Bootstrapping

[Uche_Okoro]

I need help with the codes for determining sample size for independent t tests by bootstrapping. I calculated the sample size by hand and got 62. My mu1=8, mu2=15 std dev.=12, alpha=0.05 and 1-beta=0.9.

Thank you.

[Reeza]

Please see the fully worked example here: 

http://documentation.sas.com/?docsetId=statug&docsetTarget=statug_power_gettingstarted02.htm&docsetV...

If you have more specific issues with your PROC POWER, please post back with the code you tried and explain what issues you're having.

[Uche_Okoro]

Thank you for prompt response but it does not have a closed-form solution.
By bootstrapping, I am to estimate the sample size that will give me a
power of 90%. I know from the initial calculation I got 62. I am expected
to start with eg 30 run simulations 1000 times using the independent t-test
then check the p-value each time. if I reject that could be coded as 1 when
fail to reject, I code that as 0. I am to do that a 1000 times, then take
an average of the variables which is the power. I am to continue increasing
the sample size and the power is expected to increase as I do so. Then stop
at a sample size that gives me a power of 90%.

I need a sas code to enable me so do.

Thank you again.

[Rick_SAS]

If you have SAS 9.4M5, you can use the new BOOTSTRAP statement in PROC TTEST:

http://go.documentation.sas.com/?docsetId=statug&docsetTarget=statug_ttest_syntax02.htm&docsetVersio...

[Rick_SAS · Accepted solution]

The general idea is shown in "Using simulation to estimate the power of a statistical test." That example uses simulation to generate the many (re)samples, but you can replace the simulation step by using the bootstrap resampling. A general discussion of bootstrapping in SAS is available at "Compute a bootstrap confidence interval in SAS".

If this is a MATCHED t-test, then you should use a permutation test, as shown in "Resampling and permutation tests in SAS".