# Thread: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Stat

1. ## Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Stat

I am trying to get an effect size for a Wilcoxon rank sum test. There is a postulated approach of dividing the z-score from the normalization of test by the square root of the sample size.

Though this approach does not have a respective way to get the 95% CI for the above calculated effect size. Does it make any sense to use 95% Percentile Bootstrap confidence intervals? So bootstrap the dataset and calculate the ES for each sample and use the 2.5 and 97.5 centile values?

2. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

Yes it makes sense

3. ## The Following 3 Users Say Thank You to Jake For This Useful Post:

bryangoodrich (03-28-2016), hlsmith (03-28-2016), spunky (03-28-2016)

4. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

No. It makes no sense at all.

I just wanted to provide a contrasting view. Jake is right of course but he needs to be disagreed with from time to time.

5. ## The Following 2 Users Say Thank You to Dason For This Useful Post:

bryangoodrich (03-28-2016), hlsmith (03-28-2016)

6. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

Great. It seemed fine with me as well.

Bootstrap nation - long live Efron!

7. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

Originally Posted by Dason
I just wanted to provide a contrasting view.
We always try to be fair and balanced here at Talk Stats.

8. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

No we don't. JAKE IS STUPID AND IS A COTTON-HEADED-NINNY-MUGGINS.

9. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

hah, I reread what you are trying to do.

One comment though. To do this you need to correct for bias.

10. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

Are you talking about the slanderous posts or my original post

Do you want to elaborate! I have seen bootstrap used under both scenarios. It seems when the average BS is calculated and subtracted it is a bias correction. Though it can be used as above. I heard a talk awhile back that I seem to recall the presenter mentioning correction for sampling variability and also need to control for bias - but it was a simulation approach not a BS approach.

11. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

the42up,

Perhaps, this is what you are referring to. Though, I don't think I need to correct the estimate in my presented scenario.

http://www.ats.ucla.edu/stat/sas/faq/bootstrap.htm

12. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

hi
actually I always have a bit of a bad feeling about bootstrapping high percentiles. I know that for a maximum value distribution the bootstrap would be a poor choice - so why would it be better for the 95th percentile?

Regards

13. ## Re: Bootstrap Approach for Effect Size 95% Percentile Interval for Non-parametric Sta

What do you mean in particular by this:

"maximum value distribution the bootstrap would be a poor choice "?

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