DATASET ACTIVATE DataSet1.
RECODE q2_1 (9=SYSMIS) (ELSE=Copy) INTO q2_1a.
EXECUTE.

RECODE q2_2 (9=SYSMIS) (ELSE=Copy) INTO q2_2a.
EXECUTE.

RECODE q2_3 (9=SYSMIS) (ELSE=Copy) INTO q2_3a.
EXECUTE.

RECODE q2_4 (9=SYSMIS) (ELSE=Copy) INTO q2_4a.
EXECUTE.

RECODE q2_5 (9=SYSMIS) (ELSE=Copy) INTO q2_5a.
EXECUTE.

RECODE q2_6 (9=SYSMIS) (ELSE=Copy) INTO q2_6a.
EXECUTE.

RECODE q2_7 (9=SYSMIS) (ELSE=Copy) INTO q2_7a.
EXECUTE.

RECODE q2_8 (9=SYSMIS) (ELSE=Copy) INTO q2_8a.
EXECUTE.

RECODE q2_9 (9=SYSMIS) (ELSE=Copy) INTO q2_9a.
EXECUTE.


FACTOR
  /VARIABLES q2_1a q2_2a q2_3a q2_4a q2_5a q2_6a q2_7a q2_8a q2_9a
  /MISSING LISTWISE 
  /ANALYSIS q2_1a q2_2a q2_3a q2_4a q2_5a q2_6a q2_7a q2_8a q2_9a
  /PRINT INITIAL KMO EXTRACTION ROTATION
  /FORMAT SORT BLANK(.3)
  /PLOT EIGEN ROTATION
  /CRITERIA MINEIGEN(1) ITERATE(25)
  /EXTRACTION PC
  /CRITERIA ITERATE(25)
  /ROTATION VARIMAX
  /SAVE REG(ALL)
  /METHOD=CORRELATION.

RECODE q2_9a (9=SYSMIS) (ELSE=Copy) INTO nova.
EXECUTE.

COMPUTE nova2=5-q2_9a+1.
EXECUTE.

RECODE q2_9a (5=1) (4=2) (3=3) (2=4) (1=5) (ELSE=SYSMIS) INTO nova.
EXECUTE.

RELIABILITY
  /VARIABLES=q2_1a q2_2a q2_3a
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA
  /STATISTICS=CORR
  /SUMMARY=TOTAL.

RELIABILITY
  /VARIABLES=q2_6a q2_7a q2_9a
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA
  /STATISTICS=CORR
  /SUMMARY=TOTAL.

RELIABILITY
  /VARIABLES=q2_5a q2_8a
  /SCALE('ALL VARIABLES') ALL
  /MODEL=ALPHA
  /STATISTICS=CORR
  /SUMMARY=TOTAL.


DATASET ACTIVATE DataSet1.
COMPUTE index_1=(q2_6a+q2_7a+q2_9a)/3.
EXECUTE.

COMPUTE index_2=(q2_1a+q2_2a+q2_3a)/3.
EXECUTE.

COMPUTE index_3=(q2_5a+q2_8a)/2.
EXECUTE.

CORRELATIONS
  /VARIABLES=FAC1_1 FAC2_1 FAC3_1 index_1 index_2 index_3
  /PRINT=TWOTAIL NOSIG
  /MISSING=PAIRWISE.


*mame vytvorene zavisle promenne (faktory nebo alternativne indexy) k nasledujici vicerozmerne technice - logisticke regresi. 
Je zapotrebi faktory/indexy dichotomizovat (redukovat je do dvou kategorií - moc hodnoty vs malo hodnoty). Takto vytvorenou zavislou promennou budeme vysvetlovat prostrednictvim pohlavi, vzdelani, veku.
 Muzeme vytvorit separovane regreseš podle prislusnosti ke generaci x/y.


DATASET ACTIVATE DataSet1.
RECODE index_3 (1 thru 2.49=1) (2.5 thru 3.49=SYSMIS) (3.5 thru 5=2) (ELSE=SYSMIS) INTO 
    index_3_flexi_dichotomicka.
EXECUTE.

RECODE index_2 (1 thru 2.49=1) (2.5 thru 3.49=SYSMIS) (3.5 thru 5=2) (ELSE=SYSMIS) INTO 
    index_2_flexi_dichotomicka.
EXECUTE.

RECODE index_1 (1 thru 2.49=1) (2.5 thru 3.49=SYSMIS) (3.5 thru 5=2) (ELSE=SYSMIS) INTO 
    index_1_flexi_dichotomicka.
EXECUTE.


RECODE c1 (1965 thru 1980=1) (1981 thru 1996=2) (ELSE=SYSMIS) INTO GEN.
VARIABLE LABELS  GEN 'generace'.
EXECUTE.

*vyber pouze generaci x a y
FILTER OFF.
USE ALL.
SELECT IF (GEN = 1  |  GEN = 2).
EXECUTE.

LOGISTIC REGRESSION VARIABLES index_3_flexi_dichotomicka
  /METHOD=ENTER t1 
  /CONTRAST (t1)=Indicator
  /SAVE=PRED PGROUP
  /PRINT=CI(95)
  /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).