* Categorical data analysis.

* Case I:  Comparing sample and population distributions
* Educ distribution same as 10 years ago.
data list free / educ wgt.
begin data.
1 35
2 40
3 83
4 16
5 26
end data.
weight by wgt.


NPAR TEST
  /CHISQUARE=educ  (1,6)
  /EXPECTED=36 34 64 26 34 6
  /STATISTICS  DESCRIPTIVES
  /MISSING ANALYSIS.

********************************************************************.
* Equi-probability model.  Same observed data as before.
NPAR TEST
  /CHISQUARE=educ  (1,6)
  /EXPECTED=EQUAL
  /STATISTICS  DESCRIPTIVES
  /MISSING ANALYSIS.


********************************************************************.
* Case II:  Tests of association.
Data list free / Sex Party Wgt.
Begin data.
1 1 55
2 1 50
1 2 65
2 2 30
End data.
Weight by Wgt.

CROSSTABS
  /TABLES=sex  BY party
  /FORMAT= AVALUE NOINDEX BOX LABELS TABLES
  /STATISTIC=CHISQ
  /CELLS= COUNT EXPECTED .

********************************************************************.
* N-Dimensional tables.

Data list free / sex party race wgt.
begin data.
1 1 1 20
1 1 2  5
1 2 1 20
1 2 2 15
2 1 1 18
2 1 2  2
2 2 1 15
2 2 2  5
end data.
weight by wgt.

* Model of independence.

GENLOG
  party race sex
  /MODEL=POISSON
  /PRINT FREQ
  /PLOT NONE
  /CRITERIA =CIN(95) ITERATE(20) CONVERGE(.001) DELTA(.5)
  /DESIGN party race sex  .

********************************************************************.
* Model of conditional independence.  Same data as above.

GENLOG
  party race sex
  /MODEL=POISSON
  /PRINT FREQ
  /PLOT NONE
  /CRITERIA =CIN(95) ITERATE(20) CONVERGE(.001) DELTA(.5)
  /DESIGN party race sex race*sex  .