title: Sample size calculations for randomised trials including both independent and paired data.
abstract: Randomised trials including a mixture of independent and paired data arise in many areas of health research, yet methods for determining the sample size for such trials are lacking. We derive design effects algebraically assuming clustering because of paired data will be taken into account in the analysis using generalised estimating equations with either an independence or exchangeable working correlation structure. Continuous and binary outcomes are considered, along with three different methods of randomisation: cluster randomisation, individual randomisation and randomisation to opposite treatment groups. The design effect is shown to depend on the intracluster correlation coefficient, proportion of observations belonging to a pair, working correlation structure, type of outcome and method of randomisation. The derived design effects are validated through simulation and example calculations are presented to illustrate their use in sample size planning. These design effects will enable appropriate sample size calculations to be performed for future randomised trials including both independent and paired data. Copyright © 2017 John Wiley & Sons, Ltd.
authors.affiliation: School of Public Health, The University of Adelaide, Adelaide, SA, Australia.|South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
authors.forename: Lisa N
authors.identifier: 0000-0003-3803-8728
authors.initials: LN
authors.lastname: Yelland
authors.affiliation: School of Public Health, The University of Adelaide, Adelaide, SA, Australia.
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Sullivan
authors.affiliation: School of Mathematical Sciences, The University of Adelaide, Adelaide, SA, Australia.
authors.forename: David J
authors.initials: DJ
authors.lastname: Price
authors.affiliation: Murdoch Children's Research Institute, Parkville, VIC, Australia.|Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia.
authors.forename: Katherine J
authors.initials: KJ
authors.lastname: Lee
mesh_terms: D016000:Cluster Analysis; D006801:Humans; D015233:Models, Statistical; D011897:Random Allocation; D016032:Randomized Controlled Trials as Topic; D012107:Research Design; D018401:Sample Size; D013223:Statistics as Topic / Q000379:methods*
keywords: clustered data; design effect; generalised estimating equations; sample size