+dnl PSPP - a program for statistical analysis.
+dnl Copyright (C) 2017, 2022 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([NPAR TESTS])
-AT_SETUP([NPAR TESTS BINOMIAL, P < 0.5; N1/N2 < 1])
+AT_SETUP([NPAR TESTS BINOMIAL P < 0.5; N1/N2 < 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1.000,6.000,.286,.300,.551
-,Group2,2.000,15.000,.714,,
+x,Group 1,1.000,6.000,.286,.300,.551
+,Group 2,2.000,15.000,.714,,
,Total,,21.000,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P < 0.5; N1/N2 > 1])
+AT_SETUP([NPAR TESTS BINOMIAL P < 0.5; N1/N2 > 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,7,.538,.400,.229
-,Group2,2,6,.462,,
+x,Group 1,1,7,.538,.400,.229
+,Group 2,2,6,.462,,
,Total,,13,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P < 0.5; N1/N2 = 1])
+AT_SETUP([NPAR TESTS BINOMIAL P < 0.5; N1/N2 = 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,8,.500,.400,.284
-,Group2,2,8,.500,,
+x,Group 1,1,8,.500,.400,.284
+,Group 2,2,8,.500,,
,Total,,16,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P > 0.5; N1/N2 < 1])
+AT_SETUP([NPAR TESTS BINOMIAL P > 0.5; N1/N2 < 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.478,.600,.164
-,Group2,2,12,.522,,
+x,Group 1,1,11,.478,.600,.164
+,Group 2,2,12,.522,,
,Total,,23,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P > 0.5; N1/N2 > 1])
+AT_SETUP([NPAR TESTS BINOMIAL P > 0.5; N1/N2 > 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.550,.600,.404
-,Group2,2,9,.450,,
+x,Group 1,1,11,.550,.600,.404
+,Group 2,2,9,.450,,
,Total,,20,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P > 0.5; N1/N2 = 1])
+AT_SETUP([NPAR TESTS BINOMIAL P > 0.5; N1/N2 = 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (1-tailed)
-x,Group1,1,11,.500,.600,.228
-,Group2,2,11,.500,,
+x,Group 1,1,11,.500,.600,.228
+,Group 2,2,11,.500,,
,Total,,22,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P = 0.5; N1/N2 < 1])
+AT_SETUP([NPAR TESTS BINOMIAL P = 0.5; N1/N2 < 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,8,.348,.500,.210
-,Group2,2,15,.652,,
+x,Group 1,1,8,.348,.500,.210
+,Group 2,2,15,.652,,
,Total,,23,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P = 0.5; N1/N2 > 1])
+AT_SETUP([NPAR TESTS BINOMIAL P = 0.5; N1/N2 > 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,12,.667,.500,.238
-,Group2,2,6,.333,,
+x,Group 1,1,12,.667,.500,.238
+,Group 2,2,6,.333,,
,Total,,18,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P = 0.5; N1/N2 = 1])
+AT_SETUP([NPAR TESTS BINOMIAL P = 0.5; N1/N2 = 1])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,1,10,.500,.500,1.000
-,Group2,2,10,.500,,
+x,Group 1,1,10,.500,.500,1.000
+,Group 2,2,10,.500,,
,Total,,20,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P = 0.5; N1/N2 = 1 Cutpoint])
+AT_SETUP([NPAR TESTS BINOMIAL P = 0.5; N1/N2 = 1 Cutpoint])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,<= 10,10.000,.385,.500,.327
-,Group2,,16.000,.615,,
+x,Group 1,<= 10,10.000,.385,.500,.327
+,Group 2,,16.000,.615,,
,Total,,26.000,1.000,,
])
AT_CLEANUP
-AT_SETUP([NPAR TESTS BINOMIAL, P = 0.5; N1/N2 = 1 Named values])
+AT_SETUP([NPAR TESTS BINOMIAL P = 0.5; N1/N2 = 1 Named values])
AT_DATA([npar.sps], [dnl
SET FORMAT F8.3.
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Binomial Test
,,Category,N,Observed Prop.,Test Prop.,Exact Sig. (2-tailed)
-x,Group1,10.000,10.000,.435,.500,.678
-,Group2,20.000,13.000,.565,,
+x,Group 1,10.000,10.000,.435,.500,.678
+,Group 2,20.000,13.000,.565,,
,Total,,23.000,1.000,,
])
AT_CLEANUP
+
+
+dnl Test for a bug which caused binomial to crash.
+AT_SETUP([NPAR TESTS BINOMIAL - crash])
+AT_DATA([nparX.sps], [dnl
+data list list /range *.
+begin data.
+0
+1
+end data.
+
+* This is invalid syntax
+NPAR TEST
+ /BINOMIAL(0.5) = Range().
