-
Notifications
You must be signed in to change notification settings - Fork 14
/
biblio_complete.html
2889 lines (2879 loc) · 106 KB
/
biblio_complete.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
---
output: md_document
author: "Imke Mayer"
date: 2018-10-24
url: "/bibliography/biblio_complete/"
parent: "Bibliography"
name: "Bibliography (complete)"
---
<p><br>
<a href="/bibliography/"><b>A commented version of this bibliography can be found here.</b></a></p>
<div class="container">
<div class="row">
<table class="table">
<thead>
<tr class="filters">
<th>
Publication type
<select id="pub-type-filter" class="form-control">
<option>All</option>
<option>Book</option>
<option>Article</option>
<option>Paper</option>
<option>Misc</option>
</select>
</th>
<th>
Year
<select id="year-filter" class="form-control">
</select>
</th>
<th>
Author
<input id="author-filter" class="form-control" type="text" placeholder="Search by author name..">
</th>
</tr>
</thead>
</table>
<div class="card bg-light filterable">
<table id="references-list-tbl" class="table table-hover">
<thead>
<tr>
<th>
Citation
</th>
<th>
Year
</th>
<th>
Publication type
</th>
</tr>
</thead>
<tbody>
<tr class="task-list-row" data-year="2008" data-pubtype="Article">
<td>
<cite>Abayomi, K., A. Gelman, and M. Levy. <font color="#428bca">Diagnostics for multivariate imputations</font>. In: <em>Journal of the Royal Statistical Society, Series C (Applied Statistics)</em> 57.3 (2008), pp. 273-291.</cite>
<div>
<a href="https://doi.org/10.1111/j.1467-9876.2007.00613.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2008
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2000" data-pubtype="Article">
<td>
<cite>Albert, P. S. and D. A. Follmann. <font color="#428bca">Modeling repeated count data subject to informative dropout</font>. In: <em>Biometrics</em> 56.3 (2000), pp. 667-677.</cite>
<div>
<a href="https://doi.org/10.1111/j.0006-341X.2000.00667.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2000
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2001" data-pubtype="Book">
<td>
<cite>Allison, P. D. <em><font color="#428bca">Missing Data</font></em>. Quantitative Applications in the Social Sciences. Thousand Oaks, CA, USA: Sage Publications, 2001. ISBN: 9780761916727.</cite>
<div>
<a href="https://doi.org/10.1136/bmj.38977.682025.2C" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2001
</td>
<td>
Book
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Article">
<td>
<cite>Andridge, R. and R. J. A. Little. <font color="#428bca">A review of hot deck imputation for survey non-response</font>. In: <em>International Statistical Review</em> 78.1 (2010), pp. 40-64.</cite>
<div>
<a href="https://doi.org/10.1111/j.1751-5823.2010.00103.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2010
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2016" data-pubtype="Article">
<td>
<cite>Audigier, V., F. Husson, and J. Josse. <font color="#428bca">A principal component method to impute missing values for mixed data</font>. In: <em>Advances in Data Analysis and Classification</em> 10.1 (2016), pp. 5-26.</cite>
<div>
<a href="https://doi.org/10.1007/s11634-014-0195-1" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2016
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2015" data-pubtype="Article">
<td>
<cite>Audigier, V., F. Husson, and J. Josse. <font color="#428bca">Multiple imputation for continuous variables using a Bayesian principal component analysis</font>. In: <em>Journal of Statistical Computation and Simulation</em> 86.11 (2015), pp. 2140-2156.</cite>
<div>
<a href="https://doi.org/10.1080/00949655.2015.1104683" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2015
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2016" data-pubtype="Article">
<td>
<cite>Audigier, V., F. Husson, and J. Josse. <font color="#428bca">MIMCA: multiple imputation for categorical variables with multiple correspondence analysis</font>. In: <em>Statistics and Computing</em> 27.2 (2016), pp. 1-18. eprint: 1505.08116.</cite>
<div>
<a href="https://doi.org/10.1007/s11222-016-9635-4" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2016
