Jim:
I agree with Radford Neal's comments,
and urge careful reconsideration of the
foundation behind some of the comments
made.
For example, suppose you had a department
in which the citation data were
Males Females
12220 1298
2297 1102
The male with 12220 is, let's imagine, a Nobel Prize
winner. The salaries for the 4 people are
Males Females
156,880 121,176
112,120 114,324
The females approach the dean of science and declare that
there is discrimination against them. They've measured
the labs, and the men have more space. Moreover, they
feel marginalized and depressed, as their status has
been slowly slipping in the department. Moreover, they
are paid less than men of the same age.
Careful examination of mean salary shows that the mean
salaries are 134,500 for men and only 117,750 for women.
With great brouhaha, the administration, without
publishing the above data, declares that there
was a discrimination problem, and it was addressed
by giving both the women a 16,000 raise.
As Radford Neal has pointed out succinctly, the argument about
outliers is irrelevant, and I want to emphasize with this example
that it is irrelevant on numerous levels. First of all,
it is not necessarily clear whether, and in which of several
senses, our Nobel Prize winner is an outlier in his group.
Second, even if he is -- so what? Surely you would not argue
that this means he didn't deserve his salary!
In fact, careful examination of the salary data [never
made public by the administration] together with the
performance data might well have led to the conclusion
that it is the male faculty who are underpaid.
Although, as Dr. Neal pointed out, it is not logically
relevant to the issue, I would like to
explore your notion, echoed without
justification by Rich Ulrich, that the
huge difference in citation performance between
MIT senior men and women might be due
to "one or two outliers."
Take a look at the data again, and tell me
which male data you consider to be outliers
within the male group, and why. For example,
are the men with 2133 and
893 "outliers," or those with 12830 and 11313?
The data for the senior men and women:
12 year citation counts:
Males Females
----------------------
12830 2719
11313 1690
10628 1301
4396 1051
2133 935
893
-----------------------
As for the notion of exploring the relationship between
salary, gender, and performance -- I'd be more than happy
to examine any data that MIT would make available. They
will, of course, not make such data available. It is too
private, they say.
Best regards,
Jim Steiger
--------------
James H. Steiger, Professor
Dept. of Psychology
University of British Columbia
Vancouver, B.C., V6T 1Z4
-------------
Note: I urge all members of this list to read
the following and inform themselves carefully
of the truth about the MIT Report on the Status
of Women Faculty.
Patricia Hausman and James Steiger Article,
"Confession Without Guilt?" :
http://www.iwf.org/news/mitfinal.pdf
Judith Kleinfeld's Article Critiquing the MIT Report:
http://www.uaf.edu/northern/mitstudy/#note9back
Original MIT Report on the Status of Women Faculty:
http://mindit.netmind.com/proxy/http://web.mit.edu/fnl/
On Mon, 12 Mar 2001 08:55:17 -0600, jim clark <[EMAIL PROTECTED]>
wrote:
>Hi
>
>On 12 Mar 2001, Radford Neal wrote:
>> Yes indeed. And the context in this case is the question of whether
>> or not the difference in performance provides an alternative
>> explanation for why the men were paid more (one supposes, no actual
>> salary data has been released).
>>
>> In this context, all that matters is that there is a difference. As
>> explained in many previous posts by myself and others, it is NOT
>> appropriate in this context to do a significance test, and ignore the
>> difference if you can't reject the null hypothesis of no difference in
>> the populations from which these people were drawn (whatever one might
>> think those populations are).
>
>Personally, I am not interested in the question of statistical
>testing to dismiss the alternative explanation being proposed;
>indeed, I suspect that the original claim about gender being the
>cause of salary differences would not stand up very well either
>to statistical tests. But there does seem to me to be more than
>just saying ... "see there is a difference" and that statistical
>procedures would have a role to play. For example, wouldn't the
>strength and consistency of the differences influence your
>confidence that this was indeed the underlying factor? The same
>difference in means due to one or two outliers would surely not
>mean the same thing as a uniform pattern of productivity
>differences, would it? And wouldn't you want to demonstrate that
>there was a significant and ideally strong within-group
>relationship between productivity and salary before claiming that
>it is a reasonable alternative for the between-group differences?
>Or at least, wouldn't that strengthen the case? I appreciate
>that in some domains (e.g., intelligence testing), people are
>reluctant to make inferences about between-group differences on
>the basis of within-group correlations, but that is the basic
>logic of ANCOVA and related methods.
>
>Best wishes
>Jim
>
>============================================================================
>James M. Clark (204) 786-9757
>Department of Psychology (204) 774-4134 Fax
>University of Winnipeg 4L05D
>Winnipeg, Manitoba R3B 2E9 [EMAIL PROTECTED]
>CANADA http://www.uwinnipeg.ca/~clark
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