HDTenEightyP/NetNews huggingface dataset:
From: laplante@ERE.UMONTREAL.CA ((Laplante Benoit))
Newsgroups: bit.listserv.stat-l
Subject: Artificial data (again)
Date: 14 Oct 92 16:54:08 GMT
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   I wrote something pretty stupid a few minutes ago in my last
message.

   In order to get a random sample from a multivariate normal population
of known variances and covariances, one needs as many normal random vectors
of the size of the number of variables, and not as many normal random
vectors of the size of the sample as there are variables.

   It makes no sense to sample separate variables.

   My apologies to those who helped me and may have thought their
explanations were not clear enough. It's just that the student had left
his mind somewhere else for a while.


Benoit Laplante
Departement de psychologie
Universite de Montreal
Laplante@ERE.UMontreal.CA
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Date:         Mon, 12 Oct 1992 10:53:00 EST
From:         mmz1@CCDDCD1.EM.CDC.GOV
Subject:      Independence of obs in Logistic Regress

As a follow-up to Cande V. Ananth's comments on repeated measures design for
a logistic model, the generalized estimating equations approach is not the
only approach and may not be the best approach to this kind of analysis (this
has not been determined yet, to the best of my knowledge).

See the set of references for various approaches to repeated categorical
response in Statistics in Medicine 1988 Jan-Feb;7:(1-2):95-176. [Note that
Dr. Ananth's reference #5 by JH Ware et al. is the first in this set of
references.]

                                    Matthew Zack
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Date:         Sat, 10 Oct 1992 10:27:00 EST
From:         mmz1@CCDDCD1.EM.CDC.GOV
Subject:      Disciminant analysis with dichotomies?

Logistic regression can use both dichotomous and continuous variables for
discrimination and should be applicable to your situation.  In comparisons
with discriminant analysis, logistic regression does worse only when all the
independent variables are normally distributed; otherwise, it does as good or
better than linear discriminant analysis.

                                    Matthew Zack
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Date:         Mon, 12 Oct 1992 17:08:00 EDT
From:         "(Robert I. Kabacoff Ph.D.)" <kabacoff@NOVAVAX.NOVA.EDU>
Subject:      path analysis question

Please forgive me if this question is basic. I faculty member came
to me with the following situation.

She is doing a path analysis (recursive and all variables observed) and
has found that adding variables to the model increased the goodness of
fit index (chi square) while decreasing the amount of variance accounted
for in the criterion variable.

I did not think that this was possible. Am I missing something?
--
=============================================================================
Rob Kabacoff, Ph.D.              | Internet: kabacoff@novavax.nova.edu
Center for Psychological Studies | Phone: (305) 475-7581
Nova University, College Ave.    | "Florida is Florida...it's warm, there are
Ft. Lauderdale, FL 33314         |  oranges, and safe driving is optional."
=============================================================================
From: halpin@VAX.OX.AC.UK (Brendan Halpin)
Newsgroups: bit.listserv.stat-l
Subject: Sequence matching software
Date: 13 Oct 92 17:39:58 GMT
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Via:        UK.AC.OX.MR; 13 OCT 92 18:41:49 BST

Can anyone give me a pointer to software for carrying out sequence
matching, as described in Abbot and Hryak "Measuring resemblence in
sequence data: an optimal matching analysis of musician's careers",
Am. J of Sociology 1990.

The technique is relatively unknown in the social sciences but
seems popular in the life sciences, and is used especially for DNA
sequencing.

In the paper, the "Beldings Program Series" is mentioned and
associated with David Bradley of Cal State U, Long Beach. If anyone
can identify this, or provide pointers to any suitable software,
I'd be very grateful.

Thanks in advance,

Brendan

Brendan Halpin                    Email: HALPIN@VAX.OXFORD.AC.UK
Nuffield College                  Phone: +44 865 278642
Oxford OX1 1NF
United Kingdom
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Date:         Fri, 16 Oct 1992 08:44:05 EDT
From:         Clark Gaylord <GAYLORD@VTVM2.BITNET>
Subject:      Re: Akaike's Info. Crit. & PROC MIXED

For the "bigger is better" version of AIC:
   -2*ln(like) -- the bigger the better, right?  But, in general gets
                  large (inappropriately from Akaike's viewpoint) as p
                  increases.
    2*p        -- this is our "penalty" term, to take away some of the
                  "natural growth" that -2*ln(like) has for large p.