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2005" data-pubtype="Article">
<td>
<cite>Bang, H. and J. M. Robins. <font color="#428bca">Doubly robust estimation in missing data and causal inference models</font>. In: <em>Biometrics</em> 61.4 (2005), pp. 962-973.</cite>
<div>
<a href="https://doi.org/10.1111/j.1541-0420.2005.00377.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2005
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Article">
<td>
<cite>Baraldi, A. N. and C. K. Enders. <font color="#428bca">An introduction to modern missing data analysis</font>. In: <em>Journal of School Psychology</em> 48.1 (2010), pp. 5-37.</cite>
<div>
<a href="https://doi.org/10.1016/j.jsp.2009.10.001" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2010
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2016" data-pubtype="Article">
<td>
<cite>Baretta, L. and A. Santaniello. <font color="#428bca">Nearest neighbor imputation algorithms: a critical evaluation</font>. In: <em>BMC Medical Informatics and Decision Making</em>. Proceedings of the 5th Translational Bioinformatics Conference (TBC 2015): medical informatics and decision making 16.Supp. 3 (2016), p. 74.</cite>
<div>
<a href="https://doi.org/10.1186/s12911-016-0318-z" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2016
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2015" data-pubtype="Article">
<td>
<cite>Bartlett, J. W., O. Harel, and J. R. Carpenter. <font color="#428bca">Asymptotically unbiased estimation of exposure odds ratios in complete records logistic regression</font>. In: <em>American journal of epidemiology</em> 182.8 (2015), pp. 730–736.</cite>
<div>
<a href="https://doi.org/10.1093/aje/kwv114" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2015
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Article">
<td>
<cite>Beaulac, C. and J. S. Rosenthal. <font color="#428bca">BEST: A decision tree algorithm that handles missing values</font>. In: <em>arXiv preprint</em> (2018). eprint: 1804.10168.</cite>
<div>
<a href="https://arxiv.org/pdf/1804.10168.pdf" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2018
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1995" data-pubtype="Paper">
<td>
<cite>Bengio, Y. and F. Gingras. <font color="#428bca">Recurrent neural networks for missing or asynchronous data</font>. In: <em>Proceedings of the 8th International Conference on Neural Information Processing Systems</em>. (Nov. 27, 1995-Dec. 02, 1995). Ed. by -. Cambridge, MA, USA: MIT Press, 1995, pp. 395-401.</cite>
<div>
<a href="http://papers.nips.cc/paper/1126-recurrent-neural-networks-for-missing-or-asynchronous-data.pdf" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
1995
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2017" data-pubtype="Article">
<td>
<cite>Bertsimas, D., C. Pawlowski, and Y. D. Zhuo. <font color="#428bca">From predictive methods to missing data imputation: an optimization approach</font>. In: <em>The Journal of Machine Learning Research</em> 18.1 (2017), pp. 7133–7171.</cite>
</td>
<td>
2017
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2008" data-pubtype="Article">
<td>
<cite>Beunckens, C., G. Molenberghs, G. Verbeke, et al. <font color="#428bca">A latent-class mixture model for incomplete longitudinal Gaussian data</font>. In: <em>Biometrics</em> 64.1 (2008), pp. 96–105.</cite>
<div>
<a href="https://doi.org/https://doi.org/10.1111/j.1541-0420.2007.00837.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2008
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Bianchi, F. M., L. Livi, K. Ø. Mikalsen, et al. <font color="#428bca">Learning representations of multivariate time series with missing data</font>. In: <em>Pattern Recognition</em> 96 (2019), p. 106973.</cite>
<div>
<a href="https://doi.org/10.1016/j.patcog.2019.106973" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Paper">
<td>
<cite>Biessmann, F., D. Salinas, S. Schelter, et al. <font color="#428bca">“Deep” Learning for Missing Value Imputation in Tables with Non-Numerical Data</font>. In: <em>Proceedings of the 27th ACM International Conference on Information and Knowledge Management</em>. Ed. by -. CIKM ’18. Torino, Italy: ACM, 2018, pp. 2017–2025. ISBN: 978-1-4503-6014-2.</cite>
