HDTenEightyP/NetNews huggingface dataset:
Organization: National Inst. of Animal Science, Denmark
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Date:         Tue, 5 Jan 1993 17:09:54 DNT
From:         Just Jensen <LOFJUST@VM.UNI-C.DK>
Subject:      Matrix problem

Hi,

I am working with implementing the Gibbs sampler for the linear model.

During this procedure I have to prove a matrix identity that I think is
well known but i do'nt seem to be able to prove it.

Let A be a symetric P.d. matrix.

Partition A as A = ! A11 A12 !
                   ! A21 A22 !

Let C=Inv(A)= ! C11 C12 !
              ! c21 C22 !

where C is partitioned in the same way as A and inv means inverse.

Then the following relationship exists:

Inv(A11)*A12 = -C12*Inv(C22)

what I need is the proof! (any hints?? or better full proofs)

Thanks in advance.

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Just Jensen                           | NN     N IIIII     A        SSSS
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Date:         Fri, 8 Jan 1993 20:40:37 MET
From:         "J. A. HARTOG" <ABRAMSE@HROEUR1.BITNET>
Subject:      Forgotten name

A few days ago somebody from the Leiden Giffy group sent a note
to the list. I discarded the note before jotting down name
and address. Will he (she) please contact me .
                                 Jaap Hartog
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From: tgee@alfred.carleton.ca (Travis Gee)
Subject: Re: X^2 interaction
Organization: Carleton University
Date: Thu, 7 Jan 1993 13:34:55 GMT

In <STAT-L%93010516044921@VM1.MCGILL.CA> EJOHNSO3@UA1VM.BITNET writes:

>I'd appreciate your insight in interpreting the results of a 2X3 contingency
>table.

>I've run the standard chi-square test with significant results (p<.01), but I
>see this as analogous to an omnibus ANOVA--it tells me something is happening
>among these six cells, but it doesn't tell me what; therefore, my question is
>whether there is anything like a test for main effects or interaction for a
>chi-square? 

I have an unpublished paper lying about where I argue that such a test
can be done on the following rationale:

1) chi-square is a distribution of z-squares, summed:
2) therefore (o-e)^2/e  is  an approximation to (x-mu)^2/s^2
            ____________
3) thus, \/ (o-e)^2/e    is an approximation to z and so
4) the "important" cells where the effect is occurring will have a big
   "z" score (from 3) ) which is interpretable as a "z", and the
   "important" rows/columns will have sum(z^2) that exceed some critical
   value, with df (# of cells in row/col. ) - 1.
5)   This leads us to an ANOVA-like situation where an a-priori test for
   the effect of a row or column would find sum(z^2) and test as a X^2
   with r-1 or c-1 df, using perhaps a Bonferroni-like adjustment to the
   alpha rate.  Series of tests using both rows and columns would have to
   be adjusted further, because of the non-independence of the tests.



>My gut feeling says that I can divide the critical chi-square
>by my number of cells and then compare each cell chi-square score to this new
>ciritcal value. Is this acceptable? I've not been able to find in the literat-
>ure any comments about interpreting contingency tables, and so any comment you
>could make will be a great assistance.

I don't see why the average-per cell would be a suitable critical
value, because it is tied to the final test statistic, not the value
expected under the null hypothesis.  Thus, if ONE cell has a
monstrously large value, and a second cell shows a marginal effect,
the second cell would not be considered significant because the effect
was larger elsewhere. Hence the effects are not independent by
definition. 
     The hypothesis-testing model works from a null prior distribution
- in the case of X^2, the distribution of Z^2.  I believe that my
formulation is correct, however, I would greatly appreciate any
feedback from fellow netters who have an opinion.  Many thanks in
advance!