+
+])
+AT_CHECK([pspp -O format=csv nparX.sps], [1], [ignore])
+
+AT_CLEANUP
+
+
+
AT_SETUP([NPAR TESTS CHISQUARE])
AT_DATA([npar.sps], [dnl
DATA LIST NOTABLE LIST /x * y * w *.
/EXPECTED = 6 10 3
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: x
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,3.00,2.33,.67
2.00,3.00,2.33,.67
3.10,4.00,2.33,1.67
Total,14.00,,
Table: y
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,7.00,3.50,3.50
2.00,4.00,3.50,.50
3.00,1.00,3.50,-2.50
Total,14.00,,
Table: Test Statistics
-,x,y
-Chi-Square,3.14,6.00
-df,5,3
-Asymp. Sig.,.68,.11
+,Chi-square,df,Asymp. Sig.
+x,3.14,5,.678
+y,6.00,3,.112
Table: y
-,Observed N,Expected N,Residual
+Value,Observed N,Expected N,Residual
1.00,7.00,2.63,4.38
2.00,4.00,3.50,.50
3.00,1.00,4.38,-3.38
Total,14.00,,
Table: Test Statistics
-,y
-Chi-Square,10.61
-df,3
-Asymp. Sig.,.01
+,Chi-square,df,Asymp. Sig.
+y,10.61,3,.014
Table: Frequencies
,x,,,,y,,,
Total,,10.00,,,,7.00,,
Table: Test Statistics
-,x,y
-Chi-Square,.13,4.13
-df,2,2
-Asymp. Sig.,.94,.13
+,Chi-square,df,Asymp. Sig.
+x,.13,2,.936
+y,4.13,2,.127
])
+
AT_CLEANUP
AT_SETUP([NPAR TESTS CHISQUARE expected values missing])
/EXPECTED = 3 4 5 4 3 1
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [1], [dnl
-"error: CHISQUARE test specified 6 expected values, but 4 distinct values were encountered in variable y."
+"error: CHISQUARE test specified 6 expected values, but variable y has 4 distinct values."
Table: Test Statistics
-,y
-Chi-Square,.00
-df,0
-Asymp. Sig.,1.00
+,Chi-square,df,Asymp. Sig.
+y,.00,0,1.000
])
+
AT_CLEANUP
AT_SETUP([NPAR TESTS CHISQUARE with DESCRIPTIVES])
AT_DATA([npar.sps], [dnl
DATA LIST NOTABLE LIST /x * y * w * .
BEGIN DATA.
-1 2 1
+1 2 1
2 1 3
3.1 1 4
3.2 2 1
/STATISTICS=DESCRIPTIVES
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Frequencies
,x,,,,y,,,
Total,,12.00,,,,15.00,,
Table: Test Statistics
-,x,y
-Chi-Square,17.33,22.87
-df,7,7
-Asymp. Sig.,.02,.00
+,Chi-square,df,Asymp. Sig.
+x,17.33,7,.015
+y,22.87,7,.002
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
-,,,,,
x,12.00,2.47,1.19,1.00,5.00
y,15.00,2.07,1.33,1.00,5.00
])
AT_DATA([npar.sps], [dnl
DATA LIST NOTABLE LIST /x * y * w * .
BEGIN DATA.
-1 2 1
+1 2 1
2 1 3
3.1 1 4
3.2 2 1
/STATISTICS=DESCRIPTIVES
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Frequencies
,x,,,,y,,,
Total,,14.00,,,,14.00,,
Table: Test Statistics
-,x,y
-Chi-Square,13.43,26.00
-df,7,7
-Asymp. Sig.,.06,.00
+,Chi-square,df,Asymp. Sig.
+x,13.43,7,.062
+y,26.00,7,.001
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
-,,,,,
x,14.00,2.69,1.23,1.00,5.00
y,14.00,1.86,1.10,1.00,4.00
])
/missing analysis
/method=exact.
])
-AT_CHECK([pspp -o pspp.csv npar.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
+
+AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Ranks
,,N,Mean Rank,Sum of Ranks
first - second,Negative Ranks,8,6.00,48.00
Table: Test Statistics
,first - second
Z,-.18
-Asymp. Sig. (2-tailed),.86
-Exact Sig. (2-tailed),.89
-Exact Sig. (1-tailed),.45
+Asymp. Sig. (2-tailed),.861
+Exact Sig. (2-tailed),.893
+Exact Sig. (1-tailed),.446
])
+
AT_CLEANUP
AT_SETUP([NPAR TESTS WILCOXON with missing values])
12.00 .00 1
12.00 .00 1
34.2 . 1
-12.00 1.00 1
+12.00 1.00 1
13.00 1.00 1
end data
/wilcoxon=foo with bar (paired)
/missing analysis
/method=exact.