<div>
<a href="https://doi.org/10.1145/3269206.3272005" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a><a href="http://doi.acm.org/10.1145/3269206.3272005" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2018
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Blake, H. A., C. Leyrat, K. Mansfield, et al. <font color="#428bca">Propensity scores using missingness pattern information: a practical guide</font>. In: <em>arXiv preprint</em> (2019). arXiv: 1901.03981 [stat.ME].</cite>
<div>
<a href="https://researchonline.lshtm.ac.uk/4651159/1/1901.03981v1.pdf" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Brinis, S., C. Traina, and A. J. Traina. <font color="#428bca">Hollow-tree: a metric access method for data with missing values</font>. In: <em>Journal of Intelligent Information Systems</em> (2019), pp. 1–28.</cite>
<div>
<a href="https://doi.org/10.1007/s10844-019-00567-8" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1960" data-pubtype="Article">
<td>
<cite>Buck, S. F. <font color="#428bca">A method of estimation of missing values in multivariate data suitable for use with an electronic computer</font>. In: <em>Journal of the Royal Statistical Society, Series B</em> 22 (1960), pp. 302-306.</cite>
<div>
<a href="https://doi.org/10.1177/004912417700600206" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1960
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1990" data-pubtype="Paper">
<td>
<cite>Burns, R. M. <font color="#428bca">Multiple and replicate item imputation in a complex sample survey</font>. In: <em>Proceedings of the 6th Annual Research Conference</em>. Ed. by B. of the Census. Washington DC, USA, 1990, pp. 655-665.</cite>
</td>
<td>
1990
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Article">
<td>
<cite>Candès, E. J., C. A. Sing-Long, and J. D. Trzasko. <font color="#428bca">Unbiased risk estimates for singular value thresholding and spectral estimators</font>. In: <em>IEEE Transactions on Signal Processing</em> 61.19 (2013), pp. 4643-4657.</cite>
<div>
<a href="https://doi.org/10.1109/TSP.2013.2270464" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2013
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2006" data-pubtype="Article">
<td>
<cite>Carpenter, J. R., M. G. Kenward, and S. Vansteelandt. <font color="#428bca">A comparison of multiple imputation and doubly robust estimation for analyses with missing data</font>. In: <em>Journal of the Royal Statistical Society: Series A (Statistics in Society)</em> 169.3 (2006), pp. 571–584.</cite>
<div>
<a href="https://doi.org/10.1111/j.1467-985X.2006.00407.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2006
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Book">
<td>
<cite>Carpenter, J. and M. Kenward. <em><font color="#428bca">Multiple Imputation and its Application</font></em>. Chichester, West Sussex, UK: Wiley, 2013. ISBN: 9780470740521.</cite>
<div>
<a href="https://doi.org/10.1002/9781119942283" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2013
</td>
<td>
Book
</td>
<tr class="task-list-row" data-year="2016" data-pubtype="Paper">
<td>
<cite>Chen, T. and C. Guestrin. <font color="#428bca">XGBoost: A Scalable Tree Boosting System</font>. In: <em>Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining</em>. (Aug. 13, 2016-Aug. 17, 2016). Ed. by -. New York, NY, USA: ACM, 2016, pp. 785-794. ISBN: 0450342322.</cite>
<div>
<a href="https://doi.org/10.1145/2939672.2939785" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2016
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Chen, Y. and M. Sadinle. <font color="#428bca">Nonparametric Pattern-Mixture Models for Inference with Missing Data</font>. In: <em>arXiv preprint</em> (2019). arXiv: 1904.11085 [stat.ME].</cite>
<div>
<a href="https://arxiv.org/pdf/1904.11085.pdf" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2000" data-pubtype="Article">
<td>
