Statistical Analysis for Correlated Paired-plot Designs
Dilermando Perecin, Guilherme Moraes Ferraudo, Carlos Alberto Mathias Azania, Ana Regina Schiavetto
Journal of Experimental Agriculture International · pp. 1–7 · Published 17 Sep 2015
10.9734/AJEA/2015/20722Abstract
This work is aimed to evaluate different statistical analysis with a randomized complete block design for paired-plot studies of herbicide selectivity in sugarcane experiments. Two procedures were considered: i) the construction of a t-test to assess the hypothesis of the paired-plot mean difference to be zero in each treatment; or ii) the use of an analysis of variance where the treated and paired plots were considered in a split-plot model and the interaction is sliced by treatment. By simulation with normal bivariate distributions, with uniform (zero, 0.11, 0.33, 0.44, 0.67 or 0.89) or heterogeneous correlations, the two procedures showed similar performance. The power of the tests increases as the correlation of paired-plot increases.
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