Model-based estimates for operant selection.

We present a new methodology to partition different sources of behavior change within a selectionist framework based on the Price equation-the multilevel model of behavioral selection. The multilevel model of behavioral selection provides a theoretical background to describe behavior change in terms of operant selection. Operant selection is formally captured by the covariance-based law of effect and accounts for all changes in individual behavior that involve a covariance between behavior and predictors of evolutionary fitness (e.g., food). In this article, we show how the covariance-based law of effect may be applied to different components of operant behavior (e.g., allocation, speed, and accuracy of responding), thereby providing quantitative estimates for various selection effects affecting behavior change using data from a published learning experiment with pigeons.