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Experiments with large N (2)

There are already thousands of examples of "experiments with large N" -- elections for public office. At some point in many elections, the report is ""declared winner" with n% of the polling stations yet to report". Political polls will often report "accurate 19 times out of 20 with a variation of 1.5%".




Date:    Mon, 3 Dec 2007 13:42:14 -0500
From:    Robert Zatorre <robert.zatorre@xxxxxxxxx>
Subject: Re: Experiments with large N

Huge samples are very nice if you can get 'em, though such is not always
the case, alas.

So one thing that I would like to see from people who do have gigantic N
is to do some analyses to determine at what point the data reach some
asymptote. In other words, if you've collected 1,000,000 people, at what
earlier point in your sampling could you have stopped, and come to the
identical conclusions with valid statistics?

Obviously, the answer to this question will be different for different
types of studies with different types of variance and so forth. But
having the large N allows one to perform this calculation, so that next
time one does a similar study, one could reasonably stop after reaching
a smaller and more manageable sample size.

Has anybody already done this for those large samples that were recently
discussed? It would be really helpful for those who cannot always
collect such samples.



Robert J. Zatorre, Ph.D.
Montreal Neurological Institute
3801 University St.
Montreal, QC Canada H3A 2B4
phone: 1-514-398-8903
fax: 1-514-398-1338
e-mail: robert.zatorre@xxxxxxxxx
web site: www.zlab.mcgill.ca


Date:    Mon, 3 Dec 2007 13:58:55 -0500
From:    "J. Devin McAuley" <mcauley@xxxxxxxxxxxxxx>
Subject: Re: Experiments with large N

This issue nicely highlights the need to report effect size measures. With a
large enough sample, even the smallest of effects will show up as reliable!

Best regards,