Imputation of data in analysis of variance in experiments in the Completely Randomized Design
DOI:
https://doi.org/10.5902/2179460X40447Keywords:
Missing Data, Imputation Methods, ANOVA, Analysis of Experimental DataAbstract
Unanticipated events often occur in the development of an experiment, especially in field experiments, often causing data loss. Through the present study, we sought to verify whether there is a difference in the result of the analysis of variance (ANOVA) test for unbalanced data in the Completely Randomized Design (DIC) when the inclusion of data obtained from the data imputation technique was performed of Predictive Average. Experiments were simulated in the DIC with 5 treatments and 10 repetitions, generating complete databases. From each database, 10% of the plots were removed and after the imputation method was applied, comparing the ANOVA results in each step. The imputation yielded acceptable results, but not better than those obtained when performing the specific ANOVA test for unbalanced data.
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