1 dnl PSPP - a program for statistical analysis.
2 dnl Copyright (C) 2017 Free Software Foundation, Inc.
4 dnl This program is free software: you can redistribute it and/or modify
5 dnl it under the terms of the GNU General Public License as published by
6 dnl the Free Software Foundation, either version 3 of the License, or
7 dnl (at your option) any later version.
9 dnl This program is distributed in the hope that it will be useful,
10 dnl but WITHOUT ANY WARRANTY; without even the implied warranty of
11 dnl MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 dnl GNU General Public License for more details.
14 dnl You should have received a copy of the GNU General Public License
15 dnl along with this program. If not, see <http://www.gnu.org/licenses/>.
17 AT_BANNER([ONEWAY procedure])
19 AT_SETUP([ONEWAY basic operation])
20 AT_KEYWORDS([categorical categoricals])
22 [DATA LIST NOTABLE LIST /QUALITY * BRAND * .
41 VARIABLE LABELS brand 'Manufacturer'.
42 VARIABLE LABELS quality 'Breaking Strain'.
44 VALUE LABELS /brand 1 'Aspeger' 2 'Bloggs' 3 'Charlies'.
48 /STATISTICS descriptives homogeneity
54 AT_CHECK([pspp -O format=csv oneway.sps], [0], [dnl
56 ,,,,,,95% Confidence Interval for Mean,,,
57 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
58 Breaking Strain,Aspeger,5,2.20,1.30,.58,.58,3.82,1.00,4.00
59 ,Bloggs,5,3.20,1.30,.58,1.58,4.82,2.00,5.00
60 ,Charlies,5,5.00,1.58,.71,3.04,6.96,3.00,7.00
61 ,Total,15,3.47,1.77,.46,2.49,4.45,1.00,7.00
63 Table: Test of Homogeneity of Variances
64 ,Levene Statistic,df1,df2,Sig.
65 Breaking Strain,.09,2,12,.913
68 ,,Sum of Squares,df,Mean Square,F,Sig.
69 Breaking Strain,Between Groups,20.13,2,10.07,5.12,.025
70 ,Within Groups,23.60,12,1.97,,
73 Table: Contrast Coefficients
75 ,,Aspeger,Bloggs,Charlies
80 ,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
81 Breaking Strain,Assume equal variances,1,3.80,1.54,2.47,12,.029
82 ,,2,1.80,.89,2.03,12,.065
83 ,Does not assume equal,1,3.80,1.48,2.56,8.74,.031
84 ,,2,1.80,.92,1.96,7.72,.086
89 AT_SETUP([ONEWAY with splits])
90 AT_KEYWORDS([categorical categoricals])
91 AT_DATA([oneway-splits.sps],
92 [DATA LIST NOTABLE LIST /QUALITY * BRAND * S *.
111 VARIABLE LABELS brand 'Manufacturer'.
112 VARIABLE LABELS quality 'Breaking Strain'.
114 VALUE LABELS /brand 1 'Aspeger' 2 'Bloggs' 3 'Charlies'.
120 /STATISTICS descriptives homogeneity
126 AT_CHECK([pspp -O format=csv oneway-splits.sps], [0],
127 [Variable,Value,Label
131 ,,,,,,95% Confidence Interval for Mean,,,
132 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
133 Breaking Strain,Aspeger,5,2.20,1.30,.58,.58,3.82,1.00,4.00
134 ,Bloggs,2,3.50,2.12,1.50,-15.56,22.56,2.00,5.00
135 ,Total,7,2.57,1.51,.57,1.17,3.97,1.00,5.00
137 Table: Test of Homogeneity of Variances
138 ,Levene Statistic,df1,df2,Sig.
139 Breaking Strain,1.09,1,5,.345
142 ,,Sum of Squares,df,Mean Square,F,Sig.
143 Breaking Strain,Between Groups,2.41,1,2.41,1.07,.349
144 ,Within Groups,11.30,5,2.26,,
147 Table: Contrast Coefficients
153 Table: Contrast Tests
154 ,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
155 Breaking Strain,Assume equal variances,1,2.60,2.52,1.03,5,.349
156 ,,2,1.30,1.26,1.03,5,.349
157 ,Does not assume equal,1,2.60,3.22,.81,1.32,.539
158 ,,2,1.30,1.61,.81,1.32,.539
164 ,,,,,,95% Confidence Interval for Mean,,,
165 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
166 Breaking Strain,Bloggs,3,3.00,1.00,.58,.52,5.48,2.00,4.00
167 ,Charlies,5,5.00,1.58,.71,3.04,6.96,3.00,7.00
168 ,Total,8,4.25,1.67,.59,2.85,5.65,2.00,7.00
170 Table: Test of Homogeneity of Variances
171 ,Levene Statistic,df1,df2,Sig.
