Understanding vaccination hesitancy and how political party affiliation influences it has assumed priority in light of former US President Donald Trump's efforts, during his presidency, to undermine the science behind the development of vaccines to fight COVID-19. Using the data from Kreps et al. (2020) and insights from their discrete choice question results, we construct a new parsimonious model by which to investigate the effect of political party identification on one's willingness to receive a hypothetical COVID-19 vaccine, giving specific attention to assessing the robustness of our results. Utilizing a reparameterization in R^2 of the traditional OVB framework that is used to investigate the sensitivity of regression results to unobserved confounding (Cinelli & Hazlett, 2020), and deeming the non-randomized Republican party identification of the participants as the “pseudo” treatment effect of interest, we conclude that, under our model, the difference of nearly 3 percentage points in the probability of accepting a hypothetical COVID-19 vaccine for those identifying themselves as Republican is likely not robust to confounding. The approach outlined herein and introduced in Cinelli & Hazlett (2020) to assess the robustness of regression results should be more broadly adopted in the public health literature to better scope study conclusions.