We demonstrate that prior event exposures in panel data are a serious concern for identifying ‘causal’ effects. We re-analyzed the 2010–14 (3-wave) and 2010–12 (2-wave) CCES panel datasets and find that our original conclusions hold (see Newman and Hartman, 2017): respondents who live near a mass public shooting (in this case, within 100 miles of an event) are indeed more likely to support gun control than those who do not, provided we account for pre-treatment exposure. These treatment effects are statistically and practically significant: when accounting for pre-treatment exposures in the preceding 5 years, for instance, the effects of the treatment amount to an average increase in support for firearms restrictions of 23 to 41 per cent relative to the untreated respondents (and depending on the type of modeling approach). Ultimately, our new results highlight the importance of properly accounting for pre-treatment exposure when dealing with re-occurring treatments or ‘event chains’, and they contribute to the debate about how best to assess causal effects using panel data.