HDTenEightyP/NetNews huggingface dataset:
From: SOCLYMAN@MIZZOU1.BITNET
Newsgroups: bit.listserv.stat-l
Subject: Precision Probability for Chi Square statistics
Date: 6 Nov 92 00:55:27 GMT
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  I have a set of chi square statistics (goodness of fit measures)
that I wish to compare.  I have used the PROBCHI function in SAS
(probability = PROBCHI (value, df)) to estimate the probability
of each chi square value.  I've run into the problem that the
function cannot produce a probability value precise enough to
distinguish between the significance of chi square values.
For example,
   chi-square     df      probability (from probchi)
      25.62       1       0.00000
      43.0        3       0.00000
      48.90       4       0.00000
      42.80       5       0.00000

Obviously there's not much difference in the "fit" of these
models, but I would like to be able to distinguish among
them, if possible.
  Does anyone know of a way to make probchi give greater
precision, or of an alternative program, or a *book* or
(heaven forfend!) a formula for *calculating* the differences
myself?

Katherine Lyman
Dept. of Sociology
U. Missouri-Columbia
soclyman@mizzou1
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Date:         Thu, 5 Nov 1992 17:02:45 GMT
From:         Ronan M Conroy <RCONROY@IRLEARN.UCD.IE>
Subject:      rules about keeping research data

CROSS-POSTED STAT-L AND EDSTAT-L - PF it if you've seen in before!

I've had a query from a colleague. She works in a therapy unit.
They collect data on each person they see. Recently they added
to the database a number of items as part of a research project.
There items, together with a machine-assigned subject number,
are exported to the person who is analysing the data.
Questions:
1. The ID number is useful for tracking down missing or dud
information in the datafiles exported to the researcher, and
it isn't linkable to the original record unless you have
access to the original database system. Does this adequately
protect the confidentiality of the clients?

2. Does retaining the information gathered only for research
purposes on the original, administrative database, contravene
any known code of confidentiality or use of research data. The
admin people are anxious to maintain the data there until the
end of the project, in case anything happens to the research
database, or in case a larger research dataset has to be created.
If the data items gathered purely for research are deleted as
soon as a full, cleaned version of the research database is
created, does this cover them against the requirement not to
keep unnecessary data?

3. If an administrative database system like this is set up
to aid a research project, is there any way that you can argue
that ALL the information on it is for research and should be
erased as soon as it has been exported to the researcher?

I would be grateful for any references to published guidelines
addressing these issues, as some strong opinions are being aired
on the subject over here. Much as I would also like the opinions
of my e-friends out there, what I most need is references!

with many thanks

Ronan Conroy                      EMAIL RCONROY@IRLEARN.UCD.IE
Lecturer in biostatistics         Royal College of Surgeons in Ireland
and computing and stuff           Mercer Building, Dublin 2.
                                  (353)-(1)-780200 [fax:780934]
    ---------------------------------
   "Sutor ne ultra crepidam judicaret"
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Date:         Wed, 11 Nov 1992 15:55:00 EST
From:         dkw4@NIOSHE2.EM.CDC.GOV
Subject:      Friedman's Test w/Many Ties

STAT-Lers,

Thanks to everyone (Walter Pirie, Mike Fuller, Tony Dusoir, Matt Zack, and
Tim Green, and anyone else?) who responded to my question of a few weeks
ago.  I asked if anyone knew what happened in Friedman's Test if there were a
LARGE number of ties (measuring pain in body parts, in this case) in each
block.

The consensus seemed to be that a large number of ties reduces the power of
the test.  Also, I received differing advice on how to handle the problem,
but I certainly appreciated all the thoughts.

Lastly, a colleague, who is an Ohio State University graduate, asked Doug
Wolfe his opinion about this situation.

Doug's response follows....

"The Friedman test does tend to be conservative in the presence of lots of
ties.
I would suggest running it anyway--if it rejects you are relatively safe in
declaring significance.  If it does not reject, then I would suggest
dichotomizing the data (as suggested in the memo) and see if the test on this
reduced data set leads to rejection.

If one had the patience, one could generate the permutation distribution for
Friedman's statistic, given the ties configuration. The inference would then
be exact.

