This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…

In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

In programming, one problem can usually be solved using different logics and constructs but still producing the same output. Sometimes students get marked down inappropriately if their solutions do not follow the answer scheme. In addition, lab exercises and programming assignments are not necessary graded by the instructors but most of the time…

Describes two QuickBASIC programs that provide students direct experience with interpreting correlation scatter-plots. Maintains that the programs can be used in classroom exercises to highlight factors that influence the size of a Pearson correlation coefficient. (CFR)

Describes a QuickBASIC program for demonstrating the differences between main effects and interactions in factorial designs. The program can be used in conjunction with a traditional lecture to improve student understanding and develop skills in recognizing main effects and interactions from graphic displays. (CFR)