Methods of sample size calculation for clinical trials.
MSc(R) thesis, University of Glasgow.
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Sample size calculations should be an important part of the design of a trial, but are researchers choosing sensible trial sizes? This thesis looks at ways of determining appropriate sample sizes for Normal, binary and ordinal data.
The inadequacies of existing sample size and power calculation software and methods are considered, and new software is offered that will be of more use to researchers planning randomised clinical trials. The software includes the capacity to assess the power and required sample size for incomplete block crossover trial designs for Normal data.
Following on from these the difference between calculated power for published trials and the actual results are investigated. As a result, the appropriateness of the standard equations to determine a sample size is questioned- in particular the effect of using a variance estimate based on a sample variance from a pilot study is considered.
Taking into account the distribution of this statistic alternative approaches beyond power are considered that take into account the uncertainty in sample variance. Software is also presented that will allow these new types of sample size and Expected Power calculations to be carried out.
||sample size, clinical trial, expected power, power, ordinal data, Normal data, binary data, crossover, parallel, incomplete blocks
||R Medicine > R Medicine (General)
||College of Science and Engineering > School of Mathematics and Statistics > Statistics
||Senn, Prof. Stephen
|Date of Award:
Mr Michael Tracy
||Copyright of this thesis is held by the author.
||16 Dec 2009
||10 Dec 2012 13:24
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