1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 *(Q) how to perform factor analysis with Spearman correlation thru a matrix. *(A) Posted to SPSSX-L list on 2002/02/05 by Marta Garcia-Granero. * First, some dummy data to work with. INPUT PROGRAM. - VECTOR X(10). - LOOP #I = 1 TO 100. - LOOP #J = 1 TO 10. - COMPUTE X(#J) = UNIFORM(5). - END LOOP. - END CASE. - END LOOP. - END FILE. END INPUT PROGRAM. execute. * Creation of a correlation matrix suitable for FACTOR. * It's a hybrid of two different files. * If you stop and look at every step, you will see what the syntax does. * A folder called temp must exist in the default drive. * Original matrix files: * Kendall correlation coeficients can also be used * (for ordinal variables), instead of Spearman. CORRELATIONS /VARIABLES=x1 TO x10 /MATRIX=OUT('c:\\temp\\corr1_.sav') /MISSING=PAIRWISE . NONPAR CORR /VARIABLES=x1 TO x10 /PRINT=SPEARMAN /MATRIX=OUT('c:\\temp\\corr2_.sav') /MISSING=PAIRWISE . * Files manipulation. GET FILE='c:\\temp\\corr2_.sav'. EXECUTE . SELECT IF(rowtype_ ~= 'N'). EXECUTE . RECODE rowtype_ ('RHO'='CORR') . EXECUTE . SAVE OUTFILE='c:\\temp\\corr2_.sav'. GET FILE='c:\\temp\\corr1_.sav'. EXECUTE . SELECT IF(\$casenum<4). EXECUTE . ADD FILES /FILE=* /FILE='c:\\temp\\corr2_.sav'. EXECUTE. * Final matrix (suitable as input for FACTOR). SAVE OUTFILE='c:\\temp\\c_matrix.sav'. * Now, factor analysis: * I have selected the options I normally use * (KMO index, MSA, scree plot, Bartlett test, * Varimax rotation with sorted and cleaned loadings) * Modify them if needed. FACTOR /MATRIX=IN(cor='c:\\temp\\c_matrix.sav') /ANALYSIS x1 TO x10 /PRINT KMO AIC EXTRACTION ROTATION /FORMAT SORT BLANK(0.4) /PLOT EIGEN /CRITERIA MINEIGEN(1) ITERATE(25) /EXTRACTION PC /CRITERIA ITERATE(25) /ROTATION VARIMAX /METHOD=CORRELATION . * Of course, these random data are uncorrelated, and no good for factor analysis, * That's why KMO and MSA are low and Bartlett test is not significant.
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