<cite>Chen, J. and J. Shao. <font color="#428bca">Nearest neighbor imputation for survey data</font>. In: <em>Journal of Official Statistics</em> 16.2 (2000), pp. 113-131.</cite>
<div>
<a href="http://www.jos.nu/Articles/abstract.asp?article=162113" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2000
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2007" data-pubtype="Article">
<td>
<cite>Collins, L. M., J. L. Schafer, and K. Chi-Ming. <font color="#428bca">A comparison of inclusive and restrictive strategies in modern missing data procedures</font>. In: <em>Psychological Methods</em> 6.4 (2007), pp. 330-351.</cite>
<div>
<a href="https://doi.org/10.1037/1082-989X.6.4.330" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2007
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2012" data-pubtype="Article">
<td>
<cite>Cranmer, S. J. and J. Gill. <font color="#428bca">We have to be discrete about this: a non-parametric imputation technique for missing categorical data</font>. In: <em>British Journal of Political Science</em> 43 (2012), pp. 425-449.</cite>
<div>
<a href="https://doi.org/10.1017/S0007123412000312" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2012
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2008" data-pubtype="Article">
<td>
<cite>Crookston, N. L. and A. O. Finley. <font color="#428bca">yaImpute: an R package for kNN imputation</font>. In: <em>Journal of Statistical Software</em> 23 (2008), p. 10.</cite>
<div>
<a href="https://doi.org/10.18637/jss.v023.i10" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2008
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2014" data-pubtype="Article">
<td>
<cite>Dax, A. <font color="#428bca">Imputing Missing Entries of a Data Matrix: A review</font>. In: <em>Journal of Advanced Computing</em> 3.3 (2014), pp. 98-222.</cite>
<div>
<a href="https://doi.org/10.7726/jac.2014.1007" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2014
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1977" data-pubtype="Article">
<td>
<cite>Dempster, A. P., N. M. Laird, and D. B. Rubin. <font color="#428bca">Maximum likelihood from incomplete data via the EM algorithm</font>. In: <em>Journal of the Royal Statistical Society, Series B (Methodological)</em> 39.1 (1977), pp. 1-38.</cite>
<div>
<a href="http://www.jstor.org/stable/2984875" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
1977
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1994" data-pubtype="Article">
<td>
<cite>Diggle, P. and M. G. Kenward. <font color="#428bca">Informative drop-out in longitudinal data analysis</font>. In: <em>Journal of the Royal Statistical Society, Series C (Applied Statistics)</em> 43.1 (1994), pp. 49-93.</cite>
<div>
<a href="https://doi.org/10.2307/2986113" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1994
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Article">
<td>
<cite>Ding, P. and F. Li. <font color="#428bca">Causal Inference: A Missing Data Perspective</font>. In: <em>Statistical Science</em> 33.2 (2018), pp. 214–237.</cite>
<div>
<a href="https://doi.org/10.1214/18-STS645" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2018
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Article">
<td>
<cite>Ding, Y. and J. S. Simonoff. <font color="#428bca">An investigation of missing data methods for classification trees applied to binary response data</font>. In: <em>Journal of Machine Learning Research</em> 11.1 (2010), pp. 131-170.</cite>
<div>
<a href="http://www.jmlr.org/papers/v11/ding10a.html" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2010
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Article">
<td>
<cite>Dong, Y. and C. J. Peng. <font color="#428bca">Principled missing data methods for researchers</font>. In: <em>SpringerPlus</em> 2 (2013), p. 222.</cite>
<div>
<a href="https://doi.org/10.1186/2193-1801-2-222" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2013
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Book">
<td>
<cite>Enders, C. K. <em><font color="#428bca">Applied Missing Data Analysis</font></em>. Guilford Press, 2010, p. 401. ISBN: 9781606236390.</cite>
</td>
<td>
2010
</td>
<td>
Book
</td>
