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
.
])
-AT_CHECK([pspp -O format=csv lr-data.sps], [0],
- [dnl
-Table: Dependent Variable Encoding
+AT_CHECK([pspp -o pspp.csv -o pspp.txt lr-data.sps], [0], [dnl
+note: Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001
+])
+AT_CHECK([cat pspp.csv], [0], [Table: Dependent Variable Encoding
Original Value,Internal Value
-1.000,0
-2.000,1
+1.000,.000
+2.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,66,100.000
-Missing Cases,0,.000
-Total,66,100.000
+Included in Analysis,66,100.0%
+Missing Cases,0,.0%
+Total,66,100.0%
note: Estimation terminated at iteration number 6 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,37.323,.455,.659
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,37.323,.455,.659
Table: Classification Table
-,,,Predicted,,
-,,,outcome,,"Percentage
-Correct"
-,Observed,,1.000,2.000,
-Step 1,outcome,1.000,43,5,89.583
-,,2.000,4,14,77.778
-,Overall Percentage,,,,86.364
+,Observed,,Predicted,,
+,,,outcome,,Percentage Correct
+,,,1.000,2.000,
+Step 1,outcome,1.000,43,5,89.6%
+,,2.000,4,14,77.8%
+,Overall Percentage,,,,86.4%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
Step 1,survrate,-.081,.019,17.756,1,.000,.922
,Constant,2.684,.811,10.941,1,.001,14.639
])
-
-
AT_CLEANUP
AT_SETUP([LOGISTIC REGRESSION missing values])
dnl Only the summary information should be different
AT_CHECK([diff run0 run1], [1], [dnl
8,10c8,10
-< Included in Analysis,66,100.000
-< Missing Cases,0,.000
-< Total,66,100.000
+< Included in Analysis,66,100.0%
+< Missing Cases,0,.0%
+< Total,66,100.0%
---
-> Included in Analysis,66,94.286
-> Missing Cases,4,5.714
-> Total,70,100.000
+> Included in Analysis,66,94.3%
+> Missing Cases,4,5.7%
+> Total,70,100.0%
])
AT_CLEANUP
dnl this displays the unweighted totals.
AT_CHECK([diff unweighted-result weighted-result], [1], [dnl
8c8
-< Included in Analysis,66,100.000
+< Included in Analysis,66,100.0%
---
-> Included in Analysis,63,100.000
+> Included in Analysis,63,100.0%
10c10
-< Total,66,100.000
+< Total,66,100.0%
---
-> Total,63,100.000
-23,24c23,24
-< Step 1,outcome,1.000,43,5,89.583
-< ,,2.000,4,14,77.778
+> Total,63,100.0%
+22,23c22,23
+< Step 1,outcome,1.000,43,5,89.6%
+< ,,2.000,4,14,77.8%
---
-> Step 1,outcome,1.000,43.000,5.000,89.583
-> ,,2.000,4.000,14.000,77.778
+> Step 1,outcome,1.000,43.000,5.000,89.6%
+> ,,2.000,4.000,14.000,77.8%
])
logistic regression female with constant /noconst.