-
])
-AT_CHECK([pspp -o pspp.csv npar.sps])
+
dnl This is the same output as the previous test.
-AT_CHECK([cat pspp.csv], [0], [dnl
+AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Ranks
,,N,Mean Rank,Sum of Ranks
first - second,Negative Ranks,8,6.00,48.00
Table: Test Statistics
,first - second
Z,-.18
-Asymp. Sig. (2-tailed),.86
-Exact Sig. (2-tailed),.89
-Exact Sig. (1-tailed),.45
+Asymp. Sig. (2-tailed),.861
+Exact Sig. (2-tailed),.893
+Exact Sig. (1-tailed),.446
])
AT_CLEANUP
data list notable list /age * height rank *.
begin data.
10 12 11
-12 13 13
+12 13 13
13 14 12
12 12 10
9 9 10
.
])
AT_CHECK([pspp -o pspp.csv npar.sps])
-dnl Some machines return .313 instead of .312 for the Point Probability
+dnl Some machines return .313 instead of .312
dnl (see bug #31611).
-AT_CHECK([sed 's/\.313$/.312/' pspp.csv], [0], [dnl
+AT_CHECK([sed -e 's/\.313$/.312/' -e 's/^Exact Sig\. (1-tailed),\.313/Exact Sig. (1-tailed),.312/' pspp.csv], [0], [dnl
Table: Frequencies
,,N
age - height,Negative Differences,3
1 101
2 82
2 124
-3 149
+3 149
3 166
3 147
end data.
.
])
-AT_CHECK([pspp -o pspp.csv kw-simple.sps])
+AT_CHECK([pspp -o pspp.csv -o pspp.txt kw-simple.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Ranks
-,gv,N,Mean Rank
+,,N,Mean Rank
xscore,timed out,5,4.400
-,handled the ball,4,11.500
,hit wicket,5,7.400
+,handled the ball,4,11.500
,Total,14,
Table: Test Statistics
-,,xscore
-Chi-Square,,6.406
-df,,2
-Asymp. Sig.,,.041
+,xscore
+Chi-Square,6.406
+df,2
+Asymp. Sig.,.041
])
2 135
2 109
3 115
-3 149
+3 149
3 166
3 147
2.5 344
dnl The result should be the same as before
AT_CHECK([diff pspp.csv pspp2.csv], [0])
+dnl Reverse the order of the group values
+AT_DATA([kw-reverse-group.sps], [dnl
+set format = F9.3.
+
+data list notable list /gv * xscore *.
+begin data
+1 96
+1 128
+1 83
+1 61
+1 101
+2 82
+2 124
+2 132
+2 135
+2 109
+3 115
+3 149
+3 166
+3 147
+end data.
+
+value label /gv
+ 1 "timed out"
+ 2 "hit wicket"
+ 3 "handled the ball".
+
+npar tests
+ /kruskal-wallis xscore by gv (3, 1)
+ /missing=exclude
+ .
+])
+
+AT_CHECK([pspp -o pspp2.csv kw-reverse-group.sps])
+
+dnl The result should be the same as before
+AT_CHECK([diff pspp.csv pspp2.csv], [0])
+
AT_CLEANUP
begin data
1 96 .
1 128 .
-1 83 .
+1 83 .
2 132 132
2 135 135
2 109 109
3 115 115
-1 61 .
+1 61 .
1 101 .
-2 82 82
+2 82 82
2 124 124
3 149 149
3 166 166
4 "bowled"
5 "lbw"
.
-
+
npar tests
/k-w xscore yscore by gv (1, 5)
.
AT_CHECK([pspp -o pspp.csv kw-multi.sps])
AT_CHECK([cat pspp.csv], [0], [dnl
Table: Ranks
-,gv,N,Mean Rank
+,,N,Mean Rank
xscore,timed out,5,4.400
-,handled the ball,4,11.500
,hit wicket,5,7.400
+,handled the ball,4,11.500
,Total,14,
-yscore,handled the ball,4,11.500
+yscore,hit wicket,5,7.400
+,handled the ball,4,11.500
,bowled,5,4.400
-,hit wicket,5,7.400
,Total,14,
Table: Test Statistics
-,,xscore,yscore,
-Chi-Square,,6.406,6.406,
-df,,2,2,
-Asymp. Sig.,,.041,.041,
+,xscore,yscore
+Chi-Square,6.406,6.406
+df,2,2
+Asymp. Sig.,.041,.041
])
AT_CLEANUP
begin data
4 6
. 4
-4 3
-3 20
-2 29
-1 42
-6 18
-5 7
-6 78
-5 10
-6 46
-5 5
-6 17
-5 1
-6 11
-4 2
-3 7
-2 6
-1 10
-4 13
-3 22
-3 11
-2 24
-1 18
-4 4
-3 12
-2 10
-1 25
-4 4
-3 7
-2 3
-1 4
-4 2
-3 3
-2 2
-1 4
+4 3
+3 20
+2 29
+1 42
+6 18
+5 7
+6 78
+5 10
+6 46
+5 5
+6 17
+5 1
+6 11
+4 2
+3 7
+2 6
+1 10
+4 13
+3 22
+3 11
+2 24
+1 18
+4 4
+3 12
+2 10
+1 25
+4 4
+3 7
+2 3
+1 4
+4 2
+3 3
+2 2
+1 4
end data.
