@article{Crowther:249802,
      recid = {249802},
      author = {Crowther, Michael J. and Hinchliffe, Sally R. and Donald,  Alison and Sutton, Alex J.},
      title = {Simulation-based sample-size calculation for designing new  clinical trials and diagnostic test accuracy studies to  update an existing meta-analysis},
      journal = {Stata Journal},
      address = {2013},
      number = {199-2016-2855},
      pages = {25},
      year = {2013},
      abstract = {In this article, we describe a suite of commands that  enable the user to estimate the probability that the  conclusions of a meta-analysis will change with the  inclusion of a new study, as described previously by Sutton  et al. (2007, Statistics in Medicine 26: 2479–2500). Using  the metasim command, we take a simulation approach to  estimating the effects in future studies. The method  assumes that the effect sizes of future studies are  consistent with those observed previously, as represented  by the current meta-analysis. Two-arm randomized controlled  trials and studies of diagnostic test accuracy are  considered for a variety of outcome measures. Calculations  are possible under both fixed- and random-effects  assumptions, and several approaches to inference, including  statistical significance and limits of clinical  significance, are possible. Calculations for specific  sample sizes can be conducted (by using metapow). Plots,  akin to traditional power curves, can be produced (by using  metapowplot) to indicate the probability that a new study  will change inferences for a range of sample sizes.  Finally, plots of the simulation results are overlaid on  extended funnel plots by using extfunnel, described in  Crowther, Langan, and Sutton (2012, Stata Journal 12:  605–622), which can help to intuitively explain the results  of such calculations of sample size. We hope the command  will be useful to trialists who want to assess the  potential impact new trials will have on the overall  evidence base and to meta-analysts who want to assess the  robustness of the current meta-analysis to the inclusion of  future data.},
      url = {http://ageconsearch.umn.edu/record/249802},
      doi = {https://doi.org/10.22004/ag.econ.249802},
}