])
-AT_CHECK([pspp -O format=csv non-const.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv non-const.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.00,0
-1.00,1
+.00,.000
+1.00,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,200,100.000
-Missing Cases,0,.000
-Total,200,100.000
+Included in Analysis,200,100.0%
+Missing Cases,0,.0%
+Total,200,100.0%
note: Estimation terminated at iteration number 2 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,275.637,.008,.011
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,275.637,.008,.011
Table: Classification Table
-,,,Predicted,,
-,,,female,,"Percentage
-Correct"
-,Observed,,.00,1.00,
-Step 1,female,.00,0,91,.000
-,,1.00,0,109,100.000
-,Overall Percentage,,,,54.500
+,Observed,,Predicted,,
+,,,female,,Percentage Correct
+,,,.00,1.00,
+Step 1,female,.00,0,91,.0%
+,,1.00,0,109,100.0%
+,Overall Percentage,,,,54.5%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
dnl An example to check the behaviour of LOGISTIC REGRESSION with a categorical
dnl variable. This examṕle was inspired from that at:
-dnl http://www.ats.ucla.edu/stat/spss/dae/logit.htm
+dnl http://www.ats.ucla.edu/stat/spss/dae/logit.htm
AT_SETUP([LOGISTIC REGRESSION with categorical])
AT_KEYWORDS([categorical categoricals])
AT_DATA([lr-cat.data], [dnl
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+ 620 2.85 2 4
+ 700 3.28 1 4
+ 760 4.00 1 9
+ 800 3.60 2 4
+ 580 3.34 2 4
+ 540 3.77 2 9
+ 640 3.17 2 4
+ 540 3.02 4 4
+ 680 3.08 4 4
+ 680 3.31 2 4
+ 680 2.96 3 9
+ 700 2.88 2 4
+ 580 3.77 4 4
+ 540 3.49 2 9
+ 700 3.56 2 9
+ 600 3.56 2 9
+ 560 3.59 2 4
+ 640 2.94 2 9
+ 560 3.33 4 4
+ 620 3.69 3 4
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+ 460 3.14 3 4
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+ 540 3.78 2 9
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+ 520 3.90 3 9
+ 520 3.74 4 9
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+ 620 3.09 4 4
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+ 620 3.61 1 9
+ 500 2.98 3 4
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+ 560 2.42 2 4
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+ 740 4.00 3 4
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+ 600 3.89 3 4
+ 720 3.88 3 4
+ 580 4.00 3 4
+ 420 2.26 4 4
+ 520 4.00 2 9
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+ 700 4.00 1 9
+ 480 3.43 2 4
+ 660 3.45 4 4
+ 520 3.25 3 4
+ 560 2.71 3 4
+ 600 3.32 2 4
+ 580 2.88 2 4
+ 660 3.88 2 9
+ 600 3.22 1 4
+ 580 4.00 1 4
+ 660 3.60 3 9
+ 500 3.35 2 4
+ 520 2.98 2 4
+ 660 3.49 2 9
+ 560 3.07 2 4
+ 500 3.13 2 9
+ 720 3.50 3 9
+ 440 3.39 2 9
+ 640 3.95 2 9
+ 380 3.61 3 4
+ 800 3.05 2 9
+ 520 3.19 3 9
+ 600 3.40 3 4
])
AT_DATA([lr-cat.sps], [dnl
.
])
-AT_CHECK([pspp -O format=csv lr-cat.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv lr-cat.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-4.000,0
-9.000,1
+4.000,.000
+9.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,400,100.000
-Missing Cases,0,.000
-Total,400,100.000
+Included in Analysis,400,100.0%
+Missing Cases,0,.0%
