<p>Although random assignment is the standard for drawing causal inferences within clinical trials, it is generally precluded in legal market cannabis research given its federal classification as a schedule 1 drug. Unfortunately, this may cause selection bias and compromise internal validity, and thus, alternative approaches are necessary. One such approach in this context, as well as more broadly, is quasi-random assignment whereby participants are randomly assigned to conditions but can accept or decline this assignment. This study explores whether those who accept or decline condition assignment differ in ways that impact study outcomes and informs best practices for other research areas where random assignment is not feasible or permitted. Data came from two studies examining cannabis, inflammation, and insulin sensitivity. The first included individuals who infrequently used cannabis; the second included regular users. Across studies, individuals were quasi-randomly assigned via dice roll to purchase and use either THC-dominant, CBD-dominant, or approximately equal THC:CBD ratio flower products for 1 (study 1) or 4&#xa0;weeks (study 2). Demographics, cannabis use, health behaviors (e.g., exercise), and anthropometrics (i.e., body mass index [BMI]) were compared across individuals who accepted versus declined their assigned condition. Most participants accepted their assignment (83% and 63% for studies 1 and 2, respectively). Those who accepted did not differ from those who declined on any variable (<i>p</i>s &gt; 0.11). While findings cannot rule out a selection process outside the variables assessed, results support use of this methodology in situations where true random assignment is not possible. Clinical trials: The larger project from which the current paper draws data was pre-registered on Clinicaltrials.gov (NCT04114903) on 09–06-2019.</p>