overlapping effect. The three alternatives were invariant with respect to the use of test. The proposed test is simple to adopt and can be implemented in agronomy since its asymptotic nature is in agreement with the large number of experimental units which generally exist in this type of research, where each plant represents the experimental unit being assessed.
dc.formatapplication/pdf
dc.identifier0120-9965
dc.identifierhttps://www.redalyc.org/articulo.oa?id=180333786016
dc.identifier.urihttp://hdl.handle.net/123456789/422025
dc.languageen
dc.publisherUniversidad Nacional de Colombia
dc.relationhttp://www.redalyc.org/revista.oa?id=1803
dc.rightsAgronomía Colombiana
dc.sourceAgronomía Colombiana (Colombia) Num.3 Vol.32
dc.subjectAgrociencias
dc.titleA score test for the agronomical overlap effect in a two-way classification model
dc.typeartículo científico

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