Explores more advanced issues that researchers need to consider when using analysis of variance frameworks, building on basic issues for analysis of variance discussed in Jaccard and Guilamo-Ramos (2002). These include (a) using confidence intervals, (b) asserting group equivalence after a nonsignificant result, (c) use of magnitude estimation approaches, (d) sample size and power considerations, (e) outlier analysis, (f) violations of assumptions, and (g) missing data. Suggestions are offered for analytic practices in each of these domains.