- Planned Missing Data Designs for Spline Growth Models in Salivary Cortisol Research
- Measurement in Physical Education and Exercise Science
- Volume | Issue number
- 17 | 4
- Pages (from-to)
- Document type
- Faculty of Social and Behavioural Sciences (FMG)
- Psychology Research Institute (PsyRes)
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.
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