HDTenEightyP/NetNews huggingface dataset:
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Date:         Fri, 28 Aug 1992 14:16:00 EDT
From:         "SI00::SIGNORINOC" <signorinoc%si00.decnet@V3.HANSCOM.AF.MIL>
Subject:      Re: p-value program for t/F
X-To:         "stat-l" <stat-l@vm1.mcgill.ca>

                          E L E C T R O N I C   M A I L
                     (DDN Host Address:  V3.HANSCOM.AF.MIL)

                                        Date:      28-Aug-1992 14:16
                                        From:      Lt Curtis S. Signorino
                                        Username:  SIGNORINOC
                                        Dept:      ESC/XRPM
                                        Tel No:    617-377-7483 (DSN 478)

TO:  _WINS%                               ( _DDN[STAT-L@VM1.MCGILL.CA] )


Subject: Re: p-value program for t/F

    Have you checked Press et al, _Numerical_Recipes_?  I don't have
    the book on me, so I don't know for certain if they have a t/F
    p-value program.  However, I generally find about 90% of the
    algorithms I need for functions, etc, in _Numerical_Recipes_.
    What's especially nice is that they include both the theory and
    the code; and _Numerical_Recipes_ comes in C, Pascal, and Fortran
    flavors.  It may be worth looking into anyway as a reference for
    future endeavors.  I have no connection with the book, except as a
    very impressed user of it.

    Curt Signorino
    signorinoc@v3.hanscom.af.mil

    P.S., Press et al freely admit (and some of my co-workers have
    found) that there are occasional bugs in the code.  As with
    anything else in print or on disk, be sure to verify the answers
    it gives you.
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Date:         Wed, 2 Sep 1992 09:27:00 EDT
From:         BOB <RJOHNSON@VCUVAX.BITNET>
Subject:      Equal variances, equal sample sizes, and the t-test

>>Question - I suspect this will be easy for somebody -
>>
>>Why does having equal sample sizes mitigate the requirement of equal
>>variances in an ANOVA/t-test?
>>
>>Thanks.
>>
>>Deanna Wild

The two sample t-statistic will not have an exact t-distribution if the two
population variances are unequal, regardless of the sample sizes.  One may
use an approximate distribution by adjusting the degrees of freedom and using
S1**2/n1 + S2**2/n2 in place of the pooled variance.  SAS Proc Ttest gives you
both options.

When the sample sizes are equal, the value of the t-statistic computed with the
usual pooled variance is the same as the t-statistic computed with the other
(above) variance.  But that _does_not_ mean that the statistic has an exact
t-distribution.

So...  the "requirement" of equal variances is not mitigated.

>Unequal variances bias the test depending mostly on whether the variances are
>positively or negatively correlated with the sample sizes.  Having equal
>sample sizes makes this correlation 0.
>
>------------------------------------------------  --------------,
>Russ Lenth                 rlenth@stat.uiowa.edu  \              )

Huh?


Bob Johnson
Dept. of Math Sciences
Division of OR/STAT
Virginia Commonwealth University
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Date:         Wed, 26 Aug 1992 13:23:47 PDT
From:         Gary Thomasson <3757P@NAVPGS.BITNET>
Subject:      Computer code for Inverse Normal Function

Hello Statisticians:
  Does anyone have code (preferably, in C code, but, Fortran, Pascal,
etc. will do) for the Inverse Normal Distribution Function.
This is the function that returns the standard normal (Gaussian)
random variable x given a probability p.
  I can't seem to find it in my Numerical Recipes (Press, et al) book.
Thanks in advance!
-- Gary Thomasson
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Date:         Tue, 1 Sep 1992 10:11:46 PDT
From:         Nino Pagliccia <pagli@UNIXG.UBC.CA>
Subject:      Help simulation
X-To:         "STAT-L" <STAT-L%mcgill1.BITNET@cunyvm.cuny.edu>

Hi!  Does anybody know if there is a simulation list?
I want to enquire about the simulation language DYNAMO.
Thanks.
--
NINO PAGLICCIA  	                         Ph. (604)822-5009
Centre for Health Services and Policy Research   FAX (604)822-5690
429 - 2194 Health Sciences Mall
University of British Columbia                 E-mail PAGLI@UNIXG.UBC.CA
Vancouver B.C. V6T 1Z3
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Date:         Wed, 26 Aug 1992 20:23:13 CDT
Comments:     "U. of Illinois at Chicago"
From:         Allen Herzog <U50161@UICVM.BITNET>
Subject:      Stats, Philosophy and Einstein