((((((((((((((((((((((((((((((((((((((((((((((((((((((((((
Travis Gee ()  tgee@ccs.carleton.ca     ()
           ()  tgee@acadvm1.uottawa.ca  ()        ()()()()
           ()  (Carleton address        ()              ()
           ()    preferred)             ()()()()()()()()() 
Recent government figures indicate that 43% of all statistics
are utterly worthless. 
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Date:         Mon, 11 Jan 1993 17:15:32 CST
From:         ECO_GXC@SHSU.BITNET
Subject:      pbs/advertising/&commercial interests

a couple of people have suggested (in comments re use of statisticians
in news programs) that since mcneil lerher (sp?) is on PBS and doesn't
rely on ad revevues that they are immune from commercial interests.  That's
not exactly true.  They are a syndicated program - they sell segments to
local stations.  Their ability to sydicate themselves (and non profit or not,
they would still like to draw salaries) depends on ratings.  Just as ad
revenues depend on ratings, so does syndication revenues.  PBS is subsidiczed
by public funds - not wholly funded.

gary carson
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Date:         Wed, 6 Jan 1993 15:43:33 -0500
From:         Howard Kaplon - Towson State University <E7M2KAP@TOWSONVX.BITNET>
Subject:      Calculators and Computers: Precision

Most calculators roll over into scientific notation when the values become
large.   In this mode, all of the calculators I have seen are limited to
99 as the largest exponent of 10  (i.e. E 99).  69! is approximately
1.7112 E 98  while 70! has an exponent of 10 that is 100; and this OVERFLOWS
the exopnential memory section of the calculator.

for a desktop computer, although I have not tried yet, you should be able to
get larger factorials by declaring the variables ad double precision.

Howard

-----------------------------------------------------------------------
| Howard S. Kaplon                    |  Mathematics Department       |
| BITNET:  Kaplon-H@TOWSONVX.BITNET   |  Towson State University      |
| Internet:  Kaplon-H@TOE.TOWSON.EDU  |  Towson, Maryland  21209-7097 |
| Phone:  (410) 830-3087              |  FAX: (410) 830-2604          |
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Date:         Mon, 4 Jan 1993 14:13:00 EST
From:         dxa6@CCDOSH1.EM.CDC.GOV
Subject:      Re: Spreadsheet Software

A couple of weeks ago there was a discussion on the list about the perils of
using spreadsheets for statistics.  I didn't save the postings, but I do
recall that at one point someone (Phillip Miller, I believe) responded to
a query from a fellow CDC employee, Deanna Wild, with a message that said,
"the formulas in the textbooks are wrong," or something to that effect, and
that was why one should stick to software specifically designed to do
statistics.

At the time, I was too busy to think about it, but over the holidays I began
to wonder, what formulas exactly are "wrong?"  When I sat in Dr. Fleiss'
class, I can't recall him ever saying that certain formulas in his book were
in error, and that the correct ones could only be found in his notes.  Ditto
for Dr. Kleinbaum's classes.  In fact, I can't recall any of my statistics
professors over the years saying that the formulas in the books were wrong.

Now, I admit that I'm not a statistician.  Neither am I a conspiracy buff, or
I might think that the "true and correct" formulas were hidden away in a safe
somewhere, and that only the inner circles of the statisticians guild had the
combination, while the rest of us were left wandering the dark.  But I think
that any claim that the textbooks are "wrong" ought to be substantiated.
Textbooks do contain some computational formulas which generate
approximations, but those are indicated as such.  Besides, I was taught to
use many of those "approximate" formulas exclusively when I was in
engineering school, less than 20 years ago, when a pocket calculator that did
logs and exponents was considered advanced.

I confess I have used spreadsheet software to automate simple statistics that
I used to calculate by hand: mean, median, standard deviation, standard error,
normal-approximated confidence limits on a proportion, simple linear
regression, and test statistics for z-tests, t-tests and one-way ANOVAs, to
three or four significant digits without any difficulty.  I used either the
built-in formulas or set up the computations using formulas from textbooks.
I don't use spreadsheets to calculate exact p-values and I wouldn't attempt
to do or teach complex analyses using a spreadsheet.

