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. 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. -- This address is for information only. I do not claim that these views are those of the Statistics Department or of Purdue University. Herman Rubin, Department of Statistics, Purdue University [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
