HDTenEightyP/NetNews huggingface dataset:
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Organization: McGill University  - Computing Centre
Newsgroups: bit.listserv.stat-l
Date:         Fri, 11 Sep 1992 14:21:56 EDT
From:         Lyne Thibault <LYNE@VM1.MCGILL.CA>

DELETE krane@vax.acadiau.ca
From: jerry@nutmeg.hnrc.tufts.edu (Jerry Dallal)
Newsgroups: bit.listserv.stat-l
Subject: Re: Isaac Asimov on meta-analysis
Date: 13 Sep 92 14:43:48 GMT
Organization: USDA HNRC at Tufts University

In article <STAT-L%92091214023966@VM1.MCGILL.CA>, A716HOX@HASARA11.BITNET (Joop Hox) writes:
> " I have got the works of all the old masters. I weigh them against
      AAAAAAAA              AAA                    BBBBBBBBBB

> each other - balance the disagreements - analyze the conflicting statements -
                                           BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB

> decide which is probably correct - and come to a conclusion. That is the


> scientific method. At least as I see it"


So easy in theory/abstract.  Difficult in practice.

What are the problems with meta-analysis?
(1) Being sure you have *all* of the relevant information.
(2) Accounting for the varying quality of that information.

When might meta-analysis be needed/useful?  When there is no gold-standard or 
large, unequivocal study to settle a research question.

In what situations are the problems surrounding meta-analysis most 
likely to cuase the most trouble?  In those situations where you need to use
it!

The last two paragraphs might be summarized as
(3) It is used primarily when (1) and (2) are *guaranteed* to cause the most
trouble.
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Date:         Tue, 8 Sep 1992 12:23:12 EDT
From:         Frank Dane <FDANE@UGA.BITNET>
Subject:      Re: continuous likert scales
              8 Sep 1992 08:51:18 -0500 from <MGRANAAS@CHARLIE.USD.EDU>

Mike Granaas wrote that a Likert scale could be made "continuous" by
using a continuous graphic format for responses, presumably for the
purpose of treating responses as interval measures for analyses.
Several others in this discussion have similarly indicated what
appears to be confusion between a Likert Scale and the graphic
response format most often used for such scales.  (I'm not flaming
Mike; his is the only name I saved. Nor am I flaming anyone.)

A Likert Scale hasnothing to do with the response format.  A Likert
Scale is a multi-item questionnaire containing a number (usually ten
or so) statements with which respondants are asked to indicate
agreement/disagreement.  The key to making the questionnaire a real
scale is a series of analyses throuh which one eliminates items
that do not have high interitem or item-total correlations.  The
total score on the scale may be treated as an interval measure
(that's what it was designed for), but one treats individual items
as inerval measure with great risk.  Bottom line: a single item
is not a scale.

Dr. Francis C. Dane, Associate Professor and Chair
Department of Psychology, Mercer University
Macon, GA  31207-0001  USA
Bitnet: FDANE@UGA   Internet: FDANE@UGA.CC.UGA.EDU
Tel: (912) 752-2972
Fax: (912) 752-2108
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Newsgroups: bit.listserv.stat-l
Date:         Fri, 11 Sep 1992 16:43:34 -0400
From:         RWC@UTXVM.BITNET
Subject:      Moran's I (spatial correlation)

Does anybody have any code to compute this value for OLS regression
models?  Ideally in the LIMDEP or SAS/IML or systat languages.

comments or suggestions also appreciated....

rcole@ccwf.cc.utexas.edu
From: feh@duke.edu (Frank Harrell)
Newsgroups: bit.listserv.stat-l
Subject: comparing 2 groups with censored data and competing events
Keywords: survival analysis
Date: 15 Sep 92 15:18:30 GMT


I am involved in a study of critically ill patients for whom we
wish to compare two groups with regard to the timing of
"Do Not Resussitate" (DNR) orders. Not all patients had DNRs
and many have died. The risk of DNR increases as the risk of
death increases, hence there is informative censoring.
In the spirit of the Mantel-Haenszel-logrank statistic (and
related to the work of Pepe in Stat. in Med. and JASA), I can
conceive of a cascade of 2x2 tables of the form:

	For the n patients still alive at time t,
	what is the fraction, in each treatment group,
	who had DNR before time t.

Vary t from 0 to the largest follow-up time.
I need assistance in combining these tables into a test
statistic, or a pointer to an existing statistic suitable
for comparing non-fatal endpoints in the presence of informative
censoring (a terminating event, death).

