Last data update: 2014.03.03

 R: Agreement, disagreement, and dependability statistics
A, D, E statisticsR Documentation

Agreement, disagreement, and dependability statistics

Description

Kane and Brennan's person-fit statistics.

Usage

A.KB(matrix,
     NA.method = "Pairwise", Save.MatImp = FALSE, 
     IP = NULL, IRT.PModel = "2PL", Ability = NULL, Ability.PModel = "ML", 
     mu = 0, sigma = 1)

D.KB(matrix,
     NA.method = "Pairwise", Save.MatImp = FALSE, 
     IP = NULL, IRT.PModel = "2PL", Ability = NULL, Ability.PModel = "ML", 
     mu = 0, sigma = 1)

E.KB(matrix,
     NA.method = "Pairwise", Save.MatImp = FALSE, 
     IP = NULL, IRT.PModel = "2PL", Ability = NULL, Ability.PModel = "ML", 
     mu = 0, sigma = 1)

Arguments

matrix

Data matrix of dichotomous item scores: Persons as rows, items as columns, item scores are either 0 or 1, missing values allowed.

NA.method

Method to deal with missing values. The default is pairwise elimination ("Pairwise"). Alternatively, simple imputation methods are also available. The options available are "Hotdeck", "NPModel" (default), and "PModel".

Save.MatImp

Logical. Save (imputted) data matrix to file? Default is FALSE.

IP

Matrix with previously estimated item parameters: One row per item, and three columns ([,1] item discrimination; [,2] item difficulty; [,3] lower-asymptote, also referred to as pseudo-guessing parameter).

In case no item parameters are available then IP=NULL.

IRT.PModel

Specify the IRT model to use in order to estimate the item parameters (only if IP=NULL). The options available are "1PL", "2PL" (default), and "3PL".

Ability

Vector with previoulsy estimated latent ability parameters, one per respondent, following the order of the row index of matrix.

In case no ability parameters are available then Ability=NULL.

Ability.PModel

Specify the method to use in order to estimate the latent ability parameters (only if Ability=NULL). The options available are "ML" (default), "BM", and "WL".

mu

Mean of the apriori distribution. Only used when method="BM". Default is 0.

sigma

Standard deviation of the apriori distribution. Only used when method="BM". Default is 1.

Details

Kane and Brennan (1980) discussed the agreement, disagreement, and dependability statistics. Assume that the items are ordered in increasing difficulty order (i.e., according to decreasing proportion-correct score). The agreement statistic for respondent n is

A.KB = sum(Xi*pi),

where Xi is the 0-1 score of respondent n on item i and pi is the proportion-correct score of item i.

The disagreement statistic is

D.KB = A.KB(max) - A.KB,

where A.KB(max) is the maximum value of A.KB given respondent n's total score.

The dependability statistic is

E.KB = A.KB / A.KB(max).

Small values of A.Kb and E.KB (i.e., in the left tail of the sampling distribution) are (potentially) indicative of aberrant response behavior. Large values of D.Kb (i.e., in the right tail of the sampling distribution) are (potentially) indicative of aberrant response behavior. These statistics are not computed for rows of matrix that consist of only 0s or only 1s (NA values are returned instead).

Missing values in matrix are dealt with by means of pairwise elimination by default. Alternatively, single imputation is also available. Three single imputation methods exist: Hotdeck imputation (NA.method = "Hotdeck"), nonparametric model imputation (NA.method = "NPModel"), and parametric model imputation (NA.method = "PModel"); see Zhang and Walker (2008).

  • Hotdeck imputation replaces missing responses of an examinee ('recipient') by item scores from the examinee which is closest to the recipient ('donor'), based on the recipient's nonmissing item scores. The similarity between nonmissing item scores of recipients and donors is based on the sum of absolute differences between the corresponding item scores. The donor's response pattern is deemed to be the most similar to the recipient's response pattern in the group, so item scores of the former are used to replace the corresponding missing values of the latter. When multiple donors are equidistant to a recipient, one donor is randomly drawn from the set of all donors.

  • The nonparametric model imputation method is similar to the hotdeck imputation, but item scores are generated from Bernoulli distributions with probabilities defined by donors with similar total score than the recipient (based on all items except the NAs).

  • The parametric model imputation method is similar to the hotdeck imputation, but item scores are generated from Bernoulli distributions with probabilities estimated by means of parametric IRT models (IRT.PModel = "1PL", "2PL", or "3PL"). Item parameters (IP) and ability parameters (Ability) may be provided for this purpose (otherwise the algorithm finds estimates for these parameters).

