Details of talk
|Title||Calculating the Sample Size for Trials Collecting Both Independent and Paired Data|
|Presenter||Lisa Yelland (The University of Adelaide)|
|Author(s)||Lisa N Yelland, Thomas R Sullivan, David J Price, Katherine J Lee|
|Session||Biostatistics and Bioinformatics|
Mixtures of independent and paired data arise in many areas of health research. For example, in perinatal trials, women may give birth to a single infant or a set of twins. Similarly, in ophthalmology, one or both eyes may be affected by the condition of interest and included in the trial. Since outcomes of pairs are likely to be correlated, this should be taken into account when designing the trial. The sample size can be calculated by assuming all observations are independent and then inflating the resultant sample size by an appropriate design effect. The design effect depends on a number of factors, including the strength of the correlation between outcomes from the same pair, the planned analysis approach and whether members of the same pair will be randomised to receive the same treatment, different treatments or independently. Using design effects will enable more accurate sample size calculations to be performed for trials involving both independent and paired data.