      David Nichols in an interesting remark refers to a widely
qouted statement of Albert Einstein concerning God not playing
dice.  It is difficult to trace down exactly where and when this
quotation first appeared.  The Oxford Dictionary of quotations
gives the words as "Gott Wirfelt nicht." (God does not play dice.
Einstein's habitually expressed reaction to the quantum theory.)
       The Penguin Dictionary of Modern Quotations give the
following words: "I cannot believe that God plays dice with
the cosmos." (Observer, "Sayings of the Week", 5 Apr. 1953).
       In "Albert Einstein: Philosopher-Scientist" (Ed. P.A.
Schilp, 1949) Max Born (p. 176) refers to a letter from Einstein
Born writes, "I received about four years ago (7th November 1944)
    'In our scientific expectations we have grown antipodes. You
     believe in God playing dice and I in perfect laws in the
     world of things as real objects, which I try to grasp in
     a wildly speculative way."

     Perhaps with ongoing publication of all Einstein's writings
we may eventually learn exactly where and when it was first said
and how often repeated.
                                          Allen Herzog
                                          U50161@UICVM
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Date:         Wed, 26 Aug 1992 10:18:57 +1000
From:         alan@DMSMELB.MEL.DMS.CSIRO.AU
Subject:      Re: tests for variance homogeneity
X-To:         BSAB604@UTXVM.BITNET, STAT-L@vm1.mcgill.ca

Levene's test is much less sensitive to non-normality than those of Bartlett,
Hartley and Cochran, but it does need some correction.   I suggest that you
look at my Letter to the Editor of Technometrics, vol.14, page 507, 1972,
and you read the paper:
Yitnosumarto, S. and O'Neill, M.E. (1986) On Levene's tests of variance
homogeneity, Austral. J. Statist., vol.28(2), 230-241.

Alan Miller, Quality Improvement Project
CSIRO Division of Mathematics & Statistics, Melbourne, Australia
Phone: +61 3 542-2266   Fax: +61 3 542-2474  E-mail: alan@mel.dms.csiro.au
Mail: CSIRO DMS, Private Bag 10, Clayton, Vic. 3168, Australia
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Date:         Wed, 2 Sep 1992 09:42:46 GMT
From:         Ronan M Conroy <RCONROY@IRLEARN.UCD.IE>
Subject:      polls, confidence, point estimates

Geoff Selig is right when he points out that there is a region around
a survey result representing out imprecision. The true value that we
are trying to measure has an X% (usually calculated as 5%) chance of
being contained in that region. But we sometimes act as if the
true value had a uniform chance of being anywhere in the region.
In fact, the observed value is our single best guess as to the
true value, and the values nearest to it are more likely than the
values far away. In the case he mentions, we should calculate the
difference between the two proportions and IT'S confidence interval.

To get a 4% error margin (+/-) 95 times out of a hundred, sampling from
a large population, you need a sample of 600. If the samples were actually
600 in each poll, the difference between the two percentages is 8% with
a confidence interval of 2.4% to 13.6%. So the change in Clinton's
popularity is likely to be somewhere between 2.4% (trivial) and
13.6% (uh-uh time).

Gee - sometimes I think I'll do ANYTHING in the mornings except work.

ronsn

(eep! can't even get the name right...)

ronan
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Date:         Thu, 27 Aug 1992 12:20:00 EST
From:         WEST@UNCA.BITNET
Subject:      Post-stratification of surveys question

A Survey Question for Stat-L:

        I am doing some work that involves the post-stratification
of a statewide survey.  Essentially, we tend to undersample certain
ethnic, age, and educational groups, and so we post-stratify to
correct for this design effect.

        Cochran (1975) gives a procedure for determining the relative
efficiency of post-stratification when compared to the non-stratified
survey results; does anyone know of a comparable method for comparing
two different post-stratification schemes?

        Thanks in advance..

