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Re: Multiple regression with all dummy variables
Posted:
Dec 12, 2012 11:06 AM


On 11/12/2012 7:10 PM, Bruce Weaver wrote: > On 11/12/2012 5:22 PM, Gary wrote: >> On Tuesday, 11 December 2012 20:20:48 UTC+2, paul wrote: >>> Does a multiple regression with all dummy (indicator) variables make >>> >>> sense? I work at a state university tutoring various basic subjects >  snip  >>> >>> Thanks for any help! >> >> I think you can find some of the argument in >> >> Cohen, J. (1968). Multiple regression as a general dataanalytic >> system. Psychological Bulletin, 70, 426443. >> >> Also Cohen's famous textbook. >> >> Lance >> > > See also Judd & McClelland's book "Data Analysis: A Model Comparison > Approach" if you can find a copy. > > http://psych.colorado.edu/~mcclella/statistics.html >
Oops...I also meant to comment on this bit from the OP:
"But the students are then told that the multiple regression gives more information since we can conclude from the ttests on individual coefficients that silver cars sell for more than the base case (black.)"
Most ANOVA programs have various methods for making pairwise comparisons, and many of them could make the same set of comparisons captured by the ttests in the table of regression coefficients. In the case where each of k1 treatments is compared to a control group, many experimentalists would probably use Dunnett's test, which was designed for that situation.
The point is that the ANOVA program *can* give just as much information (and more) than the info captured by the regression coefficients.
HTH.
 Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/Home "When all else fails, RTFM."