weight by w.
npar tests
/runs (MEDIAN) = score
/runs (MEAN) = score
- /runs (MODE) = score
+ /runs (MODE) = score
.
])
-AT_CHECK([pspp -o pspp.csv npar-runs.sps])
-
-AT_CHECK([cat pspp.csv], [0], [dnl
-Table: Runs Test
+AT_CHECK([pspp -O format=csv npar-runs.sps], [0],
+[Table: Runs Test
,score
Test Value (median),3.0000
Cases < Test Value,177.0000
-Cases >= Test Value,309.0000
+Cases ≥ Test Value,309.0000
Total Cases,486.0000
Number of Runs,12
Z,-20.9931
-Asymp. Sig. (2-tailed),.0000
+Asymp. Sig. (2-tailed),.000
Table: Runs Test
,score
Test Value (mean),3.6379
Cases < Test Value,259.0000
-Cases >= Test Value,227.0000
+Cases ≥ Test Value,227.0000
Total Cases,486.0000
Number of Runs,12
Z,-21.0650
-Asymp. Sig. (2-tailed),.0000
+Asymp. Sig. (2-tailed),.000
Table: Runs Test
,score
Test Value (mode),6.0000
Cases < Test Value,316.0000
-Cases >= Test Value,170.0000
+Cases ≥ Test Value,170.0000
Total Cases,486.0000
Number of Runs,11
Z,-21.0742
-Asymp. Sig. (2-tailed),.0000
+Asymp. Sig. (2-tailed),.000
])
AT_CLEANUP
+dnl Thanks to Douglas Bonett for providing this test case.
+AT_SETUP([NPAR TESTS Runs (2)])
+AT_DATA([npar-runs.sps], [dnl
+data list notable free /y.
+begin data
+1 1 2 1 2 1 1 2 1 1 1 2 1 2
+end data.
+NPAR TEST /RUNS(1.5) = y.
+])
+
+AT_CHECK([pspp -O format=csv npar-runs.sps], [0], [dnl
+Table: Runs Test
+,y
+Test Value,1.50
+Cases < Test Value,9
+Cases ≥ Test Value,5
+Total Cases,14
+Number of Runs,10
+Z,1.26
+Asymp. Sig. (2-tailed),.206
+])
+AT_CLEANUP
+
+
AT_SETUP([NPAR TESTS Friedman])
AT_DATA([npar-friedman.sps], [dnl
set format F15.4.
/friedman = x y z.
])
-AT_CHECK([pspp -o pspp.csv npar-friedman.sps])
-
-AT_CHECK([cat pspp.csv], [0], [dnl
+AT_CHECK([pspp -O format=csv npar-friedman.sps], [0], [dnl
Table: Ranks
,Mean Rank
x,2.6500
N,10
Chi-Square,10.4737
df,2
-Asymp. Sig.,.0053
+Asymp. Sig.,.005
])
AT_CLEANUP
data list notable list /height * sex (f1.0).
begin data.
-201 1
-84 1
-83 1
-94 1
-88 0
-99 0
-55 0
-69 0
-86 1
-79 1
-91 0
-201 0
-88 1
-85 1
-82 1
-88 0
-75 0
-99 0
-81 0
-72 1
-89 1
-92 1
-80 0
-82 0
-76 0
-65 0
-85 0
-76 1
-145 1
-24 1
+201 1
+84 1
+83 1
+94 1
+88 0
+99 0
+55 0
+69 0
+86 1
+79 1
+91 0
+201 0
+88 1
+85 1
+82 1
+88 0
+75 0
+99 0
+81 0
+72 1
+89 1
+92 1
+80 0
+82 0
+76 0
+65 0
+85 0
+76 1
+145 1
+24 1
+1 4
+-4 5
+34 5
+21 4
end data.
-NPAR TESTS
+NPAR TESTS
/M-W = height BY sex (0,1).
