1 AT_BANNER([LINEAR REGRESSION])
3 AT_SETUP([LINEAR REGRESSION - basic])
4 AT_DATA([regression.sps], [dnl
6 data list notable list / v0 to v2.
8 0.65377128 7.735648 -23.97588
9 -0.13087553 6.142625 -19.63854
10 0.34880368 7.651430 -25.26557
11 0.69249021 6.125125 -16.57090
12 -0.07368178 8.245789 -25.80001
13 -0.34404919 6.031540 -17.56743
14 0.75981559 9.832291 -28.35977
15 -0.46958313 5.343832 -16.79548
16 -0.06108490 8.838262 -29.25689
17 0.56154863 6.200189 -18.58219
19 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
23 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
24 Table: Model Summary (v2)
25 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
29 ,,Sum of Squares,df,Mean Square,F,Sig.
30 ,Regression,202.753,2,101.376,56.754,.000
31 ,Residual,12.504,7,1.786,,
34 Table: Coefficients (v2)
35 ,,Unstandardized Coefficients,,Standardized Coefficients,,
36 ,,B,Std. Error,Beta,t,Sig.
37 ,(Constant),2.191,2.357,.000,.930,.380
38 ,v0,1.813,1.053,.171,1.722,.129
39 ,v1,-3.427,.332,-1.026,-10.334,.000
43 .654,7.736,-23.976,-.84,-23.13
44 -.131,6.143,-19.639,-.54,-19.10
45 .349,7.651,-25.266,-1.87,-23.40
46 .692,6.125,-16.571,.97,-17.54
47 -.074,8.246,-25.800,.40,-26.20
48 -.344,6.032,-17.567,1.53,-19.10
49 .760,9.832,-28.360,1.77,-30.13
50 -.470,5.344,-16.795,.18,-16.97
51 -.061,8.838,-29.257,-1.05,-28.21
52 .562,6.200,-18.582,-.54,-18.04
57 AT_SETUP([LINEAR REGRESSION - one save])
58 AT_DATA([regression.sps], [dnl
60 data list notable list / v0 to v2.
62 0.65377128 7.735648 -23.97588
63 -0.13087553 6.142625 -19.63854
64 0.34880368 7.651430 -25.26557
65 0.69249021 6.125125 -16.57090
66 -0.07368178 8.245789 -25.80001
67 -0.34404919 6.031540 -17.56743
68 0.75981559 9.832291 -28.35977
69 -0.46958313 5.343832 -16.79548
70 -0.06108490 8.838262 -29.25689
71 0.56154863 6.200189 -18.58219
73 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
74 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
78 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
79 Table: Model Summary (v2)
80 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
84 ,,Sum of Squares,df,Mean Square,F,Sig.
85 ,Regression,202.753,2,101.376,56.754,.000
86 ,Residual,12.504,7,1.786,,
89 Table: Coefficients (v2)
90 ,,Unstandardized Coefficients,,Standardized Coefficients,,
91 ,,B,Std. Error,Beta,t,Sig.
92 ,(Constant),2.191,2.357,.000,.930,.380
93 ,v0,1.813,1.053,.171,1.722,.129
94 ,v1,-3.427,.332,-1.026,-10.334,.000
96 Table: Model Summary (v2)
97 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
101 ,,Sum of Squares,df,Mean Square,F,Sig.
102 ,Regression,202.753,2,101.376,56.754,.000
103 ,Residual,12.504,7,1.786,,
106 Table: Coefficients (v2)
107 ,,Unstandardized Coefficients,,Standardized Coefficients,,
108 ,,B,Std. Error,Beta,t,Sig.
109 ,(Constant),2.191,2.357,.000,.930,.380
110 ,v0,1.813,1.053,.171,1.722,.129
111 ,v1,-3.427,.332,-1.026,-10.334,.000
115 .654,7.736,-23.976,-.84,-23.13
116 -.131,6.143,-19.639,-.54,-19.10
117 .349,7.651,-25.266,-1.87,-23.40
118 .692,6.125,-16.571,.97,-17.54
119 -.074,8.246,-25.800,.40,-26.20
120 -.344,6.032,-17.567,1.53,-19.10
121 .760,9.832,-28.360,1.77,-30.13
122 -.470,5.344,-16.795,.18,-16.97
123 -.061,8.838,-29.257,-1.05,-28.21
124 .562,6.200,-18.582,-.54,-18.04
129 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
130 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
132 # Generate some test data based on a linear model
133 AT_DATA([gen-data.sps], [dnl
137 compute x0 = rv.normal (0,1).
138 compute x1 = rv.normal (0,2).
139 compute err = rv.normal (0,0.1).
140 compute y = 4 - 2 * x0 + 3 * x1 + err.