Mark West
WEST@UNCA.EDU / WEST@UNCA.BITNET
Dept. Mass Comm.
UNC-Asheville
Asheville, NC  28804
From: ciar04@vaxa.strath.ac.uk
Newsgroups: bit.listserv.stat-l
Subject: bit.listserv.stat-l
Date: 26 Aug 92 14:25:23 GMT
Organization: Strathclyde University VAX Cluster

In article <9208260018.AA15405@dmsmelb.mel.dms.CSIRO.AU>, alan@DMSMELB.MEL.DMS.CSIRO.AU writes:
> Levene's test is much less sensitive to non-normality than those of Bartlett,
> Hartley and Cochran, but it does need some correction.   I suggest that you
> look at my Letter to the Editor of Technometrics, vol.14, page 507, 1972,
> and you read the paper:
> Yitnosumarto, S. and O'Neill, M.E. (1986) On Levene's tests of variance
> homogeneity, Austral. J. Statist., vol.28(2), 230-241.

See also

1)  Balakrishnan, N., and Ma, C.W. (1990), "A Comparative Study of Various
    Tests for the Equality of Two Population Variances", J. of Statistical
    Computation and Simulation 35, 41-89.

2)  Brown, M.B., and Forsythe, A.B. (1974), "Robust Test for the Equality
    of Variances", J. of the American Statistical Association 69, 364-7.

3)  Conover, W.J., Johnson, M.E., and Johnson, M.M. (1981), "A Comparative
    Study of Tests for Homogeneity of Variances, with Applications to the
    Other Continental Shelf Bidding Data", Technometrics 23, 351-61.

4)  Olejnik, J.S., and Algina, J. (1988), "Tests of Variance Equality When
    Distributions Differ in Form and Location", Educational and Psychological
    Measurement 48, 317-29.

5)  Tan, W.Y. (1982), "Sampling Distributions and Robustness of t, F and
    Variance-Ratio in Two Samples and ANOVA Models with Respect to Departure
    from Normality", Communications in Statistics - Theory and Methods 11,
    2485-511.

6)  Tiku, M.L. (1982), "Robust Statistics for Testing Equality of Means or
    Variances", Communications in Statistics - Theory and Methods 11, 2543-58.

7)  Tiku, M.L. and Balakrishnan, N. (1984), "Testing Equality of Population
    Variances the Robust Way", Communications in Statistics - Theory and
    Methods 13, pg 2143-59.

8)  Wilcox, R.R. (1990), "Comparing Variances and Means When Distributions 
    have Non-Identical Shapes", Communications in Statistics - Simulation 19,
    155-73.

#----------------------------------#-------------------------------------------#
|  W.H.Watt                        #  JANET:                                   |
|  Dept. of Accounting & Finance   #           w.h.watt@uk.ac.strath.vaxa      |
|  University of Strathclyde       #  Rest of the World:                       |
|  Glasgow                         #           w.h.watt@vaxa.strath.ac.uk      |
|  United Kingdom                  #                                           |
#----------------------------------#-------------------------------------------#
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Acknowledge-to:    XIC@NIHCU.BITNET
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Newsgroups: bit.listserv.stat-l
Date:         Tue, 1 Sep 1992 09:36:32 EDT
From:         XIC@NIHCU.BITNET
Subject:      Using weighted data from sample surveys

This note is in response to Larry Layne's query about "using
weighted data in SAS."  His data came from the federal
government and seem to be sample survey data.

By far the best approach is not to use SAS at all but instead
use a package such as SUDAAN (see related discussion on
STAT-L), PC-CARP, etc.  The problem is not just weights, but
also clustering and stratification that affect the standard
errors and statistical tests.

If one must use SAS, the weights should be adjusted by
multiplying them by 767/8,448,705 (the sample size divided by
the population size).  (I assume that the estimates are means,
not totals.)  However, all standard errors must be multiplied
by a "design effect."  The design effect for the estimates
should be available from the federal agency supplying the
data.  This method is only a rough approximation.  Chi squared
tests require more complicated adjustments.

I hope this helps.

Michael P. Cohen
National Center for Education Statistics
Washington, DC 20208-5654
Bitnet XIC@NIHCU
Internet XIC@CU.NIH.GOV
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Date:         Thu, 27 Aug 1992 18:06:47 ADT
From:         Rolf Turner <rolf@MATH.UNB.CA>
Subject:      Testing for multivariate normality.

I have a (somewhat vague) recollection that someone posted a
bibliography of literature, on the subject of testing for multivariate
normality, to this list within recent months.  I thought I had saved
it, but now that I need it, of course I can't find it.

If this bibliography did indeed exist (and was not simply the product
of my fevered imagination) could some kind soul who was clever enough
to keep a copy (or perhaps the original poster) please email a copy
to me?

