HDTenEightyP/NetNews huggingface dataset:
From: steveg@eos.arc.nasa.gov (Steven Edward Gregorich)
Subject: LISREL 386 EXTENDER Installation
Organization: NASA Ames Res. Ctr, Calif.
Distribution: usa
Date: Sat, 21 Nov 1992 00:51:04 GMT

Greetings.

This is not a statistical question.
I have LISREL *software* questions.

I recently purchased LISREL 7.20 and PRELIS 1.20. for the DOS
386 Extender platform.  I have a 
DTK 386-33 motherboard, a Cyrix 33MHz math coprocessor, and DOS 5.0.  
Additionally, I have installed HYMEM.SYS, EMM386.EXE (noems), 
and SMARTDRV.EXE (all three from Windows 3.1). Currently, 
I have three questions:

(1) 
After initial installation (and without Windows running), neither 
LISREL7 or PRELIS would not properly execute until I removed 
EMM386.EXE NOEMS.  (Actually, if I booted the machine with 
EMM386 NOEMS installed and then switched EMM386 to AUTO and 
then back ON I was able to execute LISREL7 and PRELIS).  Without 
EMM386 loaded, the LISREL7 and PRELIS test stream files executed
perfectly.  Any suggestions about how I can get LISREL7 and PRELIS
386 Extender to be compatible with EMM386 NOEMS (besides my 
parenthetical voodoo method)?  The key appears to be through the 
use of the CFIG386.EXE program, but I am clueless.

(2) 
Even when I boot clean (no TSRs, no device drivers, no Windows),
I cannot properly execute PRELIS on a larger problem (N0=3500, 
NI=24).  After PRELIS sucessfully reads the raw data through both
passes the program terminates with the message "Abnormal program 
termination: Memory protection fault."  The installation manual
states that such errors might occur if conflicting TSRs (e.g.,
SMARTDRV.EXE) are present.  However, this was not the in my test
configuration.

(3) 
I noticed in the file EXTENDER.DOC that in order to run LISREL7
and PRELIS as non-Windows apps from Windows 3.x 386 Enhanced mode
CFIG386.EXE must be used to alter the -MAXDATADPMI attributes
of both applications.  While I'm asking questions, are there any
other matters related to the use of these programs within Windows
3.1 that I should know about?

TIA

Steve Gregorich
Organization: Queen's University at Kingston
Date: Fri, 20 Nov 1992 18:32:37 EST
From: Jeff Boyd <BOYDJ@QUCDN.QueensU.CA>
Newsgroups: bit.listserv.stat-l
Subject: Re: last one-and it doesn't have anything to do with star trek!


>  The engineer says:  "3 is prime... 5 is prime... 7 is prime... 9 is
>  prime... 11 is prime... ..."


Based on my wife's experience as a chemical engineering grad student:


   chem.eng. grad student  --  3 is prime
                               5 is prime
                               7 is-

   chem.eng. professor  --  That's enough.  We're fitting a line here,
                            why are you wasting your time with more
                            than 2 points?

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Date:         Tue, 17 Nov 1992 07:31:09 EST
Reply-To:     Gavin Longmuir <gavin@sorokin.anu.edu.au>
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From:         Jim Cassell <CASSELL@UNCVM1.BITNET>
Subject:      demographic mailing list

Here's a new mailing list on demography.  This list does NOT use the
Revised Listserv software, so read the signup instructions carefully.
Please send all question on the list to Gavin Longmuir, the list manager
(gavin@sorokin.anu.edu.au). -- Jim

-------------------------------------------------------------------------
Jim Cassell                                    Jim_Cassell@UNC.EDU
Institute for Research in Social Science       Phone:  919-962-0782
University of North Carolina-Chapel Hill       Fax:    919-962-4777
Chapel Hill, NC  27599-3355
-------------------------------------------------------------------------
----------------------------Original message----------------------------
Hi all!

Sometime ago I asked a question in many of the network newsgroups,
about the lack of a sci.demography newsgroup. I received a luke warm
response about creating such a newsgroup.

