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Powerful and Cost-Efficient Designs for Longitudinal Intervention Studies With Two Treatment Groups

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  • Mirjam Moerbeek

Abstract

Three issues need to be decided in the design stage of a longitudinal intervention study: the number of persons, the number of repeated measurements per person, and the duration of the study. The degree to which polynomial effects vary across persons and the drop-out pattern also influence the statistical power to detect intervention effects. This article presents a framework that allows researchers to calculate the power of a proposed design and compare alternative designs on the basis of their costs and sample sizes. A multilevel regression model with polynomial effects varying across persons is used to relate response to time. The persons’ length of stay in the study is modeled using a survival function.

Suggested Citation

  • Mirjam Moerbeek, 2008. "Powerful and Cost-Efficient Designs for Longitudinal Intervention Studies With Two Treatment Groups," Journal of Educational and Behavioral Statistics, , vol. 33(1), pages 41-61, March.
    • Handle: RePEc:sae:jedbes:v:33:y:2008:i:1:p:41-61
    DOI: 10.3102/1076998607302630
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    Cited by:

    1. Maryam Safarkhani & Mirjam Moerbeek, 2016. "D-optimal designs for a continuous predictor in longitudinal trials with discrete-time survival endpoints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 146-171, May.

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