Thanks very much.


Rolf Turner
Dep't. of Maths and Stats
U.N.B., Fredericton, N.B. Canada E3B 5A3
rolf@math.unb.ca

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Subject: (no subject given)
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Date:         Wed, 26 Aug 1992 14:10:00 +0800
From:         VLDNASEQ@HKUCC.BITNET

Dear Stat-L,

Concerning the ethics of posting question and answering questions in
electronic bulletin board, Meredith gave me the following comment. I
agree, and would like to share the advice with you.

The following is the message I received:

I hope you get help for your question.  In general, most of us on the list
find that we can give better answers if we know what field the question is
in.  A better way to have phrased it might have been to state the actual
problem, then give the balls analogy, and let us know what your level of math
background is.  That would allow people to give you the most helpful
responses.

Good luck - Meredith Warshaw

So, if the question is relevant to this Stat-L board, let the question be
here. Let us accept that different people have different standard and
different philosophy. Let the people who would like to answer the question
answer the question, up the the depth they feel comfortable. Those who do
not want to take part, feel free to go aside.

Leave Stat-L for statistics, the Philo board for philosophy.

Wai Ming
Newsgroups: bit.listserv.stat-l
From: jonathan@psych.psy.uq.oz.au (Jonathan Dwyer)
Subject: Re:      JOB POSTINGS???
Followup-To: bit.listserv.stat-l
Organization: Psychology Department, University of Queensland
Date: Mon, 24 Aug 1992 02:46:33 GMT

As an ongoing reader (rather than regular contributor)
and learner (thank you all...) to this list I think Bill Venables'
idea is a good one.

Now, is there a keeper of the FAQ to look at this?!?

Jon
--
           ____
   /\  /\ / __ \ Jonathan Dwyer (FAX+6173654466) 
  / / / // / / / Department of Psychology
 / / / // / / /  The University of Queensland
/ /_/ // /_/ <   St. Lucia, 4072. AUSTRALIA 
\____/*\_____/*  jonathan@psych.psy.uq.oz.au
From: jerry@nutmeg.hnrc.tufts.edu (Jerry Dallal)
Newsgroups: bit.listserv.stat-l
Subject: Re: Available Good Stat Software for DOS/Windows for Course Work
Date: 28 Aug 92 02:44:39 GMT
Organization: USDA HNRC at Tufts University

In article <AD882B10D4041447@CC.UTAH.EDU>, JENSEN@UTAHCCA.BITNET writes:

>    More specifically, which statistical
>    packages have you found to best aid the teaching process which
>    incorporates, among other features, user interactive graphics and
>    do not turn students off because of a miserable learning curve
>    requiring more time and frustration to learn the software than the
>    statistical concepts involved?  Are these packages available in a
>    version which can be purchased by students for less than $75?
> 

Your first reaction will be to dismiss this suggestion, but hear me out.
If you get a SYSTAT site license, a set of execuatable will cost roughly 
$30 to $40 depending on the number of sets licensed.  A full set of
dcoumentation runs about $50, for a total of $80 to $90 a copy.  When
sutdents leave the universtiy, they can upgrade to an individual license. 
(Sorry, I don't know the charge.)  Also, you can mix and match
(DOS/Windows/Mac) for a fee of $200-$300 total for each platform beyond the
first.  Why settle for a student package when, for a reasonable fee, students
can have the real thing?

(Disclaimer:  Lee Wilkinson (Systat's president) and I went through graduate
school together and have coauthored papers, so I can't claim to be completely
disinterested.  However, those who know me know that I would never recommend a 
product that I didn't truly believe in.  The thing that I particularly like
about SYSTAT is the ease with which one can construct high quality statistical
graphics.)
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Newsgroups: bit.listserv.stat-l
Date:         Tue, 25 Aug 1992 15:58:52 ADT
From:         Rolf Turner <rolf@MATH.UNB.CA>
Subject:      Homework; cheating.

John R. Vokey writes:

> What arrogant nonsense.

Un-necessarily vituperative, don't you think?

>                         We don't take any precautions that we are doing the
> work of some professional consultant, either

The situations are not at all parallel.  Homework is part of the
assessment process as well as of the teaching/learning process.  The
instructor has a duty to certify the student's competence in the subject,
including the student's ability to solve the problems set in homework
assignments.  Moreover the instructor has a duty to make sure that the
students are being assessed fairly, and that no-one has an unfair
advantage (such as having one's work done by someone else).