<tr class="task-list-row" data-year="2001" data-pubtype="Article">
<td>
<cite>Enders, C. K. <font color="#428bca">A primer on maximum likelihood algorithms available for use with missing data</font>. In: <em>Structural Equation Modeling</em> 8.1 (2001), pp. 128-141.</cite>
<div>
<a href="https://doi.org/10.1207/S15328007SEM0801_7" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2001
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Erler, N. S., D. Rizopoulos, and E. M. Lesaffre. <font color="#428bca">JointAI: joint analysis and imputation of incomplete data in R</font>. In: <em>arXiv preprint</em> (2019).</cite>
<div>
<a href="https://arxiv.org/abs/1907.10867" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Article">
<td>
<cite>Fang, F., J. Zhao, and J. Shao. <font color="#428bca">Imputation-based adjusted score equations in generalized linear models with nonignorable missing covariate values</font>. In: <em>Statistica Sinica</em> 28.4 (2018), pp. 1677–1701.</cite>
<div>
<a href="https://doi.org/10.5705/ss.202015.0437" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2018
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1996" data-pubtype="Article">
<td>
<cite>Fay, R. E. <font color="#428bca">Alternative paradigms for the analysis of imputed survey data</font>. In: <em>Journal of the American Statistical Association</em> 91.434 (1996), pp. 490-498.</cite>
<div>
<a href="https://doi.org/10.1080/01621459.1996.10476909" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1996
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1976" data-pubtype="Article">
<td>
<cite>Fellegi, I. P. and D. Holt. <font color="#428bca">A systematic approach to automatic edit and imputation</font>. In: <em>Journal of the American Statistical Association</em> 71.353 (1976), pp. 17-35.</cite>
<div>
<a href="https://doi.org/10.2307/2285726" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1976
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2011" data-pubtype="Article">
<td>
<cite>Ferrari, P. A., P. Annoni, A. Barbiero, et al. <font color="#428bca">An imputation method for categorical variables with application to nonlinear principal component analysis</font>. In: <em>Computational Statistics & Data Analysis</em> 55.7 (2011), pp. 2410-2420.</cite>
<div>
<a href="https://doi.org/10.1016/j.csda.2011.02.007" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2011
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1979" data-pubtype="Article">
<td>
<cite>Finkbeiner, C. <font color="#428bca">Estimation for the multiple factor model when data are missing</font>. In: <em>Psychometrika</em> 44.4 (1979), pp. 409-420.</cite>
<div>
<a href="https://doi.org/10.1007/BF02296204" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1979
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1995" data-pubtype="Article">
<td>
<cite>Fitzmaurice, G. M., G. Molenberghs, and S. R. Lipsitz. <font color="#428bca">Regression Models for Longitudinal Binary Responses with Informative Drop-Outs</font>. In: <em>Journal of the Royal Statistical Society. Series B (Methodological)</em> 57.4 (1995), pp. 691–704.</cite>
<div>
<a href="http://www.jstor.org/stable/2345937" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
1995
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1995" data-pubtype="Article">
<td>
<cite>Follmann, D. and M. Wu. <font color="#428bca">An approximate generalized linear model with random effects for informative missing data</font>. In: <em>Biometrics</em> 51.1 (1995), pp. 151-168.</cite>
<div>
<a href="https://doi.org/10.2307/2533322" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1995
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Article">
<td>
<cite>Gad, A. M. and N. M. M. Darwish. <font color="#428bca">A shared parameter model for longitudinal data with missing values</font>. In: <em>American Journal of Applied Mathematics and Statistics</em> 1.2 (2013), pp. 30-35.</cite>
<div>
<a href="http://pubs.sciepub.com/ajams/1/2/3" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2013
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1998" data-pubtype="Article">
<td>