Again, good to hear from you.

Doug Wolfe"


Thanks again -

Deanna (Wild)
National Institute for Occupational Safety and Health
Cincinnati, Ohio  USA
Internet: DKW4@NIOSHE2.EM.CDC.GOV
From: byron@OSIRIS.USI.UTAH.EDU (Byron Davis)
Newsgroups: bit.listserv.stat-l
Subject: Re: Outliers
Date: 12 Nov 92 16:01:18 GMT
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU

Bollen and Jackman (1985) "Regression diagnostics: an expository treatment
of outliers and influential cases" SOCIOLOGICAL METHODS AND RESEARCH.
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X-Acknowledge-To: <BONDARI@TIFTON>
Newsgroups: bit.listserv.stat-l
Date:         Thu, 5 Nov 1992 13:31:48 EST
From:         "K. Bondari" <BONDARI@TIFTON.BITNET>
Subject:      Support for Agricultural Statistics as an ASA Section

  ===================================================================
                  Potential Agricultural Statistics
                  Section Seeks Member's Support

      Several members of the American Statistical Association (ASA)
   have expressed an interest in forming a Section centered around
   agricultural statistics.  One of the most vital prerequisites
   to official recognition as a Section is the gathering of
   signatures from 100 ASA full members who would agree to join
   the Section if it were formed.   So far only 95 signatures have
   been collected.   If interested, please sign the petition form
   below and mail it to me as soon as possible.  Please make every
   effort to bring this petition into the attention of those who
   might be interested at your institution.

   ==================================================================

      I, the undersigned member of the American Statistical Association,
   wish to form a Section on Agricultural Statistics, whose broad
   objectives would be to offer a forum to statisticians to present
   and discuss statistical approaches for agricultural research data.
   I recognize that the establishment of a Section will require
   preparation of a suitable charter, annual business meetings,
   selection of officers, and the payment of section dues.


   Signature: __________________________________________________

   Name (please print): _________________________________________

   Daytime Phone: _______________________________________________

   Address: _____________________________________________________

   ______________________________________________________________


   ==================================================================


                                Sincerely,


    *-----------------------------*
     K. Bondari, Professor             E-mail: BONDARI@TIFTON.BITNET
     Statistical & Computer Serv.
     Coastal Plain Expt. Station          Fax: (912)386-7005
     The University of Georgia            Fax: (912)386-3571
     Tifton, GA 31793-0748       
    *-----------------------------*      Phone: (912) 386-3385
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Newsgroups: bit.listserv.stat-l
Date:         Fri, 13 Nov 1992 07:42:44 CST
From:         EJOHNSO3@UA1VM.BITNET
Subject:      Test for assumptions

I would like to know how regularly people on this list test for assumptions.
For example, when a t test assumes a normal distribution and equal variances,
how often do you run a Lilliefor test for normalcy and an F test for the dif-
ference of means? I'm told that it should aways be done, but these tests don't
seem to be a standard part of statistical packages such as SAS, nor do I recall
having seen these tests being mentioned in the methodology of experimental re-
search. Comments, please.

                          --Ed Johnson
                            Dept. of Mass Comm.
                            University of Alabama
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Date:         Mon, 9 Nov 1992 02:59:00 CST
From:         TCAC022@UTXVM.BITNET
Subject:      standard error of r in small sam

---
-------------( Forwarded letter follows )-----------------------
---
Date: Friday, 6 November 1992 11:37am CT
To: STAT-L
From: BILL.KOCH
Subject: standard error of r in small sam

Why not use Fisher's r to z transformation, which is applicable
regardless of the size of N?  In that case, the standard error of
z is equal to 1.0 divided by the square root of (N minus 3).  The
standard error is independent of the size of the correlation
coefficient, so it can also be used to test hypotheses other than
that rho is equal to zero.
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From: DKW0@NIOSHE2.EM.CDC.GOV
Newsgroups: bit.listserv.stat-l
Subject: ANOVA on factor scores
Date: 5 Nov 92 21:25:00 GMT
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Has anyone seen an ANOVA type approach used on factor scores?

