-AT_BANNER([REGRESSION])
+AT_BANNER([LINEAR REGRESSION])
-AT_SETUP([REGRESSION])
+AT_SETUP([LINEAR REGRESSION - basic])
AT_DATA([regression.sps], [dnl
set format = F22.3.
data list notable list / v0 to v2.
+filter by v0.
begin data
0.65377128 7.735648 -23.97588
-0.13087553 6.142625 -19.63854
])
AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
+regression.sps:16: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
+
Table: Model Summary (v2)
,R,R Square,Adjusted R Square,Std. Error of the Estimate
,.971,.942,.925,1.337
Table: ANOVA (v2)
-,,Sum of Squares,df,Mean Square,F,Significance
+,,Sum of Squares,df,Mean Square,F,Sig.
,Regression,202.753,2,101.376,56.754,.000
,Residual,12.504,7,1.786,,
,Total,215.256,9,,,
Table: Coefficients (v2)
-,,B,Std. Error,Beta,t,Significance
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
,(Constant),2.191,2.357,.000,.930,.380
,v0,1.813,1.053,.171,1.722,.129
,v1,-3.427,.332,-1.026,-10.334,.000
-,,,,,,
Table: Data List
v0,v1,v2,RES1,PRED1
])
AT_CLEANUP
+
+AT_SETUP([LINEAR REGRESSION - one save])
+AT_DATA([regression.sps], [dnl
+set format = F22.3.
+data list notable list / v0 to v2.
+begin data
+ 0.65377128 7.735648 -23.97588
+-0.13087553 6.142625 -19.63854
+ 0.34880368 7.651430 -25.26557
+ 0.69249021 6.125125 -16.57090
+-0.07368178 8.245789 -25.80001
+-0.34404919 6.031540 -17.56743
+ 0.75981559 9.832291 -28.35977
+-0.46958313 5.343832 -16.79548
+-0.06108490 8.838262 -29.25689
+ 0.56154863 6.200189 -18.58219
+end data
+regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
+regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
+list.
+])
+
+AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
+Table: Model Summary (v2)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.971,.942,.925,1.337
+
+Table: ANOVA (v2)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,202.753,2,101.376,56.754,.000
+,Residual,12.504,7,1.786,,
+,Total,215.256,9,,,
+
+Table: Coefficients (v2)
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,(Constant),2.191,2.357,.000,.930,.380
+,v0,1.813,1.053,.171,1.722,.129
+,v1,-3.427,.332,-1.026,-10.334,.000
+
+Table: Model Summary (v2)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.971,.942,.925,1.337
+
+Table: ANOVA (v2)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,202.753,2,101.376,56.754,.000
+,Residual,12.504,7,1.786,,
+,Total,215.256,9,,,
+
+Table: Coefficients (v2)
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,(Constant),2.191,2.357,.000,.930,.380
+,v0,1.813,1.053,.171,1.722,.129
+,v1,-3.427,.332,-1.026,-10.334,.000
+
+Table: Data List
+v0,v1,v2,RES1,PRED1
+.654,7.736,-23.976,-.84,-23.13
+-.131,6.143,-19.639,-.54,-19.10
+.349,7.651,-25.266,-1.87,-23.40
+.692,6.125,-16.571,.97,-17.54
+-.074,8.246,-25.800,.40,-26.20
+-.344,6.032,-17.567,1.53,-19.10
+.760,9.832,-28.360,1.77,-30.13
+-.470,5.344,-16.795,.18,-16.97
+-.061,8.838,-29.257,-1.05,-28.21
+.562,6.200,-18.582,-.54,-18.04
+])
+AT_CLEANUP
+
+
+# Test to ensure that the /SAVE subcommand works properly when SPLIT is active
+AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
+
+# Generate some test data based on a linear model
+AT_DATA([gen-data.sps], [dnl
+set seed = 1.
+input program.
+loop #c = 1 to 20.
+ compute x0 = rv.normal (0,1).
+ compute x1 = rv.normal (0,2).
+ compute err = rv.normal (0,0.1).
+ compute y = 4 - 2 * x0 + 3 * x1 + err.
+ compute g = (#c > 10).
+ end case.
+end loop.
+end file.
+end input program.
+
+print outfile='regdata.txt' /g x0 x1 y err *.
+execute.