Value

An object of class "PerFit", which is a list with 12 elements:

PFscores

A list of length N (number of respondents) with the values of the person-fit statistic.

PFstatistic

The person-fit statistic used.

PerfVects

A message indicating whether perfect response vectors (all-0s or all-1s) were removed from the analysis.

ID.all0s

Row indices of all-0s response vectors removed from the analysis (if applicable).

ID.all1s

Row indices of all-1s response vectors removed from the analysis (if applicable).

matrix

The data matrix after imputation of missing values was performed (if applicable).

Ncat

The number of response categories (2 in this case).

IRT.PModel

The parametric IRT model used in case NA.method="PModel", otherwise NULL.

IP

The Ix3 matrix of estimated item parameters in case NA.method="PModel", otherwise NULL.

Ability.PModel

The method used to estimate abilities in case NA.method="PModel", otherwise NULL.

Ability

The vector of N estimated ability parameters in case NA.method="PModel", otherwise NULL.

NAs.method

The imputation method used (if applicable).

Author(s)

Jorge N. Tendeiro j.n.tendeiro@rug.nl

References

Kane, M. T., and Brennan, R. L. (1980) Agreement coefficients as indices of dependability for domain-referenced tests. Applied Psychological Measurement, 4(1), 105–126.

Karabatsos, G. (2003) Comparing the Aberrant Response Detection Performance of Thirty-Six Person-Fit Statistics. Applied Measurement In Education, 16(4), 277–298.

Meijer, R. R., and Sijtsma, K. (2001) Methodology review: Evaluating person fit. Applied Psychological Measurement, 25(2), 107–135.

Zhang, B., and Walker, C. M. (2008) Impact of missing data on person-model fit and person trait estimation. Applied Psychological Measurement, 32(6), 466–479.

Examples

# Load the inadequacy scale data (dichotomous item scores):
data(InadequacyData)

# Compute the A.KB, D.KB, and E.KB scores:
A.out <- A.KB(InadequacyData); A.out
D.out <- D.KB(InadequacyData); D.out
E.out <- E.KB(InadequacyData); E.out

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(PerFit)
Loading required package: ltm
Loading required package: MASS
Loading required package: msm
Loading required package: polycor
Loading required package: mvtnorm
Loading required package: sfsmisc
Loading required package: mirt
Loading required package: stats4
Loading required package: lattice

Attaching package: 'mirt'

The following object is masked from 'package:ltm':

    Science

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/PerFit/ADE.KB.Rd_%03d_medium.png", width=480, height=480)
> ### Name: A, D, E statistics
> ### Title: Agreement, disagreement, and dependability statistics
> ### Aliases: A.KB D.KB E.KB
> ### Keywords: univar
> 
> ### ** Examples
> 
> # Load the inadequacy scale data (dichotomous item scores):
> data(InadequacyData)
> 
> # Compute the A.KB, D.KB, and E.KB scores:
> A.out <- A.KB(InadequacyData); A.out