141 compute g = (#c > 10).
147 print outfile='regdata.txt' /g x0 x1 y err *.
151 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
153 # Use our test data to create a predictor and a residual variable
155 AT_DATA([regression0.sps], [dnl
156 data list notable file='regdata.txt' list /g x0 x1 y err *.
167 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
172 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
174 # Use our test data to create a predictor and a residual variable
176 AT_DATA([regression1.sps], [dnl
177 data list notable file='regdata.txt' list /g x0 x1 y err *.
188 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
193 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
195 # Use our test data to create a predictor and a residual variable
196 # The data is split on G
197 AT_DATA([regression-split.sps], [dnl
198 data list notable file='regdata.txt' list /g x0 x1 y err *.
209 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
213 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
215 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
216 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
221 # Test that the procedure behaves sensibly when presented with
222 # multiple dependent variables
223 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
224 AT_DATA([regression.sps], [dnl
228 compute x0 = rv.normal (0, 1).
229 compute x1 = rv.normal (0, 2).
230 compute err = rv.normal (0, 0.8).
231 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
241 /statistics = default.
244 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
246 AT_CHECK([head -16 output > first], [0], [])
247 AT_CHECK([tail -16 output > second], [0], [])
249 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
254 # Tests the QR decomposition used by the REGRESSION command.
255 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
256 AT_DATA([regression.sps], [dnl
257 data list list / v0 to v1.
259 -12.84099361 0.873270778
260 16.64932538 0.371315664
261 -1.88061907 0.505503722
262 -6.20952354 0.734698282
263 0.33272576 0.891224610
264 -5.54912717 0.052318165
265 6.11832417 0.448853404
266 11.78124974 0.470447593
267 0.75960353 0.565082303
268 6.06432768 0.149316743
269 -2.64919436 0.752532411
270 -10.32250712 0.798263603
271 2.06355038 0.469129797
272 -9.71851742 0.927162270
273 4.65582553 0.250629262
274 9.54574474 0.847032310
275 7.35544368 0.197028541
276 -2.09609740 0.400584261
277 10.30101161 0.671546480
278 -5.24501039 0.929962876
279 1.73412473 0.758161354
280 -3.12732732 0.569785505
281 12.66261501 0.630640223
282 -2.90956805 0.576067804
283 4.89649177 0.624483995
284 13.64613114 0.591089881
285 14.03198397 0.544587572
286 2.23566810 0.967898139
287 5.37367760 0.916246929
288 9.01346888 0.451702743
289 0.75378683 0.235544137
290 -3.47470624 0.742668194
291 -1.02063266 0.860311687
292 -2.67132813 0.082460702
293 23.67661680 0.932553932
294 7.95061359 0.430161125
295 2.05300558 0.066331375
296 -2.01332644 0.163705417
297 20.00663784 0.587292630
298 3.06099417 0.161411889
299 -3.46115358 0.216684625
300 -6.85287183 0.548714855
301 -4.27923809 0.630997663
302 -0.94863395 0.880612945
303 4.47481747 0.359885215
304 -12.80962955 0.886070341
305 9.35753086 0.187176558
306 2.81002235 0.063035095
307 0.01532424 0.964327101
308 0.29867732 0.866408063
309 -2.89035649 0.812135868
310 4.17352811 0.608884061
311 18.15502183 0.920568258
312 -2.92662792 0.550792959
313 -6.08090449 0.965036595
314 -1.09135397 0.862548019
315 7.02816784 0.042277017
316 -21.20245068 0.430673493
317 -8.83397584 0.724976162
318 -0.89055843 0.017934904
319 7.03871587 0.308829557
320 3.84286316 0.685105924
321 4.50280692 0.447635420
322 11.39207346 0.875177896
323 10.86673874 0.518530912
324 7.09853081 0.588367569
325 -12.82864915 0.184667098
326 13.74888760 0.610891139
327 0.37379146 0.557720134
328 -9.79020267 0.942839981