+])
+
+AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
+
+# Use our test data to create a predictor and a residual variable
+# for G == 0
+AT_DATA([regression0.sps], [dnl
+data list notable file='regdata.txt' list /g x0 x1 y err *.
+
+select if (g = 0).
+
+regression
+ /variables = x0 x1
+ /dependent = y
+ /statistics = all
+ /save = pred resid.
+ .
+
+print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
+execute.
+])
+
+
+AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
+
+# Use our test data to create a predictor and a residual variable
+# for G == 1
+AT_DATA([regression1.sps], [dnl
+data list notable file='regdata.txt' list /g x0 x1 y err *.
+
+select if (g = 1).
+
+regression
+ /variables = x0 x1
+ /dependent = y
+ /statistics = all
+ /save = pred resid.
+ .
+
+print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
+execute.
+])
+
+
+AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
+
+# Use our test data to create a predictor and a residual variable
+# The data is split on G
+AT_DATA([regression-split.sps], [dnl
+data list notable file='regdata.txt' list /g x0 x1 y err *.
+
+split file by g.
+
+regression
+ /variables = x0 x1
+ /dependent = y
+ /statistics = all
+ /save = pred resid.
+ .
+
+print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
+execute.
+])
+
+AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
+
+# The concatenation of G==0 and G==1 should be identical to the SPLIT data
+AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
+
+AT_CLEANUP
+
+
+# Test that the procedure behaves sensibly when presented with
+# multiple dependent variables
+AT_SETUP([LINEAR REGRESSION multiple dependent variables])
+AT_DATA([regression.sps], [dnl
+set seed = 2.
+input program.
+loop #c = 1 to 200.
+ compute x0 = rv.normal (0, 1).
+ compute x1 = rv.normal (0, 2).
+ compute err = rv.normal (0, 0.8).
+ compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
+ compute ycopy = y.
+ end case.
+end loop.
+end file.
+end input program.
+
+regression
+ /variables = x0 x1
+ /dependent = y ycopy
+ /statistics = default.
+])
+
+AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
+
+AT_CHECK([head -16 output > first], [0], [])
+AT_CHECK([tail -16 output > second], [0], [])
+
+AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
+
+
+AT_CLEANUP
+
# Tests the QR decomposition used by the REGRESSION command.
-AT_SETUP([REGRESSION test of QR decomposition])
+AT_SETUP([LINEAR REGRESSION test of QR decomposition])
AT_DATA([regression.sps], [dnl
data list list / v0 to v1.
begin data
end data
regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
])
-AT_CHECK([pspp -o pspp.csv regression.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
+
+AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
Table: Reading free-form data from INLINE.
Variable,Format
v0,F8.0
,.05,.00,.00,8.11
Table: ANOVA (v0)
-,,Sum of Squares,df,Mean Square,F,Significance
-,Regression,235.23,1,235.23,3.58,.06
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,235.23,1,235.23,3.58,.059
,Residual,98438.40,1498,65.71,,
,Total,98673.63,1499,,,
Table: Coefficients (v0)
-,,B,Std. Error,Beta,t,Significance
-,(Constant),1.24,.42,.00,2.95,.00
-,v1,1.37,.72,.05,1.89,.06
-,,,,,,
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,(Constant),1.24,.42,.00,2.95,.003
+,v1,1.37,.72,.05,1.89,.059
])
+
AT_CLEANUP
-AT_SETUP([REGRESSION no crash on all missing])
+AT_SETUP([LINEAR REGRESSION no crash on all missing])
AT_DATA([regcrash.sps], [dnl
data list list /x * y.
begin data.
-AT_SETUP([REGRESSION missing dependent variable])
+AT_SETUP([LINEAR REGRESSION missing dependent variable])
dnl Test for a bug where missing values in the dependent variable were not being
dnl ignored like they should have been.
AT_CLEANUP
-AT_SETUP([REGRESSION with invalid syntax (and empty dataset)])
+AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
AT_DATA([ss.sps], [dnl
data list notable list / v0 to v2.
AT_CHECK([pspp ss.sps], [1], [ignore])
AT_CLEANUP
+
+
+dnl The following example comes from
+dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
+AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
+
+AT_DATA([conf.sps], [dnl
+set format = F22.3.
+
+data list notable list /math female socst read science *
+begin data.