    PFscores
1     1.2432
2     2.7395
3     5.1563
4     2.7705
5     1.5459
6     3.9578
7     3.2221
8     3.6600
9     1.6898
10    1.6650
11    0.8921
12    2.9814
13    4.1787
14    3.4739
15    1.8573
16    4.6787
17    0.5025
18    1.9119
19    3.0645
20    2.5037
21    2.1030
22    4.3722
23    1.4963
24    2.5174
25    4.8449
26    2.3859
27    2.7506
28    3.9355
29    2.2878
30    2.7333
31    1.9665
32    0.6129
33    0.3400
34    1.4256
35    2.0409
36    1.3201
37    0.0993
38    0.7184
39    1.0571
40    1.6675
41    4.4342
42    4.6985
43    3.0670
44    4.3871
45    4.5918
46    2.4553
47    4.1675
48    3.3424
50    5.4367
51    2.9566
52    3.2395
53    2.5347
54    2.4491
55    2.4007
56    3.7035
57    0.6873
58    2.4591
59    0.7419
60    1.6985
62    1.2208
63    0.2097
64    3.9789
65    3.1489
66    1.1352
67    4.1898
68    0.9380
70    2.8797
71    1.7419
72    0.6898
73    4.1538
74    2.2680
75    2.0968
76    0.2543
77    1.0186
78    2.0323
79    1.0881
80    0.6613
81    5.2333
82    4.0186
83    2.9194
84    1.8462
85    1.2357
86    3.6067
87    1.1253
89    4.2370
91    0.8958
92    1.5620
94    0.5372
95    3.0149
96    2.5720
97    3.8759
98    4.1799
99    3.3548
100   1.6365
101   3.8077
102   0.8524
103   2.6625
104   1.5744
106   0.8524
107   2.7407
108   1.8933
109   1.0298
110   2.1166
111   4.2171
112   2.4901
113   3.0794
114   5.5521
115   2.4677
116   2.2556
117   1.9988
118   0.3400
119   2.8325
120   1.9404
121   2.1129
122   3.8672
123   4.4429
124   1.1476
125   2.8809
127   4.0186
128   5.4181
129   4.9491
130   2.5199
131   2.1166
132   1.8387
133   0.5025
134   3.7258
135   5.1328
136   1.2618
137   0.5980
138   2.1935
139   5.8511
140   0.5980
141   4.9206
142   2.9144
143   1.3313
144   1.1253
145   3.9566
146   4.7196
147   2.4057
148   0.9342
149   3.6241
150   1.3437
151   2.8983
152   2.1935
153   3.8573
154   1.6365
155   0.9702
156   4.2047
157   0.6911
158   1.2084
159   2.4578
161   0.5980
162   1.2618
163   1.7878
164   1.8834
165   1.9032
166   1.2581
167   0.1551
168   2.7953
170   3.8424
171   3.8710
172   3.6154
173   1.3722
174   1.6576
175   0.1811
177   4.9181
178   4.0409
179   0.7407
180   3.7022
181   0.5980
182   3.9206
183   2.7444
184   3.0323
185   3.4690
186   2.4169
187   1.7395
188   6.0931
189   1.2903
190   1.8685
191   5.1960
192   0.1551
193   0.5980
194   4.0769
195   0.5273
196   3.8772
197   0.9504
198   3.8288
199   2.6290
200   0.7878
202   0.9380
203   2.7196
204   2.3251
205   3.1303
206   3.1712
207   1.5261
208   3.3424
209   1.7779
210   1.5447
211   2.6985
212   3.3114
214   0.5980
215   3.6588
216   3.3970
217   4.6030
218   2.2469
219   0.6526
220   2.0980
221   5.7109
222   2.8089
223   4.3325
224   2.5757
225   2.6228
226   0.8573
227   4.2953
228   2.7692
229   0.1427
231   2.4950
232   1.3226
233   2.0906
234   1.5471
235   3.1762
236   0.9045
237   3.1737
238   1.6799
239   2.2953
240   1.0931
241   2.1923
242   1.1998
243   4.5223
244   1.9342
245   0.8772
246   0.5980
247   3.3387
248   1.7345
249   2.0149
250   0.5273
251   1.1352
252   2.8400
253   6.0149
254   0.4789
255   0.4603
256   1.4938
257   0.3883
258   4.4479
259   0.9380
260   1.2382
261   0.6538
262   1.7246
263   1.4280
264   2.3747
265   3.3189
266   0.9702
267   0.3524
268   1.4901
270   1.6811
271   2.0422
272   1.4243
273   2.0757
274   3.8015
275   2.4380
276   3.7432
277   0.9094
278   1.2357
279   0.5980
281   3.7891
282   1.3400
283   1.4541
284   1.3065