+Total,400,100.0%
note: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,458.517,.098,.138
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,458.517,.098,.138
Table: Categorical Variables' Codings
-,,,Parameter coding,,
-,,Frequency,(1),(2),(3)
+,,Frequency,Parameter coding,,
+,,,(1),(2),(3)
bcat,1.000,61,1,0,0
,2.000,151,0,1,0
,3.000,121,0,0,1
,4.000,67,0,0,0
Table: Classification Table
-,,,Predicted,,
-,,,y,,"Percentage
-Correct"
-,Observed,,4.000,9.000,
-Step 1,y,4.000,254,19,93.040
-,,9.000,97,30,23.622
-,Overall Percentage,,,,71.000
+,Observed,,Predicted,,
+,,,y,,Percentage Correct
+,,,4.000,9.000,
+Step 1,y,4.000,254,19,93.0%
+,,9.000,97,30,23.6%
+,Overall Percentage,,,,71.0%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
,bcat(3),.211,.393,.289,1,.591,1.235
,Constant,-5.541,1.138,23.709,1,.000,.004
])
-
AT_CLEANUP
AT_KEYWORDS([categorical categoricals])
AT_DATA([lr-cat2.data], [dnl
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- 47.00 .00 9.00 42.00
- 57.00 1.00 7.00 53.00
- 60.00 .00 8.00 53.00
- 68.00 .00 8.00 66.00
- 63.00 .00 8.00 55.00
- 65.00 .00 8.00 63.00
- 52.00 .00 8.00 61.00
- 34.00 .00 9.00 42.00
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- 34.00 .00 8.00 39.00
- 47.00 .00 9.00 50.00
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- 44.00 .00 7.00 34.00
- 44.00 .00 8.00 50.00
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- 39.00 .00 8.00 39.00
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- 50.00 .00 8.00 50.00
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- 47.00 .00 8.00 58.00
- 36.00 .00 7.00 61.00
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- 63.00 .00 7.00 66.00
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- 39.00 .00 8.00 53.00
- 42.00 .00 8.00 42.00
- 42.00 .00 9.00 31.00
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- 47.00 .00 8.00 44.00
- 57.00 .00 7.00 47.00
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- 57.00 .00 8.00 58.00
- 60.00 1.00 9.00 50.00
- 50.00 .00 9.00 47.00
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+ 52.00 .00 8.00 53.00
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+ 47.00 .00 8.00 53.00
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+ 50.00 .00 8.00 50.00
+ 63.00 .00 9.00 53.00
+ 73.00 1.00 9.00 61.00
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+ 36.00 .00 7.00 61.00
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+ 50.00 .00 8.00 34.00
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+ 39.00 .00 8.00 53.00
+ 42.00 .00 8.00 42.00
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+ 46.00 .00 8.00 44.00
+ 55.00 .00 8.00 42.00
+ 42.00 .00 8.00 47.00
+ 50.00 .00 8.00 44.00
+ 44.00 .00 9.00 39.00
+ 73.00 1.00 8.00 69.00
+ 71.00 1.00 9.00 58.00
+ 50.00 .00 9.00 49.00
+ 63.00 1.00 7.00 54.00
+ 42.00 .00 8.00 36.00
+ 47.00 .00 7.00 42.00
+ 39.00 .00 9.00 26.00
+ 63.00 .00 8.00 58.00
+ 50.00 .00 8.00 55.00
+ 65.00 1.00 8.00 55.00
+ 76.00 1.00 9.00 67.00
+ 71.00 1.00 8.00 66.00
+ 39.00 .00 9.00 47.00
+ 47.00 1.00 9.00 63.00
+ 60.00 .00 7.00 50.00