Frank Harrell
Division of Biometry
Duke U.
Durham NC USA
feh@biostat.mc.duke.edu (our mail header gives an erroneous address)


-- 
----------------------------------------------------------------------------
Frank E Harrell Jr			feh@biostat.mc.duke.edu
Associate Professor of Biostatistics
Division of Biometry                    Duke University Medical Center
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X-Posting-Date: 12-SEP-1992 09:56:53.00
X-Original-To: STAT-L@VM1.MCGILL.CA
Newsgroups: bit.listserv.stat-l
Date:         Sat, 12 Sep 1992 06:56:00 -0400
Reply-To:     G6RBOH91@CINE88.CINECA.IT
From:         G6RBOH91@CINE88.CINECA.IT
Subject:      RE: PRIMER ON CHAOS THEORY

There are a lot of books and articles on Chaos.
I nice book with a number of interesting papers
from different disciplines has been published by
the American Associaton for the Advancement of Science.
However, the best book, in my opinion, is by
D. Ruelle, Chotic evolution and strange attractors,
Cambridge University Press (1989). It is a slim but
seminal book. By the way, Ruelle wrote a very nice
popular book on this subject. I read it in French
and I do not know if it is already translated in
English. Its French title is Choas and hazard.

All the best,

Gian Gabriele Ori
University of Bologna Italy
From: EYF@NIHCU.BITNET
Newsgroups: bit.listserv.stat-l
Subject: Re: Isaac Asimov on meta-analysis
Date: 13 Sep 92 15:04:45 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

> " I have got the works of all the old masters. I weigh them against
> each other - balance the disagreements - analyze the conflicting statements -
> decide which is probably correct - and come to a conclusion. That is the
> scientific method. At least as I see it"
>
>
> Amateur scientist Lord Dorwin
> in Asimov's Foundation.


    In all the replies to this quotation, no one seems to be
aware that Asimov was being ironic.  He was writing about a
society in which no one did original science and Lord Dorwin
represented the numbing orthodoxy which was suspicious of
new ideas and new research.

Mark Regets
EYF@NIHCU
U.S. Commission on Civil Rights
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Newsgroups: bit.listserv.stat-l
Date:         Sun, 13 Sep 1992 08:13:36 CDT
From:         "J. Philip Miller" <phil@WUBIOS.WUSTL.EDU>
Subject:      Isaac Asimov on meta-analysis (fwd)

Joop Hox <A716HOX@HASARA11.bitnet>  writes:
>
> " I have got the works of all the old masters. I weigh them against
> each other - balance the disagreements - analyze the conflicting statements -
> decide which is probably correct - and come to a conclusion. That is the
> scientific method. At least as I see it"
>
> Amateur scientist Lord Dorwin
> in Asimov's Foundation.
>
Some scientists would like to do some of this balancing in a quantitative
way--and thus meta-analysis was born!

-phil


--
     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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Newsgroups: bit.listserv.stat-l
Date:         Mon, 7 Sep 1992 14:25:00 +0930
From:         Bill Venables <wvenable@STATS.ADELAIDE.EDU.AU>
Subject:      Nonlinear Mixed Models
              7 Sep 1992 14:26:12 +1200
              <9209070240.AA12732@algona.stats.adelaide.edu.au>

>>>>> "Murray" == maj <maj%WAIKATO.AC.NZ@VM1.MCGILL.CA> writes:

Murray> Does anyone have references to nonlinear models with random
Murray> effects?  ie , what would be classed as a mixed model if only it
Murray> were linear?

Try

   Lindstrom, M. and Bates, D. (1990) Nonlinear mixed effects models for
   repeated measures data.  Biometrics, 46, 673-687.

and references therein.

___________________________________________________________________________
Bill Venables, Dept. of Statistics, | Email: venables@stats.adelaide.edu.au
Univ. of Adelaide, South Australia. | Tel: +61 8 228 5412  Fax: ...232 5670
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Newsgroups: bit.listserv.stat-l
Date:         Mon, 14 Sep 1992 09:03:00 CDT
From:         SCHWARZ@UOFMCC.BITNET
Subject:      Stat City Update

[Also posted to Edstat-L network].

Thank you to all who responded to my queries.

