  This article develops new closed-form variance expressions for power analyses
for commonly used panel model estimators. The main contribution is to
incorporate variation in treatment timing into the analysis, but the variance
formulas also account for other key design features that arise in practice:
autocorrelated errors, unequal measurement intervals, and clustering due to the
unit of treatment assignment. We consider power formulas for both
cross-sectional and longitudinal models and allow for covariates to improve
precision. An illustrative power analysis provides guidance on appropriate
sample sizes for various model specifications. An available Shiny R dashboard
performs the sample size calculations.