Anyway to cut a long story short, I'm announcing the formation of a
demographic mailing list. It is to be open to all, and have no
censorship.

The charter of the demographic-list mailing list follows:


This mailing list is concerned with the discussion of Demography,
and Demographic Techniques.

According to the United Nations Multilingual Demographic Distionary,
 'Demography is the scientific study of human populations, primary
  with respect to their size, their structure and their development'.

It is not just to be a forum for discussion and intellectual fray, but
also a market-place for new ideas.

This mailing list is supported by the:
        Computing Personal,
        Demography Program, Demography and Sociology Division,
        Research School of Social Sciences,
        Australian National University.


To join the mailing list just mail the following two lines to
majordomo@sorokin.anu.edu.au

subscribe demographic-list
end

From then on all mail sent to demographic-list@sorokin.anu.edu.au
will be reposted to all members subscribed to the list. Users can
also easly unsubscribe from the mailing list at anytime.


--
       *                     Gavin Longmuir - General Dog's Body and Programmer
    *    *               Demography Program, Research School of Social Sciences
       *                    Australian National University, Canberra, AUSTRALIA
Voice: +61 6 249 0530  FAX: +61 6 257 1893  InterNet: Gavin.Longmuir@anu.edu.au
*      UUCP: {uunet,ubc-vision,ukc,prlb2}!munnari!coombs.anu.edu.au!gavin
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 19 Nov 1992 16:48:00 PST
From:         Charles Chamberlin <CHAMBERLINC@AXE.HUMBOLDT.EDU>
Subject:      RE:ANSCOMBE.DAT

Are there some typos in the X1,Y1 data set?  Should the 0.84 be 8.4?
The linear regression results are the first X,Y pair don't yield the same
slope and intercept as the other three pairs.
-------------------------------------------------------------------------------
Charles E. Chamberlin
Environmental Resources Engineering
Humboldt State University
Arcata, CA  95521
USA
(707) 826-4346
(707) 826-3616 (fax)
ChamberlinC@axe.humboldt.edu
-------------------------------------------------------------------------------
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Date:         Sun, 22 Nov 1992 13:50:22 -0500
From:         NIZARD Alain-F <NIZARD@FRBDX11.BITNET>
Subject:      Reported use of S

Hi net workers,
Does anybody out there could report experience using S in
   - statistic production,
   - education
   - applied statistics
Any information would be wellcomed :-) !
Regards, Alain-F. NIZARD.
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Date:         Tue, 17 Nov 1992 08:18:00 ARG
From:         RVLEOSAR@ARCRIBA.BITNET

Does anyone know of a PC program that do a
maximun likelihood ratio test?

Thanks in advance.

Leonardo A. Saravia
rvleosar@criba.edu.ar
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Newsgroups: bit.listserv.stat-l
Date:         Tue, 17 Nov 1992 09:35:48 EST
From:         "Bruce C. Dudek" <BCD80@ALBNYVM1.BITNET>
Subject:      Stat and Visually Impaired Students

Reading the recent threads on testing assumptions, and other notes
where a focus on graphical displays is emphasized, I am reminded of
a long-standing question I have been faced with.  How can we best
teach statistics to visually handicapped (most commonly blind) students?
I rely heavily on graphical methods both as a pedagogical tool and as
data analytic necessity.  When, on occasion, I have had blind students
in class, I have certainly not felt that I did them justice (even
with extensive out of class tutoring)

Can anyone on the list suggest any literature on this topic?

************************************************************************
************************************************************************
** Bruce C. Dudek             *                                       **
** Dept. Psychology           *  BCD80@ALBNYVM1.BITNET                **
** SUNY-Albany                *  BCD80@BALDER.ALBANY.EDU              **
** 1400 Washington Ave        *  Fax:    518-442-4867                 **
** Albany, NY 12222 USA       *  Voice:  518-442-4824                 **
************************************************************************
************************************************************************
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 19 Nov 1992 16:53:13 AST
From:         Rolf Turner <rolf@MATH.UNB.CA>
Subject:      Anscombe's examples.

