HDTenEightyP/NetNews huggingface dataset:
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 3 Sep 1992 10:37:00 EST
From:         Doug Hall <D_HALL@FAUVAX.BITNET>
Subject:      Coefficient Alpha

I'm a doctoral student trying to strengthen myself methodologically, and
I'm having difficulty in understanding the concept of coefficient alpha.
The books I've referred to are beyond me, and I was hoping someone could
explain in simple terms what coefficient alpha is supposed to measure.

The context in which I've been asked to use it is in a series of variables,
each of which is a response to a survey questions, and all of which are
supposed to comprise an index (of job satisfaction, family-work conflict, etc.)

Hope someone can help.
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Newsgroups: bit.listserv.stat-l
Date:         Mon, 24 Aug 1992 09:06:24 +0930
From:         Bill Venables <wvenable@STATS.ADELAIDE.EDU.AU>
Subject:      JOB POSTINGS???
X-cc:         PMTB00A@PANAM.BITNET
              22 Aug 1992 10:19:00 CDT
              <9208221520.AA28050@algona.stats.adelaide.edu.au>

P. M. Taube writes:

Taube> Recently, I have noticed numerous listings of job vacancies as well
Taube> as resumes of job seekers. The question for all to consider is
Taube> whether these listings are appropriate for a stat bulletin board?

I agree this is a serious issue, but one we should make a definitive ruling
about and then leave it.  There is a potential for this sort of discussion
to take on a life of its own.

As someone who has already used the net for this purpose my position is
perhaps clear.  I would like to suggest that, like the Numerical analysis
mailing list, (NA-net), we do allow job advertisments, provided

1. They are brief (say 15 lines maximum),

2. They are also advertised through the regular channels, and

3. No position is advertised more than once.

They should also carry some standard subject line, such as "Job Vacancy",
so that persons not interested can easily discard them.  We should perhaps
review the position in a year's time if there is some problem emerging.

I intend to say no more on this issue and I will, of course, abide by the
consensus of the group.

Bill.
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Date:         Fri, 28 Aug 1992 10:40:15 -0500
From:         "Richard W. Cole" <rcole@CCWF.CC.UTEXAS.EDU>
Subject:      POWER REFERENCES
X-To:         STAT-L%MCGILL1.BITNET@ricevm1.rice.edu

For the list of power references be sure to add (if not already done):

O'Brien, R.G. (1984,86) in the NINTH and ELEVENTH SUGI (SAS USER'S GROUP INT)
PROCEEDINGS.

========================================================
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:         Tue, 25 Aug 1992 11:06:12 MDT
From:         vokey@HG.ULETH.CA
Subject:      Medical Statistics
X-To:         STAT-L@VM1.MCGILL.CA

In addition to a few good introductory stats books, I would encourage all
physicians and others involved in the medical professions to read:

Skrabanek, P. & McCormick, J. Follies and fallacies in medicine, now published
by Prometheus Books, ISBN 0-87975-630-6.

Actually, it's a fun book for anyone to read, and it provides numerous
examples of statistical follies for use in the classroom and as responses
as to why you don't eat oat-bran, don't worry about lowering "risk" factors,
and generally ignore most of the pronouncements of medical "experts".  It
also provides good reason to suspect that "epidemiology" is often a
euphemism for ill-informed, badly-done, and silly.

John R. Vokey <vokey@hg.uleth.ca>
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Newsgroups: bit.listserv.stat-l
Date:         Mon, 31 Aug 1992 11:33:29 CET
From:         Joop Hox <A716HOX@HASARA11.BITNET>
Subject:      meta analysis

Jerry Dallal posted a question whether meta-analysis might be a good idea
to combine data from a number of small experiments. My suggestion is: yes,
provided the data turn out to be well behaved, so you can combine them
without much loss of statistical power. The single best source of information
I know is the book by Hedges & Olkin " Statistical methods for meta analysis".
It is RATHER statistical, so you may want to consult a statistician indeed.

Joop Hox
University of Amsterdam

(^_^)
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Date:         Wed, 26 Aug 1992 21:07:42 EDT
From:         Fabio Idrobo <PSY9A3N@BUACCA.BITNET>
Subject:      Something to recommend to undergraduates.