172 Breaking Strain,.92,1,6,.374
175 ,,Sum of Squares,df,Mean Square,F,Sig.
176 Breaking Strain,Between Groups,7.50,1,7.50,3.75,.101
177 ,Within Groups,12.00,6,2.00,,
180 Table: Contrast Coefficients
186 Table: Contrast Tests
187 ,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
188 Breaking Strain,Assume equal variances,1,4.00,2.07,1.94,6,.101
189 ,,2,2.00,1.03,1.94,6,.101
190 ,Does not assume equal,1,4.00,1.83,2.19,5.88,.072
191 ,,2,2.00,.91,2.19,5.88,.072
197 AT_SETUP([ONEWAY with missing values])
198 AT_KEYWORDS([categorical categoricals])
199 dnl Check that missing are treated properly
200 AT_DATA([oneway-missing1.sps],
201 [DATA LIST NOTABLE LIST /v1 * v2 * dep * vn *.
223 /STATISTICS descriptives homogeneity
228 AT_DATA([oneway-missing2.sps],
229 [DATA LIST NOTABLE LIST /v1 * v2 * dep * vn * .
251 /STATISTICS descriptives homogeneity
258 AT_CHECK([pspp -O format=csv oneway-missing1.sps > first.out], [0])
260 AT_CHECK([pspp -O format=csv oneway-missing2.sps > second.out], [0])
262 AT_CHECK([diff first.out second.out], [0], [])
264 dnl Now a test with missing values in the independent variable
265 AT_DATA([oneway-missing3.sps],
266 [DATA LIST NOTABLE LIST /v1 * v2 * dep * vn * .
288 /STATISTICS descriptives homogeneity
293 AT_CHECK([pspp -O format=csv oneway-missing3.sps > third.out], [0])
295 AT_CHECK([diff first.out third.out], [0], [])
303 AT_SETUP([ONEWAY descriptives subcommand])
304 AT_KEYWORDS([categorical categoricals])
306 AT_DATA([oneway-descriptives.sps],
307 [DATA LIST NOTABLE LIST /QUALITY * BRAND * .
329 /STATISTICS descriptives
333 AT_CHECK([pspp -O format=csv oneway-descriptives.sps], [0],
335 ,,,,,,95% Confidence Interval for Mean,,,
336 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
337 QUALITY,11.00,5,12.20,1.30,.58,10.58,13.82,11.00,14.00
338 ,25.00,5,13.20,1.30,.58,11.58,14.82,12.00,15.00
339 ,301.00,5,15.00,1.58,.71,13.04,16.96,13.00,17.00
340 ,Total,15,13.47,1.77,.46,12.49,14.45,11.00,17.00
343 ,,Sum of Squares,df,Mean Square,F,Sig.
344 QUALITY,Between Groups,20.13,2,10.07,5.12,.025
345 ,Within Groups,23.60,12,1.97,,
353 AT_SETUP([ONEWAY homogeneity subcommand])
354 AT_KEYWORDS([categorical categoricals])
356 AT_DATA([oneway-homogeneity.sps],
357 [DATA LIST NOTABLE LIST /QUALITY * BRAND * .
379 /STATISTICS homogeneity
383 AT_CHECK([pspp -O format=csv oneway-homogeneity.sps], [0],
384 [Table: Test of Homogeneity of Variances
385 ,Levene Statistic,df1,df2,Sig.
386 QUALITY,.09,2,12,.913
389 ,,Sum of Squares,df,Mean Square,F,Sig.
390 QUALITY,Between Groups,20.13,2,10.07,5.12,.025
391 ,Within Groups,23.60,12,1.97,,
399 AT_SETUP([ONEWAY multiple variables])
400 AT_KEYWORDS([categorical categoricals])
401 dnl check that everything works ok when several different dependent variables are specified.
402 dnl This of course does not mean that we're doing a multivariate analysis. It's just like
403 dnl running several tests at once.