])
-AT_CHECK([pspp -o pspp.csv npar-mann-whitney.sps])
-
-AT_CHECK([cat pspp.csv], [0], [dnl
+AT_CHECK([pspp -O format=csv npar-mann-whitney.sps], [0], [dnl
Table: Ranks
-,N,,,Mean Rank,,Sum of Ranks,
-,0,1,Total,0,1,0,1
-height,15.0000,15.0000,30.0000,14.5333,16.4667,218.0000,247.0000
+,,N,Mean Rank,Sum of Ranks
+height,0,15,14.5333,218.0000
+,1,15,16.4667,247.0000
+,Total,30,,
Table: Test Statistics
,Mann-Whitney U,Wilcoxon W,Z,Asymp. Sig. (2-tailed)
-height,98.0000,218.0000,-.6020,.5472
+height,98.0000,218.0000,-.6020,.547
])
AT_CLEANUP
+AT_SETUP([NPAR TESTS Mann-Whitney Multiple])
+dnl Check for a bug where the ranks were inappropriately allocated, when
+dnl multiple variables were tested and MISSING=ANALYSIS chosen.
+
+cp "$abs_srcdir/language/mann-whitney.txt" .
+
+AT_DATA([npar-mann-whitney.sps], [dnl
+SET FORMAT = F11.3
+
+DATA LIST NOTABLE FILE='mann-whitney.txt'
+ LIST /I002_01 I002_02 I002_03 I002_04 sum_HL *.
+
+VARIABLE LABELS
+ I002_01 'IOS: Familie'
+ I002_02 'IOS: Freunde'
+ I002_03 'IOS: Partner*in'
+ I002_04 'IOS: Bekannte'.
+
+MISSING VALUES I002_01 I002_02 I002_03 I002_04 (-9 -1).
+
+NPAR TESTS
+ /MISSING=ANALYSIS
+ /M-W=I002_01 I002_02 I002_03 I002_04 BY sum_HL (0 1).
+])
+
+AT_CHECK([pspp -O format=csv npar-mann-whitney.sps], [0], [dnl
+Table: Ranks
+,,N,Mean Rank,Sum of Ranks
+IOS: Familie,.000,114,110.018,12542.000
+,1.000,115,119.939,13793.000
+,Total,229,,
+IOS: Freunde,.000,115,108.339,12459.000
+,1.000,115,122.661,14106.000
+,Total,230,,
+IOS: Partner*in,.000,97,95.351,9249.000
+,1.000,91,93.593,8517.000
+,Total,188,,
+IOS: Bekannte,.000,115,111.065,12772.500
+,1.000,115,119.935,13792.500
+,Total,230,,
+
+Table: Test Statistics
+,Mann-Whitney U,Wilcoxon W,Z,Asymp. Sig. (2-tailed)
+IOS: Familie,5987.000,12542.000,-1.167,.243
+IOS: Freunde,5789.000,12459.000,-1.674,.094
+IOS: Partner*in,4331.000,8517.000,-.245,.807
+IOS: Bekannte,6102.500,12772.500,-1.046,.296
+])
+
+AT_CLEANUP
+
+
+
AT_SETUP([NPAR TESTS Cochran])
AT_DATA([npar-cochran.sps], [dnl
set format f11.3.
data list notable list /v1 * v2 * v3 * v4 * v5 * v6 * v7 *.
begin data.
-2 1 1 2 1 1 2
-2 2 2 2 1 1 1
-1 1 2 2 1 1 2
-2 2 2 2 1 1 2
-2 1 2 1 1 2 1
-1 2 2 1 1 1 1
-1 2 2 2 2 2 2
-2 2 1 2 1 1 1
-1 2 1 2 1 1 2
-end data.
-
-npar tests
+2 1 1 2 1 1 2
+2 2 2 2 1 1 1
+1 1 2 2 1 1 2
+2 2 2 2 1 1 2
+2 1 2 1 1 2 1
+1 2 2 1 1 1 1
+1 2 2 2 2 2 2
+2 2 1 2 1 1 1
+1 2 1 2 1 1 2
+end data.
+
+npar tests
/cochran = v1 to v7 .
])
v7,5,4
Table: Test Statistics
+,Value
N,9
Cochran's Q,12.735
df,6
data list notable list /v1 * v2 * v3
begin data.