+ 63.00 .00 9.00 55.00
+ 54.00 1.00 9.00 55.00
+ 55.00 1.00 8.00 58.00
+ 57.00 .00 8.00 61.00
+ 55.00 1.00 9.00 63.00
+ 42.00 .00 7.00 50.00
+ 50.00 .00 8.00 44.00
+ 55.00 .00 8.00 42.00
+ 42.00 .00 7.00 50.00
+ 34.00 .00 8.00 39.00
+ 65.00 .00 9.00 46.00
+ 52.00 .00 7.00 58.00
+ 44.00 .00 8.00 39.00
+ 65.00 1.00 9.00 66.00
+ 47.00 .00 8.00 42.00
+ 41.00 .00 7.00 39.00
+ 68.00 .00 9.00 63.00
+ 63.00 1.00 8.00 72.00
+ 52.00 .00 8.00 53.00
+ 57.00 .00 8.00 50.00
+ 68.00 .00 8.00 55.00
+ 42.00 .00 8.00 56.00
+ 47.00 .00 8.00 48.00
+ 73.00 1.00 9.00 58.00
+ 39.00 .00 8.00 50.00
+ 63.00 1.00 9.00 69.00
+ 60.00 .00 8.00 55.00
+ 65.00 1.00 9.00 66.00
+ 73.00 1.00 8.00 63.00
+ 52.00 .00 8.00 55.00
+ 36.00 .00 8.00 42.00
+ 28.00 .00 7.00 44.00
+ 47.00 .00 8.00 44.00
+ 57.00 .00 7.00 47.00
+ 34.00 .00 7.00 29.00
+ 47.00 .00 9.00 66.00
+ 57.00 .00 8.00 58.00
+ 60.00 1.00 9.00 50.00
+ 50.00 .00 9.00 47.00
+ 73.00 1.00 9.00 55.00
+ 52.00 1.00 8.00 47.00
+ 55.00 .00 8.00 53.00
+ 47.00 .00 8.00 53.00
+ 50.00 .00 8.00 61.00
+ 61.00 .00 7.00 44.00
+ 52.00 .00 9.00 53.00
+ 47.00 .00 7.00 40.00
+ 47.00 .00 7.00 50.00
])
AT_DATA([stringcat.sps], [dnl
])
-AT_CHECK([pspp -O format=csv stringcat.sps], [0],
- [dnl
+AT_CHECK([pspp -O format=csv stringcat.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.000,0
-1.000,1
+.000,.000
+1.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,200,100.000
-Missing Cases,0,.000
-Total,200,100.000
+Included in Analysis,200,100.0%
+Missing Cases,0,.0%
+Total,200,100.0%
note: Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,165.701,.280,.408
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,165.701,.280,.408
Table: Categorical Variables' Codings
-,,,Parameter coding,
-,,Frequency,(1),(2)
+,,Frequency,Parameter coding,
+,,,(1),(2)
ses,a,47,1,0
,b,95,0,1
,c,58,0,0
Table: Classification Table
-,,,Predicted,,
-,,,honcomp,,"Percentage
-Correct"
-,Observed,,.000,1.000,
-Step 1,honcomp,.000,132,15,89.796
-,,1.000,26,27,50.943
-,Overall Percentage,,,,79.500
+,Observed,,Predicted,,
+,,,honcomp,,Percentage Correct
+,,,.000,1.000,
+Step 1,honcomp,.000,132,15,89.8%
+,,1.000,26,27,50.9%
+,Overall Percentage,,,,79.5%
Table: Variables in the Equation
,,B,S.E.,Wald,df,Sig.,Exp(B)
AT_KEYWORDS([categorical categoricals])
AT_DATA([data.txt], [dnl
- .00 3.69 .00
- .00 1.16 1.00
- 1.00 -12.99 .00
- .00 2.97 1.00
- .00 20.48 .00
- .00 4.90 .00
- 1.00 -4.38 .00
- .00 -1.69 1.00
- 1.00 -5.71 .00
- 1.00 -14.28 .00
- .00 9.00 .00
- .00 2.89 1.00
- .00 13.51 1.00
- .00 23.32 1.00
- .00 2.31 1.00
- .00 -2.07 1.00
- 1.00 -4.52 1.00
- 1.00 -5.83 .00
- 1.00 -1.91 .00
- 1.00 -11.12 1.00
- .00 -1.51 .00
- .00 6.59 1.00
- .00 19.28 1.00
- .00 5.94 .00
- .00 8.21 1.00
- .00 8.11 1.00
- .00 2.49 .00
- .00 9.62 .00
- 1.00 -20.74 1.00
- .00 -1.41 1.00
- .00 15.15 1.00
- .00 9.39 .00
- 1.00 -15.14 1.00
- 1.00 -5.86 .00
- 1.00 -11.64 1.00
- 1.00 -14.36 .00
- 1.00 -8.95 1.00
- 1.00 -16.42 1.00
- 1.00 -1.04 1.00
- .00 12.89 1.00
- .00 -7.08 1.00
- .00 4.87 1.00
- .00 11.53 1.00
- 1.00 -6.24 1.00
- .00 1.25 1.00
- .00 4.39 1.00
- .00 3.17 .00
