A week or so ago I suggested the following: "Some of those who think that estimation of the size of effects is more important than the testing of a nil hypothesis of no effect argue that we would be better served by reporting a confidence interval for the size of the effect. Such confidence intervals are, in my experience, most often reported in terms of the original unit of measure for the variable involved. When the unit of measure is arbitrary, those who are interested in estimating the size of effects suggest that we do so with standardized estimates. It seems to me that it would be useful to present confidence intervals in standardized units." This suggestion was not well received by this group. Others have, however, made what appears to be the same suggestion.
While reviewing the materials on the reading list for my stats class this afternoon, I came across the report of the Task Force on Statistical Inference (Wilkinson et al., American Psychologist, August 99, 594-604). This group has made several recommendations regarding how research data should be analyzed and presented in scholarly journals. On page 599 they recommend "Interval estimates should be given for any effect sizes involving principal outcomes," and "If the units of measurement are meaningful on a practical level (e. g. number of cigarettes smoked per day), then we usually prefer an unstandardized measure (regression coefficient or mean difference) to a standardized measure (r or d)." +++++++++++++++++++++++++++++++++++++++++++++++++ Karl L. Wuensch, Department of Psychology, East Carolina University, Greenville NC 27858-4353 Voice: 252-328-4102 Fax: 252-328-6283 [EMAIL PROTECTED] http://core.ecu.edu/psyc/wuenschk/klw.htm ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