- 7 7 2
- 5 6 5
- 8 6 4
- 5 7 4
- 5 4 4
- 8 6 5
- 6 3 5
- 7 6 5
+ 7 7 2
+ 5 6 5
+ 8 6 4
+ 5 7 4
+ 5 4 4
+ 8 6 5
+ 6 3 5
+ 7 6 5
8 5 5
- . 2 2
- 5 4 5
- 3 4 4
- 5 1 2
- 5 2 1
- 7 6 5
- 6 3 4
- 6 6 6
- 5 4 5
- 4 3 4
- 9 1 1
- 6 2 1
- 3 7 8
- 6 3 4
- 4 4 4
- 5 4 3
- 6 5 2
- 4 4 8
- 4 6 4
- 6 5 5
- 7 8 6
- 5 3 5
+ . 2 2
+ 5 4 5
+ 3 4 4
+ 5 1 2
+ 5 2 1
+ 7 6 5
+ 6 3 4
+ 6 6 6
+ 5 4 5
+ 4 3 4
+ 9 1 1
+ 6 2 1
+ 3 7 8
+ 6 3 4
+ 4 4 4
+ 5 4 3
+ 6 5 2
+ 4 4 8
+ 4 6 4
+ 6 5 5
+ 7 8 6
+ 5 3 5
end data.
npar tests
1 1 1
end data.
-npar tests
+npar tests
/mcnemar = v1 WITH v2 junk.
])
])
AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS McNemar Symetricity])
+
+AT_DATA([mcnemar.sps], [dnl
+data list notable list /var1 var2 w (F2.0).
+begin data
+0 0 9
+0 1 8
+1 0 1
+1 1 5
+end data.
+
+weight by w.
+
+NPAR TEST
+ /MCNEMAR var1 WITH var2 (PAIRED).
+
+NPAR TEST
+ /MCNEMAR var2 WITH var1 (PAIRED).
+])
+
+AT_CHECK([pspp -O format=csv mcnemar.sps], [0], [dnl
+Table: var1 & var2
+var1,var2,
+,0,1
+0,9,8
+1,1,5
+
+Table: Test Statistics
+,N,Exact Sig. (2-tailed),Exact Sig. (1-tailed),Point Probability
+var1 & var2,23,.039,.020,.02
+
+Table: var2 & var1
+var2,var1,
+,0,1
+0,9,1
+1,8,5
+
+Table: Test Statistics
+,N,Exact Sig. (2-tailed),Exact Sig. (1-tailed),Point Probability
+var2 & var1,23,.039,.020,.02
+])
+
+AT_CLEANUP
+
+AT_SETUP([NPAR TESTS Kolmogorov-Smirnov Uniform parameters given])
+
+AT_DATA([ks-uniform.sps], [dnl
+set format F12.3.
+data list notable list /x *.
+begin data
+.554
+.382
+.329
+.480
+.711
+.503
+.203
+.477
+.621
+.581
+end data.
+
+npar tests k-s (uniform 0 1) = x.
+])
+
+AT_CHECK([pspp -O format=csv ks-uniform.sps], [0], [dnl
+Table: One-Sample Kolmogorov-Smirnov Test
+,,x
+N,,10
+Uniform Parameters,Minimum,.000
+,Maximum,1.000
+Most Extreme Differences,Absolute,.289
+,Positive,.289
+,Negative,-.229
+Kolmogorov-Smirnov Z,,.914
+Asymp. Sig. (2-tailed),,.374
+])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS Kolmogorov-Smirnov Normal parameters imputed])
+
+AT_DATA([ks-normal.sps], [dnl
+set format = F12.3.
+
+data list notable list /foo * bar *.
+begin data.
+65 12.5
+59 14.2
+43 12.6
+57
+68
+79
+51
+62
+57
+73
+58
+58
+68
+75
+47
+70
+59
+71
+52
+48 13.0
+58 14.1
+37 15.0
+39 13.1
+58 13.2
+43 14.5
+58 13.5
+86 14.0
+63 12.5
+80 12.8
+70
+63
+53
+53
+48
+49
+51
+47
+81
+66
+78
+65
+69
+70 12.1
+63 12.5
+64 12.4
+39 13.8
+51 13.2
+68 14.0
+76 12.6
+53 12.1
+71 13.5
+47 13.8
+87 14.1
+72 12.9
+48 12.1
+75 12.8
+51 13.4
+63 13.9
+61 12.5
+61 12.4
+66 12.8
+82 12.9
+81 13.6
+46
+52
+71
+73
+58
+57
+46
+58
+52 13.5
+71 13.2
+57 12.8
+78 14.1
+73 12.1
+50 12.6
+71
+51
+51
+68
+84
+64
+66
+65
+52
+56
+70
+68
+66
+78
+65
+71
+53
+81
+53
+57
+64
+61
+43
+56
+37
+74
+66
+81
+67
+80
+68
+76
+70
+80
+42
+74
+80
+70
+60
+39
+72
+69
+63
+72
+63
+49
+53 13.2
+43 13.8
+51 12.5
+63 12.6
+64 12.9
+65 13.0
+64 12.5
+66 12.0
+55
+62
+58
+48
+67
+46
+36
+61
+55
+77
+74
+60
+70
+69
+57
+49
+63
+69
+63
+76
+53
+54
+42
+64
+66
+61
+62
+73
+73
+60
+79
+40
+48
+76
+60
+76
+54
+69
+65
+69
+51
+54
+82
+end data.
