Key result
Decisions about theoretical frameworks and hypotheses create a conceptual multiverse that introduces considerable variability in research outcomes, which can be evaluated using Bayes Factors.
Why the study?
Multiverse analyses in psychophysiology almost exclusively focus on methodological and statistical decisions, largely ignoring the role of the conceptual multiverse regarding theory-related research decisions.
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This methodological paper highlights the importance of considering theoretical frameworks (the conceptual multiverse) alongside statistical and methodological decisions in psychophysiological research.
Multiverse analyses—the systematic examination of the effects of decisions that researchers can take over the course of a research project—became more common in recent psychophysiological research. However, multiverse analyses in psychophysiology almost exclusively focus on methodological and statistical decisions that can have a considerable impact on the findings. The role of the conceptual multiverse regarding theory-related research decisions is largely ignored. We argue that the choice of a theory that guides hypotheses, study design, measurement methods, and statistical analyses is the first plane of the psychophysiological multiverse. Depending on the chosen theoretical framework, researchers will choose different methods, and statistical analyses will emphasize specific aspects. We illustrate this process with a research example studying the effects of task difficulty manipulations on cardiovascular effects reflecting effort. We argue in favor of an approach that explicitly acknowledges the various theoretical accounts that can constitute the background of a study and demonstrate how a comparative analytical approach can provide a comprehensive multiverse without increasing type I error due to mere exploration. • Multiverse data analysis has become more frequent in psychophysiology. • Most multiverse analyses focus on research outcome variability caused by decisions about data processing or analysis. • Conceptual multiverses associated with decisions about theories and hypotheses are equally important for outcome variability. • A comparative approach considering different theoretical positions provides a concise account of the conceptual multiverse.
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Richter et al. (2024) studied this question. Decisions about theoretical frameworks and hypotheses create a conceptual multiverse that introduces considerable variability in research outcomes, which can be evaluated using Bayes Factors.
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