As indicated, Stat City is the title of a book where H. Gitlow
used a hypothetical city to teach the concepts of statistics.
It is called "Stat City. Understanding Statistics through
realistic applications", and was published by Irwin. My copy is dated
1982, one reader indicates their copy was dated 1986, but books in
print does not list the book.
My primary interest was in the database of 1373 households (along
with a map of the location of the dwelling units) for use in
a class on sampling theory and methods.

The book is out of print, but
-----------------------------------------------------------------------
| 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          |
-----------------------------------------------------------------------
was kind enough to send me a file containing all the relevant
variables for all the dwelling units.
He has graciously agreed to send copies to other users via the
BITNET network. If you are on INTERNET, he asks that you contact
him with instructions on how to send over INTERNET.

On the same vein, an article in the August 1992 issue of American
Statistican "Teaching survey sampling usig simulation" describes
a similar effort. The authors give instructions on how to
obtain their program and examples via e-mail.

Once again, thanks to all members who responded to my query.

Carl J. Schwarz    SCHWARZ @ CCM.UMANITOBA.CA
Department of Statistics
University of Manitoba    (204) 474-6275   fax: (204)-275-5011
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Newsgroups: bit.listserv.stat-l
Date:         Tue, 8 Sep 1992 10:13:00 EDT
From:         "Philip Gallagher,(919)966-1065" <UPHILG@UNC.BITNET>
Subject:      Kerlinger & continuous likert scales

 mike, mgranaas@charlie.usd.edu, wrote, in part,

> I was told a few years back that a likert scale could be made continuous
> by using a line with anchors at each end rather than the traditional
> 5 (or 7 or 9) point scale.  Instead of picking a number between 1 and 5,
> the respondent marks a point along the line and the researcher measures
> the distance from the mark to one of the anchors to obtain a score.
>
> e.g.
>
>       ___________________________/________________________
>     Always                                             Never
>
> Does anybody know if this in fact works?  References where I can learn more?
>

Try Fred Kerlinger's "Foundations of Behavioral Research".

It's frightfully old (at least MY edition is!), but you should have
mastered it before you go beating the bushes for the the newer, fancier
materials.

    As an undocumented aside, my memory from courses in the late Sixties
    is that it helps people to give them some numerical hints on the
    scale (more than just the ends, but I can't remember the rules),
    along with some unequivocally forceful instructions and
    examples that show them that they need not restrict their answers
    to categorical responses, that you intend to look at their answers
    with a ruler, not just a few categories.  I suspect this technique
    is still valid, but perhaps the psychometric gurus amongst us
    will know a whole lot better by now.

    Examples:

    ________________________________________________X____________
    BAD                        NEUTRAL                       GOOD



    _____________X_______________________________________________
    -1                             0                           +1

    Please don't forget, however, that this technique means that
    someone is going to have to go through the instrument and
    measure/score every answer.  It's often worth doing it that
    way, but don't forget to budget the time and money.


                     Phil Gallagher
                     uphilg@unc
Xref: sparky bit.listserv.stat-l:1510 sci.math.stat:1825
From: maj@waikato.ac.nz
Newsgroups: bit.listserv.stat-l,sci.math.stat
Subject: Re: Nonlinear Mixed Models
Date: 9 Sep 92 08:52:08 +1200
Organization: University of Waikato, Hamilton, New Zealand

In article <1992Sep7.142612.10648@waikato.ac.nz>, maj@waikato.ac.nz writes:
> 
> Does anyone have references to nonlinear models
> with random effects?
> 
> ie , what would be classed as a mixed model if
> only it were linear?
> 

A summary of the email responses that I received follows: I hope
no-one objects to my sharing their knowledge!

From:   IN%"psolomon@akora.stats.adelaide.edu.au" [Patty Solomon]
  You might be interested in looking at a paper of mine, joint with DR Cox,
  which appeared in this year's March issue of Biometrika.
  
From:   IN%"wvenable@stats.adelaide.edu.au"  "Bill Venables"
  Try

   Lindstrom, M. and Bates, D. (1990) Nonlinear mixed effects models for
   repeated measures data.  Biometrics, 46, 673-687.

   and references therein.

From:   IN%"markp@per.dms.csiro.au"
  Try Palmer et al, Biometrics V47, pp623-635. There are also
a bunch of references at the end.

From:   IN%"jeff@biomact.biom.csiro.au" [Jeff Wood]
   There is a bit of discussion of this sort of thing in McCullagh and
   Nelder in the context of GLMs.

  
From:   IN%"gange@stat.wisc.edu" [Stephen]
  See Lindstrom and Bates (Biometrics, 1990, 46, 673), Vonesh and Carter
  (Biometrics, 1992, 48, 1) and references therein.


