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| For a theoretical background and details of specialist software have a look at graduate seminar on power at the [[StatsCourse2006|Graduate Statistics Programme October-December 2006]]. There is also [[http://homepages.gold.ac.uk/aphome/cc16work.doc|a worked example]] using "Method 2" on a t-test. | For a theoretical background and details of specialist software have a look at graduate seminar on power at the [[StatsCourse2006|Graduate Statistics Programme October-December 2006]]. There is also [[http://homepages.gold.ac.uk/aphome/cc16work.doc|a worked example]] using "Method 2" on a t-test. [[attachment:vif.pdf | F. Y. Hsieh, Philip W. Lavori, Harvey J. Cohen and John R. Feussner (2003) An Overview of Variance Inflation Factors for Sample-Size Calculation ]] ''Eval Health Prof'' '''26''' 239-257 mentions various formulae for power calculations. Note in some cases one needs to inflate the total sample size required if there is a natural clustering in the data such as patients being assessed by different exercise therapists. For example if there are b patients assessed by each exercise therapist with an intra-therapist correlation (ICC) then the design effect equals 1 + [(b-1)ICC]. The total sample needs to be multiplied by this design effect to give sample size adjusted for the clustering effect. |
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| * [[FAQ/power/roc| ROC Analysis]] | |
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| Additional power freeware (including the popular G*POWER (currently version 3)) is available for download from [[http://www.epibiostat.ucsf.edu/biostat/sampsize.html#PCSize|here.]] Some examples using G*POWER 3 are in Howell (2013). | Additional power freeware (including the popular G*POWER (currently version 3)) is available for download from [[http://www.epibiostat.ucsf.edu/biostat/sampsize.html#PCSize|here.]] Some examples using G*POWER 3 are in Howell (2013). There are also some power calculators mentioned in the Power Grad talks and [[http://powerandsamplesize.com/http://powerandsamplesize.com/ | here including Survival Analysis power computations]] and [[http://www.ai-therapy.com/psychology-statistics/effect-size-calculator | here.]] |
Power computations
Power computations can be performed in SPSS and R only using syntax. For SPSS users Chris Aberson has syntax for power calculations in his book. See reference below.
For a theoretical background and details of specialist software have a look at graduate seminar on power at the Graduate Statistics Programme October-December 2006. There is also a worked example using "Method 2" on a t-test. F. Y. Hsieh, Philip W. Lavori, Harvey J. Cohen and John R. Feussner (2003) An Overview of Variance Inflation Factors for Sample-Size Calculation Eval Health Prof 26 239-257 mentions various formulae for power calculations.
Note in some cases one needs to inflate the total sample size required if there is a natural clustering in the data such as patients being assessed by different exercise therapists. For example if there are b patients assessed by each exercise therapist with an intra-therapist correlation (ICC) then the design effect equals 1 + [(b-1)ICC]. The total sample needs to be multiplied by this design effect to give sample size adjusted for the clustering effect.
Sample sizes required for a given power
Power required for given sample sizes
Additional power freeware (including the popular G*POWER (currently version 3)) is available for download from here. Some examples using G*POWER 3 are in Howell (2013). There are also some power calculators mentioned in the Power Grad talks and here including Survival Analysis power computations and here.
References
Aberson CL (2010) Applied power analysis for the behavioral sciences. Routledge:London. This book contains examples of computing effect sizes and power using SPSS.
Howell DC (2013) Statistical methods for psychology. 8th Edition. International Edition. Wadsworth:Belmont,CA.