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dc.contributor.authorKonstantopoulos, Spyrosen_US
dc.date.accessioned2008-10-20en_US
dc.date.accessioned2010-07-07T11:52:09Z-
dc.date.available2010-07-07T11:52:09Z-
dc.date.issued2008en_US
dc.identifier.piurn:nbn:de:101:1-2008112623en_US
dc.identifier.urihttp://hdl.handle.net/10419/35462-
dc.description.abstractIn experimental designs with nested structures entire groups (such as schools) are often assigned to treatment conditions. Key aspects of the design in these cluster randomized experiments include knowledge of the intraclass correlation structure and the sample sizes necessary to achieve adequate power to detect the treatment effect. However, the units at each level of the hierarchy have a cost associated with them and thus researchers need to decide on sample sizes given a certain budget, when designing their studies. This paper provides methods for computing power within an optimal design framework (that incorporates costs of units in all three levels) for three-level cluster randomized balanced designs with two levels of nesting. The optimal sample sizes are a function of the variances at each level and the cost of each unit. Overall, larger effect sizes, smaller intraclass correlations at the second and third level, and lower cost of level-3 and level-2 units result in higher estimates of power.en_US
dc.language.isoengen_US
dc.publisherIZA Bonnen_US
dc.relation.ispartofseriesIZA discussion papers 3753en_US
dc.subject.jelI20en_US
dc.subject.ddc330en_US
dc.subject.keywordExperimental designen_US
dc.subject.keywordstatistical poweren_US
dc.subject.keywordoptimal samplingen_US
dc.subject.stwTesten_US
dc.subject.stwKostenen_US
dc.subject.stwStichprobenverfahrenen_US
dc.subject.stwStatistischer Testen_US
dc.subject.stwBildungsforschungen_US
dc.titleIncorporating cost in power analysis for three-level cluster randomized designsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn582909295en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
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