050 RCPT TO:<venables@stats.adelaide.edu.au>

To:      "Bill Venables" <venables@stats.adelaide.edu.au>


    Cohen, J. (1992).  A power Primer. Psychological Bulletin, 112,
      115-159.

ps.  Yes, only five pages!
Newsgroups: bit.listserv.stat-l
From: dclason@dante.nmsu.edu (Dennis Clason)
Subject: Re: tests for variance homogeneity
Organization: New Mexico State University, Las Cruces, NM
Date: Wed, 26 Aug 1992 20:12:32 GMT

In article <STAT-L%92082512373559@VM1.MCGILL.CA> BSAB604@UTXVM.BITNET writes:
>Stat-L'ers:
>
>    I am analyzing data from a three-factor field experiment
>with replication.  The residuals from the ANOVA model (computed
>with SAS's PROC GLM) seem fairly well-behaved in my Q-Q plot.
>Now, I need to assess the validity of the homogeneous variance
>assumption.
>
God, I hate effects models!  If you think about the 
experiment as a single classification (one-way) with
a*b*c cells defined by the treatment combinations,
it's clear that (given usual assumptions) the sufficient
statistics for the problem are the cell means and 
variances.  

The short answer is Yes, you can use Levene's test.
You should probably NOT use Bartlett's test or Hartley's
F-max, neither being very robust (to non-normality).

>   What is the best approach to testing the assumption of
>homogeneous variance?  Does anyone use Levene's test in these
>more complicated models?  The SAS code to perform Levene's test
>is trivial for one-way ANOVA...but can it be used on a model
>like this?
>

Use the same SAS code, just set the model up as
CLASS A B C;
MODEL response = A*B*C / noint;


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Newsgroups: bit.listserv.stat-l
Date:         Mon, 31 Aug 1992 06:44:12 EDT
From:         Larry of Layne <LAWORK@SUVM.BITNET>
Subject:      using weighted data in SAS

     I am currently analyzing some financial data that I obtained
from the federal government for my dissertation.  The tape
includes the usual variables one might expect (age of head of
household, number of children, family income and assets) plus a
weight variable.  When the data are used with the weight
variable, the actual sample of 767 is blown up to 8,448,705.
** The documentation and codebook that came with the data state
that the weight variable must be used. **

     The problem with SAS is that when statistical tests such as
chi square and gamma are run on the weighted data, they always
turn up as "significant."  I assume that this is because the
weighted sample is so huge and SAS reads the weighted sample size
as if it were the actual one.

     I have tried to deal with this problem by creating a new
weight variable.  For work with this sample, I did this by
dividing B3016 (the original weight variable) by different
numbers until I found one (11015.26) that produced a weighted
total in the frequency tables that is identical to the actual one
of 767.  This "solution" involved guesswork and interpolation on
my part and since using weighted data is not uncommon, there
must be a more precise way of addressing the problem in SAS!

     Can anyone suggest how I might go about correcting for the size
of the weighted sample so that all of the statistics I obtain
from SAS will be accurate?

     Thanks for any help!

 --Larry Layne,   Computing Services,       Syracuse University --
 --120 Hinds Hall, Syracuse, NY 13244 USA      (315)443-2196    --
 --Bitnet: LAWORK@SUVM       Internet: LAWORK@suvm.syr.edu      --
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X-Acknowledge-To: <CASSELL@UNCVM1>
Newsgroups: bit.listserv.stat-l
Date:         Thu, 3 Sep 1992 06:55:57 -0400
From:         Jim Cassell <cassell%uncvm1.bitnet@UTCS.UTORONTO.CA>
Subject:      Re: election polls
X-To:         "STATISTICAL CONSULTING" <STAT-L@VM1.MCGILL.CA>
              2 Sep 1992 14:52:12 GMT from
              <jerry%NUTMEG.HNRC.TUFTS.EDU@VM1.MCGILL.CA>

On Wed, 2 Sep 1992 14:52:12 GMT Jerry Dallal said:
>You might take a look at Wheeler, Michael (1976), "Lies, Damn Lies, and
>Statistics:  The Manipulation of Public Opinion in America."  New York:
>Liveright.
>
You might also look through past issues of PUBLIC OPINION QUARTERLY
for research on this topic.

