Re: testing for homoscedasticity in SPSS?

Posted by Jon Peck on Feb 24, 2018; 10:06pm
URL: http://spssx-discussion.165.s1.nabble.com/testing-for-homoscedasticity-in-SPSS-tp5735562p5735570.html

I agree, in general, but if assumption tests are done, I would substantially relax the significance level employed.  Over 40 years ago I wrote a paper on the statistical properties of regression following a preliminary test for autocorrelation, but, alas, nobody was interested.

On Sat, Feb 24, 2018 at 2:55 PM Bruce Weaver <[hidden email]> wrote:

I am not a fan of statistical tests of the assumptions for another test or
procedure.  Such tests often have too little power when n is small and too
much power when n is large.

Rather than testing, you could just estimate your model via UNIANOVA and
allow for heteroscedasticity via the ROBUST sub-command (assuming your SPSS
version is recent enough).  See the link below for details.

https://www.ibm.com/support/knowledgecenter/en/SSLVMB_25.0.0/statistics_reference_project_ddita/spss/base/syn_unianova_robust.html

HTH.



Faiz Rasool wrote
> Hi,
>
> I have a dataset of around 1200 participants. The data is of research
> on attitude   towards, and awareness of environmental issues, and
> environmentally friendly behavior.
>
> I’d like to perform multiple regressionon the data. The textbook I’m
> following is Andy field’s discovering statistics using SPSS. I have
> checked for assumptions of multiple regression, but there is one
> assumption I’m having a difficulty checking. This assumption is the
> assumption of homoscedasticity.  The book suggests using the residuals
> plot to evaluate whether there is homoscedasticity. I’m blind, and I
> cannot see the plot to decide how it looks. I have checked that there
> is no standardized residual value above + or – 3.0. I was wondering
> that is there any test available in SPSs like the cooks distance test
> that can    give me a value that I can use to learn about the scatter
> of the data.
>
> Of course, I can show the data to someone who can see it for me, but
> this is only possible in the next week, and I am hoping that if I can
> check for myself, then, why wait. I’m  also a bit confused about how
> robust is the assumption of homoscedasticity. incase the data do not
> meats this assumption, will I have to use some other method instead of
> multiple regression.
>
> Regards,
> Faiz.
>
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Bruce Weaver
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