285   1.1253
286   2.8300
287   1.9181
288   0.5372
289   1.7506
290   2.2035
291   1.3896
292   0.6129
293   1.7978
294   5.5347
295   0.6278
296   2.0360
297   5.2208
298   3.1849
299   1.5447
300   0.4392
301   0.6898
302   1.4752
303   0.3524
304   0.9156
305   0.5980
306   3.3933
307   1.2643
308   0.7730
309   2.0335
310   4.0571
311   0.5372
312   0.4330
315   4.3958
316   1.9206
317   2.1501
318   1.7047
319   0.5496
321   1.2531
322   0.1551
323   0.8710
324   1.4007
325   1.7258
326   1.9094
327   1.2854
328   2.0906
329   2.9132
330   3.1551
331   2.1303
332   1.3784
333   0.6923
334   1.5931
335   0.3400
336   0.7233
337   2.2643
338   1.2109
339   4.8883
340   0.9653
341   2.4938
342   1.7022
343   1.1191
345   0.6526
346   1.4727
347   0.7916
348   0.3400
349   2.3536
350   2.6117
351   1.7506
352   2.8623
353   2.1923
354   1.0893
355   0.5980
356   3.5223
357   0.5980
358   0.7792
359   0.7792
360   0.5596
362   1.0099
364   1.2878
365   0.4330
366   3.4206
367   1.2109
368   0.7060
369   0.7916
370   1.0310
371   0.4330
373   1.3238
375   0.5372
376   3.8834
377   0.6191
378   1.8685
379   2.7643
380   1.0968
381   2.2109
382   1.3300
383   2.5298
384   2.6538
385   2.8896
386   3.7705
387   1.0918
388   2.2022
389   2.7878
390   2.5285
391   2.8164
392   1.3598
393   4.2568
394   1.4082
395   1.3834
396   1.0968
397   5.1030
398   5.8052
399   1.5434
400   3.6452
401   1.4330
402   1.5732
403   3.9628
404   2.7705
405   0.5980
406   3.4119
407   2.6873
408   1.1774
409   0.6526
410   3.1241
411   2.7047
412   1.1563
413   0.3400
414   0.7506
415   0.6898
416   0.5372
417   2.8697
418   2.4169
419   4.0794
420   3.4305
421   2.1811
422   1.8697
423   0.5372
424   1.6141
425   0.1551
426   1.1501
427   2.1117
428   1.3784
429   0.9107
431   3.1042
432   0.9380
433   4.3697
434   3.3598
435   1.3486
436   0.9702
437   0.5372
438   0.9442
439   4.1278
440   1.1452
441   4.9194
442   1.1352
443   1.6737
444   1.3015
445   2.6849
446   3.7928
447   2.1154
448   3.3536
449   5.7742
450   0.3524
453   5.1278
454   0.7730
456   3.4491
457   0.9963
458   1.7928
459   2.0732
460   1.5608
462   4.1228
463   2.2940
464   1.1030
465   1.1439
466   2.4355
467   1.9206
468   0.9702
469   3.2965
471   2.5521
472   5.4318
473   1.2643
475   1.3176
476   3.2097
477   2.3784
478   2.0074
479   1.2357
480   0.7878
481   5.0918
482   0.7916
483   2.5496
484   1.2246
485   2.4293
486   1.3313
487   1.2878
489   3.7581
490   1.2407
491   1.1352
492   0.2072
493   1.5682
495   1.7097
496   2.9057
497   3.7357
498   0.8772
499   1.9516
500   2.1613
502   0.8077
503   1.4677
504   3.4888
505   2.2543
506   1.0620
507   1.5682
508   1.9429
509   1.1352
510   1.4529
511   3.9864
513   2.7370
514   1.9913
515   3.8400
516   1.2779
517   2.2258
518   4.2891
519   0.5372
520   3.1935
522   1.5037
524   1.3102
526   0.4330
527   2.4404
528   1.3102
529   1.1886
530   1.4045
531   0.6923
533   0.6191
534   2.1104
535   1.3213
536   2.8114
537   0.5980
538   1.3635
539   0.3524
540   0.2581
541   2.8548
542   2.2407
543   1.2705
544   4.1638
545   1.1886
546   1.2903
547   0.5372
548   0.7047
549   1.6303
550   0.9529
551   2.3040
553   0.3400
554   0.5980
555   1.5658
556   1.0794
557   0.3548
558   1.4342
559   3.4826
560   1.4330
563   2.0323
564   3.2978
565   5.4690
566   0.5980
567   1.1811
568   1.7990
569   1.6141
570   0.5372
571   1.1253
572   2.0447
573   0.0993
574   0.2978
575   0.3176
576   2.9578
577   3.6663
578   2.4628
579   1.1352