Jim

-------------------------------------------------------------------------
Jim Cassell                                    CASSELL@UNCVM1.OIT.UNC.EDU
Institute for Research in Social Science       CASSELL@UNCVM1.BITNET
University of North Carolina-Chapel Hill       Phone:  919-962-0782
Chapel Hill, NC  27599-3355                    Fax:    919-962-4777
-------------------------------------------------------------------------
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Subject: (no subject given)
Newsgroups: bit.listserv.stat-l
Date:         Tue, 25 Aug 1992 19:59:03 -0400
Reply-To:     MEM77362@USACHVM1
From:         MEM77362@USACHVM1.BITNET

HELLO, MY NAMES IS MILENKA COVARRUBIAS AND I'M DEVELOPING GUCH A
BEGINNER'S MANUAL FOR SAS USER.
COULD SOMEOVE SEEDME SOME INFORMATION ABOUT SAS PLEASE?,
ANY THING, I'D LIKE TO GET SOME ANSWERS FROM YOU.
THANK YOU VERY MUCH!!!
BYE

MILENKA COVARRUBIAS ONATE
DEPARTAMENTO DE COMPUTACION
UNIVERSIDAD DE SANTIAGO DE CHILE

MEM77362@USACHVM1
MEM77362@USACHVM1.USACH.CL
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Date:         Thu, 27 Aug 1992 11:01:58 -0500
From:         PARKERRA@VUCTRVAX.BITNET
Subject:      Mai Wing's Solution

I believe that there is a problem with your solution for P(1) [I have not
worked through the other probabilities you give.]  Specifically, the
chance of picking any one specific clone each of N times is (1/8)^N.  But there
are 8 different specific clones that you could have gotten, so that P(1), the
probability of only getting one clone is 8 * (1/8)^N, or (1/8)^(N-1).

Note that if N = 1 P(1) must equal 1.

Bob Parker
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 27 Aug 1992 19:41:23 MET
From:         "J. A. HARTOG" <ABRAMSE@HROEUR1.BITNET>
Subject:      communalities > 1

Dear Networkers,
I am doing a factor analysis on 4 variables with SPSS PC+.
One loading proved to be greater than 1 (1.01 in fact). May be
rounding difficulties. So I tried an other extraction method
(PAF). Extraction stopped because of communalities greater than
one. So I tried another method (ALPHA). Again a loading greater
than one.
Is there someone among you who can shed some light on this
dark matter.
                              Jaap Hartog
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Newsgroups: bit.listserv.stat-l
Date:         Thu, 27 Aug 1992 11:34:36 EDT
From:         J.Laurie.Snell@DARTMOUTH.EDU
Subject:      Wai Ming's solution
X-To:         "STAT-L%MCGILL1.BITNET"
              <STAT-L%MCGILL1.BITNET@dartcms1.Dartmouth.EDU>

Wai Ming's method of solution agrees completely with Brad Mann's answer and
in fact as Pacal said in the famous Pascal Fermat correspondance "Your method
is very sound and is the one which first came to my mind in this research --
I see that truth is the same in Toulouse (Hanover) as in Paris
(VLDNASEQ%HKUCC.BITNET)
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Date:         Tue, 1 Sep 1992 09:00:55 -0400
From:         "Statlib Server" <statlibd%stat.cmu.edu@CARNEGIE.BITNET>
Subject:      New StatLib entries for August 1992
X-To:         glm%ipgaix.unipg.it@CARNEGIE.BITNET,
              outnews+netnews.sci.math.stat%ANDREW.CMU.EDU@CARNEGIE.BITNET,
              s-news%stat.wisc.edu@CARNEGIE.BITNET, stat-l@mcgill1.BITNET

The following is a short list of the new or modified StatLib entries
for August 1992 (until 1 September 1992).

S               gee             # Update
                haerdle         # Update
                date            # Update
                survival3       # Update
                survival3.doc   # Update
                sas.get         # Update
                describe        # Update
                splusnotes.shar # Bill Venables notes about Splus
                sguide          # Brian Ripleys nots about Splus
                sguide.ps1
                sguide.ps2
                ripley          # Functions and datasets used for
                                # teaching at Oxford

s-news          digests 80

datasets        alr             # Update

1993.expo                       # A new collection for the 1993 ASA
                                # Data and Graphics Exposition
1993.expo       index           # Index for the graphics expo

directory       cdn             # Updated index of Canadian Statisticians

general         logist          # A MATLAB function for logistic regression.



To get started using StatLib, send the one line message
        send index
to statlib@lib.stat.cmu.edu

StatLib also has an anonymous FTP facility.
Use ftp to connect to lib.stat.cmu.edu and login with user name
"statlib".  PLEASE send your e-mail address as your password.  This
will enable us to notify you of changes to the software and notify the
contributors about who has requested the software.

