Objectives: The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative study of the US population on tobacco use and its effects on health, with 3 waves of data collection between 2013 and 2016. Prior work described the methods of the first wave. In this paper, we describe the methods of the subsequent 2 waves and provide recommendations for how to conduct longitudinal analyses of PATH Study data. Methods: We use standard survey quality metrics to evaluate the results of the follow-up waves of the PATH Study. The recommendations and examples of longitudinal and cross-sectional analyses of PATH Study data follow a design-based statistical inference framework. Results: The quality metrics indicate that the PATH Study sample of approximately 40,000 continuing respondents remains representative of its target population. Depending on the intended analysis, different survey weights may be appropriate. Conclusion: The PATH Study data are a valuable resource for regulatory scientists interested in longitudinal analysis of tobacco use and its effects on health. The availability of multiple sets of specialized survey weights enables researchers to target a wide range of tobacco-related analytic questions.

Intercalation of the ethidium analogue 3,5-diazido-5-ethyl-6-phenylphenanthridinium into double helices followed by irradiation with blue or ultraviolet light results in cross-linking between the two strands with an efficiency around 30% for DNA, RNA, and DNA-RNA hybrids. Details of this reaction and a convenient synthesis of the ethidium analogue are described. Stable tertiary structure in RNA impedes intercalation and thus reduces the efficiency of cross-linking. In contrast to the ethidium derivative, various acridine diazides show little or no cross-linking ability.

The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative study of the US population on tobacco use and its effects on health, with four waves of data collection between 2013 and 2017. Prior work described the methods of the first three waves. In this paper, we describe the methods of Wave 4, during which a replenishment sample was added to the ongoing cohort. We describe the design and estimation methods of the continuing Wave 1 cohort (with four waves of data) and the Wave 4 cohort (the new cohort created at Wave 4). We provide survey quality metrics, including response rates for both cohorts and a panel conditioning analysis, and guidance on understanding the target populations for both cohorts.