Diff for "FAQ/WilliamsSPSS" - CBU statistics Wiki
location: Diff for "FAQ/WilliamsSPSS"
Differences between revisions 4 and 5
Revision 4 as of 2006-07-11 15:07:03
Size: 2059
Editor: pc0082
Comment:
Revision 5 as of 2006-07-11 15:08:14
Size: 2090
Editor: pc0082
Comment:
Deletions are marked like this. Additions are marked like this.
Line 18: Line 18:
set format f10.5.
DATA LIST free
/r12 r13 r23 nsize.
BEGIN DATA
.50 .32 .65 50
.59 .31 .71 30
.80 .72 .89 26
END DATA.
 set format f10.5.
 DATA LIST free
 /r12 r13 r23 nsize.
 BEGIN DATA
 .50 .32 .65 50
 .59 .31 .71 30
 .80 .72 .89 26
 END DATA.
Line 27: Line 27:
***************macro and macro call**************
**** tests if rxy=rvy and outputs a t-statistic plus one and two-tailed p-values
 ***************macro and macro call**************
 **** tests if rxy=rvy and outputs a t-statistic plus one and two-tailed p-values
Line 30: Line 30:
define williams (rxy = !tokens(1)  define williams (rxy = !tokens(1)
Line 35: Line 35:
COMPUTE #diffr = !rxy - !rvy.  COMPUTE #diffr = !rxy - !rvy.
Line 37: Line 37:
COMPUTE #detR = (1 - !rxy **2 - !rvy**2 - !rxv**2)+ (2*!rxy*!rxv*!rvy).
*Calculate (rxy + rvy)^2 .
COMPUTE #rbar = (!rxy + !rvy)/2.
 COMPUTE #detR = (1 - !rxy **2 - !rvy**2 - !rxv**2)+ (2*!rxy*!rxv*!rvy).
 *Calculate (rxy + rvy)^2 .
 COMPUTE #rbar = (!rxy + !rvy)/2.
Line 41: Line 41:
* Calculate numerator of t statistic.
COMPUTE #tnum = (#diffr) * (sqrt((!n-1)*(1 + !rxv))).
 * Calculate numerator of t statistic.
 COMPUTE #tnum = (#diffr) * (sqrt((!n-1)*(1 + !rxv))).
Line 44: Line 44:
COMPUTE #tden = sqrt(2*((!n-1)/(!n-3))*#detR + ((#rbar**2) * ((1-!rxv)**3))).  COMPUTE #tden = sqrt(2*((!n-1)/(!n-3))*#detR + ((#rbar**2) * ((1-!rxv)**3))).
Line 46: Line 46:
COMPUTE t= (#tnum/#tden).
COMPUTE df = !n - 3.
 COMPUTE t= (#tnum/#tden).
 COMPUTE df = !n - 3.
Line 49: Line 49:
* Evaluate the value of the t statistic.
* against a t distribution with n - 3 degrees if freedom for.
* statistical significance.
COMPUTE p_1_tail = 1 - CDF.T(abs(t),df).
COMPUTE p_2_tail = (1 - CDF.T(abs(t),df))*2.
 * Evaluate the value of the t statistic.
 * against a t distribution with n - 3 degrees if freedom for.
 * statistical significance.
 COMPUTE p_1_tail = 1 - CDF.T(abs(t),df).
 COMPUTE p_2_tail = (1 - CDF.T(abs(t),df))*2.
Line 55: Line 55:
* Print the results.
LIST t df p_1_tail p_2_tail.
exe.
!enddefine.
 * Print the results.
 LIST t df p_1_tail p_2_tail.
 exe.
 !enddefine.
Line 60: Line 60:
*********************  *********************
Line 62: Line 62:
williams rxy=r12 rvy=r13 rxv=r23 n=nsize.  williams rxy=r12 rvy=r13 rxv=r23 n=nsize.

A variable in common (overlap) e.g. of form r(W,X) = r(W,Z).

A test for this comparison goes under various names the Williams test, Williams-Hotelling or Hotelling test.

An example of its use together with syntax is given below. Just cut and paste into a SPSS syntax window to use. You can also use the Williams-Hotelling test by typing equalcor at a UNIX prompt on a CBU machine.

* Dependent Correlation Comparison Program. * Compares correlation coefficients from the same sample. * See Cohen & Cohen (1983), p. 57. * Sam Field, sfield@mail.la.utexas.edu, March 1, 2000.

******** this input is inputted in the macro call at end of this syntax********* * Three pairs of correlations to compare*****

  • set format f10.5. DATA LIST free /r12 r13 r23 nsize. BEGIN DATA
  • 50 .32 .65 50
  • 59 .31 .71 30
  • 80 .72 .89 26 END DATA.
  • **************macro and macro call**************
  • *** tests if rxy=rvy and outputs a t-statistic plus one and two-tailed p-values define williams (rxy = !tokens(1)
    • /rvy = !tokens(1) /rxv = !tokens(1) /n = !tokens(1)).
    COMPUTE #diffr = !rxy - !rvy. COMPUTE #detR = (1 - !rxy **2 - !rvy**2 - !rxv**2)+ (2*!rxy*!rxv*!rvy).
  • Calculate (rxy + rvy)^2 . COMPUTE #rbar = (!rxy + !rvy)/2.
  • Calculate numerator of t statistic. COMPUTE #tnum = (#diffr) * (sqrt((!n-1)*(1 + !rxv))). COMPUTE #tden = sqrt(2*((!n-1)/(!n-3))*#detR + ((#rbar**2) * ((1-!rxv)**3))). COMPUTE t= (#tnum/#tden). COMPUTE df = !n - 3.
  • Evaluate the value of the t statistic.
  • against a t distribution with n - 3 degrees if freedom for.
  • statistical significance. COMPUTE p_1_tail = 1 - CDF.T(abs(t),df). COMPUTE p_2_tail = (1 - CDF.T(abs(t),df))*2.
  • Print the results. LIST t df p_1_tail p_2_tail. exe. !enddefine.
  • ******************** williams rxy=r12 rvy=r13 rxv=r23 n=nsize.

None: FAQ/WilliamsSPSS (last edited 2021-04-09 11:33:29 by PeterWatson)