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This workshop will explore strategies for optimizing the design of quantitative research, with an emphasis on simulation. In Part I, we will review basic concepts of statistical power and effect size and introduce a simulation-based approach to power analysis. In Part II, we will describe simulation methods for ANOVA designs, and in Part III applications for MLM and SEM. After the break, we will discuss at length strategies for estimating effect sizes when information is limited and uncertainty is high, buffering power against inaccurate effect size estimates, the impact of study design on effect magnitude, and strategies for optimizing power beyond increasing sample size. We will also discuss different types of power analyses (e.g. a priori vs. sensitivity), and how to sufficiently report results to enable replicability. Finally, Part IV will consist of a Q&A session in which participants are encouraged to bring their own planned studies to collectively brainstorm optimization strategies. This workshop is open to participants at all levels of pre-existing statistical expertise. Participants are encouraged but not required to bring their laptops, particularly if R, SAS, and/or MPlus is installed.