329 0.71574466 0.564570338
330 -17.56040637 0.182061777
331 2.52620466 0.306875011
332 5.37718673 0.366807049
333 -1.83964300 0.465772898
334 6.04848363 0.644501799
335 4.57402403 0.121419591
336 8.55606848 0.373011464
337 -8.46827907 0.491176571
338 -1.77989798 0.734722847
339 -0.68661121 0.540984182
340 1.55798880 0.822587656
341 5.22810831 0.333747878
342 9.50280477 0.068100934
343 -3.74521465 0.248537644
344 1.36045068 0.851827791
345 4.41604088 0.197207162
346 -3.72568327 0.726916693
347 -5.36123334 0.906513529
348 3.61594583 0.414340595
349 -10.01952852 0.140372658
350 25.48681482 0.354309660
351 -3.34529093 0.090075388
352 -18.00437582 0.461438059
353 -5.29782460 0.004362856
354 2.79608522 0.861294398
355 -1.64076209 0.345775481
356 6.82802334 0.137933862
357 -0.45416818 0.404379208
358 -1.66868582 0.797685201
359 -10.02820292 0.075876582
360 5.68232031 0.404815042
361 8.25113850 0.769173748
362 -2.83544237 0.076583474
363 0.87659945 0.092751009
364 6.60270870 0.530444351
365 -12.63924989 0.362099960
366 -6.24451253 0.641993458
367 3.53339015 0.461991892
368 -0.74012232 0.437409755
369 15.37311996 0.974913038
370 -8.09464797 0.543308711
371 -9.61320222 0.221564578
372 0.21843662 0.856512540
373 -1.56958954 0.610709221
374 6.44977372 0.200382138
375 -13.29136274 0.093222309
376 6.46257214 0.024135196
377 -3.82727990 0.601335801
378 0.43081953 0.268230667
379 19.06654416 0.219972815
380 17.02906651 0.996849502
381 -10.18073139 0.012543080
382 12.72088788 0.910600764
383 10.45328185 0.331285901
384 7.14370922 0.896312020
385 -2.81754334 0.048741266
386 6.40217095 0.075796756
387 -3.18030478 0.666325307
388 8.64585957 0.120549153
389 1.37952764 0.899991932
390 -11.81143886 0.601949630
391 0.03899706 0.363808260
392 -10.63828243 0.031092967
393 -6.66940972 0.246204205
394 -5.07374962 0.951272057
395 4.82281566 0.063928187
396 -21.93693564 0.050972680
397 -4.54569883 0.225839693
398 -0.92422779 0.437796785
399 -1.11683029 0.740215139
400 16.77765554 0.851072372
401 9.73614597 0.388180586
402 14.05345168 0.063760129
403 1.20512012 0.665964184
404 8.00307080 0.102447114
405 8.01252623 0.580929209
406 -13.54924183 0.438420739
407 9.87164361 0.970859344
408 17.63437095 0.250501797
409 -3.42503574 0.873290220
410 -2.45873197 0.847756049
411 17.29212092 0.411683187
412 1.15496098 0.530658504
413 -2.14438907 0.592255367
414 -1.79942021 0.517773009
415 -1.30677990 0.830860762
416 1.70233874 0.291826660
417 -3.05532536 0.801767829
418 -4.06732625 0.092294501
419 6.34665476 0.270426235
420 9.46946411 0.196915311
421 14.50919907 0.480357167
422 8.93767237 0.778228613
423 1.90298854 0.903146151
424 18.50500507 0.598561307
425 4.45123027 0.555898218
426 11.37344114 0.616557707
427 -12.14693218 0.409187285
428 18.27198688 0.141619222
429 -5.75939569 0.056989619
430 -4.05515382 0.369281201
431 16.69882098 0.946885257
432 6.39050536 0.679704228
433 4.04213339 0.662792380
434 6.89608366 0.419877433
435 1.56496633 0.358227958
436 5.16679947 0.095144366
437 -3.06280456 0.883265975
438 2.76279175 0.866571973
439 1.84969249 0.264869828
440 21.79840498 0.702650979
441 1.42450528 0.719308635
442 0.96797046 0.111937435
443 18.26840323 0.075621738
444 13.38288377 0.573399086
445 2.41101500 0.766238677
446 3.83866337 0.499888953
447 -1.56577367 0.695244089
448 -0.90342790 0.671654151
449 10.83775583 0.026041124
450 -9.89767935 0.745297991
451 11.74840150 0.309144074
452 1.73069359 0.814063985
453 -5.27966183 0.591005828
454 3.33030043 0.559401806
455 1.31427975 0.520950237
456 -10.04588558 0.507008362
457 10.41228345 0.425867272
458 1.71961097 0.595783108
459 -17.54904427 0.328788939
460 -2.23545419 0.223377350
461 -8.68774333 0.980964240
462 -3.48048220 0.008877675
463 -3.69635326 0.090236718
464 9.76114237 0.769375983
465 -10.25662038 0.508137553
466 0.11155446 0.468504431
467 -8.06824580 0.414098962
