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 Subject: Nonparametric equivalent to multiple regression? Category: Science > Social Sciences Asked by: gareth981-ga List Price: \$10.00 Posted: 20 Mar 2003 03:00 PST Expires: 19 Apr 2003 04:00 PDT Question ID: 178599
 ```Is there a nonparametric equivalent to multiple regression? I have three predictors which correlate (using Spearman's rho) with my outcome measure of interest. I can't do a multiple regression because the assumptions are violated, but is there a way to find out how much variance the three predictors contribute to the outcome?``` Request for Question Clarification by jeremymiles-ga on 20 Mar 2003 04:58 PST ```Why can't you use OLS regression - do you have ordered categorical (ordinal) dependent variables, or do you have non-normal distributions? (Or some other reason). If the former, the variance doesn't really exist, because the variance is a parametric statistic. However, there are ways around this. Also, what program do you use / would you be able to use? (If any.) jeremymiles-ga``` Request for Question Clarification by jeremymiles-ga on 21 Mar 2003 03:05 PST `Also, what is your sample size?` Clarification of Question by gareth981-ga on 21 Mar 2003 09:01 PST ```Hi I have non-normal distributions on the DV (highly skewed) I'm using SPSS``` ```I am going to give you three possible solutions to your problem, if none of these work, then get back to me and we will find another. 1. First, you might be surprised to hear that regression does not assume that either the DV or the IVs are normally distributed. Rather, it assumes that the residuals are normally distributed. The easiest way to check this is to click on plots from the main regression dialog, and ask for a histogram or a normal probability plot. This might show that you don't have a problem. 2. If you still have a problem, you might be able to transform your DV. If you have positive skew (i.e. lots of low values, not many high, common in reaction time, or finance) then try a log transform - this might solve the problem. If you have negative skew, try a square transform. 3. If your skew is very serious, you could consider recoding into a series of values, e.g. if it is salaries, you might split into 10 groups. 4. If we are desperate, we could try bootstrapping, although this is a bit tricky. 5. If we are more desperate and you have a large sample, we could try a technique that doesn't require normality, or is robust against it. We probably want to avoid this though. That was more than three, wasn't it? Let me know if that works, or doesn't work, and we will have another go. jeremymiles-ga p.s. I can provide some links or recommendations for further reading. Are you based in a university where you have access to a library?``` Request for Answer Clarification by gareth981-ga on 26 May 2003 09:07 PDT `Where can I read about bootstrapping?` Clarification of Answer by jeremymiles-ga on 27 May 2003 03:14 PDT ```There are some syntax files for bootstrapping in SPSS here: http://pages.infinit.net/rlevesqu/SampleSyntax.htm#Bootstrap Two books that I like, which are not too technical are: An introduction to the bootstrap, by Efron and Tibshirani, http://www.amazon.com/exec/obidos/ASIN/0412042312/qid=1054030275/sr=2-1/ref=sr_2_1/002-7345361-6416803 And Bootstrapping, by Mooney and Duval, http://www.amazon.com/exec/obidos/tg/detail/-/080395381X/qid=1054030275/sr=1-10/ref=sr_1_10/002-7345361-6416803?v=glance&s=books```  