title: ESPRESSO: taking into account assessment errors on outcome and exposures in power analysis for association studies.
abstract: BACKGROUND
  Very large studies are required to provide sufficiently big sample sizes for adequately powered association analyses. This can be an expensive undertaking and it is important that an accurate sample size is identified. For more realistic sample size calculation and power analysis, the impact of unmeasured aetiological determinants and the quality of measurement of both outcome and explanatory variables should be taken into account. Conventional methods to analyse power use closed-form solutions that are not flexible enough to cater for all of these elements easily. They often result in a potentially substantial overestimation of the actual power.
  
  
  RESULTS
  In this article, we describe the Estimating Sample-size and Power in R by Exploring Simulated Study Outcomes tool that allows assessment errors in power calculation under various biomedical scenarios to be incorporated. We also report a real world analysis where we used this tool to answer an important strategic question for an existing cohort.
  
  
  METHODS
  The software is available for online calculation and downloads at http://espresso-research.org. The code is freely available at https://github.com/ESPRESSO-research.
  
  
  BACKGROUND
  louqman@gmail.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Social and Community Medicine, University of Bristol, UK and.
authors.forename: Amadou
authors.initials: A
authors.lastname: Gaye
authors.affiliation: School of Computing Science, Newcastle University, UK.
authors.forename: Thomas W Y
authors.initials: TW
authors.lastname: Burton
authors.affiliation: School of Social and Community Medicine, University of Bristol, UK and.
authors.forename: Paul R
authors.initials: PR
authors.lastname: Burton
mesh_terms: D000465:Algorithms; D001794:Blood Pressure; D002170:Canada; D015331:Cohort Studies; D056726:Genetic Association Studies; D006801:Humans; D020407:Internet; D016014:Linear Models; D019655:Quantitative Trait, Heritable; D018401:Sample Size; D012984:Software; D013599:Systole