580   3.6675
581   0.5980
582   1.0310
583   2.1998
585   1.5273
586   0.5372
587   1.2878
588   0.8710
589   0.5372
590   0.9727
591   1.9603
592   0.1551
593   1.1774
594   1.8114
595   1.3400
596   3.3945
598   0.2543
599   0.2978
601   2.7519
602   0.5372
603   2.5720
604   0.3623
605   1.2978
606   1.4777
607   0.2047
608   1.3834
609   2.1042
611   2.5447
612   1.1799
613   0.9504
614   0.2097
615   0.3524
616   0.8524
617   2.1042
618   0.5980
619   1.0782
620   2.9876
621   4.0298
622   0.5372
623   1.9057
624   0.6092
625   0.7854
626   0.3524
627   0.6948
628   0.3362
629   0.4330
630   1.4355
631   0.5261
632   2.6042
633   1.4082
634   0.5980
635   0.2543
637   2.7395
638   0.1650
639   1.9181
640   1.3065
641   1.1352
642   1.2221
644   2.2258
645   2.2543
646   0.2730
647   1.5906
648   2.9045
649   2.1390
651   2.3350
652   2.5223
653   2.7370
654   0.7060
655   0.8896
656   1.7543
657   2.8747
658   3.0806
659   1.8387
660   1.8164
661   4.3672
662   2.9380
663   1.7481
664   2.6923
665   0.5980
666   1.0074
667   1.1328
668   0.3362
669   1.2072
670   2.7519
671   0.7432
672   3.2084
673   2.1055
675   3.1725
676   1.4504
677   0.8213
678   2.1253
679   0.2047
680   2.0323
681   0.6365
682   0.5980
683   0.2543
684   5.2494
685   4.8040
686   2.0782
687   1.4007
688   2.5670
689   1.5223
690   2.9169
691   3.1526
692   2.0174
693   2.0273
694   1.7816
695   2.5149
696   2.6836
697   3.4280
698   3.6600
699   4.5608
700   1.6588
701   0.5372
702   1.1526
703   0.5980
704   2.8412
705   4.7395
706   2.0186
707   1.5931
708   1.8275
709   1.7047
710   1.7233
711   2.1203
712   4.1625
713   2.3821
714   2.5099
715   0.9156
716   1.9615
717   2.6427
718   1.1352
719   1.4529
720   0.9404
721   1.1749
722   1.6141
723   3.0521
724   4.3958
725   1.2122
726   0.7481
727   1.4169
728   1.1514
729   1.8164
730   2.2618
731   1.2134
732   2.7196
733   3.3610
734   0.7630
735   0.9702
736   2.0037
737   1.7605
738   0.8710
739   0.8524
740   2.3573
741   2.8809
742   2.1402
743   0.5980
744   2.6675
745   3.2965
746   2.2134
747   5.0906
748   2.6055
749   0.7072
750   3.6638
751   0.8077
753   0.4330
755   1.5633
756   0.7506
757   1.1625
758   2.5546
759   1.9553
760   4.0695
761   2.1588
762   1.7258
763   1.9801
764   2.1762
766   1.7618
767   1.8660
768   2.4380
769   0.7854
770   2.7022
771   3.2754
772   3.1117
773   1.6055
774   2.3127
775   0.4988
776   1.5881
777   1.9739
778   1.0993
779   1.6625
780   0.5980
781   0.9504
782   0.6873
784   2.8027
785   3.0955
786   2.5496
787   1.8635
789   1.2295
790   1.5633
791   0.7792
792   2.0397
793   2.0236
794   2.1402
795   1.0310
796   0.5372
797   5.9417
798   2.0248
799   1.5074
800   4.6563
801   2.7940
802   0.2543
803   0.9380
804   2.1650
805   3.1476
806   2.8288
808   3.5732
809   0.6563
810   2.0831
811   5.1725
812   2.1514
813   2.5794
814   0.7060
815   1.0459
816   4.6228
817   2.1166
818   2.9901
819   1.3424
820   1.4231
821   4.0906
822   3.3809
823   2.3002
824   1.5211
825   1.3300
826   1.1315
827   2.3933
828   2.5223
829   0.8164
830   4.8747
831   1.9417
832   1.3201
833   1.0310
834   1.2295
835   2.9752
836   0.9504
837   2.2630
838   1.2878
839   1.5645
840   1.1886
841   0.2097
842   2.8660
843   2.1526
844   2.4479
845   2.0732
846   1.8970
847   0.3524
849   3.1563
850   1.7630
851   3.4665
852   3.4342
853   1.5980
854   1.7605
855   3.1365
856   5.0099
857   2.8598
858   2.1117
859   1.0310
862   1.7655
863   0.9504
865   2.7072
866   2.9541