468 3.10031660 0.327130207
469 -3.33393146 0.756896774
470 -3.96276749 0.530956360
471 14.53610268 0.846474699
472 1.70505918 0.754662464
473 -1.93495001 0.656650411
474 5.01974522 0.745337633
475 13.41249973 0.489362476
476 11.49288744 0.335924476
477 12.59019763 0.155560469
478 -10.17947298 0.677318449
479 0.05556115 0.655090105
480 3.82092860 0.051838719
481 8.23041456 0.918272190
482 -0.50314649 0.772015826
483 20.05162157 0.880265258
484 8.98816884 0.666646668
485 -6.28312120 0.138534416
486 3.68589909 0.274559458
487 0.59699510 0.253180863
488 -2.74783135 0.983525221
489 0.32515065 0.839969577
490 -3.60606166 0.330646732
491 -0.82037740 0.129591173
492 6.12444860 0.098536516
493 10.95671074 0.033546728
494 -2.84911174 0.720288722
495 6.04597572 0.577061422
496 -0.60147150 0.674096868
497 -5.30458364 0.291468008
498 2.68044943 0.379853840
499 0.85986585 0.984214339
500 -12.77906359 0.882390290
501 7.21420144 0.550884826
502 2.31817022 0.231021556
503 11.60161950 0.888496654
504 -0.19346228 0.242609713
505 5.07478120 0.759161318
506 14.54155003 0.040387654
507 3.81039636 0.874572741
508 2.23233049 0.448317248
509 0.19481869 0.201906051
510 2.81530451 0.132131690
511 12.39893259 0.674693704
512 0.47054642 0.632959494
513 2.16152913 0.734480632
514 0.33398836 0.315024718
515 7.35509037 0.304570986
516 -2.92336559 0.539062343
517 5.79622573 0.392393310
518 -2.37607425 0.403380474
519 0.04498550 0.756875541
520 -1.63674414 0.613789514
521 11.80310547 0.832651469
522 6.30630243 0.850689403
523 1.48394652 0.096243229
524 4.03361865 0.799660045
525 3.54707273 0.408520520
526 2.00327040 0.702944912
527 17.30761707 0.380542812
528 5.72738968 0.105447516
529 -13.64604891 0.328506659
530 8.35976334 0.702173924
531 -7.41197443 0.134396488
532 -15.95683040 0.618526462
533 8.76889573 0.950243069
534 -1.13482624 0.113477080
535 -0.60311407 0.090444247
536 4.95508365 0.612511543
537 5.36934491 0.979213258
538 -0.03554882 0.807185690
539 -11.58131144 0.183341373
540 4.46809041 0.796330582
541 12.49741067 0.346860912
542 8.63824488 0.073684997
543 0.49990913 0.732519306
544 12.82688360 0.109400213
545 13.20375065 0.850369092
546 -8.41110869 0.177717087
547 16.31959963 0.727704840
548 17.59203613 0.235311681
549 0.32148420 0.842195936
550 5.43148331 0.670904647
551 7.14649727 0.028190029
552 0.25410683 0.421535783
553 -12.41047826 0.086404379
554 -10.64180909 0.229659236
555 -6.40185653 0.876365242
556 15.63063324 0.667672536
557 1.94280423 0.799266628
558 -5.76507450 0.367344192
559 8.60895533 0.154109357
560 9.38306751 0.788742770
561 3.43573528 0.284535277
562 4.81848966 0.872283177
563 11.65839314 0.234109111
564 -5.57884822 0.030363060
565 -3.94238060 0.325320686
566 9.38133340 0.201141788
567 -7.65003459 0.647734396
568 11.23091019 0.084927159
569 -6.07705432 0.037273791
570 7.46380750 0.506897136
571 7.42034855 0.869351148
572 -4.43031973 0.231191152
573 -1.07351537 0.480234836
574 -1.40653281 0.690620421
575 -3.82710168 0.990191328
576 5.04583490 0.543427375
577 -11.54265099 0.270542185
578 0.49059479 0.991447248
579 -1.40871469 0.555998766
580 3.64241437 0.743840673
581 -18.30031589 0.357478210
582 4.27487959 0.770619738
583 1.28805821 0.654787106
584 -3.19542768 0.218110139
585 12.53375654 0.011857644
586 11.78889419 0.054127726
587 -5.38392310 0.839309080
588 16.38024181 0.228801038
589 -0.59622631 0.134381782
590 -0.74107258 0.258146632
591 -12.31429450 0.020524447
592 -0.79785028 0.968028764
593 6.39899711 0.038162566
594 7.42024044 0.716163692
595 -3.62470664 0.018201813
596 -2.55049724 0.162446610
597 -10.79888854 0.683070478
598 10.18490144 0.546461234
599 -2.76979044 0.198830067
600 4.85164813 0.094100357
601 0.96477200 0.381801756
602 8.13344336 0.639730450
603 9.04684412 0.786084368
604 10.41746272 0.828304181
605 0.94334368 0.798419831
606 10.13116556 0.191715972
607 -4.12728628 0.575178239
