* Encoding: UTF-8.

DATASET ACTIVATE DataSet2.
COMPUTE GSL=Autumn+Winter+Spring+Summer.
EXECUTE.



COMPUTE B_C=Benef_com+Benef_pers+Involvement.
EXECUTE.

FREQUENCIES VARIABLES=GSL B_C
  /NTILES=4
  /STATISTICS=MINIMUM MAXIMUM MEAN MEDIAN
  /HISTOGRAM
  /ORDER=ANALYSIS.

CORRELATIONS
  /VARIABLES=GSL B_C
  /PRINT=TWOTAIL NOSIG FULL
  /MISSING=PAIRWISE.

REGRESSION
  /DESCRIPTIVES MEAN STDDEV CORR SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10) TOLERANCE(.0001)
  /NOORIGIN 
  /DEPENDENT GSL
  /METHOD=ENTER B_C
  /RESIDUALS HISTOGRAM(ZRESID).

MEANS TABLES=GSL BY Gender Age Education Place_liv Work_force
  /CELLS=MEAN COUNT STDDEV
  /STATISTICS ANOVA.

SPSSINC CREATE DUMMIES VARIABLE=Age 
ROOTNAME1=Age 
/OPTIONS ORDER=A USEVALUELABELS=YES USEML=YES OMITFIRST=NO.

REGRESSION
  /DESCRIPTIVES MEAN STDDEV CORR SIG N
  /MISSING LISTWISE
  /STATISTICS COEFF OUTS R ANOVA CHANGE
  /CRITERIA=PIN(.05) POUT(.10) TOLERANCE(.0001)
  /NOORIGIN 
  /DEPENDENT GSL
  /METHOD=ENTER B_C Age_1 Age_2
  /RESIDUALS HISTOGRAM(ZRESID).

RECODE QOL (3=1) (ELSE=0) INTO Qol_ETIS.
VARIABLE LABELS  Qol_ETIS 'Indicatore di miglioramento QOL'.
EXECUTE.

FREQUENCIES VARIABLES=QOL Qol_ETIS
  /NTILES=4
  /STATISTICS=MINIMUM MAXIMUM MEAN MEDIAN
  /HISTOGRAM
  /ORDER=ANALYSIS.

CROSSTABS
  /TABLES=Qol_ETIS BY Age
  /FORMAT=AVALUE TABLES
  /STATISTICS=CHISQ 
  /CELLS=COUNT COLUMN 
  /COUNT ROUND CELL.

LOGISTIC REGRESSION VARIABLES Qol_ETIS
  /METHOD=ENTER GSL B_C Gender Age 
  /CONTRAST (Gender)=Indicator(1)
  /CONTRAST (Age)=Indicator(1)
  /PRINT=GOODFIT
  /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

* Decision Tree.
TREE GSL [s] BY Gender [n] Age [n] Education [n] Place_liv [n] Work_force [n] B_C [s] 
  /TREE DISPLAY=TOPDOWN NODES=STATISTICS BRANCHSTATISTICS=YES NODEDEFS=YES SCALE=AUTO
  /PRINT MODELSUMMARY RISK
  /GAIN SUMMARYTABLE=YES TYPE=[NODE] SORT=DESCENDING CUMULATIVE=NO
  /PLOT MEAN INCREMENT=10
  /SAVE NODEID
  /METHOD TYPE=CRT MAXSURROGATES=AUTO PRUNE=NONE
  /GROWTHLIMIT MAXDEPTH=AUTO MINPARENTSIZE=10 MINCHILDSIZE=5
  /VALIDATION TYPE=NONE OUTPUT=BOTHSAMPLES
  /CRT MINIMPROVEMENT=0.0001
  /MISSING NOMINALMISSING=MISSING.

* Decision Tree.
TREE GSL [s] BY Gender [n] Age [n] Education [n] Place_liv [n] Work_force [n] B_C [s] 
  /TREE DISPLAY=TOPDOWN NODES=STATISTICS BRANCHSTATISTICS=YES NODEDEFS=YES SCALE=AUTO
  /PRINT MODELSUMMARY RISK
  /GAIN SUMMARYTABLE=YES TYPE=[NODE] SORT=DESCENDING CUMULATIVE=NO
  /PLOT IMPORTANCE MEAN INCREMENT=10
  /SAVE NODEID
  /METHOD TYPE=CRT MAXSURROGATES=AUTO PRUNE=NONE
  /GROWTHLIMIT MAXDEPTH=AUTO MINPARENTSIZE=10 MINCHILDSIZE=5
  /VALIDATION TYPE=NONE OUTPUT=BOTHSAMPLES
  /CRT MINIMPROVEMENT=0.0001
  /MISSING NOMINALMISSING=MISSING.