> D.out <- D.KB(InadequacyData); D.out

    PFscores
1     0.6799
2     0.4913
3     0.6253
4     1.2481
5     0.7295
6     1.1365
7     1.0509
8     0.3586
9     0.5856
10    0.9504
11    0.2432
12    0.7804
13    1.1017
14    1.0087
15    0.4181
16    0.9479
17    0.6328
18    0.3635
19    0.9541
20    1.0000
21    0.5124
22    0.5223
23    0.7792
24    0.0980
25    0.4355
26    1.1179
27    0.7531
28    0.5471
29    0.6452
30    1.7494
31    0.9665
32    0.5223
33    0.2581
34    0.4975
35    0.2345
36    1.2953
37    0.4988
38    0.4169
39    0.5112
40    0.6079
41    0.8462
42    0.7630
43    0.6948
44    0.7072
45    0.6886
46    1.8176
47    1.1129
48    0.9305
50    0.8772
51    1.0620
52    0.7792
53    0.3983
54    0.7816
55    0.5323
56    0.5695
57    0.4479
58    1.0447
59    0.3933
60    0.5769
62    1.0546
63    0.3883
64    0.9156
65    1.1241
66    0.0000
67    0.9045
68    0.1973
70    1.1390
71    0.8734
72    0.4454
73    0.9404
74    0.3474
75    0.8362
76    0.3437
77    0.9045
78    0.2432
79    0.8350
80    0.9069
81    0.6985
82    0.6712
83    0.8424
84    0.7692
85    0.3325
86    0.4119
87    0.4429
89    0.8573
91    0.2395
92    0.7134
94    0.0608
95    0.4888
96    0.6588
97    0.8139
98    1.1005
99    0.6638
100   0.9789
101   0.4653
102   0.2829
103   0.5682
104   1.0409
106   0.2829
107   0.4901
108   0.7221
109   0.5385
110   0.8164
111   1.0633
112   0.7407
113   1.1935
114   0.3797
115   0.7630
116   0.6774
117   0.9342
118   0.2581
119   0.9293
120   0.6749
121   0.1625
122   0.8226
123   1.0186
124   0.7754
125   1.3921
127   0.8759
128   0.5136
129   0.3313
130   0.4132
131   0.8164
132   0.4367
133   0.6328
134   0.9640
135   0.6489
136   0.6613
137   0.0000
138   1.0372
139   0.2233
140   0.0000
141   0.7060
142   0.8474
143   0.5918
144   0.4429
145   1.5050
146   0.9069
147   1.0980
148   0.6340
149   0.3945
150   0.9318
151   0.3325
152   0.4218
153   1.0372
154   1.2965
155   0.1650
156   0.6898
157   0.8772
158   0.7146
159   1.0459
161   0.5372
162   1.0136
163   0.4876
164   0.3921
165   1.3275
166   1.0174
167   0.4429
168   0.9665
170   0.4305
171   0.8189
172   0.4032
173   0.5509
174   0.6179
175   0.4169
177   0.3623
178   1.0533
179   0.3945
180   0.5707
181   0.0000
182   0.9739
183   0.4864
184   0.7295
185   0.5496
186   1.0868
187   0.5360
188   0.3201
189   0.2779
190   1.3623
191   0.4305
192   0.4429
193   0.0000
194   0.8176
195   0.6079
196   0.6055
197   0.6179
198   0.6538
199   0.6017
200   0.3474
202   0.1973
203   1.2990
204   1.1787
205   1.3524
206   0.8474
207   0.7494
208   1.1402
209   0.1452
210   0.7308
211   0.5323
212   0.7072
214   0.0000
215   1.4355
216   1.0856
217   0.0868
218   1.5149
219   0.9156
220   1.1328
221   0.3635
222   1.2097
223   0.9479
224   0.9280
225   0.8809
226   0.7109
227   0.5993
228   0.4615
229   0.4553
231   1.0087
232   0.9529
233   0.5248
234   1.0682
235   0.3275
236   1.0186
237   1.0993
238   0.9355
239   0.9355
240   0.4752
241   0.7407
242   0.7233
243   0.3722
244   0.3412
245   0.2581
246   0.0000
247   0.4231
248   1.1985
249   1.4888
250   0.6079
251   0.0000
252   0.6638
253   0.2990
254   0.6563
255   0.6749
256   0.4293
257   0.7469
258   0.6464
259   0.1973
260   0.6849
261   0.9144
262   1.2084
263   0.4950
264   0.5583
265   0.1849
266   0.1650
267   0.2457
268   0.0782
270   0.5943
271   0.5732
272   0.8511
273   0.1998
274   0.8883
275   0.1774
276   0.7395
277   0.6588
278   0.3325
279   0.0000
281   0.4839
282   0.2283
283   0.8213
284   0.6166
285   0.4429
286   0.6737
287   0.3573
288   0.0608
289   0.1725
290   1.0273
291   0.1787
292   0.5223
293   0.4777
294   0.5397
295   0.5074
296   0.5794
297   0.5608