-- 
Murray A. Jorgensen [ maj@waikato.ac.nz ]    University of Waikato
Department of Mathematics and Statistics     Hamilton, New Zealand      
__________________________________________________________________
'Tis the song of the Jubjub! the proof is complete,
if only I've stated it thrice.'
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Date:         Fri, 4 Sep 1992 16:47:51 -0700
From:         SULLINS@NAUVAX.BITNET
Subject:      mail

set mail


thanks,


Ellen Sullins
Psychology Dept
Northern Arizona Univ.
Flagstaff, AZ   86011
602-523-9979
Bitnet: sullins@nauvax
Internet: sullins@nauvax.ucc.nau.edu
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Date:         Tue, 15 Sep 1992 09:17:24 EDT
From:         Wally Dixon <dixon@NIKE.HEIDELBERG.EDU>
Subject:      Heywood cases

I frequently run into Heywood cases and since the topic came up I wish to
answer a question that's been nagging at me.  What is the current thinking in
the statistical field about them?  If one gets Heywood cases, does that mean
that one has "bad" data and should discontinue further analyses?  Does it mean
that one should use a noniterative procedure and to just "ignore" them? Are
they statistical artifacts sometimes, that should just be constrained at 1?
Is it OK to proceed anyway, and just inform readers that a Heywood case was
obtained?  Are there any papers written for nonstatisticians that address the
issue from a theoretical/practical standpoint?  Any help would be greatly
appreciated.

_____________________________________________________________________________
                                   |
Wallace E. Dixon, Jr.              | "Humanity has been held to a limited and
Department of Psychology           |  distorted view of itself--from its
Heidelberg College                 |  interpretation of the most intimate of
Tiffin, OH  44883                  |  personal emotions to its grandest vision
dixon@nike.heidelberg.edu          |  of human possibilities--precisely by
                                   |  virtue of its subordination of women."
                                   |         -Jean Baker Miller
___________________________________|_________________________________________
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Date:         Sat, 12 Sep 1992 17:23:18 CDT
Comments:     "U. of Illinois at Chicago"
From:         Allen Herzog <U50161@UICVM.BITNET>
Subject:      StatFair - Wed. Sept. 21, 1992

         For those of you fortunate to be in the Chicago area on
September 23, 1992 the Chicago Chapter of American Statistical
Association is holding a StatFair.  What follows summarizes their
flyer describing the fair:

       Statistical Software for Persoal Computers & Workstations

       Demonstrations and Bargains

       Date - Wednesday, September 23, 1992
       Time - Noon until 6:30 PM
       Place - The Westin Hotel, Chicago
               (909 North Michigan Ave.)
       Cost - With reservations postmarked before Sept. 19
              $ 10.00 Member of the Chicago Chapter, ASA & Students
              $ 20.00 Non-members (or $22. includes Chapter dues)
            - Registration after September 21 - Add $10.00

       5 GOOD REASONS TO ATTEND StatFair

          Demonstrations   of statistical software - a chance to talk
                           to technical experts
          Bargains         A chance to purchase the software at deep
                           discounts only availabe during 6 1/2 hrs
                           of StatFair
          Handouts    -    Lists - of over 400 statistical software
                           packages with addresses and phones, cross
                           referenced by application (now available
                           on computer diskette)

          For more information ... Call Linda Clark at 708/798-0677

    I hope the list will find this information of interest and use.
I attended the last StatFair a couple of years ago and found it very
informative.
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Via:          UK.AC.LE;  5 SEP 92 13:30:38 BST
Site:         University of Leicester, Leicester, U.K.
X-Name:       David D Stretch
Phone:        +44 533 522522 ext 3251, or +44 533 523251 (direct line)
Fax:          +44 533 523293
Organisation: Organisation??? Who?? Me??? Don't make me laugh!
X-Address:    Lecturer in Psychology, Dept. of Psychiatry,
X-Address:    Clinical Sciences Building, Leicester Royal Infirmary,
X-Address:    PO Box 65, Leicester, LE2 7LX, United Kingdom.
X-Mailer:     ELM [version 2.3 PL0 (LUT)]
Newsgroups: bit.listserv.stat-l
Date:         Sat, 5 Sep 1992 13:25:26 BST
Reply-To:     dds@leicester.ac.uk
From:         David Stretch <dds@LE.AC.UK>
Subject:      npar1way (fwd)

Sorry, I am a bit busy at the moment, so my reply will be rather brief...