<cite>Gelman, A., G. King, and C. Liu. <font color="#428bca">Not asked and not answered: Multiple imputation for multiple surveys</font>. In: <em>Journal of the American Statistical Association</em> 93.443 (1998), pp. 846–857.</cite>
<div>
<a href="https://doi.org/10.1080/01621459.1998.10473737" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1998
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2005" data-pubtype="Article">
<td>
<cite>Gelman, A., I. van Mechelen, G. Verbeke, et al. <font color="#428bca">Multiple Imputation for Model Checking: Completed-Data Plots with Missing and Latent Data</font>. In: <em>Biometrics</em> 61.1 (2005), pp. 74–85.</cite>
<div>
<a href="https://doi.org/10.1111/j.0006-341X.2005.031010.x" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2005
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1997" data-pubtype="Paper">
<td>
<cite>Gill, R. D., M. J. Van Der Laan, and J. M. Robins. <font color="#428bca">Coarsening at random: Characterizations, conjectures, counter-examples</font>. In: <em>Proceedings of the First Seattle Symposium in Biostatistics</em>. Springer. 1997, pp. 255–294.</cite>
<div>
<a href="https://doi.org/10.1007/978-1-4684-6316-3_14" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1997
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2019" data-pubtype="Article">
<td>
<cite>Golden, R. M., S. S. Henley, H. White, et al. <font color="#428bca">Consequences of model misspecification for maximum likelihood estimation with missing data</font>. In: <em>Econometrics</em> 7.3 (2019), p. 37.</cite>
<div>
<a href="https://doi.org/10.3390/econometrics7030037" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2019
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Paper">
<td>
<cite>Gondara, L. and K. Wang. <font color="#428bca">MIDA: Multiple Imputation using Denoising Autoencoders</font>. In: <em>Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018)</em>. (Jun. 03, 2018-Jun. 06, 2018). Ed. by D. Phung, V. Tseng, G. Webb, B. Ho, M. Ganji and L. Rashidi. Lecture Notes in Computer Science. Springer International Publishing, 2018, pp. 260-272. ISBN: 3319930404.</cite>
<div>
<a href="https://doi.org/10.1007/978-3-319-93040-4_21" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a><a href="https://arxiv.org/abs/1705.02737" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2018
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Paper">
<td>
<cite>Goodfellow, I., M. Mirza, A. Courville, et al. <font color="#428bca">Multi-Prediction Deep Boltzmann Machines</font>. In: <em>Proceedings of the 26th International Conference on Neural Information Processing Systems</em>. (Dec. 05, 2013-Dec. 10, 2013). Ed. by C. Burges, L. Bottou, M. Welling, Z. Ghahramani and K. Weinberger. Advances in Neural Information Processing Systems 26. Curran Associates, Inc., 2013, pp. 548–556.</cite>
<div>
<a href="http://papers.nips.cc/paper/5024-multi-prediction-deep-boltzmann-machines.pdf" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2013
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2009" data-pubtype="Article">
<td>
<cite>Graham, J. W. <font color="#428bca">Missing data analysis: making it work in the real world</font>. In: <em>Annual Review of Psychology</em> 60 (2009), pp. 549-576.</cite>
<div>
<a href="https://doi.org/10.1146/annurev.psych.58.110405.085530" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2009
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2007" data-pubtype="Article">
<td>
<cite>Graham, J. W., A. E. Olchowski, and T. E. Gilreath. <font color="#428bca">How many imputations are really needed? Some practical clarifications of multiple imputation theory</font>. In: <em>Prevention Science</em> 8.3 (2007), pp. 206-213.</cite>
<div>
<a href="https://doi.org/10.1007/s11121-007-0070-9" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2007
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1997" data-pubtype="Book">
<td>