I received a request to post the information if I received a helpful
answer --- and I have already, from Jon Cryer at the University of
Iowa --- so here is the info:

>  .....  It should be required "reading" for all students of
>  regression (or basic statistics for that matter).
>
>
>  # filename: ANSCOMBE.DAT
>  # Data from Frank Anscombe article
>  # The American Statistician, Feb. 1973, pp.17-21
>  # Variables:
>  # x1   y1   x2   y2   x3   y3   x4   y4
>    10  8.04  10  9.14  10  7.46   8  6.58
>     8  6.95   8  8.14   8  6.77   8  5.76
>    13  7.58  13  8.74  13 12.74   8  7.7
>     9  8.81   9  8.77   9  7.11   8  8.84
>    11  8.33  11  9.26  11  7.81   8  8.47
>    14  9.96  14  8.10  14  8.84   8  7.04
>     6  7.24   6  6.13   6  6.08   8  5.25
>     4  4.26   4  3.10   4  5.39  19 12.50
>    12 10.84  12  9.13  12  8.15   8  5.56
>     7  4.82   7  7.26   7  6.42   8  7.91
>     5  5.68   5  4.74   5  5.73   8  6.89
>

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

----------------------------------------------------------------------
|                                                                    |
|          Nice day, isn't it?                                       |
|                                                                    |
----------------------------------------------------------------------
From: ciar04@vaxa.strath.ac.uk
Newsgroups: bit.listserv.stat-l
Subject: Re: Essential book list
Date: 23 Nov 92 15:40:38 GMT
Organization: Strathclyde University VAX Cluster

In article <9211230745.AA00168@hilbert.maths.utas.edu.au>, mcphers@HILBERT.MATHS.UTAS.EDU.AU (D. Glen McPherson) writes:

> ECONOMETRICS
> 
> E1 "Introduction to the Theory and Practice of Econometrics" 1988
>    Judge et al
>    John Wiley and Sons, 2nd ed

For econometrics, while the introductory book by Judge et al is quite good,
I think a better and more comprehensive book is

     "Econometric Analysis" - Second Edition (1993)
      William H Greene
      Macmillian Publishing Company

Greene's book contain some very recent materials, including conditional
moment testing, generalised method of moments estimation etc.  It also has
a better section on time series analysis (which is one area omitted from
the list).

#----------------------------------#-------------------------------------------#
|  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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Newsgroups: bit.listserv.stat-l
Date:         Mon, 16 Nov 1992 08:59:37 EST
From:         Walt Pirie <WLTPIRIE@VTVM1.BITNET>
Subject:      Testing for Variances

Some imply it almost doesn't matter, everything is robust, others say throw
a dandelion seed in the wind, yet others say let's vote on it, and finally many
 have their own (miriad) of favorite folk-lore remedies. What's going on here?
This is all just mirroring the inadequacy of virtually all text-book treatments
 of this topic.
The common thread through all of this is the idea that Location (means) is the
only worthwhile subject of statistical inference (testing if that's your thing)
, and questions about dispersion (variance) only arise in the context of assump
tions underlying location procedures. Bunk.
There are many situations where questions of location (accuracy)  are relativel
y minor and easily dealt with, but questions of dispersion (precision) are seri
ous and difficult to deal with. If formal statistical procedures are important
for location problems, then they must be also for dispersion problems. When we
face up to that issue, then we'll be properly equipped to discuss it in the
context of assumptions.
And I'm not eschewing the use of visual techniques. I teach all my students tha
t all statistical analysis is unacceptable unless accompanied by
insightful visual displays.
I can't help but think the reason problems of dispersion are so universally
ignored is that good analytical solutions are hard to come by, so it's easier
to pretend they aren't important.
Walt.