- .00 19.39 1.00
- .00 13.03 1.00
- .00 2.43 .00
- 1.00 -14.73 1.00
- .00 8.25 1.00
- 1.00 -13.28 1.00
- .00 5.27 1.00
- 1.00 -3.46 1.00
- .00 13.81 1.00
- .00 1.35 1.00
- 1.00 -3.94 1.00
- .00 20.73 1.00
- 1.00 -15.40 .00
- 1.00 -11.01 1.00
- .00 4.56 .00
- 1.00 -15.35 1.00
- .00 15.21 .00
- .00 5.34 1.00
- 1.00 -21.55 1.00
- .00 10.12 1.00
- .00 -.73 1.00
- .00 15.28 1.00
- .00 11.08 1.00
- 1.00 -8.24 .00
- .00 2.46 .00
- .00 9.60 .00
- .00 11.24 .00
- .00 14.13 1.00
- .00 19.72 1.00
- .00 5.58 .00
- .00 26.23 1.00
- .00 7.25 .00
- 1.00 -.79 .00
- .00 6.24 .00
- 1.00 1.16 .00
- 1.00 -7.89 1.00
- 1.00 -1.86 1.00
- 1.00 -10.80 1.00
- 1.00 -5.51 .00
- .00 7.51 .00
- .00 11.18 .00
- .00 8.73 .00
- 1.00 -11.21 1.00
- 1.00 -13.24 .00
- .00 19.34 .00
- .00 9.32 1.00
- .00 17.97 1.00
- 1.00 -1.56 1.00
- 1.00 -3.13 .00
- .00 3.98 .00
- .00 -1.21 1.00
- .00 2.37 .00
- 1.00 -18.03 1.00
+ .00 3.69 .00
+ .00 1.16 1.00
+ 1.00 -12.99 .00
+ .00 2.97 1.00
+ .00 20.48 .00
+ .00 4.90 .00
+ 1.00 -4.38 .00
+ .00 -1.69 1.00
+ 1.00 -5.71 .00
+ 1.00 -14.28 .00
+ .00 9.00 .00
+ .00 2.89 1.00
+ .00 13.51 1.00
+ .00 23.32 1.00
+ .00 2.31 1.00
+ .00 -2.07 1.00
+ 1.00 -4.52 1.00
+ 1.00 -5.83 .00
+ 1.00 -1.91 .00
+ 1.00 -11.12 1.00
+ .00 -1.51 .00
+ .00 6.59 1.00
+ .00 19.28 1.00
+ .00 5.94 .00
+ .00 8.21 1.00
+ .00 8.11 1.00
+ .00 2.49 .00
+ .00 9.62 .00
+ 1.00 -20.74 1.00
+ .00 -1.41 1.00
+ .00 15.15 1.00
+ .00 9.39 .00
+ 1.00 -15.14 1.00
+ 1.00 -5.86 .00
+ 1.00 -11.64 1.00
+ 1.00 -14.36 .00
+ 1.00 -8.95 1.00
+ 1.00 -16.42 1.00
+ 1.00 -1.04 1.00
+ .00 12.89 1.00
+ .00 -7.08 1.00
+ .00 4.87 1.00
+ .00 11.53 1.00
+ 1.00 -6.24 1.00
+ .00 1.25 1.00
+ .00 4.39 1.00
+ .00 3.17 .00
+ .00 19.39 1.00
+ .00 13.03 1.00
+ .00 2.43 .00
+ 1.00 -14.73 1.00
+ .00 8.25 1.00
+ 1.00 -13.28 1.00
+ .00 5.27 1.00
+ 1.00 -3.46 1.00
+ .00 13.81 1.00
+ .00 1.35 1.00
+ 1.00 -3.94 1.00
+ .00 20.73 1.00
+ 1.00 -15.40 .00
+ 1.00 -11.01 1.00
+ .00 4.56 .00
+ 1.00 -15.35 1.00
+ .00 15.21 .00
+ .00 5.34 1.00
+ 1.00 -21.55 1.00
+ .00 10.12 1.00
+ .00 -.73 1.00
+ .00 15.28 1.00
+ .00 11.08 1.00
+ 1.00 -8.24 .00
+ .00 2.46 .00
+ .00 9.60 .00
+ .00 11.24 .00
+ .00 14.13 1.00
+ .00 19.72 1.00
+ .00 5.58 .00
+ .00 26.23 1.00
+ .00 7.25 .00
+ 1.00 -.79 .00
+ .00 6.24 .00
+ 1.00 1.16 .00
+ 1.00 -7.89 1.00
+ 1.00 -1.86 1.00
+ 1.00 -10.80 1.00
+ 1.00 -5.51 .00
+ .00 7.51 .00
+ .00 11.18 .00
+ .00 8.73 .00
+ 1.00 -11.21 1.00
+ 1.00 -13.24 .00
+ .00 19.34 .00
+ .00 9.32 1.00
+ .00 17.97 1.00
+ 1.00 -1.56 1.00
+ 1.00 -3.13 .00
+ .00 3.98 .00
+ .00 -1.21 1.00
+ .00 2.37 .00
+ 1.00 -18.03 1.00
])
AT_DATA([miss.sps], [dnl
AT_CHECK([diff file1 file2], [1], [dnl
8,10c8,10
-< Included in Analysis,100,100.00
-< Missing Cases,0,.00
-< Total,100,100.00
+< Included in Analysis,100,100.0%
+< Missing Cases,0,.0%
+< Total,100,100.0%
---
-> Included in Analysis,100,99.01
-> Missing Cases,1,.99
-> Total,101,100.00
+> Included in Analysis,100,99.0%
+> Missing Cases,1,1.0%
+> Total,101,100.0%
])
AT_CLEANUP
set FORMAT=F20.3
data list notable list /disease age sciostat sector savings *.
begin data.