>
>     1.  Why should these tests give wildly different P values such as
>         P =< .007 in one test and P=<.17 on another?

Because they are testing different things (If you still have it, read my
previous message about Likert scales, looking at the bit where I talk about
the paper by MacRae (1988) --- I imagine that going back to the sources *may*
be the only way of finding out what *exactly* the assumptions (and hence the
null hypostheses etc) of these tests are, but try looking at Bradley's book
on nonparametric statistics - although its now old, it may have the
information you need).

>     2.  What statistical or theoretical criteria should I use to determine
>         which test to believe?

If you haven't, you need to look very carefully at what you want help with
in deciding what's going on in the data. If you can be more specific in
*exactly* what you are prepared to assume and what the research question in
this instance is, then this should be used to direct your choice, in preference
to using purely statistical criteria that do not take account too much of the
area of application.

>     3.  Is there any such measure in any of these non-parametric tests that
>         would be equivelent to a Tukey or Scheffe post-hoc?

Hmmm... I think so - For example, with the Kruskall-Wallis Test, isn't it
advisable to do post-hoc comparisons on pairwise comparisons using the
Wilcoxen Rank Sum Test (Mann Whitney U test, to some), but adjusting the
alpha level (for example, by making sure that the overall significance
level is still as close to, say, 0.05 as possible - I think this *may* be
something related to the Bonferroni correction, but others on here will
probably know more about it than me.)

I hope this helps. Sorry for being very brief - I may suffer being a bit
incomprehensible in places because of it.

David Stretch

  +-----------------------+---------------------------------------------+
  |  Dr. David D Stretch  | I was gratified to be able to answer        |
  |  Dept. of Psychiatry  | promptly, and I did. I said I don't know.   |
  |  dds@leicester.ac.uk  |                                  Mark Twain |
  +-----------------------+---------------------------------------------+
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Date:         Thu, 10 Sep 1992 09:33:04 -0500
From:         "Robert K. Toutkoushian" <TOUTKOUS@UMNACVX.BITNET>
Subject:      Primer on chaos theory??

Hello,

        I was hoping that someone could point me in the direction of
an intuitive explanation of how 'chaos theory' works. I would like to
have my students read this, so the easier it is to understand, the
better. I have given them the more traditional approach to modelling,
as far as selecting the appropriate functional form and regressors to
include in a model. However, my limited knowledge of chaos theory is
that this is similar to ARIMA-type modelling where you try and exploit
patterns in a time series for prediction purposes, and that this may
work fairly well even when the data appear to be dominated by noise.

        Thanks in advance for any suggestions, and please excuse my
ignorance on this topic.

Robert K. Toutkoushian
University of Minnesota
INTERNET: toutkous@vx.cis.umn.edu
From: gilpin@iscsvax.uni.edu
Newsgroups: bit.listserv.stat-l
Subject: Re: continuous likert scales
Date: 9 Sep 92 07:43:33 -0500
Organization: University of Northern Iowa

In article <920908085118.1928@charlie.usd.edu>, MGRANAAS@CHARLIE.USD.EDU writes:
> I was told a few years back that a likert scale could be made continuous
> by using a line with anchors at each end rather than the traditional
> 5 (or 7 or 9) point scale.  Instead of picking a number between 1 and 5,
> the respondent marks a point along the line and the researcher measures
> the distance from the mark to one of the anchors to obtain a score.
... etc.

  I agree with several comments that the term "Likert scale" is widely misused, 
in fact I have seen many folks refer to ANY numeric response scale to a
questionnaire as a Likert scale.  The reference to Likert's work is remarkably
obscure--most people invoke his name without any reference.

  For anyone who wants to check out what Likert actually did, I'd suggest:

Likert, R. A. (1932).  A technique for the measurement of attitudes.  Archives
of Psychology, 140, 1-55.

  Incidentally, I am also somewhat skeptical that the graphic technique will
yield better results than a numeric scale.  I have used the graphic approach
successfully, but I do not think that the additional work is worth it. 
However, I don't know of any systematic comparisons.  I do seem to recall a
body of work in semantic differential which used 11-point scales.

--------
Andy Gilpin, Dept. of Psychology,     |Internet: gilpin@uni.edu
Univ. of Northern Iowa, Cedar Falls,  |Phone: (319) 273-6104
Iowa 50614-0505                       |

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