[RsR] minimum sample size for the robust counterpart of the t-test #2

[Rand Wilcox]

When dealing with M-estimators and the goal is to compute confidence intervals, one thing you have to be careful about is skewed distributions. Have not encountered any non-bootstrap method that performs well in simulations where the confidence interval is based on an estimate of the standard error. Just how symmetric the distribution must be seems unclear. What works better is a percentile bootstrap method, even with fairly small sample sizes. This is why the methods in my book focus on bootstrap techniques when dealing with M-estimators.


However, have not yet seen the Koller and Stahel paper. Maybe this problem has been addressed.

Rand

Rand Wilcox
Professor
Dept of Psychology
USC
Los Angeles, CA 90089-1061

FAX: 213-746-9082
For information about statistics books and software, see http://www-rcf.usc.edu/~rwilcox/
as well as
http://college.usc.edu/labs/rwilcox/home

----- Original Message -----
From: Richard Friedman <friedman using cancercenter.columbia.edu>
Date: Thursday, June 16, 2011 9:02 am
Subject: Re: [RsR] minimum sample size for the robust counterpart of the t-test #2
To: Rand Wilcox <rwilcox using usc.edu>, r-sig-robust using r-project.org

> Dear Rand (and List),
> 
> 	I read the relevant sections of your book and while informative it 
> did not answer my question
> directly as best I can see. I will restate the question more 
> explicitly:
> A robust analog of the two sample  t-test is performed with the rlm 
> function with the default parameters of
> the Huber method with K=1.345. Is there a minimum sample size for 
> which it should be trusted?
> are 5 samples enough? 10 samples?
> 
> If this question does not have a simple answer please let me know.
> 
> Thanks and best wishes,
> Rich
> 
> 
> On Jun 15, 2011, at 3:19 PM, Rand Wilcox wrote:
> 
> >There is general information about sample sizes and p-values, when 
> using robust analogs of t, in my 2005 book (Introduction to Robust 
> Estimation and Hypothesis Testing, Academic Press) .
> >(A third edition will be out early in 2012. )
> >
> >Hope this helps.
> >
> >Rand
> >
> >Rand Wilcox
> >Professor
> >Dept of Psychology
> >USC
> >Los Angeles, CA 90089-1061
> >
> >FAX: 213-746-9082
> >For information about statistics books and software, see 
> http://www-rcf.usc.edu/~rwilcox/
> >as well as
> >http://college.usc.edu/labs/rwilcox/home
> >
> >----- Original Message -----
> >From: Richard Friedman <friedman using cancercenter.columbia.edu>
> >Date: Wednesday, June 15, 2011 12:11 pm
> >Subject: [RsR] minimum sample size for the robust counterpart of 
> the t-test
> >To: r-sig-robust using r-project.org
> >
> >>Dear List,
> >>
> >>	I am a beginner in the use of robust methods. Is there a minimum
> >>sample size
> >>for which the robust analog of a two sample t-test using rlm with
> >>default parameters and categorical
> >>explanatory variables may be trusted to yield reliable p-values?
> >>Is so, can you please point me at a reference which treats this
> >>problem.
> >>Thanks and best wishes,
> >>Rich
> >>------------------------------------------------------------
> >>Richard A. Friedman, PhD
> >>Associate Research Scientist,
> >>Biomedical Informatics Shared Resource
> >>Herbert Irving Comprehensive Cancer Center (HICCC)
> >>Lecturer,
> >>Department of Biomedical Informatics (DBMI)
> >>Educational Coordinator,
> >>Center for Computational Biology and Bioinformatics (C2B2)/
> >>National Center for Multiscale Analysis of Genomic Networks (MAGNet)
> >>Room 824
> >>Irving Cancer Research Center
> >>Columbia University
> >>1130 St. Nicholas Ave
> >>New York, NY 10032
> >>(212)851-4765 (voice)
> >>friedman using cancercenter.columbia.edu
> >>http://cancercenter.columbia.edu/~friedman/
> >>
> >>I am a Bayesian. When I see a multiple-choice question on a test
> >>and I don't
> >>know the answer I say "eeney-meaney-miney-moe".
> >>
> >>Rose Friedman, Age 14
> >>
> >>_______________________________________________
> >>R-SIG-Robust using r-project.org mailing list
> >>https://stat.ethz.ch/mailman/listinfo/r-sig-robust
> >>
> 
>