Pearson's correlations and dichotomous pairs?

[Robert-126]

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

[statisticsdoc]

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]

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
>
>
>
>

[Robert Edgell]

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

[Sibusiso Moyo]

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