All tools and methodologies have their uses and limitations.  It would be nice
if we could all have a pocket computer that had built in SAS, SPSS, BMDP,
SYSTAT, etc. and cost $99.95 with documentation, so that we could always do
the best possible statistical computations for every problem.  Flame me if
you like, but if a textbook and a pocket calculator were sufficient under
some circumstances, then a textbook and a spreadsheet program can be
sufficient sometimes as well.

David R. Arday, B.S.Ch.E., M.D., M.P.H.
Office on Smoking and Health
Centers for Disease Control
dxa6@ccdosh1.cdc.em.gov
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Date:         Tue, 5 Jan 1993 13:48:53 -0600
From:         "J. Philip Miller" <phil@WUBIOS.WUSTL.EDU>
Subject:      Re: Spreadsheet Software

> A couple of weeks ago there was a discussion on the list about the perils of
> using spreadsheets for statistics.  I didn't save the postings, but I do
> recall that at one point someone (Phillip Miller, I believe) responded to
> a query from a fellow CDC employee, Deanna Wild, with a message that said,
> "the formulas in the textbooks are wrong," or something to that effect, and
> that was why one should stick to software specifically designed to do
> statistics.
>
>
I did not ever say [or at least I hope I never said] that the "text book
formulas are wrong." What I several others have continually said is that
when computations are done on computers the algebraic formulas that are
given in the text books are frequently not numerically accurate because
computers work on finite precision arithmetic.  If you read Fleiss's book,
for example, it gives the formula for the Fisher's exact test in terms of
factorials [I hope I remember correctly, if not there, then pick a different
text that does].  If you use this formula, and any of the numbers are
larger than 69 (on an IBM PC and many other computers), you will not get
the right answer because it overflows the exponent because of the way in
which floating point numbers are stored.  You have to use a different,
computational strategy that worries about numerical overflow.

One of the great difficulties is that when individuals who are not well
versed in numerical methods go to program these tests they tend to debug
their routines on the "text book" problems.  Most authors try to be gentile
with readers and so only present "well behaved" problems.  The difficulty
is to produce programs which tend to not get into problems, and, more
importantly to recognize when they are in trouble and give the user useful
information about the problems encountered.

-phil

PS: The classical text books that discuss many of these issues are Chambers,
Computational Methods for Data Analysis, Wiley, 1977; Kennedy & Gentle,
Statistical Computing, Marcel Dekker, 1980; Thisted, Elements of Statistical
Computing: Numerical Computation, Chapman and Hall, 1988.




--
     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)]
Newsgroups: bit.listserv.stat-l
Date:         Wed, 6 Jan 1993 14:32:16 -0600
From:         "Richard W. Cole" <rcole@CCWF.CC.UTEXAS.EDU>
Subject:      contingency tables

another way to generate comparisons among rows or comparisons
among columns for contingency tables is to use Correspondence Analysis
where each row is defined as a point in a weighted Euclidean metric
of dimensions (min(r,c)-1).  This is a chi-squared metric where
distances among points can be considered a single degree of freedom
chi-square test.  More interesting is the notion of confidence
ellipses around each point and the origin of the space.

========================================================
Richard Cole, Stat/Math Services         Learning to
Computation Center UT Austin TX, 78712   Paint by
rcole@ccwf.cc.utexas.edu                 Numbers
========================================================
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Date:         Thu, 7 Jan 1993 18:50:31 -0600
From:         PARKERRA@VUCTRVAX.BITNET
Subject:      Public Presence of Statisticians

I was just watching the McNeil-Lehrer report (US Public TV News report, for
those of you outside USA) discussing today's Environmental Protection Agency
report about passive smoking as a carcinogen.  Much of the discussion
revolved around the statistical analysis (i.e., the industry spokesperson saying
that the analysis was "unusual" "non-standard" etc, etc.), but of the four
people talking on the show, one was a spokesperson for EPA, one for the tobacco
industry lobby, and two for lobbying groups (one pro-smokers rights, one
anti-smokers rights).  None of them were statisticians.

