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
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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- 800 4.00 3 9
- 580 3.40 2 4
- 600 3.13 2 4
- 540 2.70 2 4
- 660 3.31 4 4
- 480 3.58 1 9
- 620 4.00 1 9
- 680 3.98 2 9
- 580 3.40 4 4
- 760 3.35 3 4
- 700 3.72 2 4
- 460 3.64 1 9
- 540 3.28 3 4
- 680 3.48 3 4
- 740 3.31 1 4
- 460 3.77 3 4
- 740 3.54 1 4
- 600 3.63 3 4
- 620 3.05 2 4
- 560 3.04 3 4
- 520 2.70 3 4
- 640 3.35 3 4
- 620 3.58 2 4
- 660 3.70 4 9
- 500 2.86 4 4
- 640 3.50 2 4
- 720 4.00 3 4
- 720 3.94 3 4
- 400 3.65 2 4
- 800 2.90 2 4
- 520 2.90 3 4
- 440 3.24 4 4
- 580 3.51 2 4
- 500 3.31 3 4
- 440 3.22 1 4
- 540 3.17 1 9
- 420 3.02 1 4
- 780 3.22 2 9
- 440 3.13 4 4
- 800 3.66 1 9
- 580 3.32 2 9
- 480 2.67 2 9
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- 740 2.97 2 9
- 700 3.83 2 4
- 640 3.93 2 4
- 800 3.90 2 4
- 400 3.38 2 4
- 700 3.52 2 4
- 680 3.00 4 9
- 540 3.20 1 4
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- 780 4.00 2 9
- 220 2.83 3 4
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- 460 2.63 2 4
- 440 2.76 2 4
- 740 3.62 4 4
- 380 3.38 2 4
- 640 3.63 1 9
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- 660 3.67 2 4
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- 660 3.67 3 9
- 400 3.35 3 4
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- 800 4.00 3 9
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- 460 3.14 3 4
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- 560 3.69 3 9
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- 740 3.86 2 9
- 800 3.53 1 9
- 620 3.78 3 4
- 700 3.27 2 4
- 540 3.78 2 9
- 700 3.65 2 4
- 800 3.22 1 9
- 560 3.59 2 9
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- 520 3.90 3 9
- 520 3.74 4 9
- 480 2.55 1 4
- 800 4.00 4 4
- 620 3.09 4 4
- 560 3.49 4 4
- 500 3.17 3 4
- 480 3.40 2 4
- 460 2.98 1 4
- 580 3.58 1 9
- 640 3.30 2 4
- 480 3.45 2 4
- 440 3.17 2 4
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- 500 3.08 3 4
- 660 3.94 2 4
- 720 3.31 1 4
- 460 3.64 3 9
- 500 2.93 4 4
- 800 3.54 3 4
- 580 2.93 2 4
- 620 3.61 1 9
- 500 2.98 3 4
- 660 4.00 2 9
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- 720 3.50 3 9
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+ 380 3.61 3 4
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+ 520 3.19 3 9
+ 600 3.40 3 4
])
AT_DATA([lr-cat.sps], [dnl
AT_KEYWORDS([categorical categoricals])
AT_DATA([lr-cat2.data], [dnl
- 60.00 1.00 8.00 50.00
- 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
- 37.00 .00 8.00 39.00
- 68.00 1.00 9.00 69.00
- 60.00 .00 9.00 61.00
- 44.00 .00 9.00 58.00
- 42.00 .00 8.00 47.00
- 57.00 1.00 7.00 61.00
- 55.00 1.00 8.00 50.00
- 55.00 .00 9.00 58.00
- 44.00 .00 8.00 63.00
- 50.00 1.00 9.00 66.00
- 44.00 .00 8.00 39.00
- 55.00 .00 8.00 58.00
- 44.00 .00 8.00 50.00
- 47.00 1.00 7.00 34.00
- 48.00 .00 8.00 44.00
- 45.00 .00 7.00 31.00
- 43.00 .00 8.00 50.00
- 39.00 .00 8.00 42.00
- 63.00 .00 9.00 50.00
- 47.00 .00 8.00 58.00
- 42.00 .00 7.00 50.00
- 50.00 .00 9.00 36.00
- 47.00 .00 7.00 33.00
- 60.00 .00 9.00 61.00
- 47.00 .00 7.00 42.00
- 68.00 1.00 9.00 69.00
- 52.00 .00 8.00 54.00
- 63.00 1.00 9.00 61.00
- 65.00 1.00 9.00 61.00
- 63.00 1.00 9.00 53.00
- 57.00 .00 8.00 51.00
- 34.00 .00 8.00 36.00
- 50.00 .00 8.00 39.00
- 52.00 1.00 7.00 56.00
- 45.00 .00 7.00 34.00
- 47.00 1.00 7.00 53.00
- 34.00 .00 7.00 39.00
- 50.00 1.00 8.00 55.00
- 60.00 .00 9.00 58.00
- 63.00 .00 8.00 58.00
- 35.00 .00 7.00 51.00
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- 47.00 .00 8.00 47.00
- 76.00 .00 9.00 64.00
- 44.00 .00 8.00 44.00
- 36.00 .00 9.00 50.00
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- 47.00 1.00 8.00 50.00
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- 68.00 .00 8.00 74.00
- 39.00 .00 7.00 44.00
- 50.00 .00 8.00 55.00
- 52.00 .00 9.00 61.00
- 47.00 .00 8.00 53.00
- 39.00 .00 7.00 47.00
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- 68.00 1.00 8.00 50.00
- 52.00 1.00 9.00 63.00
- 55.00 .00 8.00 58.00
- 57.00 .00 8.00 55.00
- 66.00 1.00 9.00 61.00
- 65.00 1.00 7.00 58.00
- 42.00 .00 7.00 42.00
- 68.00 1.00 7.00 59.00
- 60.00 1.00 9.00 61.00
- 52.00 .00 8.00 55.00