+ 41.00 .00 57.00 57.00 47.00
+ 53.00 1.00 61.00 68.00 63.00
+ 54.00 .00 31.00 44.00 58.00
+ 47.00 .00 56.00 63.00 53.00
+ 57.00 .00 61.00 47.00 53.00
+ 51.00 .00 61.00 44.00 63.00
+ 42.00 .00 61.00 50.00 53.00
+ 45.00 .00 36.00 34.00 39.00
+ 54.00 .00 51.00 63.00 58.00
+ 52.00 .00 51.00 57.00 50.00
+ 51.00 .00 61.00 60.00 53.00
+ 51.00 .00 61.00 57.00 63.00
+ 71.00 .00 71.00 73.00 61.00
+ 57.00 .00 46.00 54.00 55.00
+ 50.00 .00 56.00 45.00 31.00
+ 43.00 .00 56.00 42.00 50.00
+ 51.00 .00 56.00 47.00 50.00
+ 60.00 .00 56.00 57.00 58.00
+ 62.00 .00 61.00 68.00 55.00
+ 57.00 .00 46.00 55.00 53.00
+ 35.00 .00 41.00 63.00 66.00
+ 75.00 .00 66.00 63.00 72.00
+ 45.00 .00 56.00 50.00 55.00
+ 57.00 .00 61.00 60.00 61.00
+ 45.00 .00 46.00 37.00 39.00
+ 46.00 .00 31.00 34.00 39.00
+ 66.00 .00 66.00 65.00 61.00
+ 57.00 .00 46.00 47.00 58.00
+ 49.00 .00 46.00 44.00 39.00
+ 49.00 .00 41.00 52.00 55.00
+ 57.00 .00 51.00 42.00 47.00
+ 64.00 .00 61.00 76.00 64.00
+ 63.00 .00 71.00 65.00 66.00
+ 57.00 .00 31.00 42.00 72.00
+ 50.00 .00 61.00 52.00 61.00
+ 58.00 .00 66.00 60.00 61.00
+ 75.00 .00 66.00 68.00 66.00
+ 68.00 .00 66.00 65.00 66.00
+ 44.00 .00 36.00 47.00 36.00
+ 40.00 .00 51.00 39.00 39.00
+ 41.00 .00 51.00 47.00 42.00
+ 62.00 .00 51.00 55.00 58.00
+ 57.00 .00 51.00 52.00 55.00
+ 43.00 .00 41.00 42.00 50.00
+ 48.00 .00 66.00 65.00 63.00
+ 63.00 .00 46.00 55.00 69.00
+ 39.00 .00 47.00 50.00 49.00
+ 70.00 .00 51.00 65.00 63.00
+ 63.00 .00 46.00 47.00 53.00
+ 59.00 .00 51.00 57.00 47.00
+ 61.00 .00 56.00 53.00 57.00
+ 38.00 .00 41.00 39.00 47.00
+ 61.00 .00 46.00 44.00 50.00
+ 49.00 .00 71.00 63.00 55.00
+ 73.00 .00 66.00 73.00 69.00
+ 44.00 .00 42.00 39.00 26.00
+ 42.00 .00 32.00 37.00 33.00
+ 39.00 .00 46.00 42.00 56.00
+ 55.00 .00 41.00 63.00 58.00
+ 52.00 .00 51.00 48.00 44.00
+ 45.00 .00 61.00 50.00 58.00
+ 61.00 .00 66.00 47.00 69.00
+ 39.00 .00 46.00 44.00 34.00
+ 41.00 .00 36.00 34.00 36.00
+ 50.00 .00 61.00 50.00 36.00
+ 40.00 .00 26.00 44.00 50.00
+ 60.00 .00 66.00 60.00 55.00
+ 47.00 .00 26.00 47.00 42.00
+ 59.00 .00 44.00 63.00 65.00
+ 49.00 .00 36.00 50.00 44.00
+ 46.00 .00 51.00 44.00 39.00
+ 58.00 .00 61.00 60.00 58.00
+ 71.00 .00 66.00 73.00 63.00
+ 58.00 .00 66.00 68.00 74.00
+ 46.00 .00 51.00 55.00 58.00
+ 43.00 .00 31.00 47.00 45.00
+ 54.00 .00 61.00 55.00 49.00
+ 56.00 .00 66.00 68.00 63.00
+ 46.00 .00 46.00 31.00 39.00
+ 54.00 .00 56.00 47.00 42.00
+ 57.00 .00 56.00 63.00 55.00
+ 54.00 .00 36.00 36.00 61.00
+ 71.00 .00 56.00 68.00 66.00
