])
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
,x,y
Chi-Square,3.14,6.00
df,5,3
-Asymp. Sig.,.68,.11
+Asymp. Sig.,.678,.112
Table: y
,Observed N,Expected N,Residual
,y
Chi-Square,10.61
df,3
-Asymp. Sig.,.01
+Asymp. Sig.,.014
Table: Frequencies
,x,,,,y,,,
,x,y
Chi-Square,.13,4.13
df,2,2
-Asymp. Sig.,.94,.13
+Asymp. Sig.,.936,.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."
,y
Chi-Square,.00
df,0
-Asymp. Sig.,1.00
+Asymp. Sig.,1.000
])
+
AT_CLEANUP
AT_SETUP([NPAR TESTS CHISQUARE with DESCRIPTIVES])
/STATISTICS=DESCRIPTIVES
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Frequencies
,x,,,,y,,,
,x,y
Chi-Square,17.33,22.87
df,7,7
-Asymp. Sig.,.02,.00
+Asymp. Sig.,.015,.002
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
/STATISTICS=DESCRIPTIVES
.
])
+
AT_CHECK([pspp -O format=csv npar.sps], [0], [dnl
Table: Frequencies
,x,,,,y,,,
,x,y
Chi-Square,13.43,26.00
df,7,7
-Asymp. Sig.,.06,.00
+Asymp. Sig.,.062,.001
Table: Descriptive Statistics
,N,Mean,Std. Deviation,Minimum,Maximum
/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
-second - first,Negative Ranks,5,8.60,43.00
-,Positive Ranks,8,6.00,48.00
+first - second,Negative Ranks,8,6.00,48.00
+,Positive Ranks,5,8.60,43.00
,Ties,2,,
,Total,15,,
Table: Test Statistics
-,second - first
+,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])
/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
-second - first,Negative Ranks,5,8.60,43.00
-,Positive Ranks,8,6.00,48.00
+first - second,Negative Ranks,8,6.00,48.00
+,Positive Ranks,5,8.60,43.00
,Ties,2,,
,Total,15,,
Table: Test Statistics
-,second - first
+,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_CHECK([pspp -o pspp.csv npar.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
+dnl Some machines return .313 instead of .312
+dnl (see bug #31611).
+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
-height - age,Negative Differences,1
-,Positive Differences,3
+age - height,Negative Differences,3
+,Positive Differences,1
,Ties,2
,Total,6
-rank - height,Negative Differences,3
-,Positive Differences,2
+height - rank,Negative Differences,2
+,Positive Differences,3
,Ties,1
,Total,6
Table: Test Statistics
-,height - age,rank - height
+,age - height,height - rank
Exact Sig. (2-tailed),.625,1.000
Exact Sig. (1-tailed),.312,.500
Point Probability,.250,.312
])
AT_CLEANUP
+
+
+AT_SETUP([NPAR Kruskal-Wallis test])
+
+dnl Simple case
+AT_DATA([kw-simple.sps], [dnl
+set format = F9.3.
+
+data list notable list /gv * xscore *.
+begin data
+1 96
+1 128
+1 83
+2 132
+2 135
+2 109
+3 115
+1 61
+1 101
+2 82
+2 124
+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 (1, 3)
+ .
+])
+
+AT_CHECK([pspp -o pspp.csv kw-simple.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Ranks
+,gv,N,Mean Rank
+xscore,timed out,5,4.400
+,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
+])
+
+
+dnl Now try a missing value in the group variable
+AT_DATA([kw-missing-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
+2.5 344
+end data.
+
+missing values gv (2.5).
+
+value label /gv
+ 1 "timed out"
+ 2 "hit wicket"
+ 3 "handled the ball".
+
+npar tests
+ /kruskal-wallis xscore by gv (1, 3)
+ /missing=exclude
+ .
+])
+
+AT_CHECK([pspp -o pspp2.csv kw-missing-group.sps])
+
+dnl The result should be the same as before
+AT_CHECK([diff pspp.csv pspp2.csv], [0])
+
+AT_CLEANUP
+
+
+AT_SETUP([NPAR Kruskal-Wallis multiple-variables])
+
+AT_DATA([kw-multi.sps], [dnl
+set format = F9.3.
+
+data list notable list /gv * xscore * yscore.
+begin data
+1 96 .
+1 128 .
+1 83 .
+2 132 132
+2 135 135
+2 109 109
+3 115 115
+1 61 .
+1 101 .
+2 82 82
+2 124 124
+3 149 149
+3 166 166
+3 147 147
+4 . 96
+4 . 128
+4 . 83
+4 . 61
+4 . 101
+end data.