<cite>Graham, J. W., S. M. Hofer, S. I. Donaldson, et al. <font color="#428bca">The Science of Prevention: Methodological Advances from Alcohol and Substance Abuse Research</font>. In: <em><font color="#428bca">The Science of Prevention: Methodological Advances from Alcohol and Substance Abuse Research</font></em>. Ed. by K. Bryant, M. Windle and S. West. Washington, DC, USA: American Psychological Association, 1997. Chap. Analysis with missing data in prevention research, pp. 325-366. ISBN: 1-55798-439-5.</cite>
<div>
<a href="https://doi.org/10.1037/10222-010" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1997
</td>
<td>
Book
</td>
<tr class="task-list-row" data-year="1976" data-pubtype="Article">
<td>
<cite>Heckman, J. J. <font color="#428bca">The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models</font>. In: <em>Annals of Economic and Social Measurement</em> 5.4 (1976), pp. 475-492.</cite>
<div>
<a href="http://ideas.repec.org/h/nbr/nberch/10491.html" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
1976
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1979" data-pubtype="Article">
<td>
<cite>Heckman, J. <font color="#428bca">Sample selection bias as a specification error</font>. In: <em>Econometrica</em> 47.1 (1979), pp. 153-161.</cite>
<div>
<a href="https://doi.org/10.2307/1912352" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
1979
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1997" data-pubtype="Article">
<td>
<cite>Hogan, J. W. and N. M. Laird. <font color="#428bca">Mixture models for the joint distribution of repeated measures and event times</font>. In: <em>Statistics in Medecine</em> 16.1-3 (1997), pp. 239-257.</cite>
</td>
<td>
1997
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2004" data-pubtype="Article">
<td>
<cite>Hogan, J. W. and T. Lancaster. <font color="#428bca">Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studies</font>. In: <em>Statistical Methods in Medical Research</em> 13.1 (2004), pp. 17-48.</cite>
<div>
<a href="https://doi.org/10.1191/0962280204sm351ra" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2004
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2011" data-pubtype="Article">
<td>
<cite>Honaker, J., G. King, and M. Blackwell. <font color="#428bca">Amelia II: a program for missing data</font>. In: <em>Journal of Statistical Software</em> 45.7 (2011). eprint: arXiv:1501.0228.</cite>
<div>
<a href="https://doi.org/10.18637/jss.v045.i07" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2011
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2017" data-pubtype="Article">
<td>
<cite>Horton, N. J. and K. P. Kleinman. <font color="#428bca">Much Ado About Nothing - A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models</font>. In: <em>The American Statistician</em> 61.1 (2017), pp. 79-90.</cite>
<div>
<a href="https://doi.org/10.1198/000313007X172556" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2017
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2012" data-pubtype="Article">
<td>
<cite>Hothorn, T., K. Hornik, and A. Zeileis. <font color="#428bca">Unbiased Recursive Partitioning: A Conditional Inference Framework</font>. In: <em>Journal of Computational and Graphical Statistics</em> 15.3 (2012), pp. 651-674.</cite>
<div>
<a href="https://doi.org/10.1198/106186006X133933" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2012
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2000" data-pubtype="Article">
<td>
<cite>Huisman, M. <font color="#428bca">Imputation of missing item responses: some simple techniques</font>. In: <em>Quality & Quantity</em> 34.4 (2000), pp. 331-351.</cite>
<div>
<a href="https://doi.org/10.1023/A:1004782230065" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2000
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2013" data-pubtype="Article">
<td>
<cite>Husson, F. and J. Josse. <font color="#428bca">Handling missing values in multiple factor analysis</font>. In: <em>Food Quality and Preference</em> 30 (2013), pp. 77-85.</cite>
<div>
<a href="https://doi.org/10.1016/j.foodqual.2013.04.013" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2013
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2001" data-pubtype="Article">
<td>