Hence:
   AIC = -2*ln(like) - 2*p

I will not comment much on the appropriateness of this measure, though I
think it is fair to say that the jury is still out regarding its usefulness.

*************************************************************************
* Clark K. Gaylord                  | I do not write experimental music.*
* Dept. of Statistics and           | I do my experimenting before I    *
* Office of Institutional Research  | write my music.  After that is    *
* Virginia Tech                     | the listener who must experiment. *
* internet: gaylord@vtvm2.cc.vt.edu |      -- Edgard Varese             *
*************************************************************************
From: maj@waikato.ac.nz
Newsgroups: bit.listserv.stat-l
Subject: Bioequivalence
Date: 14 Oct 92 08:54:05 +1300
Organization: University of Waikato, Hamilton, New Zealand

This bioequivalence testing thing is interesting. But is it
any different to requiring that the confidence interval for
the effect be confined to a pre-specified interval about
zero or whatever?

If so why not express it this way and avoid all the mystique?
-- 
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:         Wed, 7 Oct 1992 11:54:12 -0400
From:         Allan Reese <R.A.Reese@SEQ.HULL.AC.UK>
Subject:      Long string variables.

I've so far seen Mr Wang's original question and the SPSS reply
noting that it had been answered. So that I don't duplicate too
much of what you awaits me in the ether, I'll comment that SPSS
(the full language) has powerful facilities for string handling,
but SPSS PC+ lacks most of these, especially substring extraction
which I think is essential. Under Windows, you get the whole works
(I haven't checked that, and that's often fatal!).

My own inclinations when tabulating long strings are to use either
REPORT or AUTORECODE.  AUTORECODE has one trap, which is the excuse
for this mailing.

I had a use who input job titles as part of the data. (The data subjects
wouldn't have recognized the term "job title" but they've been dead a
couple of hundred years.) Since the data were transcribed verbatim, there
was little consistency of spelling or word choice. So my colleague used
something like:

autorecode var=jobtitle /into=jobcode /print

and after examining the printout he was able to classify the jobs in an
ad hoc way:

recode jobcode(1,3,6=1)(2,11,27,28,29=2) etc.

That worked fine, and reduced the job titles to a managable number of
discrete categories. HOWEVER, he then wanted to work on a subset, so
edited:

select if (date < 1800)

BEFORE the autorecode.  Of course (with hindsight!), the autorecode now
allocates quite different numbers to each job title and the recode is
a nonsense. But I can't remember how we picked up on it.

--
(R.) Allan Reese        Janet:          r.a.reese@uk.ac.hull
Head of Applications    Direct voice:   +44 482 465296
Computer Centre         Voice messages: +44 482 465685
Hull University         Fax:            +44 482 466441
Hull HU6 7RX, U.K.
From: saswss@UNX.SAS.COM ((Warren Sarle))
Newsgroups: bit.listserv.stat-l
Subject: Re: "proving" no difference
Date: 14 Oct 92 22:24:08 GMT
Organization: SAS Institute Inc.
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In article <9210130300.AA07825@>, ataylor%LALA.ZOO.HAWAII.EDU@VM1.MCGILL.CA
writes:
|> ...
|> How best can we use statistical inference to "prove" (give strong evidence
for)
|> the _absence_ of a difference or effect?

You can't. You can only give evidence that the difference is small.

|> As Meredith says, clients/authors often want to use a nonsignificant test
(or
|> better, a P-value >> 0.05) as evidence two groups don't differ (or the
regressio
|> slope is 0, or whatever). What can/should they do instead?