-0 33 1 1 1
-0 35 1 1 1
-0 6 1 1 0
-0 60 1 1 1
-1 18 3 1 0
-0 26 3 1 0
-0 6 3 1 0
-1 31 2 1 1
-1 26 2 1 0
-0 37 2 1 0
-0 23 1 1 0
-0 23 1 1 0
-0 27 1 1 1
-1 9 1 1 1
-1 37 1 2 1
-1 22 1 2 1
-1 67 1 2 1
-0 8 1 2 1
-1 6 1 2 1
-1 15 1 2 1
-1 21 2 2 1
-1 32 2 2 1
-1 16 1 2 1
-0 11 2 2 0
-0 14 3 2 0
-0 9 2 2 0
-0 18 2 2 0
-0 2 3 1 0
-0 61 3 1 1
-0 20 3 1 0
-0 16 3 1 0
-0 9 2 1 0
-0 35 2 1 1
-0 4 1 1 1
-0 44 3 2 0
-1 11 3 2 0
-0 3 2 2 1
-0 6 3 2 0
-1 17 2 2 0
-0 1 3 2 1
-1 53 2 2 1
-1 13 1 2 0
-0 24 1 2 0
-1 70 1 2 1
-1 16 3 2 1
-0 12 2 2 1
-1 20 3 2 1
-0 65 3 2 1
-1 40 2 2 0
-1 38 2 2 1
-1 68 2 2 1
-1 74 1 2 1
-1 14 1 2 1
-1 27 1 2 1
-0 31 1 2 1
-0 18 1 2 1
-0 39 1 2 0
-0 50 1 2 1
-0 31 1 2 1
-0 61 1 2 1
-0 18 3 1 0
-0 5 3 1 0
-0 2 3 1 1
-0 16 3 1 0
-1 59 3 1 1
-0 22 3 1 0
-0 24 1 1 1
-0 30 1 1 1
-0 46 1 1 1
-0 28 1 1 0
-0 27 1 1 1
-1 27 1 1 0
-0 28 1 1 1
-1 52 1 1 1
-0 11 3 1 1
-0 6 2 1 1
-0 46 3 1 0
-1 20 2 1 1
-0 3 1 1 1
-0 18 2 1 0
-0 25 2 1 0
-0 6 3 1 1
-1 65 3 1 1
-0 51 3 1 1
-0 39 2 1 1
-0 8 1 1 1
-0 8 2 1 0
-0 14 3 1 0
-0 6 3 1 0
-0 6 3 1 1
-0 7 3 1 0
-0 4 3 1 0
-0 8 3 1 0
-0 9 2 1 0
-1 32 3 1 0
-0 19 3 1 0
-0 11 3 1 0
-0 35 3 1 0
-0 16 1 1 0
-0 1 1 1 1
-0 6 1 1 1
-0 27 1 1 1
-0 25 1 1 1
-0 18 1 1 0
-0 37 3 1 0
-1 33 3 1 0
-0 27 2 1 0
-0 2 1 1 0
-0 8 2 1 0
-0 5 1 1 0
-0 1 1 1 1
-0 32 1 1 0
-1 25 1 1 1
-0 15 1 2 0
-0 15 1 2 1
-0 26 1 2 1
-1 42 1 2 1
-0 7 1 2 1
-0 2 1 2 0
-1 65 1 2 1
-0 33 2 2 1
-1 8 2 2 0
-0 30 2 2 0
-0 5 3 2 0
-0 15 3 2 0
-1 60 3 2 1
-1 13 3 2 1
-0 70 3 1 1
-0 5 3 1 0
-0 3 3 1 1
-0 50 2 1 1
-0 6 2 1 0
-0 12 2 1 1
-1 39 3 2 0
-0 15 2 2 1
-1 35 2 2 0
-0 2 2 2 1
-0 17 3 2 0
-1 43 3 2 1
-0 30 2 2 1
-0 11 1 2 1
-1 39 1 2 1
-0 32 1 2 1
-0 17 1 2 1
-0 3 3 2 1
-0 7 3 2 0
-0 2 2 2 0
-1 64 2 2 1
-1 13 1 2 2
-1 15 2 2 1
-0 48 2 2 1
-0 23 1 2 1
-1 48 1 2 0
-0 25 1 2 1
-0 12 1 2 1
-1 46 1 2 1
-0 79 1 2 1
-0 56 1 2 1
-0 8 1 2 1
-1 29 3 1 0
-1 35 3 1 0
-1 11 3 1 0
-0 69 3 1 1
-1 21 3 1 0
-0 13 3 1 0
-0 21 1 1 1
-1 32 1 1 1
-1 24 1 1 0
-0 24 1 1 1
-0 73 1 1 1
-0 42 1 1 1
-1 34 1 1 1
-0 30 2 1 0
-0 7 2 1 0
-1 29 3 1 0
-1 22 3 1 0
-0 38 2 1 1
-0 13 2 1 1