404 AT_DATA([multivar.sps],
405 [DATA LIST notable LIST /x * y * z * g *.
434 /STATISTICS = DESCRIPTIVES HOMOGENEITY
440 AT_CHECK([pspp -o pspp.csv multivar.sps])
442 dnl Some machines return 3.88 instead of 3.87 below (see bug #31611).
443 AT_CHECK([sed 's/^,Within Groups,3.88/,Within Groups,3.87/' pspp.csv], [0], [dnl
445 ,,,,,,95% Confidence Interval for Mean,,,
446 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
447 x,10.00,3,3.67,4.62,2.67,-7.81,15.14,1.00,9.00
448 ,20.00,5,.80,.45,.20,.24,1.36,.00,1.00
449 ,30.00,8,.88,.64,.23,.34,1.41,.00,2.00
450 ,40.00,8,4.00,3.42,1.21,1.14,6.86,1.00,9.00
451 ,Total,24,2.25,2.83,.58,1.05,3.45,.00,9.00
452 y,10.00,3,1.00,.00,.00,1.00,1.00,1.00,1.00
453 ,20.00,5,1.00,.00,.00,1.00,1.00,1.00,1.00
454 ,30.00,8,1.50,.53,.19,1.05,1.95,1.00,2.00
455 ,40.00,8,2.38,.52,.18,1.94,2.81,2.00,3.00
456 ,Total,24,1.63,.71,.15,1.32,1.93,1.00,3.00
457 z,10.00,3,3.67,4.73,2.73,-8.07,15.41,.00,9.00
458 ,20.00,5,3.40,2.70,1.21,.05,6.75,1.00,8.00
459 ,30.00,8,5.00,3.21,1.13,2.32,7.68,.00,9.00
460 ,40.00,8,5.50,2.45,.87,3.45,7.55,2.00,9.00
461 ,Total,24,4.67,2.99,.61,3.40,5.93,.00,9.00
463 Table: Test of Homogeneity of Variances
464 ,Levene Statistic,df1,df2,Sig.
470 ,,Sum of Squares,df,Mean Square,F,Sig.
471 x,Between Groups,56.16,3,18.72,2.92,.059
472 ,Within Groups,128.34,20,6.42,,
474 y,Between Groups,7.75,3,2.58,13.33,.000
475 ,Within Groups,3.87,20,.19,,
477 z,Between Groups,17.47,3,5.82,.62,.610
478 ,Within Groups,187.87,20,9.39,,
481 Table: Contrast Coefficients
483 ,,10.00,20.00,30.00,40.00
487 Table: Contrast Tests
488 ,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
489 x,Assume equal variances,1,-7.40,6.67,1.11,20,.280
490 ,,2,6.26,12.32,.51,20,.617
491 ,Does not assume equal,1,-7.40,10.04,-.74,4.53,.497
492 ,,2,6.26,5.85,1.07,2.87,.366
493 y,Assume equal variances,1,-6.88,1.16,5.94,20,.000
494 ,,2,3.50,2.14,1.63,20,.118
495 ,Does not assume equal,1,-6.88,.91,-7.51,7.00,.000
496 ,,2,3.50,1.32,2.65,7.00,.033
497 z,Assume equal variances,1,-9.70,8.07,1.20,20,.243
498 ,,2,11.73,14.91,.79,20,.440
499 ,Does not assume equal,1,-9.70,9.57,-1.01,3.64,.373
500 ,,2,11.73,14.53,.81,9.88,.438
507 dnl Tests that everything treats weights properly
508 AT_SETUP([ONEWAY vs. weights])
509 AT_KEYWORDS([categorical categoricals])
511 AT_DATA([oneway-unweighted.sps],
512 [DATA LIST NOTABLE LIST /QUALITY * BRAND * W *.
539 /STATISTICS descriptives homogeneity
543 AT_CHECK([pspp -o pspp-unweighted.csv oneway-unweighted.sps], [0], [ignore], [ignore])
545 AT_DATA([oneway-weighted.sps],
546 [DATA LIST NOTABLE LIST /QUALITY * BRAND * W *.
568 /STATISTICS descriptives homogeneity
572 AT_CHECK([pspp -o pspp-weighted.csv oneway-weighted.sps], [0], [ignore], [ignore])
574 AT_CHECK([diff pspp-weighted.csv pspp-unweighted.csv], [0])
580 AT_SETUP([ONEWAY posthoc LSD and BONFERRONI])
581 AT_KEYWORDS([categorical categoricals])
582 AT_DATA([oneway-pig.sps],[dnl
584 data list notable list /pigmentation * family *.