+
+value label /gv
+ 1 "timed out"
+ 2 "hit wicket"
+ 3 "handled the ball"
+ 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
+xscore,timed out,5,4.400
+,hit wicket,5,7.400
+,handled the ball,4,11.500
+,Total,14,
+yscore,hit wicket,5,7.400
+,handled the ball,4,11.500
+,bowled,5,4.400
+,Total,14,
+
+Table: Test Statistics
+,,xscore,yscore,
+Chi-Square,,6.406,6.406,
+df,,2,2,
+Asymp. Sig.,,.041,.041,
+])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([NPAR TESTS Runs])
+AT_DATA([npar-runs.sps], [dnl
+set format F11.4.
+data list notable list /score * w *.
+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
+end data.
+
+weight by w.
+
+npar tests
+ /runs (MEDIAN) = score
+ /runs (MEAN) = score
+ /runs (MODE) = score
+ .
+])
+
+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
+Total Cases,486.0000
+Number of Runs,12
+Z,-20.9931
+Asymp. Sig. (2-tailed),2.000
+
+Table: Runs Test
+,score
+Test Value (mean),3.6379
+Cases < Test Value,259.0000
+Cases ≥ Test Value,227.0000
+Total Cases,486.0000
+Number of Runs,12
+Z,-21.0650
+Asymp. Sig. (2-tailed),2.000
+
+Table: Runs Test
+,score
+Test Value (mode),6.0000
+Cases < Test Value,316.0000
+Cases ≥ Test Value,170.0000
+Total Cases,486.0000
+Number of Runs,11
+Z,-21.0742
+Asymp. Sig. (2-tailed),2.000
+])
+
+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.
+data list notable list /x * y * z.
+begin data
+9.5 6.5 8.1
+8.0 6.0 6.0
+7.0 6.5 4.2
+9.5 5.0 7.3
+9.0 7.0 6.2
+8.5 6.9 6.5
+7.5 8.0 6.5
+6.0 8.0 3.1
+5.0 6.0 4.9
+7.5 7.5 6.2
+end data.
+
+npar tests
+ /friedman = x y z.
+])
+
+AT_CHECK([pspp -O format=csv npar-friedman.sps], [0], [dnl
+Table: Ranks
+,Mean Rank
+x,2.6500
+y,2.1000
+z,1.2500
+
+Table: Test Statistics
+N,10
+Chi-Square,10.4737
+df,2
+Asymp. Sig.,.005
+])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([NPAR TESTS Mann-Whitney])
+AT_DATA([npar-mann-whitney.sps], [dnl
+SET FORMAT = F11.4
+
+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
+end data.
+
+NPAR TESTS
+ /M-W = height BY sex (0,1).
+])
+
+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
+
+Table: Test Statistics
+,Mann-Whitney U,Wilcoxon W,Z,Asymp. Sig. (2-tailed)
+height,98.0000,218.0000,-.6020,.547
+])
+
+
+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
+ /cochran = v1 to v7 .
+
+])
+
+AT_CHECK([pspp -o pspp.csv npar-cochran.sps])
+
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Frequencies
+,Value,
+,Success (2),Failure (1)
+v1,5,4
+v2,6,3
+v3,6,3
+v4,7,2
+v5,1,8
+v6,2,7
+v7,5,4
+
+Table: Test Statistics
+N,9
+Cochran's Q,12.735
+df,6
+Asymp. Sig.,.047
+])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([NPAR TESTS Kendall])
+AT_DATA([npar-kendall.sps], [dnl
+SET FORMAT F14.3.
+
+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
+ 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
+end data.
+
+npar tests
+ /kendall = all
+ .
+])
+
+AT_CHECK([pspp -o pspp.csv npar-kendall.sps])
+
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Ranks
+,Mean Rank
+v1,2.500
+v2,1.817
+v3,1.683
+
+Table: Test Statistics
+N,30
+Kendall's W,.233
+Chi-Square,13.960
+df,2
+Asymp. Sig.,.001
+])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([NPAR TESTS McNemar])
+
+AT_DATA([mcnemar.sps], [dnl
+set format = F12.3.
+data list notable list /v1 * v2 * junk *.
+begin data.
+0 0 0
+0 0 0
+0 0 0
+0 0 0
+0 1 0
+0 1 0
+0 1 0
+0 1 0
+0 1 1
+0 1 1
+0 1 1
+0 1 1
+0 1 1
+1 0 1
+1 0 1
+1 1 1
+1 1 1
+1 1 0
+1 1 0
+1 1 1
+end data.
+
+npar tests
+ /mcnemar = v1 WITH v2 junk.
+])
+
+AT_CHECK([pspp -O format=csv mcnemar.sps], [0], [dnl
+Table: v1 & v2
+v1,v2,
+,.000,1.000
+.000,4,9
+1.000,2,5
+
+Table: v1 & junk
+v1,junk,
+,.000,1.000
+.000,8,5
+1.000,2,5
+
+Table: Test Statistics
+,N,Exact Sig. (2-tailed),Exact Sig. (1-tailed),Point Probability
+v1 & v2,20,.065,.033,.027
+v1 & junk,20,.453,.227,.164
+])
+
+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
projects / pspp / blobdiff