608 -9.59222379 0.876405375
609 1.64680258 0.391003085
610 -4.58897613 0.039176486
611 0.38394379 0.511577564
612 -4.80428215 0.222785463
613 0.35363661 0.681658725
614 -9.63685708 0.183035382
615 3.54363414 0.766127414
616 6.89610808 0.967514568
617 -2.03781105 0.464416752
618 8.67956196 0.421424078
619 -1.09959038 0.061231448
620 7.12587456 0.028601318
621 -6.93064672 0.402561175
622 8.57989199 0.925089270
623 -9.55071810 0.454993099
624 -8.11914736 0.509644286
625 -5.41909698 0.077813151
626 -17.03336572 0.875713545
627 -1.27438609 0.602163625
628 3.09834374 0.105599007
629 -1.59865741 0.439939102
630 11.82272089 0.754984309
631 4.30969696 0.483834579
632 -10.76886192 0.222486992
633 7.05419803 0.903020271
634 7.36096847 0.440357053
635 -2.05864869 0.581170147
636 -9.08366913 0.318677911
637 8.57119930 0.605668919
638 7.87702340 0.570206991
639 5.22035786 0.542344385
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1692 -2.59318107 0.571116303
1693 6.95988992 0.650760909
1694 14.00074797 0.623645969
1695 1.66101456 0.558763985
1696 -2.57968349 0.648185379
1697 -5.47584253 0.716901151
1698 6.37222581 0.060563130
1699 2.83664864 0.842419730
1700 1.48926558 0.620280308
1701 0.33471689 0.170312461
1702 5.21648412 0.317639631
1703 0.51733642 0.843867329
1704 9.86005834 0.306036746
1705 -5.81145791 0.975655452
1706 -5.43219061 0.303385368
1707 5.87157118 0.677369776
1708 2.08889926 0.310200439
1709 -2.53433085 0.194730908
1710 7.01359575 0.674259533
1711 -2.00936260 0.682056466
1712 -2.98240739 0.787899917
1713 -7.43289210 0.357483044
1714 -12.58905988 0.981387385
1715 5.78095517 0.533526274
1716 -1.23065889 0.687266774
1717 -6.82309960 0.293249774
1718 8.47000829 0.842056399
1719 -5.81624772 0.303700280
1720 -14.83571031 0.311387926
1721 4.66808472 0.091222946
1722 -2.90144463 0.438301785
1723 10.62458662 0.828335698
1724 7.88002491 0.990156110
1725 10.27680283 0.251087079
1726 -9.42498970 0.292462244
1727 6.73027640 0.213065205
1728 1.28169895 0.353152789
1729 -14.29203733 0.264563048
1730 20.35772711 0.265208837
1731 3.55095071 0.242905653
1732 -17.97067670 0.373951756
1733 10.53141139 0.247520698
1734 0.05293205 0.579940423
1735 12.79674707 0.288031751
1736 -5.44235185 0.075899079
1737 14.29464811 0.960707538
1738 -1.36753291 0.124265178
1739 -4.25946974 0.521720352
1740 -12.46519252 0.385503339
1741 -6.65343143 0.540942219
1742 5.55949184 0.143194404
1743 -1.20480594 0.515905644
1744 -4.13839908 0.164461445
1745 -2.21345425 0.812969725
1746 3.94223380 0.229238952
1747 -10.78661097 0.395049514
1748 3.06997341 0.791234255
1749 24.82205477 0.110859039
1750 6.28791249 0.867125744
1751 -2.80296119 0.703583849
1752 13.24274039 0.425951975
1753 -0.19577471 0.361568727
1754 -2.34894781 0.954814545
1755 19.76339577 0.635462177
1756 -1.87591480 0.149121567
1757 -7.70962391 0.711708342
1758 -2.46291902 0.390902746
1760 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1763 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
1764 Table: Reading free-form data from INLINE.
1769 Table: Model Summary (v0)
1770 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1774 ,,Sum of Squares,df,Mean Square,F,Sig.
1775 ,Regression,235.23,1,235.23,3.58,.059
1776 ,Residual,98438.40,1498,65.71,,
1777 ,Total,98673.63,1499,,,
1779 Table: Coefficients (v0)
1780 ,,Unstandardized Coefficients,,Standardized Coefficients,,
1781 ,,B,Std. Error,Beta,t,Sig.
1782 ,(Constant),1.24,.42,.00,2.95,.003
1783 ,v1,1.37,.72,.05,1.89,.059
1788 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1789 AT_DATA([regcrash.sps], [dnl
1790 data list list /x * y.
1805 regression /variables=x y /dependent=y.
1808 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1814 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1816 dnl Test for a bug where missing values in the dependent variable were not being
1817 dnl ignored like they should have been.