+
+npar tests
+ /k-s (normal) = foo bar.
+])
+
+AT_CHECK([pspp -O format=csv ks-normal.sps], [0], [dnl
+Table: One-Sample Kolmogorov-Smirnov Test
+,,foo,bar
+N,,174,48
+Normal Parameters,Mean,62.109,13.108
+,Std. Deviation,11.548,.718
+Most Extreme Differences,Absolute,.059,.115
+,Positive,.055,.115
+,Negative,-.059,-.082
+Kolmogorov-Smirnov Z,,.785,.795
+Asymp. Sig. (2-tailed),,.569,.552
+])
+
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS Median Test (median imputed)])
+
+AT_DATA([median1.sps], [dnl
+set format F12.3.
+data list notable list /ignore * animal * years * w *.
+begin data
+99 1 10 1
+99 4 1 1
+99 5 11 1
+99 5 10 1
+99 3 7 1
+99 6 10 1
+99 0 7 1
+99 3 14 1
+99 2 3 1
+99 1 1 1
+99 4 7 1
+99 5 12 1
+99 3 6 1
+99 4 1 1
+99 3 5 1
+99 5 7 1
+99 4 6 1
+99 3 14 1
+99 4 8 1
+99 5 13 1
+99 2 0 1
+99 4 7 1
+99 4 7 1
+99 1 0 1
+99 2 8 1
+99 4 10 1
+99 2 3 1
+99 2 0 1
+99 4 8 1
+99 1 8 1
+end data.
+
+
+variable label years 'Years expected'.
+variable label animal 'Animal Genus'.
+
+add value labels animal 1 'Animal 1' 2 'Animal 2' 3 'Animal 3' 4 'Animal 4' 5 'Animal 5'.
+
+npar tests
+ /median = years by animal (1, 5)
+ .
+])
+
+
+AT_CHECK([pspp -O format=csv median1.sps], [0], [dnl
+Table: Frequencies
+,,Animal Genus,,,,
+,,Animal 1,Animal 2,Animal 3,Animal 4,Animal 5
+Years expected,> Median,2,1,2,3,4
+,≤ Median,2,4,3,6,1
+
+Table: Test Statistics
+,N,Median,Chi-Square,df,Asymp. Sig.
+Years expected,28,7.000,4.317,4,.365
+])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS Median Test (median given)])
+
+AT_DATA([median2.sps], [dnl
+set format F12.3.
+data list notable list /ignore * animal * years * w *.
+begin data
+99 1 10 1
+99 4 1 1
+99 5 11 1
+99 5 10 1
+99 3 7 1
+99 3 14 1
+99 2 3 1
+99 1 1 1
+99 4 7 1
+99 5 12 1
+99 3 6 1
+99 4 1 1
+99 3 5 1
+99 5 7 1
+99 4 6 1
+99 3 14 1
+99 4 8 1
+99 5 13 1
+99 2 0 1
+99 4 7 1
+99 4 7 1
+99 1 0 1
+99 2 8 1
+99 4 10 1
+99 2 3 1
+99 2 0 1
+99 4 8 1
+99 1 8 1
+end data.
+
+
+variable label years 'Years expected'.
+variable label animal 'Animal Genus'.
+
+add value labels animal 1 'Animal 1' 2 'Animal 2' 3 'Animal 3' 4 'Animal 4' 5 'Animal 5'.
+
+npar tests
+ /median (7) = years by animal (1, 5)
+ .
+])
+
+
+AT_CHECK([pspp -O format=csv median2.sps], [0], [dnl
+Table: Frequencies
+,,Animal Genus,,,,
+,,Animal 1,Animal 2,Animal 3,Animal 4,Animal 5
+Years expected,> Median,2,1,2,3,4
+,≤ Median,2,4,3,6,1
+
+Table: Test Statistics
+,N,Median,Chi-Square,df,Asymp. Sig.
+Years expected,28,7.000,4.317,4,.365
+])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS Median Test (two sample)])
+
+AT_DATA([median3.sps], [dnl
+set format F12.3.
+data list notable list /xx * animal * years * w *.
+begin data
+99 1 10 1
+99 4 1 1
+99 5 11 1
+99 5 10 1
+99 3 7 1
+99 3 14 1
+99 2 3 1
+99 1 1 1
+99 4 7 1
+99 5 12 1
+99 3 6 1
+99 4 1 1
+99 3 5 1
+99 5 7 1
+99 4 6 1
+99 3 14 1
+99 4 8 1
+99 5 13 1
+99 2 0 1
+99 4 7 1
+99 4 7 1
+99 1 0 1
+99 2 8 1
+99 4 10 1
+99 2 3 1
+99 2 0 1
+99 4 8 1
+99 1 8 1
+end data.
