Salivary cortisol is often used as an index of physiological and psychological stress in exercise science and psychoneuroendocrine research. A primary concern when designing research studies examining cortisol stems from the high cost of analysis. Planned missing data designs involve intentionally omitting a random subset of observations from data collection, reducing both the cost of data collection and participant burden. These designs have the potential to result in more efficient, cost-effective analyses with minimal power loss. Using salivary cortisol data from a previous study (Hogue, Fry, Fry, & Pressman, 2013), this article examines statistical power and estimated costs of six different planned missing data designs using growth curve modeling. Results indicate that using a planned missing data design would have provided the same results at a lower cost relative to the traditional, complete data analysis of salivary cortisol.
|Original language||English (US)|
|Number of pages||16|
|Journal||Measurement in Physical Education and Exercise Science|
|State||Published - Oct 1 2013|
All Science Journal Classification (ASJC) codes
- Orthopedics and Sports Medicine
- Physical Therapy, Sports Therapy and Rehabilitation