Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…

Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons…

Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…

The increasing volume of large-scale assessment data poses a challenge for testing organizations to manage data and conduct psychometric analysis efficiently. Traditional psychometric software presents barriers, such as a lack of functionality for managing data and conducting various standard psychometric analyses efficiently. These challenges…

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…