dnl PSPP - a program for statistical analysis.
dnl Copyright (C) 2017 Free Software Foundation, Inc.
-dnl
+dnl
dnl This program is free software: you can redistribute it and/or modify
dnl it under the terms of the GNU General Public License as published by
dnl the Free Software Foundation, either version 3 of the License, or
dnl (at your option) any later version.
-dnl
+dnl
dnl This program is distributed in the hope that it will be useful,
dnl but WITHOUT ANY WARRANTY; without even the implied warranty of
dnl MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
dnl GNU General Public License for more details.
-dnl
+dnl
dnl You should have received a copy of the GNU General Public License
dnl along with this program. If not, see <http://www.gnu.org/licenses/>.
dnl
select if (g = 0).
-regression
+regression
/variables = x0 x1
/dependent = y
/statistics = all
select if (g = 1).
-regression
+regression
/variables = x0 x1
/dependent = y
/statistics = all
split file by g.
-regression
+regression
/variables = x0 x1
/dependent = y
/statistics = all
end file.
end input program.
-regression
+regression
/variables = x0 x1
/dependent = y ycopy
/statistics = default.
AT_CLEANUP
-dnl The following example comes from
+dnl The following example comes from
dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
/variables = math female socst read
/statistics = coeff r anova ci (95)
/dependent = science
- /method = enter
+ /method = enter
])
AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])
-AT_CLEANUP
+AT_CLEANUP
DATA LIST notable LIST /number * value *.
BEGIN DATA
- 16 7.25
- 0 .00
- 1 .10
- 9 27.9
- 0 .00
- 7 3.65
- 14 16.8
- 24 9.15
- 0 .00
- 24 19.0
- 7 4.05
- 12 7.90
- 6 .75
- 11 1.40
- 0 .00
- 3 2.30
- 12 7.60
- 11 6.80
- 16 8.65
+ 16 7.25
+ 0 .00
+ 1 .10
+ 9 27.9
+ 0 .00
+ 7 3.65
+ 14 16.8
+ 24 9.15
+ 0 .00
+ 24 19.0
+ 7 4.05
+ 12 7.90
+ 6 .75
+ 11 1.40
+ 0 .00
+ 3 2.30
+ 12 7.60
+ 11 6.80
+ 16 8.65
END DATA.
REGRESSION
number,.611,.192,.612,3.189,.005
])
-AT_CLEANUP
+AT_CLEANUP
DATA LIST notable LIST /number * value *.
BEGIN DATA
- 16 7.25
- 0 .00
- 1 .10
- 9 27.9
- 0 .00
- 7 3.65
- 14 16.8
- 24 9.15
- 0 .00
- 24 19.0
- 7 4.05
- 12 7.90
- 6 .75
- 11 1.40
- 0 .00
- 3 2.30
- 12 7.60
- 11 6.80
- 16 8.65
+ 16 7.25
+ 0 .00
+ 1 .10
+ 9 27.9
+ 0 .00
+ 7 3.65
+ 14 16.8
+ 24 9.15
+ 0 .00
+ 24 19.0
+ 7 4.05
+ 12 7.90
+ 6 .75
+ 11 1.40
+ 0 .00
+ 3 2.30
+ 12 7.60
+ 11 6.80
+ 16 8.65
END DATA.
REGRESSION
number,.672,.118,.802,5.699,.000
])
-AT_CLEANUP
+AT_CLEANUP
dnl This is an example from doc/tutorial.texi
dnl So if the results of this have to be changed in any way,
REGRESSION /VARIABLES=mtbf duty_cycle /DEPENDENT=mttr.
REGRESSION /VARIABLES=mtbf /DEPENDENT=mttr.
])
-AT_CHECK([pspp -o pspp.csv -o pspp.txt regression.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
+
+AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
Table: Model Summary (Mean time to repair (hours) )
R,R Square,Adjusted R Square,Std. Error of the Estimate
-.99,.99,.99,2.24
+.94,.89,.88,6.54
Table: ANOVA (Mean time to repair (hours) )
,Sum of Squares,df,Mean Square,F,Sig.
