This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Moerbeek, M. Articles by Berger, M. P. F. Search for Related Content Social Bookmarking                         What's this?

Design Issues for Experiments in Multilevel Populations

Maastricht University

For the design of experiments in multilevel populations the following questions may arise: What is the optimal level of randomization? Given a certain budget for sampling and measuring, what is the optimal allocation of units? What is the required budget for obtaining a certain power on the test of no treatment effect? In this article these questions will be dealt with for populations with two or three levels of nesting and continuous outcomes. Multilevel models are used to model the relationship between experimental condition and the outcome variable. The estimator of the regression, coefficient associated with treatment condition, a parameter assumed to be fixed in this paper; is of main interest and should be estimated as efficiently as possible. Therefore, its variance is used as a criterion for optimizing the level of randomization and the allocation of units.

Key Words: multilevel models • experimental designs • level of randomization • allocation of units • power

Journal of Educational and Behavioral Statistics, Vol. 25, No. 3, 271-284 (2000)
DOI: 10.3102/10769986025003271


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				M. J. Candel Optimal Designs for Empirical Bayes Estimators of Individual Linear and Quadratic Growth Curves in Linear Mixed Models Statistical Methods in Medical Research, August 1, 2009; 18(4): 397 - 419. [Abstract] [PDF]

				S. Teerenstra, M. Moerbeek, T. van Achterberg, B. J Pelzer, and G. F Borm Sample size calculations for 3-level cluster randomized trials Clinical Trials, October 1, 2008; 5(5): 486 - 495. [Abstract] [PDF]

				M. Moerbeek Powerful and Cost-Efficient Designs for Longitudinal Intervention Studies With Two Treatment Groups Journal of Educational and Behavioral Statistics, March 1, 2008; 33(1): 41 - 61. [Abstract] [Full Text] [PDF]

				B. Winkens, H. J. A. Schouten, G. J. P. van Breukelen, and M. P. F. Berger Optimal designs for clinical trials with second-order polynomial treatment effects Statistical Methods in Medical Research, December 1, 2007; 16(6): 523 - 537. [Abstract] [PDF]

				X. Liu Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs per Unit of Randomization Journal of Educational and Behavioral Statistics, January 1, 2003; 28(3): 231 - 248. [Abstract] [PDF]