<cite>Ibrahim, J. G., M. Chen, and S. R. Lipsitz. <font color="#428bca">Missing responses in generalised linear mixed models when the missing data mechanism is nonignorable</font>. In: <em>Biometrika</em> 88.2 (2001), pp. 551-564.</cite>
<div>
<a href="https://doi.org/10.1093/biomet/88.2.551" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2001
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="1999" data-pubtype="Article">
<td>
<cite>Ibrahim, J. G., S. R. Lipsitz, and M. Chen. <font color="#428bca">Missing Covariates in Generalized Linear Models When the Missing Data Mechanism is Non-Ignorable</font>. In: <em>Journal of the Royal Statistical Society</em>. Series B (Statistical Methodology) 61.1 (1999), pp. 173-190.</cite>
<div>
<a href="https://doi.org/10.1111/1467-9868.00170" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a><a href="http://www.jstor.org/stable/2680744" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
1999
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Article">
<td>
<cite>Ilin, A. and T. Raiko. <font color="#428bca">Practical approaches to Principal Component Analysis in the presence of missing values</font>. In: <em>Journal of Machine Learning Research</em> 11 (2010), pp. 1957-2000.</cite>
<div>
<a href="http://jmlr.csail.mit.edu/papers/v11/ilin10a.html" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2010
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Article">
<td>
<cite>Imbert, A., A. Valsesia, C. Le Gall, et al. <font color="#428bca">Multiple hot-deck imputation for network inference from RNA sequencing data</font>. In: <em>Bioinformatics</em> 34.10 (2018), pp. 1726-1732.</cite>
<div>
<a href="https://doi.org/10.1093/bioinformatics/btx819" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2018
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2020" data-pubtype="Paper">
<td>
<cite>Ipsen, N. B., P. Mattei, and J. Frellsen. <font color="#428bca">not-MIWAE: Deep generative modelling with missing not at random data</font>. In: <em>arXiv preprint</em> (2020).</cite>
<tr class="task-list-row" data-year="2020" data-pubtype="Paper">
<td>
<cite>Ipsen, N., P. Mattei, and J. Frellsen. <font color="#428bca">How to deal with missing data in supervised deep learning?</font> In: <em>ICML Workshop on the Art of Learning with Missing Values (Artemiss)</em>. 2020.</cite>
<div>
<a href="https://hal.inria.fr/hal-03044144/" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2020
</td>
<td>
Paper
</td>
<tr class="task-list-row" data-year="2020" data-pubtype="Article">
<td>
<cite>Ipsen, N. B., P. Mattei, and J. Frellsen. <font color="#428bca">not-MIWAE: Deep generative modelling with missing not at random data</font>. In: <em>arXiv preprint</em> (2020).</cite>
<div>
<a href="https://arxiv.org/abs/2006.12871" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >URL</a>
</div>
</td>
<td>
2020
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2014" data-pubtype="Article">
<td>
<cite>Jamshidian, M., S. Jalal, and C. Jansen. <font color="#428bca">MissMech: an R package for testing homoscedasticity, multivariate normality, and missing completely at random (MCAR)</font>. In: <em>Journal of Statistical Software</em> 56.6 (2014), pp. 1-31.</cite>
<div>
<a href="https://doi.org/10.18637/jss.v056.i06" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2014
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2010" data-pubtype="Article">
<td>
<cite>Jamshidian, M. and S. Jalal. <font color="#428bca">Tests of homoscedasticity, normality, and missing completely at random for incomplete multivariate data</font>. In: <em>Psychometrika</em> 75.4 (2010), pp. 649-674. eprint: NIHMS150003.</cite>
<div>
<a href="https://doi.org/10.1007/s11336-010-9175-3" target="_blank" role="button" class="btn btn-outline-secondary btn-sm" >DOI</a>
</div>
</td>
<td>
2010
</td>
<td>
Article
</td>
<tr class="task-list-row" data-year="2018" data-pubtype="Article">
<td>
<cite>Jiang, W., J. Josse, and M. Lavielle. <font color="#428bca">Logistic Regression with Missing Covariates–Parameter Estimation, Model Selection and Prediction</font>. In: <em>arXiv preprint</em> (2018). arXiv: 1805.04602 [stat.ME].</cite>
</td>