Does this seem appropriate to others?  It doesn't to me.

How can we (statisticians) make it apparent to people who run news shows
(as one example) that maybe they ought to have statisticians talking about
statistical issues?

Bob Parker
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Date:         Wed, 6 Jan 1993 17:09:15 +0000
From:         Jim Mitchell <jim_mitchell@MSMAIL.KGS.UKANS.EDU>
Subject:      Joint Probability Plots

     I have a colleague who is in need of plotting joint probability elipses.
She has limited (no) access to most packages.  Does anyone have C or FORTRAN
code which will do the trick?

     Thanks, in advance,

     Jim

<<<<<<<<<<<<<<<<<<<<<<<< Attached TEXT file follows >>>>>>>>>>>>>>>>>>>>>>>>
*******************************************************
*                                                      **
*                   Dr. James E. Mitchell                *
*              Hydrologic Data Manager/Analyst          *
*      Geohydrology Section, Kansas Geological Survey   **
*                 The University of Kansas                ***
*             1930 Constant Avenue, Campus West             *
*                    Lawrence, KS 66047                     *
*                                                           *
*      Phone: 913/864-3965          FAX: 913/864-5317       *
*         EMAIL: JIM_MITCHELL@MSMAIL.KGS.UKANS.EDU          *
*                                                           *
*************************************************************
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Date:         Tue, 5 Jan 1993 19:57:48 MEZ
From:         Suitbert Ertel <SERTEL@IBM.GWDG.DE>
Subject:      Plotting ASCII-graphs

I wonder why people on this stat-l board don't
use graphs to illustrate quantitative relations, results,
trends etc. I often would have liked to use such tools
for e-mail exchange of research results. Is there any
public domain program providing such facility?
Looking forward to helful messages.

Suitbert Ertel
Institut fuer Psychologie
Gossler Strasse 14
3400 Goettingen / Germany
SERTEL@DGOGWDG1
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Date:         Thu, 7 Jan 1993 20:35:36 CST
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From:         EJOHNSO3@UA1VM.BITNET
Subject:      Public Presence of Statisticians

Bob Parker asked:

How can we (statisticians) make it apparent to people who run news shows
(as one example) that maybe they ought to have statisticians talking about
statistical issues?
- - -

Here Bob makes the common assumption that there is a positive correlation be-
tween managing "news" shows and the design to correctly inform, when in fact
there is no significant relationship. At best they are independent variables,
if not mutually exclusive. The confounding variable is ratings. The sole rea-
son the major networks now carry "news" shows is to sell air time. You can bet
if the networks can get higher ratings by offering more entertainment than
facts during the "news" they surely will.

Here's the best example I know of this. An extraordally gifted masters student
of mine auditioned as a weekend anchor in a mid-sized market. No one could
match his journalistic skills, but he failed to get the job because his eyes
didn't match the teddybear image they wanted to play off the woman anchor. It
was enough  for me to forget cable TV payments and invest that money in a news-
paper subscription. I know those folks aren't hired for their looks.


 ___________________________________________________________________
 |                         |                                        |
 |  Ed Johnson             |   "...of making many books there is    |
 |  Dept. of Mass Comm.    |   no end; and much study is a weari-   |
 |  University of Alabama  |   ness of the flesh."                  |
 |  Tuscaloosa, AL 35487   |            --Ecclesiastes 12:12        |
 |                         |                                        |
 |_________________________|________________________________________|
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Date:         Tue, 5 Jan 1993 16:32:14 ECT
From:         Lary Jones <LJONES@BINGVMB.BITNET>
Subject:      Re: X^2 interaction

On Tue, 5 Jan 1993 11:36:29 CST <EJOHNSO3@UA1VM> said:
>I'd appreciate your insight in interpreting the results of a 2X3 contingency
>table.
>
>I've run the standard chi-square test with significant results (p<.01), but I
>see this as analogous to an omnibus ANOVA--it tells me something is happening
>among these six cells, but it doesn't tell me what; therefore, my question is
>whether there is anything like a test for main effects or interaction for a
>chi-square?  ...