That is, you have a number of responses which you collapse into three or four
factors. An analysis of variance would then be run to compare mean factor
scores for EXPOSED and UNEXPOSED workers.   We could also conceivably do a
MANOVA on all the factors simultaneously.   Has anyone done this before?
(The researcher is attempting to mimic an earlier study which used a factor
analysis approach.  The ANOVA on the factor scores would be a new twist.)

Thanks very much for any help.

  David K. Wall
  National Institute for Occupational Safety and Health
  4676 Columbia Parkway, MS R-4
  Cincinnati, OH 45226
  Phone: (513) 841-4331
  Internet:  dkw0@nioshe2.em.cdc.gov
  "If art is communication, then Andy Warhol stutters."  -- me
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Organization: York University
Newsgroups: bit.listserv.stat-l
Date:         Fri, 13 Nov 1992 23:53:27 EST
From:         MCCUBBIN@YORKVM1.BITNET
Subject: Help: Explain Bayes Theorem?

I have statistical background at grad level in social sciences but very rusty,
and never studied Bayes Theorem.  May need it now for modelling of decision-mak
ing under "best interests" model whereby others make treatment decisions on beh
alf of patients.  Basically, interested in estimating distribution of error in
estimating patient preferences.  I have Bayes theorem in stat books, but would
like to here an explanation in English as to what it says.  Thanks folks.

Love & Peace, Michael McCubbin, York U. (Master's prog., Poli Sci.)
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Date:         Sun, 8 Nov 1992 23:46:00 MST
From:         Haiyi Xie <SOCHX@FREUD.SBS.UTAH.EDU>
Subject:      LISREL AND NON-MORMALITY

1. In structural equation modeling, if multinormality assumption is not held,
what is an appropriate estimation method and an appropriate way to assess the
goodness of fit?

2. To construct the composite variable, can I simply add up several original
variables?  (I have small cases and Factor analysis did not give me expected
results).

H.Y. Xie
Department of Sociology
University of Utah
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Date:         Wed, 11 Nov 1992 13:05:00 EST
From:         DKW0@NIOSHE2.EM.CDC.GOV
Subject:      ANOVA on factor scores

Thanks to everyone who responded to my question about doing ANOVA's on factor
scores.   That list would include Karl Wuensch, Tim Dorcey, Francis C. Dane,
Dallas E. Johnson, and Wolfgang L. Grichting.  My apologies if I've omitted
anyone.

I now am a lot more comfortable using that approach and am also more aware of
the limitations...as in not using a MANOVA for orthogonal factors.

Thanks very much again.

Sincerely,

  David K. Wall
  National Institute for Occupational Safety and Health
  4676 Columbia Parkway, MS R-4
  Cincinnati, OH 45226
  Phone: (513) 841-4331
  Internet:  dkw0@nioshe2.em.cdc.gov
  "If art is communication, then Andy Warhol stutters."  -- me
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Newsgroups: bit.listserv.stat-l
Date:         Wed, 11 Nov 1992 10:01:12 EST
From:         Kamala V Mukunda <KVMWORK@SUVM.BITNET>

I apologize if this is a question that has been asked before: but can anyone
suggest a good introductory book for cluster analysis? This will be used
in conjunction with the PROC CLUSTER chapter of a SAS manual.
Thanks a lot,
Kamala V. Mukunda
KVMWORK@SUVM.ACS.SYR.EDU
KVMWORK@SUVM.BITNET
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Date:         Thu, 12 Nov 1992 08:53:44 -0500
From:         g40_jrg1@GRAY.WHOI.EDU
Subject:      ANOVA ON FACTOR SCORES

From:   GRAY::G40_JRG1     12-NOV-1992 08:55:07.87
To:     AQUA::"STA-L@VM1.MCGILL.CA"
CC:     G40_JRG1
Subj:   ANOVA ON FACTOR SCORES

I must comment on the recent discussions.

MANOVA would be appropriate, even on orthogonal rotated factors.  Consider
that the pooled correlation between two factors could be 0 (orthogonal) while
the correlation in each of two categories were significant of opposite sign.
The categories did not enter into the extraction of the factors.