- 57.00 1.00 7.00 54.00
- 42.00 .00 9.00 50.00
- 42.00 .00 8.00 47.00
- 57.00 .00 8.00 50.00
- 47.00 .00 7.00 45.00
- 44.00 .00 7.00 40.00
- 43.00 .00 9.00 55.00
- 31.00 .00 8.00 39.00
- 37.00 .00 7.00 33.00
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- 47.00 .00 8.00 39.00
- 57.00 1.00 8.00 63.00
- 52.00 .00 8.00 44.00
- 44.00 .00 7.00 35.00
- 52.00 .00 7.00 55.00
- 55.00 .00 7.00 69.00
- 52.00 .00 8.00 53.00
- 55.00 .00 9.00 61.00
- 65.00 1.00 9.00 63.00
- 55.00 .00 8.00 44.00
- 63.00 .00 7.00 65.00
- 44.00 .00 7.00 39.00
- 47.00 .00 7.00 36.00
- 63.00 1.00 9.00 55.00
- 68.00 .00 8.00 66.00
- 34.00 .00 8.00 39.00
- 47.00 .00 9.00 50.00
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- 63.00 .00 8.00 66.00
- 44.00 .00 7.00 34.00
- 44.00 .00 8.00 50.00
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- 50.00 .00 8.00 50.00
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- 36.00 .00 7.00 61.00
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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
- 42.00 .00 8.00 72.00
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- 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
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- 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
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- 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
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- 52.00 .00 9.00 53.00
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+ 47.00 .00 7.00 50.00
])
AT_DATA([stringcat.sps], [dnl
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
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- .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
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- .00 15.21 .00
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- .00 15.28 1.00
- .00 11.08 1.00
- 1.00 -8.24 .00
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- .00 14.13 1.00
- .00 19.72 1.00
- .00 5.58 .00
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- 1.00 -.79 .00
- .00 6.24 .00
- 1.00 1.16 .00
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- 1.00 -1.86 1.00
- 1.00 -10.80 1.00
- 1.00 -5.51 .00
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- .00 8.73 .00
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- 1.00 -13.24 .00
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- .00 17.97 1.00
- 1.00 -1.56 1.00
- 1.00 -3.13 .00
- .00 3.98 .00
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- .00 2.37 .00
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+ .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
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+ .00 12.89 1.00
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+ .00 4.87 1.00
+ .00 11.53 1.00
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+ .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
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+ .00 8.25 1.00
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+ .00 5.27 1.00
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+ .00 13.81 1.00
+ .00 1.35 1.00
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+ .00 20.73 1.00
+ 1.00 -15.40 .00
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+ .00 4.56 .00
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+ .00 15.21 .00
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+ .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
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+ .00 7.25 .00
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+ .00 9.32 1.00
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+ 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
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
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-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
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-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
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end data.
-logistic regression
+logistic regression
disease WITH age sciostat sector savings
/categorical = sciostat sector
/print = ci(95).
projects / pspp / blobdiff