```Date: Wed, 3 Oct 2007 07:44:19 -0700 Reply-To: "Ornelas, Fermin" Sender: "SPSSX(r) Discussion" From: "Ornelas, Fermin" Subject: Re: Regression Analysis Comments: To: Björn Türoque In-Reply-To: A<2c55fecd0710030630w1c219279u50f7b8676aaa2f9f@mail.gmail.com> Content-Type: TEXT/plain; charset="iso-8859-1" Whenever you have dummy variables you will always have one dummy less fit into the model. As Hector already pointed out you want to avoid perfect correlation between two predictors. The effect on the missing dummy is collapsed into the constant coefficient. -----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Björn Türoque Sent: Wednesday, October 03, 2007 6:31 AM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: Regression Analysis Matt, This may sound like a dumb question, but did you happen to make two gender variables one for male (values 1 and 0) and one for female (values 1 and ))? Putting both of them in will cause problems, but I don't know if it will cause the problem you are talking about. For your regression you should only use one variable for gender. I only bring this possiblity up because one very simple mistake I often see when people first run regression with recoded dummy variables is that they place all of the dummy variables into the equation, when you need to leave at least one out. On 10/2/07, Matt Donley wrote: > > Hello all, > > My name is Matt, I am a third year psychology student at Monash University > in Melbourne, Australia. > My group is conducting a research project into the relationship between > alcohol consumption and sex-related alcohol expectancies, with gender and > age as moderating factors. In order to obtain results, we are running a > hierarchical multiple regression using SPSS v15.0 but have encountered a > problem. > After centering relevant variables including age and recoding gender using > dummy variables (0,1) and performing interaction terms, we ran the > regression analysis. > First level: sexual expectancies > Second level: age and gender > Third level: interaction terms > We found significant results for enhancement (a sexual expectancy) and > genderXenhancement. We are now calculating an interaction graph and > require unstandardised correlation coefficients but for some reason SPSS > has excluded gender. > > Can anyone please suggest possible solutions as to how we would go about > getting this data from the regression analysis? We have tried recoding the > gender data as suggested by our tutor but we still do not get the data we > need to produce the interaction graph. Any help would be greatly > appreciated as we are really sturggling and running out of time before we > have to hand it in. > > Thank-you in advance, > > Matt > -- Björn Türoque 375 Hudson Street New York, NY 10014-3657 212-366-2000 Some people are just born to rock! NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR CONFIDENTIAL information and is intended only for the use of the specific individual(s) to whom it is addressed. It may contain information that is privileged and confidential under state and federal law. This information may be used or disclosed only in accordance with law, and you may be subject to penalties under law for improper use or further disclosure of the information in this e-mail and its attachments. If you have received this e-mail in error, please immediately notify the person named above by reply e-mail, and then delete the original e-mail. Thank you. ```

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