1818 AT_DATA([reg-mdv-ref.sps], [dnl
1819 data list notable list / v0 to v2.
1821 0.65377128 7.735648 -23.97588
1822 -0.13087553 6.142625 -19.63854
1823 0.34880368 7.651430 -25.26557
1824 0.69249021 6.125125 -16.57090
1825 -0.07368178 8.245789 -25.80001
1826 -0.34404919 6.031540 -17.56743
1827 0.75981559 9.832291 -28.35977
1828 -0.46958313 5.343832 -16.79548
1829 -0.06108490 8.838262 -29.25689
1830 0.56154863 6.200189 -18.58219
1832 regression /variables=v0 v1
1833 /statistics defaults
1838 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1840 AT_DATA([reg-mdv.sps], [dnl
1841 data list notable list / v0 to v2.
1843 0.65377128 7.735648 -23.97588
1844 -0.13087553 6.142625 -19.63854
1845 0.34880368 7.651430 -25.26557
1846 0.69249021 6.125125 -16.57090
1847 -0.07368178 8.245789 -25.80001
1848 -0.34404919 6.031540 -17.56743
1849 0.75981559 9.832291 -28.35977
1850 -0.46958313 5.343832 -16.79548
1851 -0.06108490 8.838262 -29.25689
1852 0.56154863 6.200189 -18.58219
1856 missing values v2 (9).
1858 regression /variables=v0 v1
1859 /statistics defaults
1864 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1866 AT_CHECK([diff pspp.csv pspp-ref.csv])
1871 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1873 AT_DATA([ss.sps], [dnl
1874 data list notable list / v0 to v2.
1878 regression /variables=v0 v1
1879 /statistics r coeff anova
1884 AT_CHECK([pspp ss.sps], [1], [ignore])
1889 dnl The following example comes from
1890 dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
1891 AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
1893 AT_DATA([conf.sps], [dnl
1896 data list notable list /math female socst read science *
1898 41.00 .00 57.00 57.00 47.00
1899 53.00 1.00 61.00 68.00 63.00
1900 54.00 .00 31.00 44.00 58.00
1901 47.00 .00 56.00 63.00 53.00
1902 57.00 .00 61.00 47.00 53.00
1903 51.00 .00 61.00 44.00 63.00
1904 42.00 .00 61.00 50.00 53.00
1905 45.00 .00 36.00 34.00 39.00
1906 54.00 .00 51.00 63.00 58.00
1907 52.00 .00 51.00 57.00 50.00
1908 51.00 .00 61.00 60.00 53.00
1909 51.00 .00 61.00 57.00 63.00
1910 71.00 .00 71.00 73.00 61.00
1911 57.00 .00 46.00 54.00 55.00
1912 50.00 .00 56.00 45.00 31.00
1913 43.00 .00 56.00 42.00 50.00
1914 51.00 .00 56.00 47.00 50.00
1915 60.00 .00 56.00 57.00 58.00
1916 62.00 .00 61.00 68.00 55.00
1917 57.00 .00 46.00 55.00 53.00
1918 35.00 .00 41.00 63.00 66.00
1919 75.00 .00 66.00 63.00 72.00
1920 45.00 .00 56.00 50.00 55.00
1921 57.00 .00 61.00 60.00 61.00
1922 45.00 .00 46.00 37.00 39.00
1923 46.00 .00 31.00 34.00 39.00
1924 66.00 .00 66.00 65.00 61.00
1925 57.00 .00 46.00 47.00 58.00
1926 49.00 .00 46.00 44.00 39.00
1927 49.00 .00 41.00 52.00 55.00
1928 57.00 .00 51.00 42.00 47.00
1929 64.00 .00 61.00 76.00 64.00
1930 63.00 .00 71.00 65.00 66.00
1931 57.00 .00 31.00 42.00 72.00
1932 50.00 .00 61.00 52.00 61.00
1933 58.00 .00 66.00 60.00 61.00
1934 75.00 .00 66.00 68.00 66.00
1935 68.00 .00 66.00 65.00 66.00
1936 44.00 .00 36.00 47.00 36.00
1937 40.00 .00 51.00 39.00 39.00
1938 41.00 .00 51.00 47.00 42.00
1939 62.00 .00 51.00 55.00 58.00
1940 57.00 .00 51.00 52.00 55.00
