Measurement Error

Introduction In Part 1 of this series, we showed that six different methods for estimating individual means—James-Stein, classical true score estimation, empirical Bayes, ridge regression, and hierarchical models (frequentist and Bayesian)—all converge on the same fundamental principle: shrink each individual’s estimate toward the group mean by a factor of \(\sigma^2_{\text{pop}} / (\sigma^2_{\text{pop}} + \sigma^2_{\text{obs}}/n)\).

Introduction If I asked you to estimate 30 means, you would probably compute 30 sample means. And you would be provably wrong (well.. maybe not wrong, but at least provably inefficient).

Introduction The Dunning-Kruger effect is perhaps one of the most well-known effects in all of social psychology, defined as the phenomenon wherein people with low “objective” skill tend to over-estimate their objective skill, whereas people with high objective skill tend to under-estimate their skill.

Introduction In this post, we will explore how measurement error arising from imprecise parameter estimation can be corrected for. Specifically, we will explore the case where our goal is to estimate the correlation between a self-report and behavioral measure–a common situation throughout the social and behavioral sciences.