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 data-analytic >> system. Psychological Bulletin, 70, 426-443. >> >> 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 t-tests on individual coefficients that silver cars sell for more than the base case (black.)"
Most ANOVA programs have various methods for making pair-wise comparisons, and many of them could make the same set of comparisons captured by the t-tests in the table of regression coefficients. In the case where each of k-1 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.