Compute a confidence interval for the difference.
--

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513       those of SAS Institute.
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 8 Oct 1992 08:10:30 CDT
From:         ECO_GXC@SHSU.BITNET
Subject:      crime rates

darlington's suggestion of biomial/chi-square would work well and I
doubt any statisticsion would quible with it but you might get a
quibble from some criminologits.  The problem is with the crime rate
itself, not the statistics.  Although a binomial model gives you
a good procedure to test for differences between rates (proportions),
the crime rate does not really arise from a binomial process.  The population
are not the sample elements.  A binomial model is saying that for each
person in the populationj a crime either does or does not occur.  The
process that generates the crime counts is closer to a poisson process, you
cannon identify those sample points where a crime does not occur.  Depending
on how much data you are looking at you might want to test a hypotheses
that the crime processes of the two cities come from a common poison process.
If all you've got is one rate for each city (one time period observation)
then darlington's suggestion is your best bet.

By the way, i'd be interested in hearing about the context in which you
are interested in this test.  I'm a criminologist who teaches statistics
and has an education in OR.

Gary Carson
From: RFRCC@CUNYVM.BITNET (r.f. rockwell)
Newsgroups: bit.listserv.stat-l
Subject: kurtosis and distributions
Date: 8 Oct 92 15:03:56 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

Sorry for double posting this but I thought I might get a wider range of
suggestions.  We are interested in generating samples of size n from
distributions that have the same mean and variance but different values
of kurtosis.  I'll appreciate any references, equations, code or ideas.

please respond directly to me and I will summarize them for the lists.


+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
                                    +
r.f. rockwell                       +  bitnet:      RFRCC@CUNYVM.BITNET
                                    +  internet:    RFRCC@CUNYVM.CUNY.EDU
                                    +
Department of Ornithology           +  voice:       212-769-5793
American Museum of Natural History  +  voice mail:  212-650-8503
Central Park West at 79th Street    +  fax:         212-769-5759
New York, NY 10024  USA             +
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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Date:         Sat, 10 Oct 1992 10:51:00 EST
From:         mmz1@CCDDCD1.EM.CDC.GOV
Subject:      Another logistic reg questions

Alan Agresti's book on ordinal categorical analysis.

Introduction to SAS reference on PROC LOGISTIC.

Matthew Zack
From: ANANTH@UNC.BITNET (Cande V Ananth)
Newsgroups: bit.listserv.stat-l
Subject: Re: Independence of obs in Logistic Regress
Date: 12 Oct 92 16:18:00 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

Netters,


##  Mathew Zack writes.....

> As a follow-up to Cande V. Ananth's comments on repeated measures design for
> a logistic model, the generalized estimating equations approach is not the
> only approach and may not be the best approach to this kind of analysis (this
> has not been determined yet, to the best of my knowledge).

##  Sorry folks ! I apologise for the mistake if my posting reflected
    that GEE (generalized estimating equations) approach was **the**
    only method to analyzing non independent (repeated measures)
    observations. What I meant to convey was that GEE is a robust and
    one of the good methods. There are definitely other approaches
    to analyzing such data.

>
> See the set of references for various approaches to repeated categorical
> response in Statistics in Medicine 1988 Jan-Feb;7:(1-2):95-176. [Note that
> Dr. Ananth's reference #5 by JH Ware et al. is the first in this set of
> references.]
>

... Cande V Ananth
    Dept of Biostatistics, SPH
    Univ of North Carolina, Chapel Hill
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Date:         Wed, 7 Oct 1992 13:54:15 GMT
From:         Leslie Daly <LDALY@IVEAGH.UCD.IE>
Subject:      Interactive Graphics on the PC

I recently asked for the list's collective wisdom on Interactive
Statistical Graphics packages for the PC akin to the Mac's JMP or
Datadesk.   This mail summarizes the responses.

Firstly thanks to the following who send me a reply and apologies for
not responding individually: (in random order) Don MacQueen, Albyn
Jones, J Philip Miller, Adam Gehr, Nelson R Pardee, Teresa Hyslop,
Jim Handsfield, Alana Boltwood, John Collins, Meredith Warshaw, Paul
March, Aaron M Ellison, Ruy Luiz Milidiu, Stan Jones, John R Vokey,
WH Watt, Jeff Jensen, Allan Reese, Don Plock. (Sorry if I've forgotten
anyone).