+ 48.00 .00 56.00 63.00 63.00
+ 40.00 .00 41.00 55.00 44.00
+ 64.00 .00 66.00 55.00 63.00
+ 51.00 .00 56.00 52.00 53.00
+ 39.00 .00 56.00 34.00 42.00
+ 40.00 .00 31.00 50.00 34.00
+ 61.00 .00 56.00 55.00 61.00
+ 66.00 .00 46.00 52.00 47.00
+ 49.00 .00 46.00 63.00 66.00
+ 65.00 1.00 61.00 68.00 69.00
+ 52.00 1.00 48.00 39.00 44.00
+ 46.00 1.00 51.00 44.00 47.00
+ 61.00 1.00 51.00 50.00 63.00
+ 72.00 1.00 56.00 71.00 66.00
+ 71.00 1.00 71.00 63.00 69.00
+ 40.00 1.00 41.00 34.00 39.00
+ 69.00 1.00 61.00 63.00 61.00
+ 64.00 1.00 66.00 68.00 69.00
+ 56.00 1.00 61.00 47.00 66.00
+ 49.00 1.00 41.00 47.00 33.00
+ 54.00 1.00 51.00 63.00 50.00
+ 53.00 1.00 51.00 52.00 61.00
+ 66.00 1.00 56.00 55.00 42.00
+ 67.00 1.00 56.00 60.00 50.00
+ 40.00 1.00 33.00 35.00 51.00
+ 46.00 1.00 56.00 47.00 50.00
+ 69.00 1.00 71.00 71.00 58.00
+ 40.00 1.00 56.00 57.00 61.00
+ 41.00 1.00 51.00 44.00 39.00
+ 57.00 1.00 66.00 65.00 46.00
+ 58.00 1.00 56.00 68.00 59.00
+ 57.00 1.00 66.00 73.00 55.00
+ 37.00 1.00 41.00 36.00 42.00
+ 55.00 1.00 46.00 43.00 55.00
+ 62.00 1.00 66.00 73.00 58.00
+ 64.00 1.00 56.00 52.00 58.00
+ 40.00 1.00 51.00 41.00 39.00
+ 50.00 1.00 51.00 60.00 50.00
+ 46.00 1.00 56.00 50.00 50.00
+ 53.00 1.00 56.00 50.00 39.00
+ 52.00 1.00 46.00 47.00 48.00
+ 45.00 1.00 46.00 47.00 34.00
+ 56.00 1.00 61.00 55.00 58.00
+ 45.00 1.00 56.00 50.00 44.00
+ 54.00 1.00 41.00 39.00 50.00
+ 56.00 1.00 46.00 50.00 47.00
+ 41.00 1.00 26.00 34.00 29.00
+ 54.00 1.00 56.00 57.00 50.00
+ 72.00 1.00 56.00 57.00 54.00
+ 56.00 1.00 51.00 68.00 50.00
+ 47.00 1.00 46.00 42.00 47.00
+ 49.00 1.00 66.00 61.00 44.00
+ 60.00 1.00 66.00 76.00 67.00
+ 54.00 1.00 46.00 47.00 58.00
+ 55.00 1.00 56.00 46.00 44.00
+ 33.00 1.00 41.00 39.00 42.00
+ 49.00 1.00 61.00 52.00 44.00
+ 43.00 1.00 51.00 28.00 44.00
+ 50.00 1.00 52.00 42.00 50.00
+ 52.00 1.00 51.00 47.00 39.00
+ 48.00 1.00 41.00 47.00 44.00
+ 58.00 1.00 66.00 52.00 53.00
+ 43.00 1.00 61.00 47.00 48.00
+ 41.00 1.00 31.00 50.00 55.00
+ 43.00 1.00 51.00 44.00 44.00
+ 46.00 1.00 41.00 47.00 40.00
+ 44.00 1.00 41.00 45.00 34.00
+ 43.00 1.00 46.00 47.00 42.00
+ 61.00 1.00 56.00 65.00 58.00
+ 40.00 1.00 51.00 43.00 50.00
+ 49.00 1.00 61.00 47.00 53.00
+ 56.00 1.00 66.00 57.00 58.00
+ 61.00 1.00 71.00 68.00 55.00
+ 50.00 1.00 61.00 52.00 54.00
+ 51.00 1.00 61.00 42.00 47.00
+ 42.00 1.00 41.00 42.00 42.00
+ 67.00 1.00 66.00 66.00 61.00
+ 53.00 1.00 61.00 47.00 53.00
+ 50.00 1.00 58.00 57.00 51.00
+ 51.00 1.00 31.00 47.00 63.00