609 oneway pigmentation by family
610 /statistics = descriptives
611 /posthoc = lsd bonferroni alpha (0.05)
615 AT_CHECK([pspp -O format=csv oneway-pig.sps], [0],
617 ,,,,,,95% Confidence Interval for Mean,,,
618 ,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
619 pigmentation,1.000,5,38.600,2.702,1.208,35.245,41.955,36.000,43.000
620 ,2.000,5,46.000,1.732,.775,43.849,48.151,43.000,47.000
621 ,3.000,5,46.400,4.336,1.939,41.016,51.784,40.000,50.000
622 ,4.000,5,52.400,4.506,2.015,46.806,57.994,45.000,56.000
623 ,Total,20,45.850,5.967,1.334,43.057,48.643,36.000,56.000
626 ,,Sum of Squares,df,Mean Square,F,Sig.
627 pigmentation,Between Groups,478.950,3,159.650,12.927,.000
628 ,Within Groups,197.600,16,12.350,,
631 Table: Multiple Comparisons (pigmentation)
632 ,,,Mean Difference,,,95% Confidence Interval,
633 ,(I) family,(J) family,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
634 LSD,1.000,2.000,-7.400,2.223,.004,-12.112,-2.688
635 ,,3.000,-7.800,2.223,.003,-12.512,-3.088
636 ,,4.000,-13.800,2.223,.000,-18.512,-9.088
637 ,2.000,1.000,7.400,2.223,.004,2.688,12.112
638 ,,3.000,-.400,2.223,.859,-5.112,4.312
639 ,,4.000,-6.400,2.223,.011,-11.112,-1.688
640 ,3.000,1.000,7.800,2.223,.003,3.088,12.512
641 ,,2.000,.400,2.223,.859,-4.312,5.112
642 ,,4.000,-6.000,2.223,.016,-10.712,-1.288
643 ,4.000,1.000,13.800,2.223,.000,9.088,18.512
644 ,,2.000,6.400,2.223,.011,1.688,11.112
645 ,,3.000,6.000,2.223,.016,1.288,10.712
646 Bonferroni,1.000,2.000,-7.400,2.223,.025,-14.086,-.714
647 ,,3.000,-7.800,2.223,.017,-14.486,-1.114
648 ,,4.000,-13.800,2.223,.000,-20.486,-7.114
649 ,2.000,1.000,7.400,2.223,.025,.714,14.086
650 ,,3.000,-.400,2.223,1.000,-7.086,6.286
651 ,,4.000,-6.400,2.223,.065,-13.086,.286
652 ,3.000,1.000,7.800,2.223,.017,1.114,14.486
653 ,,2.000,.400,2.223,1.000,-6.286,7.086
654 ,,4.000,-6.000,2.223,.095,-12.686,.686
655 ,4.000,1.000,13.800,2.223,.000,7.114,20.486
656 ,,2.000,6.400,2.223,.065,-.286,13.086
657 ,,3.000,6.000,2.223,.095,-.686,12.686
663 AT_SETUP([ONEWAY posthoc Tukey HSD and Games-Howell])
664 AT_KEYWORDS([categorical categoricals])
665 AT_DATA([oneway-tukey.sps],[dnl
667 data list notable list /libido * dose *.
686 variable label dose 'Dose of Viagra'.
688 add value labels dose 0 'Placebo' 1 '1 Dose' 2 '2 Doses'.
690 oneway libido by dose
694 AT_CHECK([pspp -O format=csv oneway-tukey.sps], [0],
696 ,,Sum of Squares,df,Mean Square,F,Sig.