|==================================|============================|
|  Walter R. Pirie                 |                            |
|  Department of Statistics        |                            |
|  Virginia Tech                   |                            |
|  Blacksburg, VA 24061-0439       |                            |
|                                  |                            |
|  Tel. 703-231-5441               |                            |
|  Bitnet WLTPIRIE@VTFVM1          |                            |
|  Telnet WLTPIRIE@VTVM1.CC.VT.EDU |                            |
|                                  |                            |
|  Fax  703-231-3863               |                            |
|==================================|============================|
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU
Subject: (no subject given)
Newsgroups: bit.listserv.stat-l
Date:         Thu, 19 Nov 1992 16:53:17 -0500
From:         KIRK@IDUI1.BITNET

There has been some interest in information on chi-square goodness-
of-fit vs. edf vs. Shapiro-Wilks tests for normality.  For those of
you who do not want to spring for the price of the d'Agostino book,
look at the article by

M. A. Stevens, EDF statistics for goodness of fit and some comparisons,
JASA 1974, vol. 69, pp. 730-737.

It is a very nice (and readable) paper.  As alluded to by others, it
shows that chi-square tests are passe and that the Shapiro-Wilks test
is the test of choice for testing normality.  For other distributions
where Shapiro-Wilks does not apply, various EDF tests beat the chi-
square test hands down.  I heartily recommend this paper.

Kirk Steinhorst, University of Idaho
kirk@laplace.mathstat.uidaho.edu
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Date:         Mon, 23 Nov 1992 13:06:46 -0600
From:         "J. Philip Miller" <phil@WUBIOS.WUSTL.EDU>
Subject:      survival analysis to a threshold

Recently I have reviewed several papers which utilized a survival analysis
where the endpoint was defined as the first time that a measurement dropped
below some predefined level.  While I would personally prefer to use something
that utilizes the continuous measurements, the threshold concept has clinical
appeal.

Does anyone know of any literature which addresses the implications of using
this type of model.  Of primary interest is what is the loss in efficiency of
the analysis as a function of the measurement variability of the outcome
variable.

-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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Date:         Mon, 16 Nov 1992 08:32:00 PST
From:         Charles Chamberlin <CHAMBERLINC@AXE.HUMBOLDT.EDU>
Subject: Re: Normal probability plots

With respect to the normal probability plot correlation coefficient:

The MINITAB Reference Manual also provides a set of citations in support of this
method, including a technical report by Ryan and Joiner (no date) "Normal
Probability Plots and Tests for Normality", Statistics Dept., Penn. State Univ.
Ryan and Joiner demonstrate that this test is "essentially equivalent to the
powerful Shapiro-Wilk Test W and its approximation W' ..." and also desccribe
how he test may be extended to other distributional forms.
-------------------------------------------------------------------------------
Charles E. Chamberlin
Environmental Resources Engineering
Humboldt State University
Arcata, CA  95521
USA
(707) 826-4346
(707) 826-3616 (fax)
ChamberlinC@axe.humboldt.edu
-------------------------------------------------------------------------------
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Date:         Mon, 23 Nov 1992 08:20:00 EST
From:         jmk2@CIDHIV1.EM.CDC.GOV
Subject:      Expository sessions at ASA meetings

The latest Amstat News contains a letter from Meredith Warshaw pointing out
that the ASA does relatively little for masters level statisticians (to some
extent, the same is true about Ph.D. applied statisticians).  I wish to point
out to others on this list that there is something that they can do about
this: organize sessions at ASA meetings.

ANYONE can organize a "special contributed paper" session at an ASA meeting
(in the past, these were called "topic contributed" sessions).  The format is
4 or 5 20 minute talks (4 if there is a discussant); see the registration
from in the November Amstat News.  The organizer needs to submit all the
abstracts as a package by 1 February, and all speakers must pay a
registration fee at that time (just as for a contributed abstract).  In
contrast to an "invited" session, you do not need to submit a proposal in
advance, and no approval by the program committee is required.

The problem Meredith refers to in her letter was brought home to me at the
ASA meeting in Boston when, on Wednesday evening, I heard someone ask a very
experienced masters statistician, "Have you heard anything interesting?"  She
responded, "There was finally a session this afternoon that had some
interesting talks."  It struck me that what she said was true: there are very
few expository sessions on general methodology (in contrast to some of the
sections which organize nice expository sessions on some topics, such as
clinical trials).  Tom Louis, president of ENAR, was among those who agreed
that there should be more expository sessions.