If the number of variables, v, is much greater than the number of factors, p,
then MANOVA on the factors rather than on the original variables has a
an advantage.  The discriminant function used to maximize the differences across
categories will be sharper.  That is the confidence on the parameters of the
discriminant function will be narrower, and the resultant f-test will have a
greater power.  This comes at a cost:  some of the variance of the original
variables will have been discarded in the v-p factors that were not kept.
The MANOVA test of differences across categories really tests the hypothesis
that the v variables were sampled from a single p-variate normal population
with a given correlation structure (orthogonal or what have you).  I am
thinking purely in terms of principal component factor extraction.  I don't
know if these comments hold for other factor extractions.

Julien R Goulet Jr
JGOULET@GRAY.WHOI.EDU
National Marine Fisheries Service
Narragansett RI
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Via:         UK.AC.HULL.SEQ;  6 NOV 92 10:56:05 GMT
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Date:         Fri, 6 Nov 1992 10:50:45 WET
From:         "R.A.Reese" <R.A.Reese@SEQ.HULL.AC.UK>
Subject:      Re: rules about keeping research data

> 1. The ID number is useful for tracking down missing or dud
> information in the datafiles exported to the researcher, and
> it isn't linkable to the original record unless you have
> access to the original database system. Does this adequately
> protect the confidentiality of the clients?

Under UK law, the Data Protection Act applies to ANY personal information
held on a COMPUTER, relating to a living identifiable individual.  In other
words, it doesn't matter how many coding or encryption schemes you have
to go through, nor whether the real identities are not on the computer.
So the DP Act applies and you would have to register and declare the
content and use of the data.

Note also that you don't have to store names and addresses to identify
individuals. That's why the Census data are not made available as less
than district aggregates - "the head of the household that has 8 members
and a house with 6 bedrooms" might uniquely identify someone.
From: tarkkone@klaava.Helsinki.FI (Lauri Tarkkonen)
Newsgroups: bit.listserv.stat-l
Subject: Re: guttmann scales
Date: 7 Nov 92 07:09:42 GMT
Organization: University of Helsinki

In <STAT-L%92110617193393@VM1.MCGILL.CA> ZUMBO@ACADVM1.UOTTAWA.CA (Bruno D. Zumbo) writes:

>     We have developed a clinical questionnaire for head injured
>patients on their social and adaptive functioning.  The
>questionnaire consists of 6 or 7 major scales, each represented by
>8 to 12 questions.  Each scale, e.g. "taking intiative" or "being
>organized", is Guttman scaled more or less so that there is some
>sort of threshold for problem behaviour depending on how impaired
>the patient is.  But instead of YES/NO responses, we supply a
>Likert scale.  We then adjust the polarity appropriately and simply
>add up the scores on the 1 to 5 ratings.  We have found the results
>useful and have externally validity in appropriate places.  Now, I
>have an honours student doing a project on checking some
>psychometric features (something new for me), such as doing a
>proper item analysis, seeing whether the Guttman scaling is as we
>hoped, factor analysis, etc.  The reason I am writing is that I
>have not been able to find any relevant discussant in psychometry
>books on such a type of test with Likert ratings on Guttman scales.
>Do you know of any? and is there anything I should be aware of?

There is a problem in trying to fit a Guttman scale and factor analysis
in the same package. In Factor analysis you think that there are one
or more factors affecting the variables observed, the strong correla-
tions are caused by common factors. In a Guttman scale the items by
structure cannot correlate very well:

                 items
observations  i1  i2  i3    ....  ip
        o1     0   0   0    ....   0
        o2     0   0   0           1
         .     .   .   .    ....   1
         .     .   .   .    ....   1
         .     .   .   1    ....   1
        on-1   0   1   1           1
        on     1   1   1           1

The correlation of items  i1 and ip is -1 but the variance is about 0.
The correlation of first and last items to the middle items are about 0.

If i draw a picture of the situation:

                               median item
                             ^
                             !
                             !
                             !
                        i1 <-!->  in

The variance of the median iten is largest and the variance of the first
and last item is smallest, aproaching nill. The direction you are supposed
to separate your objets has almost no variance, the main variance is ortho-
gonal to this. So Guttman leads you into trouble.