There seems to be some interest in PC packages in this area, and for
brevity I am just listing those suggested.  Some have or will have
shortly Windows versions.  I have been given a few contact
addresses for the vendors but I have not included these.  The
interactive capability of the packages seems to vary a lot, as do
their ease of use.  The packages are:

SAS/INSIGHT  and perhaps SAS/LAB.  This is modelled on JMP and looks
    as if it could be good.  The beta version for Windows is
    available.
S and S-plus were mentioned by many as excellent and apparently
    there is or will be a Windows version.
Systat/Sysgraph  was also mentioned by many, and again a Windows
    version is soon to be available.  Jeff Jenson gave a long
    critique of Systat for the Mac and hoped the Windows version would
    be better.  This seems however to be well liked in general.
XLISP-STAT also got a mention with the general comment that it was
    not the easiest to program.  It is available free via ftp which
    is a plus.
SPSS for Windows was mentioned by a few.

Other packages that were mentioned only once were: EXECUSTAT, NCSS,
STATGRAPHICS, STATA, STATISTICA.

I received by mail brochures for ISP and for UNISTAT for Windows.

Leslie Daly, Dept of Public Health Medicine and Epidemiology, UCD,
Dublin, Ireland.








Leslie Daly,
Lecturer in Medical Statistics,
Department of Public Health Medicine and Epidemioilogy,
University College Dublin,
Earlsfort Terrace,  Dublin 2, IRELAND

Email:  LDALY@IRLEARN.BITNET
        LDALY@IVEAGH.UCD.IE

Tel:    +(353)-1-7067315   or   +(353)-1-693244 ext 7315
Fax:    +(353)-1-754568
Newsgroups: bit.listserv.stat-l
From: mb2p@fermi.clas.Virginia.EDU (Marco  Bertamini)
Subject: loss function
Organization: University of Virginia
Date: Mon, 12 Oct 1992 20:16:32 GMT



I have a simple question. I'm under the impression that 
the loss function in regression is somehow unrelated to
theoretical assumptions.

My point is, if we assume a normal distribution of data 
points around a true linear relationship, shouldn't we
wheight the regression in terms of the inverse of the
probability of that data point? This value would be
given by a normal function, not by a quadratic one as
in least square regression.

I'd appreciated any comment or pointer to clear
literature.


Thanks,  Marco
+------------------------------------------------------------------+
| Marco Bertamini     Department of Psychology    Univ.of Virginia |
| mb2p@Virginia.EDU   Office phone:(804)982-4744  Home: 293-5453   |
+------------------------------------------------------------------+
| "America doesn't exist. I know it because I lived there."|
| from _Mon Oncle d'Amerique_  (1980)     by Alain Resnais |
+----------------------------------------------------------+
From: ILFC594@VAX2.CONCORDIA.CA (GEOFF SELIG - CONCORDIA U. COMPUTING SERVICES)
Newsgroups: bit.listserv.stat-l
Subject: Artificial data...
Date: 15 Oct 92 20:50:00 GMT
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 >    I need to generate several random samples of size 200 to 400 from a
 > normal multivariate theoretical population of which the variance-covariance
 > matrix is known.
 >    So does anyone on the list know of a software, program or big macro that
 > would generate artificial random samples for up to at least 14 variables?

Have a look at the most recent edition of SPSS Inc.'s magazine Keywords
(August, 1992).  In it (on page 11) is exactly what you are looking for.

Geoff Selig        Phone (514)-848-7666 |        _,  /|     The Cat's Meow
Academic Services    FAX (514)-848-7622 |        \ o.O'
Department of Computing Services        |        =(___)=
Concordia University   (H928)           |            U
Montreal, Quebec   H3G 1M8              |  ilfc594@vax2.concordia.ca
                                        |  ilfc594@conu2.BITNET
From: sdd@LE.AC.UK (Simon Dunkley)
Newsgroups: bit.listserv.stat-l
Subject: Weird subject line.
Date: 16 Oct 92 14:33:47 GMT
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Forwarded message:
Rolf Turner <rolf@CA.UNB.MATH> comments:
>
> Reading my email this morning I found a heap of STAT-L items with the
> subject line ``RETURNED BY ADMINISTRATOR''.  These items included some
> postings which I had previously read on the list, some which I hadn't,
> and a posting of my own.  Has this happened to anyone else?  Can
> someone tell me what's going on?
>

    We all got it.  Since I have, unwittingly, been the "cause" of such a
problem in the past, I can tell you what's up.

