+dnl PSPP - a program for statistical analysis.
+dnl Copyright (C) 2017 Free Software Foundation, Inc.
+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 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 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_BANNER([ONEWAY procedure])
AT_SETUP([ONEWAY basic operation])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway.sps],
[DATA LIST NOTABLE LIST /QUALITY * BRAND * .
BEGIN DATA
.
])
-AT_CHECK([pspp -O format=csv oneway.sps], [0],
-[Table: Descriptives
+AT_CHECK([pspp -O format=csv oneway.sps], [0], [dnl
+Table: Descriptives
,,,,,,95% Confidence Interval for Mean,,,
,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
Breaking Strain,Aspeger,5,2.20,1.30,.58,.58,3.82,1.00,4.00
Table: Test of Homogeneity of Variances
,Levene Statistic,df1,df2,Sig.
-Breaking Strain,.09,2,12,.91
+Breaking Strain,.09,2,12,.913
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-Breaking Strain,Between Groups,20.13,2,10.07,5.12,.02
+Breaking Strain,Between Groups,20.13,2,10.07,5.12,.025
,Within Groups,23.60,12,1.97,,
,Total,43.73,14,,,
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,3.80,1.54,2.47,12,.03
-,,2,1.80,.89,2.03,12,.07
-,Does not assume equal,1,3.80,1.48,2.56,8.74,.03
-,,2,1.80,.92,1.96,7.72,.09
+Breaking Strain,Assume equal variances,1,3.80,1.54,2.47,12,.029
+,,2,1.80,.89,2.03,12,.065
+,Does not assume equal,1,3.80,1.48,2.56,8.74,.031
+,,2,1.80,.92,1.96,7.72,.086
])
AT_CLEANUP
AT_SETUP([ONEWAY with splits])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-splits.sps],
[DATA LIST NOTABLE LIST /QUALITY * BRAND * S *.
BEGIN DATA
Table: Test of Homogeneity of Variances
,Levene Statistic,df1,df2,Sig.
-Breaking Strain,1.09,1,5,.35
+Breaking Strain,1.09,1,5,.345
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-Breaking Strain,Between Groups,2.41,1,2.41,1.07,.35
+Breaking Strain,Between Groups,2.41,1,2.41,1.07,.349
,Within Groups,11.30,5,2.26,,
,Total,13.71,6,,,
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,2.60,2.52,1.03,5,.35
-,,2,1.30,1.26,1.03,5,.35
-,Does not assume equal,1,2.60,3.22,.81,1.32,.54
-,,2,1.30,1.61,.81,1.32,.54
+Breaking Strain,Assume equal variances,1,2.60,2.52,1.03,5,.349
+,,2,1.30,1.26,1.03,5,.349
+,Does not assume equal,1,2.60,3.22,.81,1.32,.539
+,,2,1.30,1.61,.81,1.32,.539
Variable,Value,Label
S,2.00,
Table: Test of Homogeneity of Variances
,Levene Statistic,df1,df2,Sig.
-Breaking Strain,.92,1,6,.37
+Breaking Strain,.92,1,6,.374
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-Breaking Strain,Between Groups,7.50,1,7.50,3.75,.10
+Breaking Strain,Between Groups,7.50,1,7.50,3.75,.101
,Within Groups,12.00,6,2.00,,
,Total,19.50,7,,,
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-Breaking Strain,Assume equal variances,1,4.00,2.07,1.94,6,.10
-,,2,2.00,1.03,1.94,6,.10
-,Does not assume equal,1,4.00,1.83,2.19,5.88,.07
-,,2,2.00,.91,2.19,5.88,.07
+Breaking Strain,Assume equal variances,1,4.00,2.07,1.94,6,.101
+,,2,2.00,1.03,1.94,6,.101
+,Does not assume equal,1,4.00,1.83,2.19,5.88,.072
+,,2,2.00,.91,2.19,5.88,.072
])
AT_CLEANUP
AT_SETUP([ONEWAY with missing values])
+AT_KEYWORDS([categorical categoricals])
dnl Check that missing are treated properly
AT_DATA([oneway-missing1.sps],
[DATA LIST NOTABLE LIST /v1 * v2 * dep * vn *.
AT_SETUP([ONEWAY descriptives subcommand])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-descriptives.sps],
[DATA LIST NOTABLE LIST /QUALITY * BRAND * .
