Analyzing learning rates (pt. 1): Common pitfalls

Do you want to learn how to analyze learning? In this first post of a two-part series, Jake Zureich discussed common pitfalls when comparing learning curves using an illustrative example.

'Effect sizes don't matter in experiments.' Or do they?

Some accounting researchers argue that effect sizes do not matter in experiments. In this post, I explain why effect sizes do matter and why they can be particularly valuable for experiments in the field of accounting.

When and how to cluster standard errors in experimental data?

Choosing whether and on which level to cluster standard errors in experimental data turns out to be less straightforward that I originally thought. However, some practical advice for experimental researchers is emerging.

Stata commands for multi-period experimental data

Multi-period experimental designs are a popular way to generate more observations and examine changes in behavior over time. Yet, choosing the most appropriate model to analyze the data can be challenging. In this post, I showcase two Stata commands that help you select among different empirical models.