298   1.2978
299   1.3883
300   0.6960
301   0.4454
302   1.4578
303   0.2457
304   0.2196
305   0.0000
306   0.8797
307   0.6588
308   0.3623
309   1.1973
310   0.8375
311   0.0608
312   0.1650
315   0.4988
316   0.0025
317   0.7829
318   1.2283
319   0.5856
321   0.6700
322   0.4429
323   0.2643
324   0.8747
325   0.1973
326   0.3660
327   0.2829
328   0.5248
329   0.3176
330   1.1179
331   0.8027
332   0.5447
333   0.8759
334   0.6824
335   0.2581
336   0.4119
337   0.6687
338   0.3573
339   0.5732
340   0.6030
341   0.4392
342   0.9132
343   0.4491
345   0.9156
346   1.1427
347   0.3437
348   0.2581
349   0.8772
350   0.3213
351   0.5248
352   0.6414
353   0.4231
354   0.4789
355   0.0000
356   0.4963
357   0.0000
358   0.3561
359   0.3561
360   0.5757
362   0.5583
364   0.2804
365   0.1650
366   0.3412
367   0.3573
368   0.4293
369   0.3437
370   0.1042
371   0.1650
373   0.5993
375   0.0608
376   0.3896
377   0.5161
378   0.7469
379   0.7395
380   0.4715
381   0.4045
382   0.5931
383   0.9739
384   0.8499
385   0.6141
386   1.1241
387   1.1836
388   0.7308
389   0.7159
390   1.2333
391   1.4566
392   0.5633
393   1.2047
394   0.1600
395   0.1849
396   0.4715
397   0.5236
398   0.5087
399   0.3797
400   0.3734
401   0.4901
402   0.3499
403   0.3102
404   0.7333
405   0.0000
406   0.6067
407   0.2457
408   0.3908
409   0.4826
410   0.8945
411   1.0571
412   0.4119
413   0.2581
414   0.3846
415   0.4454
416   0.0608
417   1.1489
418   0.8139
419   0.4032
420   0.3313
421   1.5806
422   0.7457
423   0.0608
424   0.6613
425   0.4429
426   0.4181
427   0.5037
428   0.5447
429   0.6576
431   1.1687
432   0.1973
433   0.9107
434   0.4020
435   0.2196
436   0.1650
437   0.0608
438   0.6241
439   0.3548
440   0.7779
441   1.0124
442   0.0000
443   0.6017
444   0.6216
445   0.8189
446   0.4801
447   0.1600
448   1.3362
449   0.4206
450   0.2457
453   0.4988
454   0.3623
456   0.8238
457   0.5720
458   0.1303
459   0.2022
460   0.3623
462   0.7717
463   0.9367
464   0.4653
465   0.4243
466   0.7953
467   0.0025
468   0.1650
469   0.7221
471   1.2097
472   0.3499
473   1.0112
475   0.6055
476   1.2730
477   0.5546
478   0.2680
479   0.3325
480   0.3474
481   0.8400
482   0.3437
483   0.6811
484   0.6985
485   0.5037
486   0.5918
487   0.2804
489   0.5149
490   0.6824
491   0.0000
492   0.3908
493   0.0000
495   0.5658
496   0.8561
497   0.5372
498   0.2581
499   0.3238
500   0.7717
502   0.3275
503   0.4553
504   0.9938
505   0.3610
506   0.8610
507   0.0000
508   0.3325
509   0.4330
510   1.1625
511   0.7035
513   0.1960
514   0.2841
515   0.8499
516   0.2903
517   1.2779
518   0.4007
519   0.0608
520   0.8251
522   0.4194
524   0.2581
526   0.1650
527   0.4926
528   0.2581
529   0.3797
530   0.5186
531   0.4429
533   0.5161
534   0.5050
535   0.2469
536   0.4194
537   0.0000
538   0.5596
539   0.2457
540   0.3400
541   0.3759
542   0.6923
543   0.6526
544   0.5261
545   0.3797
546   0.2779
547   0.0608
548   0.8635
549   0.2928
550   0.1824
551   0.6290
553   0.2581
554   0.0000
555   1.0496
556   1.1960
557   0.2432
558   0.4888
559   0.7903
560   0.1352
563   0.5831
564   0.7208
565   0.6055
566   0.0000
567   0.3871
568   0.4764
569   0.6613
570   0.0608
571   0.4429
572   0.5707
573   0.4988
574   0.3002
575   0.2804
576   0.8040
577   0.3524
578   0.7680
579   0.0000
580   0.3511
581   0.0000
582   0.1042
583   0.7333
585   0.3958
586   0.0608
587   0.2804
588   0.2643
589   0.0608
590   0.9504
591   0.3151
592   0.4429
593   0.3908
594   0.4640
595   0.5831
596   0.8784
598   0.3437
599   0.3002
601   0.7519
602   0.0608
603   0.6588
604   0.7730
605   0.6253
606   0.7978
607   0.3933
608   0.1849
609   0.8288
611   0.9591
612   1.0955
613   0.1849
