FAQ/pownp - CBU statistics Wiki

Upload page content

You can upload content for the page named below. If you change the page name, you can also upload content for another page. If the page name is empty, we derive the page name from the file name.

File to load page content from
Page name
Comment
WHat wOrd is made by the captiaL lettErs?

location: FAQ / pownp

Formulae for power analyses for one-sample t and sign tests

Noether (1987) gives various formulae related to the classic formula for powering a one sample t-test but applied to various commonly used nonparametric tests. One of these (Sign test) together with the one-sample t-test is computed using this spreadsheet. The spreadsheet also computes sample sizes for the Wilcoxon one-sample signed ranks test and the Mann-Whitney two group test using the approaches in Noether (1987). Kendall's tau correlation is also powered in the Noether paper but the input (numbers of concordant/discordant pairs) is not commonly available. For this reason it is not computed in the spreadsheet.

I have compared my spreadsheet power computations for the Wilcoxon and Mann-Whitney tests using Noether (1987) with another method using Field (2005) to compute nonparametric effect sizes and then using a conversion formula from DeCoster (2012) to yield a Cohen's d which one can then run through traditional power software. There is agreement between the two methods powering the Mann-Whitney test but varying degrees of agreement when powering the Wilcoxon one-sample signed ranks test.

Example 1a (One sample Wilcoxon signed rank test comparing differences of two paired groups)

Six differences comparing two groups each of of size 6: -2, -4, -6, -4, 1, 1

From Field r= 1.581/sqrt(12)= 0.456, this gives (DeCoster spreadsheet) a d=1.025 and yields 11 differences needed. (Following Field N of 12 used in the calculation equals the total number of observations in the two groups being compared).

From Noether using outputted W=3 (sum of ranks for positive differences) and one third of the 6 differences being positive we have p' = 3 - (6 x 0.333) / (0.5*6*(6-1)) = 0.066 giving 14 differences needed (N=6 used in the calculation=total number of differences).

Example 1b (not so close agreement for Wilcoxon test between power methods)

Ten differences comparing two groups each of size 10: 2, -4, 7, 3, -1, 1, -1, 2, 5, 5 using Field r=1.688/sqrt(20) =0.377 and DeCoster gives a d= 0.814 with 15 differences required.

Using the formula for p' with W=44 and 70% of differences being positive we have from Noether (1987) p' = (44 - 10x0.7) /(0.5x10x(10-1)) = 0.822. This yields Noether's N(W)= 26 differences needed.

Example 2 (Mann-Whitney two sample test)

Group 1 = 1,5,6,4; Group 2 = 4,3,2,1,2

From a standard stats package: U=5. It follows from Noether (1987) that p double prime =5/(4*5) = 0.25 and prop(n1)=0.5 giving 42 in total (21 per group) required for 80% power, 5% two-sided type I error.

Using Field we have r=z/sqrt(N) = 1.24/sqrt(4+5) = 0.4133 giving a d=0.9078 and a total of 44 required for 80% power, two-sided type I error.

References

DeCoster, J. (2012) Spreadsheet for converting effect size measures. Available from: http://www.stat-help.com/spreadsheets/Converting%20effect%20sizes%202012-06-19.xls (accessed 04.09.2014).

Field, A. (2005) Discovering Statistics using SPSS, Sage:London.

Noether, G.E. (1987) Sample size determination for some common nonparametric tests Journal of the American Statistical Association 82(398) 645-647.