1941 43.00 .00 41.00 42.00 50.00
1942 48.00 .00 66.00 65.00 63.00
1943 63.00 .00 46.00 55.00 69.00
1944 39.00 .00 47.00 50.00 49.00
1945 70.00 .00 51.00 65.00 63.00
1946 63.00 .00 46.00 47.00 53.00
1947 59.00 .00 51.00 57.00 47.00
1948 61.00 .00 56.00 53.00 57.00
1949 38.00 .00 41.00 39.00 47.00
1950 61.00 .00 46.00 44.00 50.00
1951 49.00 .00 71.00 63.00 55.00
1952 73.00 .00 66.00 73.00 69.00
1953 44.00 .00 42.00 39.00 26.00
1954 42.00 .00 32.00 37.00 33.00
1955 39.00 .00 46.00 42.00 56.00
1956 55.00 .00 41.00 63.00 58.00
1957 52.00 .00 51.00 48.00 44.00
1958 45.00 .00 61.00 50.00 58.00
1959 61.00 .00 66.00 47.00 69.00
1960 39.00 .00 46.00 44.00 34.00
1961 41.00 .00 36.00 34.00 36.00
1962 50.00 .00 61.00 50.00 36.00
1963 40.00 .00 26.00 44.00 50.00
1964 60.00 .00 66.00 60.00 55.00
1965 47.00 .00 26.00 47.00 42.00
1966 59.00 .00 44.00 63.00 65.00
1967 49.00 .00 36.00 50.00 44.00
1968 46.00 .00 51.00 44.00 39.00
1969 58.00 .00 61.00 60.00 58.00
1970 71.00 .00 66.00 73.00 63.00
1971 58.00 .00 66.00 68.00 74.00
1972 46.00 .00 51.00 55.00 58.00
1973 43.00 .00 31.00 47.00 45.00
1974 54.00 .00 61.00 55.00 49.00
1975 56.00 .00 66.00 68.00 63.00
1976 46.00 .00 46.00 31.00 39.00
1977 54.00 .00 56.00 47.00 42.00
1978 57.00 .00 56.00 63.00 55.00
1979 54.00 .00 36.00 36.00 61.00
1980 71.00 .00 56.00 68.00 66.00
1981 48.00 .00 56.00 63.00 63.00
1982 40.00 .00 41.00 55.00 44.00
1983 64.00 .00 66.00 55.00 63.00
1984 51.00 .00 56.00 52.00 53.00
1985 39.00 .00 56.00 34.00 42.00
1986 40.00 .00 31.00 50.00 34.00
1987 61.00 .00 56.00 55.00 61.00
1988 66.00 .00 46.00 52.00 47.00
1989 49.00 .00 46.00 63.00 66.00
1990 65.00 1.00 61.00 68.00 69.00
1991 52.00 1.00 48.00 39.00 44.00
1992 46.00 1.00 51.00 44.00 47.00
1993 61.00 1.00 51.00 50.00 63.00
1994 72.00 1.00 56.00 71.00 66.00
1995 71.00 1.00 71.00 63.00 69.00
1996 40.00 1.00 41.00 34.00 39.00
1997 69.00 1.00 61.00 63.00 61.00
1998 64.00 1.00 66.00 68.00 69.00
1999 56.00 1.00 61.00 47.00 66.00
2000 49.00 1.00 41.00 47.00 33.00
2001 54.00 1.00 51.00 63.00 50.00
2002 53.00 1.00 51.00 52.00 61.00
2003 66.00 1.00 56.00 55.00 42.00
2004 67.00 1.00 56.00 60.00 50.00
2005 40.00 1.00 33.00 35.00 51.00
2006 46.00 1.00 56.00 47.00 50.00
2007 69.00 1.00 71.00 71.00 58.00
2008 40.00 1.00 56.00 57.00 61.00
2009 41.00 1.00 51.00 44.00 39.00
2010 57.00 1.00 66.00 65.00 46.00
2011 58.00 1.00 56.00 68.00 59.00
2012 57.00 1.00 66.00 73.00 55.00
2013 37.00 1.00 41.00 36.00 42.00
2014 55.00 1.00 46.00 43.00 55.00
2015 62.00 1.00 66.00 73.00 58.00
2016 64.00 1.00 56.00 52.00 58.00
2017 40.00 1.00 51.00 41.00 39.00
2018 50.00 1.00 51.00 60.00 50.00
2019 46.00 1.00 56.00 50.00 50.00
2020 53.00 1.00 56.00 50.00 39.00
2021 52.00 1.00 46.00 47.00 48.00
2022 45.00 1.00 46.00 47.00 34.00
2023 56.00 1.00 61.00 55.00 58.00
2024 45.00 1.00 56.00 50.00 44.00
2025 54.00 1.00 41.00 39.00 50.00
2026 56.00 1.00 46.00 50.00 47.00
2027 41.00 1.00 26.00 34.00 29.00
2028 54.00 1.00 56.00 57.00 50.00
2029 72.00 1.00 56.00 57.00 54.00
2030 56.00 1.00 51.00 68.00 50.00
2031 47.00 1.00 46.00 42.00 47.00
2032 49.00 1.00 66.00 61.00 44.00
