Robustness is better assessed with a few thoughtful models than with billions of regressions

Embrace this beer-and-cheese-loving Midwestern capital with farmers’ markets, cozy supper clubs and picturesque lakeside strolls.

IBE, in y.

This Assistant Professor position will teach graduate and undergraduate courses, conduct research in the field of Sociology, participate in departmental service, and mentor graduate students.

The brain constantly generates predictions based on one’s knowledge of the world, as captured in memory. When these predictions are in error, our knowledge base must be revised to remain relevant. Her...

How does your brain decide what it’s seeing, from the physical world to other people? For decades, scientists have tried to understand how our brains work, not realising that the answer lies much clos...

The persistent contentiousness of research on the age–happiness relationship is puzzling; it should be possible to gain clarity and consensus about how to address the question effectively. In this paper I show that a key reason for the lack of clarity consists of overreliance on statistical significance as a means of evaluating empirical results. The statistical significance of a quadratic specification (age plus age-squared) is often taken as evidence in support of a ‘u-shaped’ relationship between age and happiness. But statistical significance on its own cannot tell us whether the age–happiness relationship is ‘u-shaped’ (nor indeed whether it takes any other shape). On the contrary, statistical significance can mislead us about it: a set of quadratic age coefficients can be ‘significant’ even when the relationship is obviously characterised by a different shape. When we have clarity on how to construct the analysis so that we can ‘see’ the underlying patterns in the data, it becomes obvious that the age–happiness relationship in European countries commonly shows other patterns; a u-shape is evident only in a minority of countries.