-Regression,5308.87,2,2654.44,530.75,.000
-Residual,60.02,12,5.00,,
-Total,5368.89,14,,,
+Regression,9576.26,2,4788.13,111.94,.000
+Residual,1154.94,27,42.78,,
+Total,10731.20,29,,,
Table: Coefficients (Mean time to repair (hours) )
,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
,B,Std. Error,Beta,,
-(Constant),9.81,1.50,.00,6.54,.000
-Mean time between failures (months) ,3.10,.10,.99,32.43,.000
-Ratio of working to non-working time,1.09,1.78,.02,.61,.552
+(Constant),10.59,3.11,.00,3.40,.002
+Mean time between failures (months) ,3.02,.20,.95,14.88,.000
+Ratio of working to non-working time,-1.12,3.69,-.02,-.30,.763
Table: Model Summary (Mean time to repair (hours) )
R,R Square,Adjusted R Square,Std. Error of the Estimate
-.99,.99,.99,2.18
+.94,.89,.89,6.43
Table: ANOVA (Mean time to repair (hours) )
,Sum of Squares,df,Mean Square,F,Sig.
-Regression,5307.00,1,5307.00,1114.73,.000
-Residual,61.89,13,4.76,,
-Total,5368.89,14,,,
+Regression,9572.30,1,9572.30,231.28,.000
+Residual,1158.90,28,41.39,,
+Total,10731.20,29,,,
Table: Coefficients (Mean time to repair (hours) )
,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
,B,Std. Error,Beta,,
-(Constant),10.50,.96,.00,10.96,.000
-Mean time between failures (months) ,3.11,.09,.99,33.39,.000
+(Constant),9.90,2.10,.00,4.71,.000
+Mean time between failures (months) ,3.01,.20,.94,15.21,.000
])
+
+AT_CLEANUP
+
+
+AT_SETUP([LINEAR REGRESSION vif])
+AT_DATA([regression-vif.sps], [dnl
+SET FORMAT=F10.3.
+
+data list notable list /competence_x1 motivation_x2 performance_y.
+begin data
+32 34 36
+35 37 39
+38 45 49
+31 41 41
+36 40 38
+32 38 36
+33 39 37
+31 40 41
+30 37 40
+35 37 43
+31 34 36
+34 32 35
+31 42 34
+25 36 40
+35 42 40
+36 41 44
+30 38 32
+34 41 41
+34 41 44
+22 27 26
+27 26 33
+30 30 35
+30 35 37
+37 39 44
+29 35 36
+31 35 29
+31 45 41
+29 30 32
+29 35 36
+31 37 37
+36 45 42
+32 44 39
+27 26 31
+33 39 35
+20 25 28
+30 36 39
+27 37 39
+25 39 36
+32 38 38
+32 38 35
+end data.
+
+regression /variables=competence_x1 motivation_x2
+ /statistics=defaults tol
+ /dependent=performance_y
+ .
+])
+
+
+AT_CHECK([pspp -O format=csv regression-vif.sps], [0], [dnl
+Table: Model Summary (performance_y)
+R,R Square,Adjusted R Square,Std. Error of the Estimate
+.785,.616,.595,2.980
+
+Table: ANOVA (performance_y)
+,Sum of Squares,df,Mean Square,F,Sig.
+Regression,526.494,2,263.247,29.641,.000
+Residual,328.606,37,8.881,,
+Total,855.100,39,,,
+
+Table: Coefficients (performance_y)
+,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.,Collinearity Statistics,
+,B,Std. Error,Beta,,,Tolerance,VIF
+(Constant),7.220,4.020,.000,1.796,.080,,
+competence_x1,.432,.166,.358,2.609,.013,.552,1.812
+motivation_x2,.453,.125,.499,3.636,.001,.552,1.812
+])
+
AT_CLEANUP