Such considerations simply do not apply with respect to professional
consultants; the consultant must get the job done, any way she can.
There is nothing unfair or unethical in getting assistance from another
person who is willing to provide such assistance.

>                                              The student is likely to
> learn a lot more from the posting of a problem than he/she probably would
> by "solving" it on his/her own, or by consulting his/her textbook.

This is an unrealistic assertion in most circumstances.

>                                                             Posting the
> problem to the list is creative problem solving.

Possibly.  It is also quite possibly an attempt to get a pass in a stats
course while doing as little work as possible.

I have no quarrel whatever with students posting problems to this list
if they are up-front about it.  If the question they ask is a homework
problem it should be identified as such and they should explicitly
request hints, pointers to the literature, etc. but ***NOT*** simply to
be told the solution.  They should also, I believe, seek (and idicate that
they've obtained) their instructor's approval to ask for guidance from
the list.  (Why not just ask the instructor's guidance?  Good question.
To get different points of view, alternative approaches, I guess.)  At
any rate I would have no qualms about giving all the hints and insight
which I could under those circumstances.

Without the foregoing provisos however, doing a student's homework for
them (via the list or any other way) is unethical.  It is comparable to
sitting a student's exam for her, as a ``ring-in'', for which people
get expelled from university if they are caught.

Rolf Turner
Dep't. of Maths and Stats
U.N.B., Fredericton, N.B. Canada E3B 5A3
rolf@math.unb.ca

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|          Nice day, isn't it?                                       |
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Date:         Wed, 26 Aug 1992 09:53:30 EST
From:         "A. NARAYANAN DECISION & INFO. SYSTEMS--855-2665"
              <NARAYANA@UCS.INDIANA.EDU>
Subject:      test of variance homogeneity

There is also another test called the O'Brien's test(O'Brien, R.C.(1981).A
simple test for variance effects in experimental designs,Psychological
Bulletin,89,570-574) which might be appropriate here. At the recent ASA
meeting someone presented a study of different tests of variance in normal
populations and found superior performance for O'Brien's test. There is also
a related JASA paper by O'Brien (JASA, 74, 877-880).

Note: The simulation study was based on 2 samples (for a 2-sample t-test),but,
I suspect the results may carry over to several samples.

Narayanan,A
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Date:         Wed, 2 Sep 1992 15:59:29 CDT
From:         "J. Philip Miller" <phil@WUBIOS.WUSTL.EDU>
Subject:      unequal variances (fwd)
X-To:         "STAT-L Distribution List" <stat-l@vm1.mcgill.ca>

Forwarded message:
> There is another aspect to the unequal variance problem - that of power under
> alternatives. In a recent study, (Comm. Stat., 1991) I compared the size and
> power of the F, Kruskal-Wallis, and Normal Scores tests when variances were
 un-
> equal. The F test was badly hurt, but the KW and NS tests were relatively un-
> affected. I suspect that the rank transformation will work pretty well in most
> anova problems.

it is also very important to worry about the sample sizes you are concerned
with.  In papers I gave in 1981 (Proceedings of SUGI and of Stat Computing
Section of ASA) I looked at 11 different methods of estimating solutions for
the Behrens-Fisher problem EVEN WHEN THE POPULATION VARIANCES WERE EQUAL.  For
even the case of n1=n2 with n1 < 6 many of the methods provide empirical
two-sided Type I error rates substantially different than the nomial levels.
To take an example for n1=n2=2, the method utilized by SAS produces an
empirical error rate of about .025 for a nominal level of .05.  For unequal
sample sizes, it gets even worse, e.g. for n1=2, n2=50 the SAS method produces
an empirical error rate of of .12.  Even using an F test for the equality of
the variances as a pretest estimator does not eliminate the problem.

Having said all of that, I think it is important for me to remark that in most
actual cases of data where there appear to be unequal variances, it is also
the case that the normal distribution assumption is not reasonable.
Frequently a transformation of the data either by a analytic function, e.g.
log or one of the rank transformations will produce better results than any of
the BF solutions which assume only different variances but still normal
distributions.

-phil

> Tony
>


--
     J. Philip Miller, Professor, Division of Biostatistics, Box 8067
	 Washington University Medical School, St. Louis MO 63110
     phil@wubios.WUstl.edu - Internet  (314) 362-3617 [362-2694(FAX)]
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