A reminder that there is also an archive of SAS related material.
Send the message
        send sas from general
for details about the SAS-L archive.

Thanks to all the contributors -- please keep the contributions
coming!

Mike Meyer, Carnegie Mellon.
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Newsgroups: bit.listserv.stat-l
Date:         Wed, 2 Sep 1992 10:02:00 EDT
From:         "GEOFF SELIG - CONCORDIA U. COMPUTING SERVICES"
              <ILFC594@VAX2.CONCORDIA.CA>
Subject: Re: Equal sample sizes - unequal variances?

Deanna Wild writes:

 > Why does having equal sample sizes mitigate the requirement of equal
 > variances in an ANOVA/t-test?

The SSE term in ANOVA estimates the cell variances.  It is generated, for
all intents and purposes, by _weighting_ the observed cell variability by
the cell size.  With equal cell size, cells with overly large or small
variances contribute an equal but "opposite" share of variability to the
overall SSE value. However, with unequal cell sizes, the cell with the
largest _n_ will contribute more than its share to SSE while the cell with
the smallest _n_ will contribute less.  Should the largest _n_ fall in a
cell with an overly large or overly small variability, the SSE value will
over- or under-estimate the _true_ value for the (overall) cell
variability.  That is to say, SSE will be overly large if the largest _n_
falls in the cell with the largest variability or SSE will be
overly small in the largest _n_ falls in the cell with the smallest _n_.

I hope this helps.

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
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Subject: (no subject given)
Via:           UK.AC.HULL.SEQ;  2 SEP 92 10:51:18 BST
Apparently-To: stat-l@earn.mcgill1
Original-Sender: R.A.Reese@uk.ac.hull.seq
Newsgroups: bit.listserv.stat-l
Date:         Wed, 2 Sep 1992 10:47:50 +0000
From:         Allan Reese <R.A.Reese@SEQ.HULL.AC.UK>

From rar Wed Sep  2 10:47:10 1992 remote from sequent
Subject: Re: Election polls
To: ILFC594@ca.CONCORDIA.VAX2 (GEOFF SELIG - CONCORDIA U. COMPUTING SERVICES)
Date: Wed, 2 Sep 92 10:47:10 WET DST
 U. COMPUTING SERVICES" at Sep 1, 92 2:01 pm
X-Mailer: ELM [version 2.3 PL11]

> actual (population) percentage of voters supporting Clinton would lie in

Before the UK election this April the polls consistently predicted a
Labour victory. This was widely promoted (especially on the BBC) by
a not-very-well-defined meta-analysis that they called the "poll of polls".
Following the Conservative victory there was an enquiry and I think
a report was produced by the Market Research Society. You may be able to
buy a copy (Any other listers with firmer information?).

As far as I recall, the explanation for the failure was put down as the
effect of marginal constituencies where very small local factors meant
that the national picture, as produced from a quota sample, was not
reflected on the day. More cynical observers thought that the Great
British Public had become poll-crazy (cf stir-crazy) and "would lie".
It was also suggested that the Conservative Party used its large resources
and excellent organization to recruit ex-pat voters who could choose where
to register, and the Party thoughtfully registered them in marginal
constituencies where a few hundred votes could change the result. That is
democracy.

--
(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.
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Newsgroups: bit.listserv.stat-l
Date:         Fri, 4 Sep 1992 08:54:37 +0930
From:         Bill Venables <wvenable@STATS.ADELAIDE.EDU.AU>
Subject:      New New S
              2 Sep 1992 21:26:58 GMT
              <9209032151.AA06776@algona.stats.adelaide.edu.au>

>>>>> Naftaly Stramer <naftaly%SUPERGAS.DAZIXCO.INGR.COM@VM1.MCGILL.CA>
>>>>> writes:

Naftaly> Is there someting on the Public Domain for the new S software?

On statlib (ftp to statlib@lib.stat.cmu.edu:S/) there are two introductory
guides that cover some aspects of the new New S stuff: One by Brian Ripley
(sguide) that emphasises doing statistics with S-PLUS and one by Venables
and Smith that looks more at nuts and bolts stuff (splusnotes).  Both are
more-or-less S-PLUS specific.

