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Date:         Mon, 11 May 2009 16:14:03 +0200
Reply-To:     Marta García-Granero <mgarciagranero@gmail.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Marta García-Granero <mgarciagranero@gmail.com>
Subject:      Re: Regression Analysis
In-Reply-To:  <276732.66243.qm@web82808.mail.mud.yahoo.com>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed

Caroline Davis wrote: > Hello list! > > I would like to perform a regression analysis for 4, however here are > my constraints: > > Var 1: Prototype rating (Likert scale 1 to 5), not normally distributed > Var 2: Influence rating (Likert scale 1 to 5), not normally distributed > Var 3: Accuracy (binary 0 or 1) > Var 4: Score on test (normally distributed). > > The goal is to determine how well Var 1-3 predict Var 4. Is a > regression analysis the best way to get at this question? It seems > tricky, because Var 1 & 2 are not normally distributed. Normality of the IV (or "predictor variables") is NOT a condition for linear regression. Anyway, check for linearity in the response to your Likert predictors. Binary (0/1 coded) variables are also OK, you don't have to worry about Accuracy (Var 3).

> If I do a regression analysis for the accuracy and test variables, > should it be a binary logistic regression, with accuracy as the > dependent variable and score as the independent variable?

Then you would be predicting Accuracy as a function of the other variables, including Var 4 (clearly not your goal). > > Thanks for any suggestions you may have. 1) Is sample size enough? (you don't mention it). As a rule of thumb, there should be 10 to 20 cases for each IV (30 to 60 cases for your study) 2) Plot (scatter plot) Var 4 against Var1 first, then Var 4 against Var 2. Visually check for for departures from linearity. Recode Var 1 and/or Var 2 if necessary. 3) Are there any missing values? A listwise deletion might lower your sample size a lot.

HTH, Marta García-Granero

-- For miscellaneous SPSS related statistical stuff, visit: http://gjyp.nl/marta/

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