-0 12 2 1 1
-0 42 3 1 0
-1 17 3 1 0
-0 21 3 1 1
-0 34 1 1 1
-0 1 3 1 0
-0 14 2 1 0
-0 16 2 1 0
-0 9 3 1 0
-0 53 3 1 0
-0 27 3 1 0
-0 15 3 1 0
-0 9 3 1 0
-0 4 2 1 1
-0 10 3 1 1
-0 31 3 1 0
-0 85 3 1 1
-0 24 2 1 0
+0 33 1 1 1
+0 35 1 1 1
+0 6 1 1 0
+0 60 1 1 1
+1 18 3 1 0
+0 26 3 1 0
+0 6 3 1 0
+1 31 2 1 1
+1 26 2 1 0
+0 37 2 1 0
+0 23 1 1 0
+0 23 1 1 0
+0 27 1 1 1
+1 9 1 1 1
+1 37 1 2 1
+1 22 1 2 1
+1 67 1 2 1
+0 8 1 2 1
+1 6 1 2 1
+1 15 1 2 1
+1 21 2 2 1
+1 32 2 2 1
+1 16 1 2 1
+0 11 2 2 0
+0 14 3 2 0
+0 9 2 2 0
+0 18 2 2 0
+0 2 3 1 0
+0 61 3 1 1
+0 20 3 1 0
+0 16 3 1 0
+0 9 2 1 0
+0 35 2 1 1
+0 4 1 1 1
+0 44 3 2 0
+1 11 3 2 0
+0 3 2 2 1
+0 6 3 2 0
+1 17 2 2 0
+0 1 3 2 1
+1 53 2 2 1
+1 13 1 2 0
+0 24 1 2 0
+1 70 1 2 1
+1 16 3 2 1
+0 12 2 2 1
+1 20 3 2 1
+0 65 3 2 1
+1 40 2 2 0
+1 38 2 2 1
+1 68 2 2 1
+1 74 1 2 1
+1 14 1 2 1
+1 27 1 2 1
+0 31 1 2 1
+0 18 1 2 1
+0 39 1 2 0
+0 50 1 2 1
+0 31 1 2 1
+0 61 1 2 1
+0 18 3 1 0
+0 5 3 1 0
+0 2 3 1 1
+0 16 3 1 0
+1 59 3 1 1
+0 22 3 1 0
+0 24 1 1 1
+0 30 1 1 1
+0 46 1 1 1
+0 28 1 1 0
+0 27 1 1 1
+1 27 1 1 0
+0 28 1 1 1
+1 52 1 1 1
+0 11 3 1 1
+0 6 2 1 1
+0 46 3 1 0
+1 20 2 1 1
+0 3 1 1 1
+0 18 2 1 0
+0 25 2 1 0
+0 6 3 1 1
+1 65 3 1 1
+0 51 3 1 1
+0 39 2 1 1
+0 8 1 1 1
+0 8 2 1 0
+0 14 3 1 0
+0 6 3 1 0
+0 6 3 1 1
+0 7 3 1 0
+0 4 3 1 0
+0 8 3 1 0
+0 9 2 1 0
+1 32 3 1 0
+0 19 3 1 0
+0 11 3 1 0
+0 35 3 1 0
+0 16 1 1 0
+0 1 1 1 1
+0 6 1 1 1
+0 27 1 1 1
+0 25 1 1 1
+0 18 1 1 0
+0 37 3 1 0
+1 33 3 1 0
+0 27 2 1 0
+0 2 1 1 0
+0 8 2 1 0
+0 5 1 1 0
+0 1 1 1 1
+0 32 1 1 0
+1 25 1 1 1
+0 15 1 2 0
+0 15 1 2 1
+0 26 1 2 1
+1 42 1 2 1
+0 7 1 2 1
+0 2 1 2 0
+1 65 1 2 1
+0 33 2 2 1
+1 8 2 2 0
+0 30 2 2 0
+0 5 3 2 0
+0 15 3 2 0
+1 60 3 2 1
+1 13 3 2 1
+0 70 3 1 1
+0 5 3 1 0
+0 3 3 1 1
+0 50 2 1 1
+0 6 2 1 0
+0 12 2 1 1
+1 39 3 2 0
+0 15 2 2 1
+1 35 2 2 0
+0 2 2 2 1
+0 17 3 2 0
+1 43 3 2 1
+0 30 2 2 1
+0 11 1 2 1
+1 39 1 2 1
+0 32 1 2 1
+0 17 1 2 1
+0 3 3 2 1
+0 7 3 2 0
+0 2 2 2 0
+1 64 2 2 1
+1 13 1 2 2
+1 15 2 2 1
+0 48 2 2 1
+0 23 1 2 1
+1 48 1 2 0
+0 25 1 2 1
+0 12 1 2 1
+1 46 1 2 1
+0 79 1 2 1
+0 56 1 2 1
+0 8 1 2 1
