We show that group sequential designs (which allow to perform interim analyses while data collection is ongoing) can unlock numerous benefits for researchers engaged in confirmatory hypothesis testing: They facilitate sample size decisions, allow researchers to achieve a desired level of statistical power with a smaller number of observations, and help conduct more efficient pilot studies. We validate this cost-saving potential through a comprehensive re-analysis of 212 studies published in the Journal of Consumer Research, which shows that using these designs would have reduced costs by 20% to 29%. We conclude with a discussion of limitations and possible alternatives.

Would people report a different valuation for a 50 dollars Amazon gift card that is certain to be available, and for the same gift card that has a 10% chance of being available? In violation of expected utility theory, we show that people anticipate less utility from uncertain outcomes than from certain outcomes, even conditional on their realization. We show that it isn’t driven by beliefs about the quality the good (we always use gift cards, which are of unambiguous quality), by a misunderstanding of the instructions, or by differences in “weirdness“ (Mislavsky and Simonsohn 2018) between the transactions.

How should researchers exclude outliers: Across the data, or within conditions? In this paper, I show that when outlier exclusions are performed in a way that is not ‘blind’ to the researchers’ hypothesis (e.g., within conditions), they increase Type I error to unacceptable levels.

Can loss aversion disappear and reverse? In this article, we show that the shifts in loss aversion reported in Walasek and Stewart (2015) are driven by an invalid experimental paradigm. After correcting this error, we do not see evidence that loss aversion is shaped by the distribution of gains and losses that people have encountered.

Consumers intuitively categorize front-of-packaging claims displayed on food into 4 broad categories: (1) Claims about “removing negatives,” (2) claims about “adding positives,” (3) claims about “not adding negatives,” and (4) claims about “not removing positives.” Each type of claim is associated with different beliefs about the healthiness, tastiness, and dieting properties of the food.