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-QUALITY,Between Groups,20.13,2,10.07,5.12,.02
+QUALITY,Between Groups,20.13,2,10.07,5.12,.025
,Within Groups,23.60,12,1.97,,
,Total,43.73,14,,,
])
AT_SETUP([ONEWAY homogeneity subcommand])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-homogeneity.sps],
[DATA LIST NOTABLE LIST /QUALITY * BRAND * .
AT_CHECK([pspp -O format=csv oneway-homogeneity.sps], [0],
[Table: Test of Homogeneity of Variances
,Levene Statistic,df1,df2,Sig.
-QUALITY,.09,2,12,.91
+QUALITY,.09,2,12,.913
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-QUALITY,Between Groups,20.13,2,10.07,5.12,.02
+QUALITY,Between Groups,20.13,2,10.07,5.12,.025
,Within Groups,23.60,12,1.97,,
,Total,43.73,14,,,
])
AT_SETUP([ONEWAY multiple variables])
+AT_KEYWORDS([categorical categoricals])
dnl check that everything works ok when several different dependent variables are specified.
dnl This of course does not mean that we're doing a multivariate analysis. It's just like
dnl running several tests at once.
/CONTRAST 2 -9 7 0
.
])
+
AT_CHECK([pspp -o pspp.csv multivar.sps])
+
dnl Some machines return 3.88 instead of 3.87 below (see bug #31611).
-AT_CHECK([sed 's/^,Within Groups,3.88/,Within Groups,3.87/' pspp.csv], [0],
-[Table: Descriptives
+AT_CHECK([sed 's/^,Within Groups,3.88/,Within Groups,3.87/' pspp.csv], [0], [dnl
+Table: Descriptives
,,,,,,95% Confidence Interval for Mean,,,
,,N,Mean,Std. Deviation,Std. Error,Lower Bound,Upper Bound,Minimum,Maximum
x,10.00,3,3.67,4.62,2.67,-7.81,15.14,1.00,9.00
Table: Test of Homogeneity of Variances
,Levene Statistic,df1,df2,Sig.
-x,18.76,3,20,.00
-y,71.41,3,20,.00
-z,.89,3,20,.46
+x,18.76,3,20,.000
+y,71.41,3,20,.000
+z,.89,3,20,.463
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-x,Between Groups,56.16,3,18.72,2.92,.06
+x,Between Groups,56.16,3,18.72,2.92,.059
,Within Groups,128.34,20,6.42,,
,Total,184.50,23,,,
-y,Between Groups,7.75,3,2.58,13.33,.00
+y,Between Groups,7.75,3,2.58,13.33,.000
,Within Groups,3.87,20,.19,,
,Total,11.63,23,,,
-z,Between Groups,17.47,3,5.82,.62,.61
+z,Between Groups,17.47,3,5.82,.62,.610
,Within Groups,187.87,20,9.39,,
,Total,205.33,23,,,
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-x,Assume equal variances,1,-7.40,6.67,1.11,20,.28
-,,2,6.26,12.32,.51,20,.62
-,Does not assume equal,1,-7.40,10.04,-.74,4.53,1.50
-,,2,6.26,5.85,1.07,2.87,.37
-y,Assume equal variances,1,-6.88,1.16,5.94,20,.00
-,,2,3.50,2.14,1.63,20,.12
-,Does not assume equal,1,-6.88,.91,-7.51,7.00,2.00
-,,2,3.50,1.32,2.65,7.00,.03
-z,Assume equal variances,1,-9.70,8.07,1.20,20,.24
-,,2,11.73,14.91,.79,20,.44
-,Does not assume equal,1,-9.70,9.57,-1.01,3.64,1.63
-,,2,11.73,14.53,.81,9.88,.44
+x,Assume equal variances,1,-7.40,6.67,1.11,20,.280
+,,2,6.26,12.32,.51,20,.617
+,Does not assume equal,1,-7.40,10.04,-.74,4.53,.497
+,,2,6.26,5.85,1.07,2.87,.366
+y,Assume equal variances,1,-6.88,1.16,5.94,20,.000
+,,2,3.50,2.14,1.63,20,.118
+,Does not assume equal,1,-6.88,.91,-7.51,7.00,.000
+,,2,3.50,1.32,2.65,7.00,.033
+z,Assume equal variances,1,-9.70,8.07,1.20,20,.243
+,,2,11.73,14.91,.79,20,.440
+,Does not assume equal,1,-9.70,9.57,-1.01,3.64,.373
+,,2,11.73,14.53,.81,9.88,.438
])
AT_CLEANUP
dnl Tests that everything treats weights properly
AT_SETUP([ONEWAY vs. weights])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-unweighted.sps],
[DATA LIST NOTABLE LIST /QUALITY * BRAND * W *.