I have already organized a special contributed paper session on the bootstrap
for the 1993 ASA meetings.  My procedure was simple: I sent an e-mail to Brad
Efron, asking for suggested speakers, and he replied very promptly (the IMS
e-mail address list on statlib is helpful here).  Most of the people I
contacted agreed to speak.  Colleagues are working on organizing other
sessions on robust smoothing and on meta-analysis.

Anyone can do what I have done.  All it takes is about a working day's time
to contact people.  A session presenting applications of a particular method
or interesting applications in a subject matter area would also be
interesting.  Another possibility is to organize a roundtable discussion
(November Amstat News, p. 10).  If you don't like the current format of ASA
meetings, use the system!  It's there!

John M. Karon
Centers for Disease Control
jmk2@cidhiv1.em.cdc.gov
voice (404) 639-2032
From: mcphers@HILBERT.MATHS.UTAS.EDU.AU (D. Glen McPherson)
Newsgroups: bit.listserv.stat-l
Subject: Re: essential books for consultants
Date: 18 Nov 92 13:50:44 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU
X-Mailer: ELM [version 2.2 PL11]

I posted an item yesterday asking for contributions to a list of essential
books for the bookshelf of a consultant statistician who does consulting over
a broad spectrum of disciplines. As I noted, I will provide an edited version
of this list for STAT-L members.

To those who have already responded, many thanks.

To those members who are still contemplating their selections, I make the plea
that you provide FULL DETAILS including publisher, etc. so that those
 interestedin purchasing your recommendations have sufficient detail to do so.
My e-mail address is

    mcphers@hilbert.maths.utas.edu.au

Many thanks,

Glen.

--
 ---------------------------------------------------------------------------
|  Glen McPherson            |                                   |  _--_|\  |
|  Department of Mathematics |-----------------------------------| /      \ |
|  University of Tasmania    |               E-Mail:             | \_.--._/ |
|  Australia.                | mcphers@hilbert.maths.utas.edu.au |       *  |
 ---------------------------------------------------------------------------
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Via:           UK.AC.KING; 17 NOV 92 15:56:23 GMT
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Date:         Tue, 17 Nov 1992 15:55:45 +0000
From:         Stephen Gourlay <BS_S467@NEPTUNE.KINGSTON.AC.UK>
Subject:      the meaning of transformations

In the discussion of testing assumptions, someone mentioned transformations.

I have always had a problem with these, namely, that whilst I know that my
data represented e.g. counts of something, I cannot figure out a
non-mathematical understanding of what transformed counts mean.  As a result
I am very reluctant to transform data just to 'make it fit'.

Has anyone any references, discussion of this problem, explanation of what
particular common transformations mean in 'ordinary' language?

I will compile any suggestions, comments mailed to me and send the result to
the list.

Stephen Gourlay
Senior Lecturer
Kingston University
Kingston on Thames
UK

bs_s467@neptune.kingston.ac.uk
From: DWINSLOW@UCS.INDIANA.EDU
Newsgroups: bit.listserv.stat-l
Subject: Mayfield statistics
Date: 18 Nov 92 21:43:35 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

We have data on avian nest success for which we have calculated "Mayfield"
statistics.  This is basically the ratio of all of the nests lost divided
by all of the nest-days for which the nests were active.  That is, it is
a proportion to describe the daily mortality (or 1-m = survivorship)
for the population.  Douglas Johnson (Auk 96:651-661) describes a method
of estimating the variance of survivorship based on maximum likelihood
estimation.  He gives a test statistic to test the null hypothesis of
no difference between daily survival rates (say, between two populations),
but fails to mention which distribution to test it with.  The test
statistic is the difference between the survivorship values divided
by the standard error of the difference.

Anyone know what distribution to compare it with?
                Thanks, Donald (DWINSLOW@UCS.INDIANA.EDU)
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