+ 72.00 1.00 61.00 57.00 61.00
+ 48.00 1.00 61.00 52.00 55.00
+ 40.00 1.00 31.00 44.00 40.00
+ 53.00 1.00 61.00 50.00 61.00
+ 39.00 1.00 36.00 39.00 47.00
+ 63.00 1.00 41.00 57.00 55.00
+ 51.00 1.00 37.00 57.00 53.00
+ 45.00 1.00 43.00 42.00 50.00
+ 39.00 1.00 61.00 47.00 47.00
+ 42.00 1.00 39.00 42.00 31.00
+ 62.00 1.00 51.00 60.00 61.00
+ 44.00 1.00 51.00 44.00 35.00
+ 65.00 1.00 66.00 63.00 54.00
+ 63.00 1.00 71.00 65.00 55.00
+ 54.00 1.00 41.00 39.00 53.00
+ 45.00 1.00 36.00 50.00 58.00
+ 60.00 1.00 51.00 52.00 56.00
+ 49.00 1.00 51.00 60.00 50.00
+ 48.00 1.00 51.00 44.00 39.00
+ 57.00 1.00 61.00 52.00 63.00
+ 55.00 1.00 61.00 55.00 50.00
+ 66.00 1.00 56.00 50.00 66.00
+ 64.00 1.00 71.00 65.00 58.00
+ 55.00 1.00 51.00 52.00 53.00
+ 42.00 1.00 36.00 47.00 42.00
+ 56.00 1.00 61.00 63.00 55.00
+ 53.00 1.00 66.00 50.00 53.00
+ 41.00 1.00 41.00 42.00 42.00
+ 42.00 1.00 41.00 36.00 50.00
+ 53.00 1.00 56.00 50.00 55.00
+ 42.00 1.00 51.00 41.00 34.00
+ 60.00 1.00 56.00 47.00 50.00
+ 52.00 1.00 56.00 55.00 42.00
+ 38.00 1.00 46.00 42.00 36.00
+ 57.00 1.00 52.00 57.00 55.00
+ 58.00 1.00 61.00 55.00 58.00
+ 65.00 1.00 61.00 63.00 53.00
+end data.
+
+regression
+ /variables = math female socst read
+ /statistics = coeff r anova ci (95)
+ /dependent = science
+ /method = enter
+])
+
+AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
+Table: Model Summary (science)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.699,.489,.479,7.148
+
+Table: ANOVA (science)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,9543.721,4,2385.930,46.695,.000
+,Residual,9963.779,195,51.096,,
+,Total,19507.500,199,,,
+
+Table: Coefficients (science)
+,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
+,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
+,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
+,math,.389,.074,.368,5.252,.000,.243,.535
+,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
+,socst,.050,.062,.054,.801,.424,-.073,.173
+,read,.335,.073,.347,4.607,.000,.192,.479
+])
+
+
+AT_CLEANUP
+
+
+dnl Checks for regression against bug #44877.
+AT_SETUP([LINEAR REGRESSION crash with long string variables])
+AT_DATA([regression.sps], [dnl
+SET DECIMAL=DOT.
+
+DATA LIST notable LIST /text (A24) Y * X1 *
+BEGIN DATA.
+V00276601 0.00 90.00
+V00292909 10.00 30.00
+V00291204 20.00 20.00
+V00300070 0.00 90.00
+END DATA.
+
+REGRESSION
+/VARIABLES= Y
+/DEPENDENT= X1
+/METHOD=ENTER
+/STATISTICS=COEFF R ANOVA
+/SAVE= RESID.
+
+LIST.