AT_SETUP([ONEWAY posthoc LSD and BONFERRONI])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-pig.sps],[dnl
SET FORMAT F12.3.
data list notable list /pigmentation * family *.
AT_SETUP([ONEWAY posthoc Tukey HSD and Games-Howell])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-tukey.sps],[dnl
set format = f11.3.
data list notable list /libido * dose *.
AT_CLEANUP
AT_SETUP([ONEWAY posthoc Sidak])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-sidak.sps],[dnl
SET FORMAT F20.4.
AT_CHECK([pspp -O format=csv oneway-sidak.sps], [0],
[Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-score,Between Groups,54.9500,3,18.3167,7.0449,.0031
+score,Between Groups,54.9500,3,18.3167,7.0449,.003
,Within Groups,41.6000,16,2.6000,,
,Total,96.5500,19,,,
Table: Multiple Comparisons (score)
,,,Mean Difference,,,95% Confidence Interval,
,(I) program,(J) program,(I - J),Std. Error,Sig.,Lower Bound,Upper Bound
-Šidák,1.0000,2.0000,3.0000,1.0198,.0561,-.0575,6.0575
-,,3.0000,-.4000,1.0198,.9993,-3.4575,2.6575
-,,4.0000,3.2000,1.0198,.0375,.1425,6.2575
-,2.0000,1.0000,-3.0000,1.0198,.0561,-6.0575,.0575
-,,3.0000,-3.4000,1.0198,.0250,-6.4575,-.3425
-,,4.0000,.2000,1.0198,1.0000,-2.8575,3.2575
-,3.0000,1.0000,.4000,1.0198,.9993,-2.6575,3.4575
-,,2.0000,3.4000,1.0198,.0250,.3425,6.4575
-,,4.0000,3.6000,1.0198,.0166,.5425,6.6575
-,4.0000,1.0000,-3.2000,1.0198,.0375,-6.2575,-.1425
-,,2.0000,-.2000,1.0198,1.0000,-3.2575,2.8575
-,,3.0000,-3.6000,1.0198,.0166,-6.6575,-.5425
+Šidák,1.0000,2.0000,3.0000,1.0198,.056,-.0575,6.0575
+,,3.0000,-.4000,1.0198,.999,-3.4575,2.6575
+,,4.0000,3.2000,1.0198,.038,.1425,6.2575
+,2.0000,1.0000,-3.0000,1.0198,.056,-6.0575,.0575
+,,3.0000,-3.4000,1.0198,.025,-6.4575,-.3425
+,,4.0000,.2000,1.0198,1.000,-2.8575,3.2575
+,3.0000,1.0000,.4000,1.0198,.999,-2.6575,3.4575
+,,2.0000,3.4000,1.0198,.025,.3425,6.4575
+,,4.0000,3.6000,1.0198,.017,.5425,6.6575
+,4.0000,1.0000,-3.2000,1.0198,.038,-6.2575,-.1425
+,,2.0000,-.2000,1.0198,1.000,-3.2575,2.8575
+,,3.0000,-3.6000,1.0198,.017,-6.6575,-.5425
])
AT_CLEANUP
AT_SETUP([ONEWAY posthoc Scheffe])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-scheffe.sps],[dnl
set format = f11.3.
data list notable list /usage * group *.
AT_SETUP([ONEWAY bad contrast count])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([oneway-bad-contrast.sps],[dnl
DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
Table: ANOVA
,,Sum of Squares,df,Mean Square,F,Sig.