2033 60.00 1.00 66.00 76.00 67.00
2034 54.00 1.00 46.00 47.00 58.00
2035 55.00 1.00 56.00 46.00 44.00
2036 33.00 1.00 41.00 39.00 42.00
2037 49.00 1.00 61.00 52.00 44.00
2038 43.00 1.00 51.00 28.00 44.00
2039 50.00 1.00 52.00 42.00 50.00
2040 52.00 1.00 51.00 47.00 39.00
2041 48.00 1.00 41.00 47.00 44.00
2042 58.00 1.00 66.00 52.00 53.00
2043 43.00 1.00 61.00 47.00 48.00
2044 41.00 1.00 31.00 50.00 55.00
2045 43.00 1.00 51.00 44.00 44.00
2046 46.00 1.00 41.00 47.00 40.00
2047 44.00 1.00 41.00 45.00 34.00
2048 43.00 1.00 46.00 47.00 42.00
2049 61.00 1.00 56.00 65.00 58.00
2050 40.00 1.00 51.00 43.00 50.00
2051 49.00 1.00 61.00 47.00 53.00
2052 56.00 1.00 66.00 57.00 58.00
2053 61.00 1.00 71.00 68.00 55.00
2054 50.00 1.00 61.00 52.00 54.00
2055 51.00 1.00 61.00 42.00 47.00
2056 42.00 1.00 41.00 42.00 42.00
2057 67.00 1.00 66.00 66.00 61.00
2058 53.00 1.00 61.00 47.00 53.00
2059 50.00 1.00 58.00 57.00 51.00
2060 51.00 1.00 31.00 47.00 63.00
2061 72.00 1.00 61.00 57.00 61.00
2062 48.00 1.00 61.00 52.00 55.00
2063 40.00 1.00 31.00 44.00 40.00
2064 53.00 1.00 61.00 50.00 61.00
2065 39.00 1.00 36.00 39.00 47.00
2066 63.00 1.00 41.00 57.00 55.00
2067 51.00 1.00 37.00 57.00 53.00
2068 45.00 1.00 43.00 42.00 50.00
2069 39.00 1.00 61.00 47.00 47.00
2070 42.00 1.00 39.00 42.00 31.00
2071 62.00 1.00 51.00 60.00 61.00
2072 44.00 1.00 51.00 44.00 35.00
2073 65.00 1.00 66.00 63.00 54.00
2074 63.00 1.00 71.00 65.00 55.00
2075 54.00 1.00 41.00 39.00 53.00
2076 45.00 1.00 36.00 50.00 58.00
2077 60.00 1.00 51.00 52.00 56.00
2078 49.00 1.00 51.00 60.00 50.00
2079 48.00 1.00 51.00 44.00 39.00
2080 57.00 1.00 61.00 52.00 63.00
2081 55.00 1.00 61.00 55.00 50.00
2082 66.00 1.00 56.00 50.00 66.00
2083 64.00 1.00 71.00 65.00 58.00
2084 55.00 1.00 51.00 52.00 53.00
2085 42.00 1.00 36.00 47.00 42.00
2086 56.00 1.00 61.00 63.00 55.00
2087 53.00 1.00 66.00 50.00 53.00
2088 41.00 1.00 41.00 42.00 42.00
2089 42.00 1.00 41.00 36.00 50.00
2090 53.00 1.00 56.00 50.00 55.00
2091 42.00 1.00 51.00 41.00 34.00
2092 60.00 1.00 56.00 47.00 50.00
2093 52.00 1.00 56.00 55.00 42.00
2094 38.00 1.00 46.00 42.00 36.00
2095 57.00 1.00 52.00 57.00 55.00
2096 58.00 1.00 61.00 55.00 58.00
2097 65.00 1.00 61.00 63.00 53.00
2101 /variables = math female socst read
2102 /statistics = coeff r anova ci (95)
2103 /dependent = science
2107 AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
2108 Table: Model Summary (science)
2109 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2110 ,.699,.489,.479,7.148
2112 Table: ANOVA (science)
2113 ,,Sum of Squares,df,Mean Square,F,Sig.
2114 ,Regression,9543.721,4,2385.930,46.695,.000
2115 ,Residual,9963.779,195,51.096,,
2116 ,Total,19507.500,199,,,
2118 Table: Coefficients (science)
2119 ,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
2120 ,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
2121 ,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
2122 ,math,.389,.074,.368,5.252,.000,.243,.535
2123 ,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
2124 ,socst,.050,.062,.054,.801,.424,-.073,.173
2125 ,read,.335,.073,.347,4.607,.000,.192,.479