Into the multiverse: Applications to neuropsychology

In neuropsychology, the heterogeneity of clinical syndromes combined with extensive methodological options creates a complex decision tree of pathways that result in a range of possible findings. A multiverse approach is a framework for navigating this uncertainty, allowing researchers to explore the impact of analytic decisions and assess the robustness of research findings. In this article, we demonstrate how multiverse can be applied to examine outcomes following traumatic brain injury (TBI).

Publicly available data from the Citicoline Brain Injury Treatment Trial research study (Zafonte et al., 2012) was used to showcase how multiverse can assess the effects of TBI severity using the specr and multiverse packages in R (v 4.3.1). We analyzed data from 159 adults (122 male; M = 40.30, SD = 15.80) with complicated mild or moderate-to-severe TBI. We also simulate data sets of various sample sizes (N = 40, 100, 300, 1000) to further evaluate the robustness of our results.

For quality-of-life outcomes, 66.7% of models showed a significant relationship with TBI severity. Increased TBI severity did not predict life satisfaction (Satisfaction With Life Scale) but was consistently associated with greater disability on the Disability Rating Scale. Processing speed models were significant in 88% of cases, with greater TBI severity predicting decreased processing speed. Mood symptom models were nonsignificant, indicating that TBI severity alone did not predict mood.

Multiverse uncovers insights that would have remained hidden under traditional approaches and has broad applications which can enhance scientific rigor and facilitate the translation of research into clinical interventions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).