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Date:         Thu, 15 Jun 2006 15:12:19 -0400
Reply-To:     Lou <charl_bean@YAHOO.CO.UK>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Lou <charl_bean@YAHOO.CO.UK>
Subject:      Re: Logistic regression help
Content-Type: text/plain; charset=ISO-8859-1

Dear Keith,

Thanks for your advice which was very helpful. I feel a bit stuck as to know what to do about this really. My boss (who knows rougly zero about statistics) is insisting that I categorise these variables since I am comparing results with a previous report which did the same. Does it take meaning away from the analysis if I discuss results obtained using the original continuous variables and then discuss results separately using the categorised versions (i.e. generate two separate models)? Not sure if this really defies logic too much and how I would justify this in the final report. Although I have a lot to learn in this field, the report that this work is being based on has a lot of dubious findings with regards to the stats, so I'm very keen to ensure that the one I produce is accurate!!

Many thanks,

Lou

On Thu, 15 Jun 2006 11:36:45 -0400, Statisticsdoc <statisticsdoc@cox.net> wrote:

>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 > >-- >For personalized and experienced consulting in statistics and research design, visit www.statisticsdoc.com


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