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Date:         Thu, 15 Jun 2006 11:36:45 -0400
Reply-To:     Statisticsdoc <statisticsdoc@cox.net>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Statisticsdoc <statisticsdoc@cox.net>
Subject:      Re: Logistic regression help
Comments: To: Lou <charl_bean@YAHOO.CO.UK>
Content-Type: text/plain; charset=utf-8

Keith Starborn www.statisticsdoc.com

Dear Lou,

Categorizing continuous variables into categorical variables can result is a considerable loss of statistical power because the test for the categorized version of the variable uses more degrees of freedom that the test for the continuous variable. In addition, categorizing a continuous variable can result in a loss of predictive information.

HTH,

KS

---- Lou <charl_bean@YAHOO.CO.UK> wrote: > Dear list > > I am trying to carry out a logistic regression analysis and have a quick > question with regards to the best way to input my independent variables. > I have three input variables: ethnicity (5 groups), age and deprivation > score. Although age and deprivation score are continuous variables, I > have also been asked to split them into groups (4 for age and 5 for > deprivation) which are pre-determined by previous work on this subject > matter. The dependent variable is simply whether or not a person took a > particular test. > > I have tried generating models both with the age and deprivation variables > as they are and also with the new categorical age and deprivation > variables. However, when looking at interaction terms, I find that the > interaction between age and deprivation is significant when they are input > as the continuous variables but not significant when I used the > categorical versions. Why would this happen? Furthermore, which is the > best way to go? I have read information on logistic regression until my > head hurts, but still don’t feel completely satisfied as to how I should > determine the best model possible. > > Any advice would be appreciated please! > > Thanks > > Lou

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