Herman Rubin wrote:
> In article <[EMAIL PROTECTED]>, R. Martin <[EMAIL PROTECTED]> wrote:
> 
>>Art Kendall wrote:
> 
> 
>>><part 2>
>>>If you have re-entered the data, or re-run the experiment, and done very
>>>thorough exploration of the data, you are stuck as a last resort with
>>>doing multiple analyses: including vs excluding the case(s); changing
>>>the values for the case(s) to hotdeck values, to some central tendency
>>>value, or to max or min on the response scale (e.g., for achievement,
>>>personality,  or attitude measures), modeling the specialness of the
>>>particular value, etc.
> 
> 
>>>A very good book on regression is:
>>>Cohen, Jacob, et al (2003) Applied multiple regression/correlation
>>>analysis for the behavioral sciences, third edition.  Mahwah, NJ.
>>>ISBN 0-8058-2223-2
>>>LoC HA31.3 .A67.2003
>>>Outliers are discussed though out the book.
> 
> 
> I have not seen this, but I am greatly suspicious.


The earlier editions of the Cohen & Cohen book describe how 
to add a binary variable that codes for whether or not a 
person/subject has valid data on a given predictor variable. 
  Dave Howell's page has a brief summary and an example:

http://www.uvm.edu/~dhowell/StatPages/More_Stuff/Missing_Data/Missing.html


> 
> BTW, the earliest treatment I know for outliers was for
> astronomy and physics in the 19th century.  There, the
> effect of improperly discarding suspected outliers was
> primarily an affordable loss of efficiency, but biases also
> resulted.  The published values of the speed of light kept
> decreasing until really good observations were made, as the
> first values were high, and outliers were rejected, partly
> using previous experiments.
> 
> 
>>>The best way to deal with outliers is to prevent them through thorough
>>>quality assurance efforts in the data gathering (measurement), data
>>>entry, and exploratory analysis phases of the research.
> 
> 
>>But that takes thinking and work, and statistics is supposed to save
>>us all that effort, right? ;-)
> 
> 
> Anyone who takes this attitude should not try to do
> anything with data.  The results are very likely to be BAD,
> and this IS the case with much of the statistical studies
> in psychology, education, and medicine.
> 
> Until one understands decision problems, it would be wise
> NOT to take any methods courses.

I do believe that Art Kendall had his tongue firmly in his 
cheek when he made that comment about thinking and work.

Cheers,
Bruce
-- 
Bruce Weaver
[EMAIL PROTECTED]
www.angelfire.com/wv/bwhomedir/

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