    Someone's mail address is not accepting mail, either because they don't
exist, their mailbox is full, or their system was down in a slightly odd
way.  Their mail got returned to the listserver to which they have subscribed,
the one at McGill University.  The ListServ software at McGill1 isn't the most
up to date version available, and it sent the message back out to everyone
on the list, rather than trapping it.  This particular 'bug' has been known
for, well, at least 3 years to my knowledge, as a 'fix' has been available
for that length of time.  The problem lies with mcgill, I'm afraid.  Until
they do something, this sort of thing will sporadically happen, most often,
it seems, with VAX/VMS mailers.

    Simon

      00 0 O o o...
     0     ___         _________________ _________________ _________________
    ][_n_i_|(  ooo___  | Simon Dunkley | |    sdd@le     | |  sdd@le.ac.uk |
   (  _____| | |     | | Department of | | University of | |      +44      |
   _||_____|_|_|_____|_|__Psychiatry___|_|___Leicester___|_|__533__523259__|
    o-o  O--O   o o o    o-o       o-o     o-o       o-o     o-o       o-o
-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-
From: UPHILG@UNC.BITNET (Philip Gallagher,(919)966-1065)
Newsgroups: bit.listserv.stat-l
Subject: Elementary IMPUTATION discussion?
Date: 9 Oct 92 20:39:00 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU


    I feel the need to write a background expository note on
    imputation for a paper my colleagues are writing.

    Does anyone have a favorite text/article/whatever that
    gives a good, general discussion of the pros and cons
    of various imputation techniques?  (I'll log all answers
    I may receive and send the log out sometime early next
    week.)

    We have an interesting situation:  my predecessors first
    tried imputing for a person's missing values over time with
    by regression techniques, but since there are only four
    time points possible, the imputations were often too outlandish
    to tolerate with a straight face.  Then they tried using the
    predicted value based on the mean of the center, controlling
    for covars, etc., but that wasn't satisfactory to the investigator
    who is ill-at-ease with the idea of using a center's value in
    the imputation for an individual.  (I understand, I understand!)
    Now we are trying a version of the Hot Deck method, in which an
    individual's earlier value is carried through if subsequent values
    missing.  It seems to work quite reasonably, I will be happy to
    defend it in print and in person, but I would like to do some
    homework first, so that I can not only not make stupid mistakes,
    but also make use of the most eloquent phraseology I can find.
       (Not plagiarism, I just hate to use my own cumbersome word flow
       if there is perfectly lucid exposition right in the open litera-
       ture.  My students will hasten (HASTEN!!!) to agree.)

                                 Muchas gracias,
                                 Phil Gallagher
                                 uphilg@unc

    To borrow another phrase, too good to not be borrowed widely:
             "No cerveza, no trabajo!"
From: ph@physiology.oxford.ac.uk (Patrick Haggard)
Newsgroups: bit.listserv.stat-l
Subject: Estimating effects in proc glm;
Date: 12 Oct 92 09:35:31 GMT
Organization: Physiology Department, Oxford University, Oxford, UK.
Originator: ph@galen.physiol


How does the estimate statement in proc glm; decide which effect
you wish to estimage?  According to the manual 
estimate 'my effect' EFFECT 1 -1; 
will estimate the difference between the first and second levels
of the effect called EFFECT.  But what are the first and second
levels?  Are they the first and second levels as encountered in 
the datafile, or are they the first and second levels used by
proc glm after sorting the dataset?  Do they *always* correspond
to the order of levels given in the "class level information"
section of the output?

Thankyou

--------------------------------------------------------------------------
Patrick Haggard				Email (WORLD): ph@physiol.ox.ac.uk
University Laboratory of Physiology	Email (JANET): ph@uk.ac.ox.physiol
Parks Road,				Tel. (0865) 272116
Oxford, OX1 3PT				Fax. (0865) 272469
England
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