Improving methods for estimating sample size in statistical models
Official title: Power and sample size for generalized linear models
Funded at University of Texas at Austin · NIH-10866519 · Data updated 2026-11-12
This study is working on making it easier for researchers to plan their studies in mental health by improving how they figure out the right number of participants needed, so they can get more reliable results.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas at Austin NIH-funded |
| Lab location | 1 site (Austin, United States) |
| Project start | June 15, 2023 |
| Project end | May 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $190,478 |
| NIH project number | 5R21MH133371-02 |
| Project ID | NIH-10866519 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals involved in clinical trials or studies related to mental health and psychiatric conditions.
✕Less likely to help
Patients not involved in research studies or those with conditions not addressed by generalized linear models may not receive direct benefits from this research.
What this research studies
This research focuses on enhancing the methods used to estimate power and sample size in generalized linear models (GLMs), which are commonly used in various fields including mental health research. The project aims to develop user-friendly and interpretable methods that can help researchers design studies more effectively, particularly in psychiatric populations. By addressing the challenges faced by statisticians and non-statistical collaborators, the research seeks to improve the accuracy of study designs and the reliability of their outcomes. The methodologies developed will be applicable to a wide range of research scenarios involving GLMs.
Why it matters
Potential benefit: If successful, this research could lead to more effective and reliable study designs in mental health and other fields, ultimately improving patient outcomes.
How similar studies have gone: Previous research has shown success in improving statistical methodologies, indicating that this approach has the potential for meaningful advancements.
Where this research is happening
-
University of Texas at Austin
Austin, United States Active
Researchers
- Principal investigator: Rathouz, Paul Joseph — University of Texas at Austin
- Study coordinator: Rathouz, Paul Joseph
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.