It is my understanding that when Pearson's Correlation is used, SPSS (v13
and later) will calculate the exact correlation regardless of whether the variables are continuous or dichotomous. So in case of a pair of dichotomous variables, SPSS will "automatically" compute using phi . . . can anyone confirm if this is true or not? Many thanks, Robert |
Stephen Brand
www.statisticsdoc.com Robert, The phi coefficient and Pearson's R are algebraically equivalent when you are computing correlations between dichotomous variables. So, yes, SPSS will give you phi, but not because it "switches" to a different formula, but because the results are the same. Phi and many other formulae are computationally simpler than Pearson's R but yield the same coefficient. Pragmatically, you never need to worry about SPSS giving you something other than the Phi coefficient when you are dealing with a pair of dichotomous variables. HTH, Stephen Brand For personalized and professional consultation in statistics and research design, visit www.statisticsdoc.com -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of Robert Sent: Wednesday, November 15, 2006 5:39 PM To: [hidden email] Subject: Pearson's correlations and dichotomous pairs? It is my understanding that when Pearson's Correlation is used, SPSS (v13 and later) will calculate the exact correlation regardless of whether the variables are continuous or dichotomous. So in case of a pair of dichotomous variables, SPSS will "automatically" compute using phi . . . can anyone confirm if this is true or not? Many thanks, Robert |
I concur.
In addition, even version 1 (1969?) would give the correct answer, not just pc version 13 on. Art Kendall Social Research Consultants Statisticsdoc wrote: >Stephen Brand >www.statisticsdoc.com > >Robert, > >The phi coefficient and Pearson's R are algebraically equivalent when you >are computing correlations between dichotomous variables. So, yes, SPSS >will give you phi, but not because it "switches" to a different formula, but >because the results are the same. Phi and many other formulae are >computationally simpler than Pearson's R but yield the same coefficient. >Pragmatically, you never need to worry about SPSS giving you something other >than the Phi coefficient when you are dealing with a pair of dichotomous >variables. > >HTH, > >Stephen Brand > >For personalized and professional consultation in statistics and research >design, visit >www.statisticsdoc.com > > >-----Original Message----- >From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of >Robert >Sent: Wednesday, November 15, 2006 5:39 PM >To: [hidden email] >Subject: Pearson's correlations and dichotomous pairs? > > >It is my understanding that when Pearson's Correlation is used, SPSS (v13 >and later) will calculate the exact correlation regardless of whether the >variables are continuous or dichotomous. So in case of a pair of >dichotomous variables, SPSS will "automatically" compute using phi . . . >can anyone confirm if this is true or not? > >Many thanks, >Robert > > > >
Art Kendall
Social Research Consultants |
In reply to this post by statisticsdoc
Stephen,
Many thanks for the clarification! Best, Robert -----Original Message----- From: Statisticsdoc [mailto:[hidden email]] Sent: Wednesday, November 15, 2006 5:14 PM To: Robert; [hidden email] Subject: RE: Pearson's correlations and dichotomous pairs? Stephen Brand www.statisticsdoc.com Robert, The phi coefficient and Pearson's R are algebraically equivalent when you are computing correlations between dichotomous variables. So, yes, SPSS will give you phi, but not because it "switches" to a different formula, but because the results are the same. Phi and many other formulae are computationally simpler than Pearson's R but yield the same coefficient. Pragmatically, you never need to worry about SPSS giving you something other than the Phi coefficient when you are dealing with a pair of dichotomous variables. HTH, Stephen Brand For personalized and professional consultation in statistics and research design, visit www.statisticsdoc.com -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of Robert Sent: Wednesday, November 15, 2006 5:39 PM To: [hidden email] Subject: Pearson's correlations and dichotomous pairs? It is my understanding that when Pearson's Correlation is used, SPSS (v13 and later) will calculate the exact correlation regardless of whether the variables are continuous or dichotomous. So in case of a pair of dichotomous variables, SPSS will "automatically" compute using phi . . . can anyone confirm if this is true or not? Many thanks, Robert |
In reply to this post by Robert-126
Dear all,
What is the null hypothesis for a standard REPEATED MEASURES ANOVA? I have 8 speed of adoption variables and I am trying to test if method 1 is different from 2, etc..up to 8. Or are all eight the same? Some form of a difference of means test. So is it correct to assume the null hypothesis for this F-Test is jointly: Ho: M1 = M2 = M3.....= M8 Ha: M1 ne M2 ne M3 ... ne M8. The results look something like this: Would anyone please help interepret these results? Assuming the assumptions of the model were satisfied? Tests of Within-Subjects Effects Measure: MEASURE_1 Source Type III Sum of Squares df Mean Square F Sig. Adoption Sphericity Assumed 56.111 7 8.016 1.041 .403 Greenhouse-Geisser 56.111 2.274 24.675 1.041 .365 Huynh-Feldt 56.111 2.426 23.125 1.041 .368 Lower-bound 56.111 1.000 56.111 1.041 .314 Error(Adoption) Sphericity Assumed 2048.258 266 7.700 Greenhouse-Geisser 2048.258 86.412 23.703 Huynh-Feldt 2048.258 92.204 22.214 Lower-bound 2048.258 38.000 53.902 Tests of Within-Subjects Contrasts Measure: MEASURE_1 Source Adoption Type III Sum of Squares df Mean Square F Sig. Adoption Linear 1.999 1 1.999 .104 .748 Quadratic 6.692 1 6.692 1.018 .319 Cubic 5.824 1 5.824 .932 .341 Order 4 2.735 1 2.735 .375 .544 Order 5 17.496 1 17.496 3.249 .079 Order 6 16.038 1 16.038 3.641 .064 Order 7 5.327 1 5.327 1.103 .300 Error(Adoption) Linear 728.158 38 19.162 Quadratic 249.881 38 6.576 Cubic 237.529 38 6.251 Order 4 277.114 38 7.292 Order 5 204.665 38 5.386 Order 6 167.391 38 4.405 Order 7 183.518 38 4.829 |
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