# Innovative Statistical Methods for Evaluating the Impact of Tobacco Product Standards

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2020 · $383,070

## Abstract

SUMMARY
 The FDA Center for Tobacco Products (FDACTP) has identified impact analyses of
potential FDA regulatory action as an area of scientific interest. Randomized controlled trials
(RCTs) are the gold-standard for understanding the impact of an intervention, but standard
approaches to analyzing RCTs have a number of drawbacks which limit our understanding of
the impact of a product standard. First, subjects may not adhere to their randomized treatment
assignment. Second, an RCT that was designed to evaluate the effect of a product standard in
the overall population may not be adequately powered to estimate the treatment effect within
important sub-groups. Finally, the characteristics of the population enrolled in the RCT may not
represent the target population. These limitations must be addressed to obtain a complete
understanding of the impact of potential product standards on public health.
 The goal of this application is to develop novel statistical methodology that addresses
these concerns. In Aim 1, we will develop statistical methods to estimate causal effects
(i.e., the effect if compliance were legally mandated) from multiple RCTs. Estimating
causal effects is central to understanding the impact of an intervention as a regulatory policy
and combining data from multiple trials in a principled manner will result in more efficient
estimators of causal effects without introducing bias. In Aim 2, we will develop a robust
approach for estimating causal effects in vulnerable populations. A number of vulnerable
populations are disproportionally burdened by tobacco, and the methodology developed in this
aim will result in precise estimates of the impact of a product standard in these sub-populations,
while providing a novel approach to elucidating population heterogeneity. In Aim 3, we will
develop methods to calibrate estimation of causal effects to a relevant target population.
The enrolled population of a RCT may not be representative of the target population and the
methodology developed in this aim will allow results of RCTs to be extrapolated to a target
population in the presence of treatment effect heterogeneity.
 This application addresses FDACTP scientific interest “Impact Analysis –
Understanding the impact of potential FDA regulatory actions”. Our application represents
a significant contribution to the field of tobacco regulatory science through the development of
innovative statistical methods that will result in more precise estimates of the impact of
potential FDA regulatory action (including impact in vulnerable populations) by principally
combining data from the many trials or product standards funded by FDACTP.

## Key facts

- **NIH application ID:** 9976479
- **Project number:** 5R01DA046320-03
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Joseph S. Koopmeiners
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $383,070
- **Award type:** 5
- **Project period:** 2018-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9976479

## Citation

> US National Institutes of Health, RePORTER application 9976479, Innovative Statistical Methods for Evaluating the Impact of Tobacco Product Standards (5R01DA046320-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9976479. Licensed CC0.

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