However there is really no substitute for the official documentation.
___________________________________________________________________________
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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Date:         Fri, 28 Aug 1992 17:47:13 JST
From:         "john.derrick.shillaw" <jds@SAKURA.CC.TSUKUBA.AC.JP>
Subject:      advice sought on language test analysis

[I posted this 3 days ago but I have a feeling that it didn't get
through to the list.  My apologies if it did.]

I'm working on research into the effectiveness of the different English
language tests that we use in the Center where I work and although I
have some experience in statistics, I have three problems where I feel a
little out of my depth.  I'd be very grateful for advice on the
following questions.  For analysis, I have access to SPSS/PC 3.0 and
Testfact (Scientific Software).

1.  I have 4 parallel tests of listening, each administered to a sample
of the total population, each sample balanced for ability.  Each test is
made up of 3 sub-tests identical in format and length.  I have
correlated the 3 sub-tests on each test and corrected for attenuation.
I now want to get the average correlation from the sub-tests (Form A,
part 1 + Form B, part 1 ...) on the 4 tests to get some idea of the
relationship between the sub-tests for the total population.  Is this
valid or is some further correction necessary?

2.  I want to find out if I can reduce the 3 sub-tests to 2 in the final
form and so need to discover which of the sub-tests are the best
predictors of performance on the test.  To this end, a) is it valid to
regress the 3 sub-tests on the test total, and if so, b) how can I get
around the problem that part 2 of the test is only half the number of
items of the other two parts and its contribution to the total will
therefore automatically be reduced? and c) more generally, is there a
way of minimizing the relationship between the dependent and independent
variables?  If regression is out, is there another way I can achieve the
same objective?

3.  If I want to test for unidimensionality of trait on the listening
tests, should a factor analysis be done on the inter-item tetrachoric
correlation matrix, or on the total scores on the 3 sub-tests?

Could somebody please tell me the BITNET address for the EDSTAT-L
listserver.  I subscribed some months back, then set the mail off for
the vacation and now I've lost the address!

Thanks in advance for any help.

======================================================================
John Shillaw
Associate Professor
Foreign Language Center
University of Tsukuba
Ibaraki-ken
Japan
e-mail: jds@sakura.cc.tsukuba.ac.jp
fax:  +81-(0)298-53-6616
======================================================================
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X-Vmsmail-To: SMTP%"STAT-L@VM1.MCGILL.CA"
Newsgroups: bit.listserv.stat-l
Date:         Sun, 23 Aug 1992 13:27:16 -0700
From:         JAMES@UCRAC1.UCR.EDU
Subject:      RE: stats books
X-To:         STAT-L@VM1.MCGILL.CA

very well said, Bob! I alway get irked by those who assume that a couple
of stat courses in stats is all one needs to be a statistician.
james ssemakula

ps: how are your studies going?
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X-Acknowledge-To: <ECHDTS@LSUVM>
Newsgroups: bit.listserv.stat-l
Date:         Fri, 28 Aug 1992 10:06:15 CDT
From:         ECHDTS@LSUVM.BITNET
Subject:      Ref to power calculations

I recently used the following text for a group of epidemiology students:

How many subjects: Statistical power analysis in research
Kraemer and Thiemann
1987
Dept. of Psychiatry and Behavioral Sciences
Stanford University
Stanford California

Daniel Scholl
ECHDTS@LSUVM.LSU.EDU
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Newsgroups: bit.listserv.stat-l
Date:         Tue, 1 Sep 1992 10:20:13 PDT
From:         scowles@CKM.UCSF.EDU
Subject:      Re: Help simulation

orig:  From: Nino Pagliccia <pagli%UNIXG.UBC.CA@ucsfvm.ucsf.edu>
orig:  Subject:      Help simulation
orig:  Hi!  Does anybody know if there is a simulation list?
orig:  I want to enquire about the simulation language DYNAMO.
orig:  Thanks.

there is a newsgroup, comp.simulation, that deals with simulation
topics.


sid cowles               voice: +1-415-476-1582
internet:                uucp:
scowles@ckm.ucsf.edu
scowles@llnl.gov         {backbone}!lll-winken!humpty!scowles
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Date:         Sun, 23 Aug 1992 19:24:43 -0500
From:         PARKERRA@VUCTRVAX.BITNET
Subject:      Job Postings

I support Bill Venables comments, especially indicating subject in the
header.
Bob Parker.
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