697 libido,Between Groups,20.133,2,10.067,5.119,.025
698 ,Within Groups,23.600,12,1.967,,
701 Table: Multiple Comparisons (libido)
702 ,,,Mean Difference,,,95% Confidence Interval,
703 ,(I) Dose of Viagra,(J) Dose of Viagra,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
704 Tukey HSD,Placebo,1 Dose,-1.000,.887,.516,-3.366,1.366
705 ,,2 Doses,-2.800,.887,.021,-5.166,-.434
706 ,1 Dose,Placebo,1.000,.887,.516,-1.366,3.366
707 ,,2 Doses,-1.800,.887,.147,-4.166,.566
708 ,2 Doses,Placebo,2.800,.887,.021,.434,5.166
709 ,,1 Dose,1.800,.887,.147,-.566,4.166
710 Games-Howell,Placebo,1 Dose,-1.000,.887,.479,-3.356,1.356
711 ,,2 Doses,-2.800,.887,.039,-5.439,-.161
712 ,1 Dose,Placebo,1.000,.887,.479,-1.356,3.356
713 ,,2 Doses,-1.800,.887,.185,-4.439,.839
714 ,2 Doses,Placebo,2.800,.887,.039,.161,5.439
715 ,,1 Dose,1.800,.887,.185,-.839,4.439
720 AT_SETUP([ONEWAY posthoc Sidak])
721 AT_KEYWORDS([categorical categoricals])
722 AT_DATA([oneway-sidak.sps],[dnl
725 DATA LIST notable LIST /program score.
755 AT_CHECK([pspp -O format=csv oneway-sidak.sps], [0],
757 ,,Sum of Squares,df,Mean Square,F,Sig.
758 score,Between Groups,54.9500,3,18.3167,7.0449,.003
759 ,Within Groups,41.6000,16,2.6000,,
762 Table: Multiple Comparisons (score)
763 ,,,Mean Difference,,,95% Confidence Interval,
764 ,(I) program,(J) program,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
765 Šidák,1.0000,2.0000,3.0000,1.0198,.056,-.0575,6.0575
766 ,,3.0000,-.4000,1.0198,.999,-3.4575,2.6575
767 ,,4.0000,3.2000,1.0198,.038,.1425,6.2575
768 ,2.0000,1.0000,-3.0000,1.0198,.056,-6.0575,.0575
769 ,,3.0000,-3.4000,1.0198,.025,-6.4575,-.3425
770 ,,4.0000,.2000,1.0198,1.000,-2.8575,3.2575
771 ,3.0000,1.0000,.4000,1.0198,.999,-2.6575,3.4575
772 ,,2.0000,3.4000,1.0198,.025,.3425,6.4575
773 ,,4.0000,3.6000,1.0198,.017,.5425,6.6575
774 ,4.0000,1.0000,-3.2000,1.0198,.038,-6.2575,-.1425
775 ,,2.0000,-.2000,1.0198,1.000,-3.2575,2.8575
776 ,,3.0000,-3.6000,1.0198,.017,-6.6575,-.5425
781 AT_SETUP([ONEWAY posthoc Scheffe])
782 AT_KEYWORDS([categorical categoricals])
783 AT_DATA([oneway-scheffe.sps],[dnl
785 data list notable list /usage * group *.
829 variable label usage 'Days of Use'.
831 add value labels group 0 'none' 1 'one' 2 'two' 3 'three' 4 'four'.
833 oneway usage by group
837 AT_CHECK([pspp -O format=csv oneway-scheffe.sps], [0],
839 ,,Sum of Squares,df,Mean Square,F,Sig.
840 Days of Use,Between Groups,555.275,3,185.092,6.663,.001
841 ,Within Groups,1000.100,36,27.781,,
842 ,Total,1555.375,39,,,
844 Table: Multiple Comparisons (Days of Use)
845 ,,,Mean Difference,,,95% Confidence Interval,
846 ,(I) group,(J) group,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
847 Scheffé,one,two,3.800,2.357,.467,-3.112,10.712
848 ,,three,10.300,2.357,.001,3.388,17.212
849 ,,four,6.000,2.357,.110,-.912,12.912
850 ,two,one,-3.800,2.357,.467,-10.712,3.112
851 ,,three,6.500,2.357,.072,-.412,13.412
852 ,,four,2.200,2.357,.832,-4.712,9.112
853 ,three,one,-10.300,2.357,.001,-17.212,-3.388
854 ,,two,-6.500,2.357,.072,-13.412,.412
855 ,,four,-4.300,2.357,.358,-11.212,2.612
856 ,four,one,-6.000,2.357,.110,-12.912,.912
857 ,,two,-2.200,2.357,.832,-9.112,4.712
858 ,,three,4.300,2.357,.358,-2.612,11.212
864 AT_SETUP([ONEWAY bad contrast count])
865 AT_KEYWORDS([categorical categoricals])
867 AT_DATA([oneway-bad-contrast.sps],[dnl
868 DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
880 ONEWAY /VARIABLES= height weight temperature BY sex
889 AT_CHECK([pspp -O format=csv oneway-bad-contrast.sps], [0], [dnl
890 "oneway-bad-contrast.sps:18: warning: ONEWAY: In contrast list 3, the number of coefficients (3) does not equal the number of groups (2). This contrast list will be ignored."
