“I have a data file on which I’d like to carry out several regression analyses. I have four dependent variables, v1 through v4. The independent variables (v5 through v14) are the same for all analyses. How can I carry out these four analyses in an efficient way that would also work for 100 dependent variables?”
SPSS Python Syntax Example
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*Run REGRESSION repeatedly over different dependent variables. begin program. import spss,spssaux dependent = ‘v1 to v4’ # dependent variables. spssSyntax = ” # empty Python string that we’ll add SPSS REGRESSION commands to depList = spssaux.VariableDict(caseless = True).expand(dependent) # create Python list of variable names for dep in deplist: # “+=” (below) concatenates SPSS REGRESSION commands to spssSyntax spssSyntax += ”’ REGRESSION /MISSING PAIRWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT %s /METHOD=STEPWISE v5 to v14. ”’%dep # replace “%s” in syntax by by dependent var print spssSyntax # prints REGRESSION commands to SPSS output window end program.*If REGRESSION commands look good, have SPSS run them. begin program. spss.Submit(spssSyntax) end program. |
Description
- That this syntax uses Python so you need to have the SPSS Python Essentials installed in order to run it;
- The syntax will simply run a standard SPSS regression analysis analysis over different dependent variables one-by-one;
- Except for the occurrence of
%s, Python will submit to SPSS a textbook example of regression syntax generated by the GUI. It can be modified as desired. - The TO and ALL keywords may be used for specifying the dependent and independent variables. The entire specification is enclosed in quotes.
- As a test file for this solution, you could use supermarket.sav.
