# Improve Power in Dental Research

> **NIH NIH R03** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $160,669

## Abstract

Project Summary
Statistical power is one key element of robust results and scientific rigor, so sample size and power calculation
is a crucial step in designing a study and especially important for dental outcomes with excess zeros when
many subjects have not experienced the oral disease. Different approaches have been developed to model
outcomes with excess zeros (Duan et al 1983; Lambert 1992; Long 1997; Min and Agresti 2002; Hilbe 2011;
Kassahun et al. 2014; Neelon et al. 2016). However, the existing models may have limited power (Williamson
et al. 2007; Follman et al. 2009). This project will examine intensively the statistical power of existing analysis
methods specifically on longitudinal dental outcomes with a large amount of zeros under different realistic
settings, and develop software for sample size and power calculation for overall treatment effects and mediation
effects specifically on longitudinal zero-inflated (ZI) dental outcomes for more accurate estimate on the sample
size needed. The software we will develop will provide investigators a tool to design a study with good power to
examine not only the overall treatment effects but also potential mechanisms or pathways the treatment works.
A larger sample size is usually required with ZI models than standard models (Williamson et al. 2007).
However, recruiting large samples will significantly increase the cost. Therefore, given the potentially limited
power of existing methods, this project will develop a more powerful tool allow investigators to detect a
meaningful treatment effect on ZI dental outcomes with a realistic sample size.
With successful completion of this project, we expect to fill the gap in literature to have better understanding of
how excess zeros observed in common dental outcomes affect the statistical power of existing methods,
provide dental researchers software for power calculation on overall and mediation treatment effects, and
develop more powerful tools for treatment effect evaluations on longitudinal dental outcomes with excess zeros.

## Key facts

- **NIH application ID:** 9857008
- **Project number:** 5R03DE028410-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Jing Cheng
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $160,669
- **Award type:** 5
- **Project period:** 2019-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9857008

## Citation

> US National Institutes of Health, RePORTER application 9857008, Improve Power in Dental Research (5R03DE028410-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9857008. Licensed CC0.

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