-height,Between Groups,92629.63,1,92629.63,120.77,.00
+height,Between Groups,92629.63,1,92629.63,120.77,.000
,Within Groups,4601.87,6,766.98,,
,Total,97231.50,7,,,
-weight,Between Groups,2451.65,1,2451.65,174.59,.00
+weight,Between Groups,2451.65,1,2451.65,174.59,.000
,Within Groups,84.25,6,14.04,,
,Total,2535.90,7,,,
-temperature,Between Groups,1.80,1,1.80,.13,.73
+temperature,Between Groups,1.80,1,1.80,.13,.733
,Within Groups,84.55,6,14.09,,
,Total,86.36,7,,,
Table: Contrast Tests
,,Contrast,Value of Contrast,Std. Error,t,df,Sig. (2-tailed)
-height,Assume equal variances,1,-222.27,20.23,10.99,6,.00
-,,2,-666.80,60.68,10.99,6,.00
-,,3,-2000.40,182.03,10.99,6,.00
-,Does not assume equal,1,-222.27,27.67,-8.03,2.00,1.98
-,,2,-666.80,83.02,-8.03,2.00,1.98
-,,3,-2000.40,249.07,-8.03,2.00,1.98
-weight,Assume equal variances,1,-36.16,2.74,13.21,6,.00
-,,2,-108.48,8.21,13.21,6,.00
-,,3,-325.44,24.63,13.21,6,.00
-,Does not assume equal,1,-36.16,2.19,-16.48,5.42,2.00
-,,2,-108.48,6.58,-16.48,5.42,2.00
-,,3,-325.44,19.75,-16.48,5.42,2.00
-temperature,Assume equal variances,1,-.98,2.74,.36,6,.73
-,,2,-2.94,8.22,.36,6,.73
-,,3,-8.83,24.67,.36,6,.73
-,Does not assume equal,1,-.98,2.07,-.47,4.19,1.34
-,,2,-2.94,6.22,-.47,4.19,1.34
-,,3,-8.83,18.66,-.47,4.19,1.34
+height,Assume equal variances,1,-222.27,20.23,10.99,6,.000
+,,2,-666.80,60.68,10.99,6,.000
+,,3,-2000.40,182.03,10.99,6,.000
+,Does not assume equal,1,-222.27,27.67,-8.03,2.00,.015
+,,2,-666.80,83.02,-8.03,2.00,.015
+,,3,-2000.40,249.07,-8.03,2.00,.015
+weight,Assume equal variances,1,-36.16,2.74,13.21,6,.000
+,,2,-108.48,8.21,13.21,6,.000
+,,3,-325.44,24.63,13.21,6,.000
+,Does not assume equal,1,-36.16,2.19,-16.48,5.42,.000
+,,2,-108.48,6.58,-16.48,5.42,.000
+,,3,-325.44,19.75,-16.48,5.42,.000
+temperature,Assume equal variances,1,-.98,2.74,.36,6,.733
+,,2,-2.94,8.22,.36,6,.733
+,,3,-8.83,24.67,.36,6,.733
+,Does not assume equal,1,-.98,2.07,-.47,4.19,.660
+,,2,-2.94,6.22,-.47,4.19,.660
+,,3,-8.83,18.66,-.47,4.19,.660
])
AT_CLEANUP
AT_SETUP([ONEWAY crash on single category independent variable])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([crash.sps],[
input program.
loop #i = 1 to 10.
AT_SETUP([ONEWAY crash on missing dependent variable])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([crash2.sps],[dnl
data list notable list /dv1 * dv2 * y * .
begin data.
AT_SETUP([ONEWAY Games-Howell test with few cases])
+AT_KEYWORDS([categorical categoricals])
AT_DATA([crash3.sps],[dnl
data list notable list /dv * y * .
begin data.
AT_CHECK([pspp -O format=csv crash3.sps], [0], [ignore])
AT_CLEANUP
+
+
+AT_SETUP([ONEWAY Crash on empty data])
+AT_KEYWORDS([categorical categoricals])
+AT_DATA([crash4.sps],[dnl
+DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
+BEGIN DATA.
+1801 . . 0
+1606 . . 1
+END DATA.
+
+ONEWAY /VARIABLES= height weight temperature BY sex
+ /CONTRAST = -1 1
+ /CONTRAST = -3 3
+ /CONTRAST = 2 -2 1
+ /CONTRAST = -9 9
+ .
+])
+
+AT_CHECK([pspp -O format=csv crash4.sps], [0], [ignore])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([ONEWAY Crash on invalid dependent variable])
+AT_KEYWORDS([categorical categoricals])
+AT_DATA([crash5.sps],[dnl
+data list notable list /a * b *.
+begin data.
+3 0
+2 0
+6 2
+end data.
+
+oneway a"by b.
+
+])
+
+AT_CHECK([pspp -O format=csv crash5.sps], [1], [ignore])
+
+AT_CLEANUP
+
+
+
+
+AT_SETUP([ONEWAY Crash on unterminated string])
+AT_KEYWORDS([categorical categoricals])
+
+AT_DATA([crash6.sps], [dnl
+DATA LIST NOTABLE LIST /height * weight * temperature * sex *.
+BEGIN DATA.
+1801 . . 0
+1606 . 0 . 1
+END DATA.
+
+ONEWAY /VARIABLES= height weight temperature BY sex
+ /CONTRAST =" 2 -2 1
+ .
+])
+
+AT_CHECK([pspp -O format=csv crash6.sps], [1], [ignore])
+
+AT_CLEANUP
projects / pspp / blobdiff