+
+
+variable label years 'Years expected'.
+variable label animal 'Animal Genus'.
+
+add value labels animal 1 'Animal 1' 2 'Animal 2' 3 'Animal 3' 4 'Animal 4' 5 'Animal 5'.
+
+npar tests
+ /median (7) = xx years by animal (5, 1)
+ .
+])
+
+
+AT_CHECK([pspp -O format=csv median3.sps], [0], [dnl
+Table: Frequencies
+,,Animal Genus,
+,,Animal 1,Animal 5
+xx,> Median,4,5
+,≤ Median,0,0
+Years expected,> Median,2,4
+,≤ Median,2,1
+
+Table: Test Statistics
+,N,Median,Chi-Square,df,Asymp. Sig.
+xx,9,7.000,NaN,1,NaN
+Years expected,9,7.000,.900,1,.343
+])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS Jonckheere-Terpstra])
+
+AT_DATA([jt.sps], [dnl
+set format = F12.3.
+data list notable list /x * g * w *.
+begin data.
+52 2 2
+58 2 1
+60 2 1
+62 2 1
+58 0 1
+44 2 1
+46 2 1
+14 3 1
+32 2 1
+16 3 1
+56 2 1
+26 3 1
+40 3 2
+50 4 1
+6 5 1
+34 2 3
+36 2 2
+40 2 2
+50 2 1
+end data.
+
+weight by w.
+
+npar test /jonckheere-terpstra = x by g (5, 2).
+])
+
+
+AT_CHECK([pspp -O format=csv jt.sps], [0], [dnl
+Table: Jonckheere-Terpstra Test
+,Number of levels in g,N,Observed J-T Statistic,Mean J-T Statistic,Std. Deviation of J-T Statistic,Std. J-T Statistic,Asymp. Sig. (2-tailed)
+x,4,24.000,29.500,65.000,15.902,-2.232,.026
+])
+
+AT_CLEANUP
+
+dnl Checks that (PAIRED) can have lists where the same
+dnl variable appears more than once.
+AT_SETUP([NPAR TESTS (PAIRED)])
+AT_DATA([npar.sps], [dnl
+set format = F12.3.
+data list notable list /a * b * c *.
+begin data.
+1 2 4
+4 5 3
+1 2 2
+4 5 1
+end data.
+
+npar tests /wilcoxon a b with c c (paired).
+])
+
+AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
+Table: Ranks
+,,N,Mean Rank,Sum of Ranks
+a - c,Negative Ranks,2,2.500,5.000
+,Positive Ranks,2,2.500,5.000
+,Ties,0,,
+,Total,4,,
+b - c,Negative Ranks,1,1.500,1.500
+,Positive Ranks,2,2.250,4.500
+,Ties,1,,
+,Total,4,,
+
+Table: Test Statistics
+,a - c,b - c
+Z,.000,-.816
+Asymp. Sig. (2-tailed),1.000,.414
+])
+
+
+AT_CLEANUP
+
+
+
+AT_SETUP([NPAR TESTS CHISQUARE crash])
+dnl This syntax had been observed to crash pspp
+
+AT_DATA([npar.sps], [dnl
+data list list /x *.
+begin data.
+1
+2
+3
+4
+5
+6
+7
+8
+9
+10
+end data.
+
+* This happens to be invalid syntax. But should not crash.
+NPAR TEST
+ /CHISQUARE= x(0.098, 99.098)
+ /EXPECTED = 1.2.
+])
+
+AT_CHECK([pspp -O format=csv npar.sps], [1], [ignore])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR TESTS - crash on invalid syntax])
+
+AT_DATA([npar.sps], [dnl
+data list notable list /ev * xscore *.
+begin data.
+2 109
+3 115
+1 61
+1 101
+3 147
+end data.
+
+
+npar tests
+ /kruskal-wallis xscore by(gv (1, 3).
+])
+
+AT_CHECK([pspp -O format=csv npar.sps], [1], [ignore])
+
+AT_CLEANUP
+
+
+
+
+AT_SETUP([NPAR TESTS - crash on unterminated string])
+
+AT_DATA([npar.sps], [dnl
+DATA LIST NOTABLE LIST /x * y * w * .
+BEGIN DATA.
+3.1 1 4
+3.2 2 1
+4 2 6
+END DATA.
+
+
+NPAR TESTS
+" CHISQUARE=x y(-2,5)
+ /STATISTICS=DESCRIPTIVES
+ .
+])
+
+AT_CHECK([pspp -O format=csv npar.sps], [1], [ignore])
+
+AT_CLEANUP
+