- Lauri Tarkkonen
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Date:         Wed, 11 Nov 1992 08:24:56 EST
From:         Frank Dane <FDANE@UGA.BITNET>
Subject:      Re: repeated measures categorical data

SAS's PROC CATMOD includes the ability to analyze repeated measures
categorical data.  Design elements among the repeated measures can
also be established.

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
Newsgroups: bit.listserv.stat-l
From: H.Edwards@massey.ac.nz (H. Edwards)
Subject: Re: ANOVA & Kruskal-Wallis details
Keywords: ordered alternatives, multiple comparisons, testing vs. estimation
Organization: Massey University, Palmerston North, New Zealand
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Date: Fri, 6 Nov 92 01:22:08 GMT

Re: ordered alternatives mu1 <= mu2 <=  .. <= muk.

You may also want to look at:  Hayter, AJ (1990) "A one-sided studentised
range test for testing against a simple ordered alternative", J.Amer.Stat.
Assoc. 85, 778-785, which shows how the test can be inverted to give
simultaneous one-sided confidence intervals for pairwise differences
mu(i) - mu(j), i < j.  This allows one to make useful inferences about
the sizes of ordered differences.

Another useful reference if you are only interested in estimating differences
(as opposed to testing for them) is Bofinger, E (1985), "Multiple comparisons
and Type III errors", J.Amer.Stat. Assoc. 80, 433-437, replacing Bofinger's
approximate o statistic with Hayter's more accurate h statistic.  A Type III
error occurs when a test concludes that mu(i) > mu(j) (for some i,j different)
when in fact  mu(i) < mu(j).  Personally I don't see much point in protecting
P(Type I error|H0) if you know that the equality hypothesis is untrue anyway,
but that's another chapter in the long-running multiple comparisons saga .

-- 


Howard Edwards				Ph: (64)(6)3569099 ext 8331
Dept of Statistics			Fax: (64)(6)3505611
Massey University			email: H.Edwards@massey.ac.nz
Palmerston North
NEW ZEALAND
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Date:         Mon, 9 Nov 1992 08:56:15 -0700
From:         "(Byron Davis)" <byron@OSIRIS.USI.UTAH.EDU>
Subject: Re: ANOVA on factor scores

When you have multiple dependent variables which you wish to do an ANOVA on,
I would use MANOVA to approach the problem rather than generate factor scores
and then do ANOVAs on them.

Running MANOVA with multiple dependent variables creates a weighted linear
combination based on a discriminant function (one that tries to maximize
differences of the grouping variable) and then performs an omnibus test on the
resulting WLC. This gives you a single F test to see if there exists in the
data a significant difference. If you find that this mulitivariate F shows
differences by the grouping variable, you can proceed to the individual
ANOVAs and the correlations between the WLC and each of the dependent variables
to further define where the differences originate.

Byron L. Davis
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Date:         Fri, 6 Nov 1992 15:59:10 EST
From:         Frank Dane <FDANE@UGA.BITNET>
Subject:      Re: ANOVA on factor scores
              5 Nov 1992 16:25:00 EST from <DKW0@NIOSHE2.EM.CDC.GOV>

I have used ANOVA on factor scores (estimates) in several different
studies (none of which have yet seen publication).  Depending on
the rotation used, MANOVA would not be appropriate; an orthogonal
rotation produces uncorrelated scores (MANOVA inappropriate) but
an oblique rotation might produce correlated scores (MANOVA appropriate).

As far as I know, there is no statistical / mathematical reason for
not usingANOVA on factor scores, assuming the theoretical / design
basis for the analysis is sensible.

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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Date:         Sat, 7 Nov 1992 14:13:59 -0600
From:         COROZCO@UADECVMS.SAL.UADEC.MX
Subject:      Lisrel analysis (software)

I will appreciate information about brand name of software to perform Lisrel
Analysis. I have statistical references on books, but since I am working on
educational research, I need to find a software to analize the data.

Thank you,

Carmen Orozco
Facultad de Ciencias de la Educacion y Humanidades
Universidad Autonoma de Coahuila
Mexico