+])
+AT_CHECK([pspp -o pspp.csv regression.sps])
+AT_CHECK([cat pspp.csv], [0], [dnl
+Table: Model Summary (X1)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.95,.89,.84,15.08
+
+Table: ANOVA (X1)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,3820.45,1,3820.45,16.81,.055
+,Residual,454.55,2,227.27,,
+,Total,4275.00,3,,,
+
+Table: Coefficients (X1)
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,(Constant),85.45,10.16,.00,8.41,.004
+,Y,-3.73,.91,-.95,-4.10,.055
+
+Table: Data List
+text,Y,X1,RES1
+V00276601 ,.00,90.00,4.55
+V00292909 ,10.00,30.00,-18.18
+V00291204 ,20.00,20.00,9.09
+V00300070 ,.00,90.00,4.55
+])
+AT_CLEANUP
+
+
+dnl Test for a crash which happened on bad input syntax
+AT_SETUP([LINEAR REGRESSION -- Empty Parentheses])
+
+AT_DATA([empty-parens.sps], [dnl
+set format = F22.3.
+
+data list notable list /math female socst read science *
+begin data.
+ 58.00 1.00 61.00 55.00 58.00
+ 65.00 1.00 61.00 63.00 53.00
+end data.
+
+regression
+ /variables = math female socst read
+ /statistics = coeff r anova ci ()
+ /dependent = science
+ /method = enter
+])
+
+AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])
+
+AT_CLEANUP
+
+
+
+
+AT_SETUP([LINEAR REGRESSION varibles on ENTER subcommand])
+AT_DATA([regression.sps], [dnl
+SET FORMAT=F10.3.
+
+DATA LIST notable LIST /number * value *.
+BEGIN DATA
+ 16 7.25
+ 0 .00
+ 1 .10
+ 9 27.9
+ 0 .00
+ 7 3.65
+ 14 16.8
+ 24 9.15
+ 0 .00
+ 24 19.0
+ 7 4.05
+ 12 7.90
+ 6 .75
+ 11 1.40
+ 0 .00
+ 3 2.30
+ 12 7.60
+ 11 6.80
+ 16 8.65
+END DATA.
+
+REGRESSION
+ /STATISTICS COEFF R ANOVA
+ /DEPENDENT value
+ /METHOD=ENTER number.
+])
+
+
+AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
+Table: Model Summary (value)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.612,.374,.338,6.176
+
+Table: ANOVA (value)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,388.065,1,388.065,10.173,.005
+,Residual,648.498,17,38.147,,
+,Total,1036.563,18,,,
+
+Table: Coefficients (value)
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,(Constant),.927,2.247,.000,.413,.685
+,number,.611,.192,.612,3.189,.005
+])
+
+AT_CLEANUP
+
+
+
+AT_SETUP([LINEAR REGRESSION /ORIGIN])
+AT_DATA([regression-origin.sps], [dnl
+SET FORMAT=F10.3.
+
+DATA LIST notable LIST /number * value *.
+BEGIN DATA
+ 16 7.25
+ 0 .00
+ 1 .10
+ 9 27.9
+ 0 .00
+ 7 3.65
+ 14 16.8
+ 24 9.15
+ 0 .00
+ 24 19.0
+ 7 4.05
+ 12 7.90
+ 6 .75
+ 11 1.40
+ 0 .00
+ 3 2.30
+ 12 7.60
+ 11 6.80
+ 16 8.65
+END DATA.
+
+REGRESSION
+ /STATISTICS COEFF R ANOVA
+ /DEPENDENT value
+ /ORIGIN
+ /METHOD=ENTER number.
+])
+
+
+AT_CHECK([pspp -O format=csv regression-origin.sps], [0], [dnl
+Table: Model Summary (value)
+,R,R Square,Adjusted R Square,Std. Error of the Estimate
+,.802,.643,.622,6.032
+
+Table: ANOVA (value)
+,,Sum of Squares,df,Mean Square,F,Sig.
+,Regression,1181.726,1,1181.726,32.475,.000
+,Residual,654.989,18,36.388,,
+,Total,1836.715,19,,,
+
+Table: Coefficients (value)
+,,Unstandardized Coefficients,,Standardized Coefficients,,
+,,B,Std. Error,Beta,t,Sig.
+,number,.672,.118,.802,5.699,.000
+,,,,,,
+])
+
+AT_CLEANUP