Date: Dec 12, 2012 11:06 AM
Author: Bruce Weaver
Subject: Re: Multiple regression with all dummy variables
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.

HTH.

--

Bruce Weaver

bweaver@lakeheadu.ca

http://sites.google.com/a/lakeheadu.ca/bweaver/Home

"When all else fails, RTFM."