893 ,,Sum of Squares,df,Mean Square,F,Sig.
894 height,Between Groups,92629.63,1,92629.63,120.77,.000
895 ,Within Groups,4601.87,6,766.98,,
897 weight,Between Groups,2451.65,1,2451.65,174.59,.000
898 ,Within Groups,84.25,6,14.04,,
900 temperature,Between Groups,1.80,1,1.80,.13,.733
901 ,Within Groups,84.55,6,14.09,,
904 Table: Contrast Coefficients
911 Table: Contrast Tests
912 ,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
913 height,Assume equal variances,1,-222.27,20.23,10.99,6,.000
914 ,,2,-666.80,60.68,10.99,6,.000
915 ,,3,-2000.40,182.03,10.99,6,.000
916 ,Does not assume equal,1,-222.27,27.67,-8.03,2.00,.015
917 ,,2,-666.80,83.02,-8.03,2.00,.015
918 ,,3,-2000.40,249.07,-8.03,2.00,.015
919 weight,Assume equal variances,1,-36.16,2.74,13.21,6,.000
920 ,,2,-108.48,8.21,13.21,6,.000
921 ,,3,-325.44,24.63,13.21,6,.000
922 ,Does not assume equal,1,-36.16,2.19,-16.48,5.42,.000
923 ,,2,-108.48,6.58,-16.48,5.42,.000
924 ,,3,-325.44,19.75,-16.48,5.42,.000
925 temperature,Assume equal variances,1,-.98,2.74,.36,6,.733
926 ,,2,-2.94,8.22,.36,6,.733
927 ,,3,-8.83,24.67,.36,6,.733
928 ,Does not assume equal,1,-.98,2.07,-.47,4.19,.660
929 ,,2,-2.94,6.22,-.47,4.19,.660
930 ,,3,-8.83,18.66,-.47,4.19,.660
936 AT_SETUP([ONEWAY crash on single category independent variable])
937 AT_KEYWORDS([categorical categoricals])
938 AT_DATA([crash.sps],[
952 AT_CHECK([pspp -O format=csv crash.sps], [0], [ignore])
958 AT_SETUP([ONEWAY crash on missing dependent variable])
959 AT_KEYWORDS([categorical categoricals])
960 AT_DATA([crash2.sps],[dnl
961 data list notable list /dv1 * dv2 * y * .
973 /VARIABLES= dv1 dv2 BY y
974 /STATISTICS = DESCRIPTIVES
975 /POSTHOC = BONFERRONI LSD SCHEFFE SIDAK TUKEY
980 AT_CHECK([pspp -O format=csv crash2.sps], [0], [ignore])
987 AT_SETUP([ONEWAY Games-Howell test with few cases])
988 AT_KEYWORDS([categorical categoricals])
989 AT_DATA([crash3.sps],[dnl
990 data list notable list /dv * y * .
1005 AT_CHECK([pspp -O format=csv crash3.sps], [0], [ignore])
1010 AT_SETUP([ONEWAY Crash on empty data])
1011 AT_KEYWORDS([categorical categoricals])
1012 AT_DATA([crash4.sps],[dnl
1013 DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
1019 ONEWAY /VARIABLES= height weight temperature BY sex
1027 AT_CHECK([pspp -O format=csv crash4.sps], [0], [ignore])
1033 AT_SETUP([ONEWAY Crash on invalid dependent variable])
1034 AT_KEYWORDS([categorical categoricals])
1035 AT_DATA([crash5.sps],[dnl
1036 data list notable list /a * b *.
1047 AT_CHECK([pspp -O format=csv crash5.sps], [1], [ignore])
1054 AT_SETUP([ONEWAY Crash on unterminated string])
1055 AT_KEYWORDS([categorical categoricals])
1057 AT_DATA([crash6.sps], [dnl
1058 DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
1064 ONEWAY /VARIABLES= height weight temperature BY sex
1069 AT_CHECK([pspp -O format=csv crash6.sps], [1], [ignore])