PERFORMANCE OF SIMPLE LINEAR REGRESSION ANALYSIS UNDER A RANDOMIZED COMPLETE BLOCK DESIGN - Alassane, Daibou; Ribeiro, Alice dos Santos; Ribeiro Júnior, José Ivo; Sediyama, Jaqueline Akemi S.; Muetanene, Belo Afonso (REVISTA DE AGRICULTURA, 2023)
In experiments conducted under a randomized complete block design, the fitting of the simple linear regression model can be performed under different combinations of the number of treatments and the number of replications. To determine the best combination, considering the same number of experimental units, it was concluded through a data simulation study that the quality of the fit increases when regression is performed in experiments with fewer treatments and more replications. Therefore, if linearity is expected, it is recommended to use two treatments for model fitting. Otherwise, three treatments are recommended. This applies to experiments with coefficients of variation between 10% and 30%.