Confounding in studies on metacognition: a preliminary causal analysis framework

By definition, metacognitive processes may monitor or regulate various stages of first-order processing. By combining formal causal analysis with hypotheses expressed by other authors we derive the theoretical and methodological consequences of this special relation between metacognition and the underlying processes. In particular, we prove that 1) without additional causal assumptions, neither metacognitive judgements (e.g., confidence ratings) nor correlations between performance (e.g., accuracy or sensitivity) and metacognitive judgements are unbiased measures of metacognitive monitoring or regulation; 2) that without additional causal assumptions, typical methods of controlling for first-order task performance (i.e., calibration, staircase, including first-order task performance in a regression analysis, or analyzing correct and incorrect trials separately) do not deconfound measures of metacognition; 3) that the first two problems cannot be solved by using simple models of decision-making derived from Signal Detection Theory. We conclude the paper by advocating robust methods of discovering properties of latent mechanisms.

This is the preprint version of the following published article: Paulewicz, B., Siedlecka, M., & Koculak, M. (2020). Confounding in Studies on Metacognition: A Preliminary Causal Analysis Framework. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.01933.