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This study was conducted to compare Type I error and test power of ANOVA, REML and ML methods by Monte Carlo simulation technique under different experimental conditions. Simulation results indicated that the variance ratios, sample size and number of groups were important factors in determining appropriate methods which were used to estimate variance components. The ML method was found slightly superior when compared to ANOVA and REML methods. On the other hand, ANOVA and REML methods generated similar results in general. As a results, regardless of distribution shapes and number of groups and if n<15; ML, REML methods might be preferred to the ANOVA. However, when either number of groups or sample size was increased (n≥15) ANOVA method may also be used along with ML and REML

Type I error rates and test power for some variance components estimation methods: one-way random effect model