*/==========================================================
*.
*.
*/                             Select Mail Questionnaires, 
*/            Split Sample by Sex, Renormalize Weights
*/                             Copyright Kelly Shaver, 2006
*/         Questions to ShaverK@cofc.edu.  Please cite.  :-)
*/                                       October 28, 2006
*.
*/==========================================================
*.
*.
*/ Run this only after having cleaned the original data set from 1,261
*/ down to the 1,216 who should be there, using kscleans06.sps 
*.

*/-------------------------------------------------------------------------------------------------------------------
*.
*/  Reduce the sample to cases with returned mail questionnaires.
*.
*/-------------------------------------------------------------------------------------------------------------------
*.
*/ Check survey return dates to identify number of cases with mail
*/ questionnaires returned.
*.
FREQ mailqyr.
*.
*/ Select only those cases with a valid (not missing) mail questionnaire
*/ return year (MAILQYR).  This should reduce the sample to 871.

FILTER OFF.
USE ALL.
SELECT IF(SYSMIS(mailqyr)   ~=  1).
EXECUTE .

CROSSTABS
  /TABLES=autonsu3  BY ncgender
  /FORMAT= AVALUE TABLES
  /CELLS= COUNT .
*.
*/ The counts should be as follows:
*/ Full autonomy (245 females, 235 males, total of 480).
*/ Partial autonomy (41 females, 32 males, total of 73).
*/ Comparison group (173 females, 145 males, total of 318).
*.
*/--------------------------------------------------------------------------------------------------------------
*/
*/   Determine the actual value of the weights after splitting the sample 
*/   into the six categories created by the combination of autonomy (AUTONSU3)
*/   by sex (NCGENDER).
*/---------------------------------------------------------------------------------------------------------------
*.
*/ Create a new variable, SEXAUT to establish 6 cells.  Then use each 
*/ value of SEXAUT successively to determine the value of AUTWT.  
*/ Within each SEXAUT cell, the values of AUTWT will not sum to the 
*/ number of cases in the cell.  Rather, they will sum to a value that must
*/ subsequently be used to renormalize the weights.
*/
*/ SEXAUT will have six values, depending on
*/ the combination of NCGENDER (F=2; M=1) and AUTONSU3
*/ (full=100; partial=200; control=300).
*.
COMPUTE SEXAUT=99.
VARIABLE LABEL
	SEXAUT 'Combination of NCGENDER and AUTONSU3'.
EXECUTE.
MISSING VALUE
	SEXAUT (99).
EXECUTE.
IF ((ncgender = 2) & (autonsu3 = 100)) SEXAUT = 1 .
EXECUTE .
IF ((ncgender = 2) & (autonsu3 = 200)) SEXAUT = 2 .
EXECUTE .
IF ((ncgender = 2) & (autonsu3 = 300)) SEXAUT = 3 .
EXECUTE .
IF ((ncgender = 1) & (autonsu3 = 100)) SEXAUT = 4 .
EXECUTE .
IF ((ncgender = 1) & (autonsu3 = 200)) SEXAUT = 5 .
EXECUTE .
IF ((ncgender = 1) & (autonsu3 = 300)) SEXAUT = 6 .
EXECUTE .
*.
VALUE LABELS SEXAUT
	1	'Female Full'
	2	'Female Partial'
	3	'Female CG'
	4	'Male Full'
	5	'Male Partial'
	6	'Male CG'
	99	'Missing'.
EXECUTE.
*.
*.
*/ Now find the sums of weights for each of the 6 cells.  Filter by successive
*/ values of SEXAUT, so that descriptives are done by individual cells.
USE ALL.
COMPUTE filter_$=(SEXAUT = 1).
VARIABLE LABEL filter_$ 'SEXAUT = 1 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 2).
VARIABLE LABEL filter_$ 'SEXAUT = 2 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 3).
VARIABLE LABEL filter_$ 'SEXAUT = 3 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 4).
VARIABLE LABEL filter_$ 'SEXAUT = 4 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 5).
VARIABLE LABEL filter_$ 'SEXAUT = 5 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 6).
VARIABLE LABEL filter_$ 'SEXAUT = 6 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=autwt
  /STATISTICS=MEAN SUM STDDEV .
*.
FILTER OFF.
USE ALL.
*.
*/-------------------------------------------------------------------------------------------------------------------
*.
*/      Finally, create a corrected mail weight, RETWT, based on the values
*/      obtained above.  For each of the six SEXAUT cells, the general  
*/      formula is [original weight]*[(cell N) / (sum of cell weights)].
*.
*/-------------------------------------------------------------------------------------------------------------------
*.
COMPUTE RETWT = 99.
VARIABLE LABEL RETWT
	'Mail weight corrected by returns and NCGENDER and AUTONSU3'.
IF (SEXAUT=1) RETWT = autwt*(245/186.03).
IF (SEXAUT=2) RETWT = autwt*(41/33.27).
IF (SEXAUT=3) RETWT = autwt*(173/171.53).
IF (SEXAUT=4) RETWT = autwt*(235/293.51).
IF (SEXAUT=5) RETWT = autwt*(32/39.32).
IF (SEXAUT=6) RETWT = autwt*(145/156.92).
MISSING VALUES RETWT (99).
EXECUTE.
*.
*/ Now, finally, check to make sure that the returned questionnaire weight 
*/ value, RETWT, has values for each of the six Sex x Autonomy cells that
*/ sum to the number of individuals in each of the six cells.
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 1).
VARIABLE LABEL filter_$ 'SEXAUT = 1 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 2).
VARIABLE LABEL filter_$ 'SEXAUT = 2 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 3).
VARIABLE LABEL filter_$ 'SEXAUT = 3 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 4).
VARIABLE LABEL filter_$ 'SEXAUT = 4 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 5).
VARIABLE LABEL filter_$ 'SEXAUT = 5 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
USE ALL.
COMPUTE filter_$=(SEXAUT = 6).
VARIABLE LABEL filter_$ 'SEXAUT = 6 (FILTER)'.
VALUE LABELS filter_$  0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE .
DESCRIPTIVES
  VARIABLES=RETWT
  /STATISTICS=MEAN SUM STDDEV .
*.
FILTER OFF.
USE ALL.
*.
*.
*/  At this point, you have renormalized the weights for the Sex X Autonomy cut of
*/  the mail questionnaire data.  These weights will work perfectly ONLY if the 
*/  items of interest to you have been answered by EVERYONE who returned a 
*/  mail questionnaire.  If some of the items have been omitted, the weights should
*/  be re-normalized using the syntax above as a model, but obviously adjusting the
*/  particular numbers in the fraction.