+1 29 3 1 0
+1 35 3 1 0
+1 11 3 1 0
+0 69 3 1 1
+1 21 3 1 0
+0 13 3 1 0
+0 21 1 1 1
+1 32 1 1 1
+1 24 1 1 0
+0 24 1 1 1
+0 73 1 1 1
+0 42 1 1 1
+1 34 1 1 1
+0 30 2 1 0
+0 7 2 1 0
+1 29 3 1 0
+1 22 3 1 0
+0 38 2 1 1
+0 13 2 1 1
+0 12 2 1 1
+0 42 3 1 0
+1 17 3 1 0
+0 21 3 1 1
+0 34 1 1 1
+0 1 3 1 0
+0 14 2 1 0
+0 16 2 1 0
+0 9 3 1 0
+0 53 3 1 0
+0 27 3 1 0
+0 15 3 1 0
+0 9 3 1 0
+0 4 2 1 1
+0 10 3 1 1
+0 31 3 1 0
+0 85 3 1 1
+0 24 2 1 0
end data.
-logistic regression
+logistic regression
disease WITH age sciostat sector savings
/categorical = sciostat sector
/print = ci(95).
AT_CHECK([pspp -O format=csv ci.sps], [0], [dnl
Table: Dependent Variable Encoding
Original Value,Internal Value
-.000,0
-1.000,1
+.000,.000
+1.000,1.000
Table: Case Processing Summary
Unweighted Cases,N,Percent
-Included in Analysis,196,100.000
-Missing Cases,0,.000
-Total,196,100.000
+Included in Analysis,196,100.0%
+Missing Cases,0,.0%
+Total,196,100.0%
note: Estimation terminated at iteration number 4 because parameter estimates changed by less than 0.001
Table: Model Summary
-Step 1,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
-,211.195,.120,.172
+Step,-2 Log likelihood,Cox & Snell R Square,Nagelkerke R Square
+1,211.195,.120,.172
Table: Categorical Variables' Codings
-,,,Parameter coding,
-,,Frequency,(1),(2)
+,,Frequency,Parameter coding,
+,,,(1),(2)
sciostat,1.000,77,1,0
,2.000,49,0,1
,3.000,70,0,0
,2.000,79,0,
Table: Classification Table
-,,,Predicted,,
-,,,disease,,"Percentage
-Correct"
-,Observed,,.000,1.000,
-Step 1,disease,.000,131,8,94.245
-,,1.000,41,16,28.070
-,Overall Percentage,,,,75.000
+,Observed,,Predicted,,
+,,,disease,,Percentage Correct
+,,,.000,1.000,
+Step 1,disease,.000,131,8,94.2%
+,,1.000,41,16,28.1%
+,Overall Percentage,,,,75.0%
Table: Variables in the Equation
-,,,,,,,,95% CI for Exp(B),
-,,B,S.E.,Wald,df,Sig.,Exp(B),Lower,Upper
+,,B,S.E.,Wald,df,Sig.,Exp(B),95% CI for Exp(B),
+,,,,,,,,Lower,Upper
Step 1,age,.027,.009,8.647,1,.003,1.027,1.009,1.045
,savings,.061,.386,.025,1,.874,1.063,.499,2.264
,sciostat,,,.440,2,.803,,,
projects / pspp / blobdiff