Chi-Square for a contingency table is an omnibus statistic, similar to
the "Explained" term which is sometimes displayed in ANOVA tables. I
remember seeing procedures for computing the "main effects" -- which
is really testing the goodness of fit of the marginal (one way)
frequencies. I am going to guess that this may not be of interest.

There is a procedure for multiple comparisons. The only reference
that I have at hand is an old one:

Ryan, T. A. Significance tests for multiple comparison of proportions,
  variances and other statistics.  _Psychological Bulletin_, 1960, _57_,
  318-328.

You should get additional verification for the appropriateness of this
procedure.

The basic idea follows that for SNK and other procedures working with
tables of means. One decomposes the 2 by N contincency table into a
series of 2 x 2 comparisons. This makes the most sense when the two
category dimension is something like Agree/Disagree, and the other
dimension represents "groups".

The entries in the table are the Chi-Square values for the 2 x 2
comparisons. The rows and columns are the categories of the larger
dimension ordered by the proportion falling into a target category of
the 2-level dimension (i.e., "agree" in the present example). These
Chi-Square values are then compared to Ryan's table of critical
values. For the problem you describe, the critical values are
X(2)=5.76, X(1)=4.54 . (The value in parentheses is the range tested
-- largest-smallest is 2, adjacent levels are 1).

Hope this helps,
__________________________________________________________________
Lary Jones...Computing Services...Binghamton Univ...(607) 777-2879
School of Management Research Support ...... LJones@BingVMB.Bitnet
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Date:         Wed, 6 Jan 1993 10:08:06 GMT
From:         Ronan M Conroy <RCONROY@IRLEARN.UCD.IE>
Subject:      calculators and computers: precision

Dave Arday is interested in comparing the precision of his
calculator and computer. Phil Miller mentioned 69! as the
biggest factorial that the PC will handle. This, by less than
a coincidence, is the limit of what my Sharp EL-506H and my Tandy
(submerged on the desk, no doubt, at the moment) will handle.
69!/68! is correctly evaluated by them both as being 69. 70!
simply produces an error. But Fisher's exact test is a good case
in point: even with frequencies less than 69, the calculation
will overflow if you multiply out the top of the line and then
the bottom, before dividing. Anyone who has done this test by hand
will know that a little factor finding often reduces the calculation
to the very manageable.

ronan
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Date:         Thu, 7 Jan 1993 23:10:00 EST
From:         FLICKER@FORDMULC.BITNET
Subject:      Network news

While we all like to be cynical about the commercial media and the
ratings systems, and Ed Johnson certainly sounds like he has grounds
for additional distrust, lets not let impatience and distaste make
us lose sight of  --  the data.

The original posting referred to the "McNeil/Lehrer Report" (pardon
me if I misspelled a name) -- the PBS (not-for-profit/Public Broadcasting
System) news program -- a show that does not sell advertising time.

I suspect we may have to look more closely at Robin McNeil and Jim
Lehrer's omission of a statistician on the program. Perhaps the
professional field needs to educate the media that truly understanding
statistical results is not self-evident.

Marcia Flicker
Fordham University

P.S. -- It won't be easy to convince journalists that specialists are needed.
My own personal bias, having been exposed to a few print and broadcast
journalists, is that their own professional training may undermine their
appreciation of the depth of knowledge required in academic fields. After
all, many of them switch from covering environmental issues to war coverage
to the economy, etc., etc., -- picking up enough information in each area
to write a story that at least sounds credible to the rest of us laymen.

Alenxander Pope wrote, "A little learning is a dangerous thing, drink deep
or touch not the Pierian spring." Some of the journalists I've met never
seemed to have heard that quote.
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