How can process-based researchers bridge the gap between individuals and groups? Discover the dynamic p-technique

Abstract

Behavioral researchers are concluding that conventional group-based analyses often mask meaningful individual differences and do not necessarily map onto the change processes within the lives of individual humans. Hayes et al. (2018) have called for a renewed focus on idiographic research, but with methods capable of nuanced multivariate insights and capable of scaling to nomothetic generalizations. To that end, we present a statistical technique we believe may be useful for the task: the dynamic p-technique. The dynamic p-technique can accommodate multivariate longitudinal data and may be used to conduct single-subject and group-level analyses. After introducing the dynamic p-technique, we provide several examples of how it may be used in practice by presenting the step-by-step analyses of single-subject daily-diary dataset wherein we examined the day-to-day associations between ADHD difficulties and psychotropic medication. Although it has been underutilized by behavioral researchers, we believe p-technique analyses are particularly well-suited to model personal dynamics with nuance and within context and allow researchers to inductively build from idiographic patterns to nomothetic trends. For a fine-grain walk-through of the analyses presented, including the data and statistical code, link to our supplemental materials: https://osf.io/cbyj3/.

@article{kurzHowCanProcessBased2019,
  title = {How can process-based researchers bridge the gap between individuals and groups? Discover the dynamic p-technique},
  author = {A. Solomon Kurz and Yelena L. Johnson and Karen Kate Kellum and Kelly G. Wilson},
  journal = {Journal of Contextual Behavioral Science},
  year = 2019,
  volume = 13,
  page = 60--65,
  doi = {https://doi.org/10.1016/j.jcbs.2019.07.001}
}
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