614   0.3883
615   0.2457
616   0.2829
617   0.1712
618   0.0000
619   0.4901
620   0.7742
621   0.6600
622   0.0608
623   1.0273
624   0.5261
625   0.3499
626   0.2457
627   0.4404
628   0.7990
629   0.1650
630   0.4876
631   0.6092
632   0.6266
633   0.1600
634   0.0000
635   0.3437
637   0.4913
638   0.4330
639   0.6973
640   0.6166
641   0.0000
642   0.7010
644   0.0496
645   1.2494
646   0.3251
647   0.6849
648   0.3263
649   0.4764
651   0.2804
652   0.4107
653   0.4938
654   0.4293
655   0.2457
656   0.1687
657   0.3561
658   0.4231
659   0.7767
660   1.1166
661   0.7270
662   0.8238
663   0.1749
664   0.2407
665   0.0000
666   0.5608
667   0.7903
668   0.7990
669   1.0682
670   0.4789
671   0.8251
672   0.5533
673   0.5099
675   0.5893
676   0.4727
677   0.7469
678   0.1501
679   0.3933
680   0.5831
681   0.4988
682   0.0000
683   0.3437
684   0.8251
685   0.6576
686   0.1973
687   0.8747
688   0.3660
689   0.4007
690   0.5868
691   0.6092
692   0.2581
693   0.2481
694   0.4938
695   0.1005
696   0.8201
697   0.3337
698   0.6129
699   0.3337
700   0.2643
701   0.0608
702   0.4156
703   0.0000
704   0.6625
705   0.1551
706   0.5968
707   0.3300
708   1.1055
709   0.9107
710   0.1998
711   0.1551
712   0.9318
713   0.2333
714   0.4231
715   0.2196
716   0.6538
717   0.5881
718   0.0000
719   0.1154
720   0.6278
721   0.3933
722   1.0012
723   0.4516
724   0.6985
725   0.3561
726   0.3871
727   0.5062
728   0.4169
729   1.1166
730   0.3536
731   0.3548
732   0.5112
733   0.4007
734   0.8052
735   0.1650
736   0.6117
737   0.1625
738   0.2643
739   0.2829
740   0.5757
741   0.3499
742   0.1352
743   0.0000
744   0.5633
745   0.4653
746   0.4020
747   0.5360
748   0.3275
749   0.4280
750   0.6092
751   0.3275
753   0.1650
755   0.7122
756   0.3846
757   0.4057
758   0.3784
759   0.3201
760   0.4132
761   0.1166
762   0.1973
763   0.6352
764   0.4392
766   0.8536
767   0.4094
768   1.3238
769   0.3499
770   0.2308
771   0.4864
772   0.9069
773   0.6700
774   0.9181
775   0.6365
776   0.6873
777   0.3015
778   0.4690
779   0.2605
780   0.0000
781   0.1849
782   0.4479
784   0.1303
785   0.4082
786   0.3834
787   0.4119
789   0.3387
790   0.7122
791   0.3561
792   0.5757
793   0.2519
794   0.1352
795   0.1042
796   0.0608
797   0.3722
798   0.5906
799   0.4156
800   0.4380
801   0.9677
802   0.3437
803   0.1973
804   0.7680
805   1.5422
806   0.4020
808   0.4454
809   0.4789
810   0.5323
811   0.6092
812   0.4640
813   0.9243
814   0.4293
815   0.5223
816   0.4715
817   0.4988
818   0.2407
819   0.2258
820   0.5000
821   0.3921
822   0.1228
823   0.6328
824   0.4020
825   0.5931
826   0.4367
827   0.2221
828   0.7084
829   0.7519
830   0.9069
831   0.6737
832   0.6030
833   0.1042
834   1.0459
835   0.7866
836   0.1849
837   0.6700
838   0.6352
839   0.7109
840   0.3797
841   0.3883
842   0.0670
843   0.7804
844   0.1675
845   0.5422
846   0.3784
847   0.2457
849   0.3474
850   0.1600
851   0.5521
852   0.3275
853   0.3251
854   0.1625
855   0.3672
856   0.2705
857   0.6439
858   0.8213
859   0.1042
862   0.5099
863   0.1849
865   0.5236
866   0.8077

> E.out <- E.KB(InadequacyData); E.out

    PFscores
1     0.6465
2     0.8479
3     0.8918
4     0.6894
5     0.6794
6     0.7769
7     0.7541
8     0.9108
9     0.7426
10    0.6366
11    0.7858
12    0.7925
13    0.7914
14    0.7750
15    0.8162
16    0.8315
17    0.4426
18    0.8402
19    0.7626
20    0.7146
21    0.8041
22    0.8933
23    0.6576
24    0.9625
25    0.9175
26    0.6809
27    0.7851
28    0.8779
29    0.7800
30    0.6097
31    0.6705
32    0.5399
33    0.5685
34    0.7413
35    0.8969
36    0.5047
37    0.1660
38    0.6328
39    0.6741
40    0.7328
41    0.8398
42    0.8603
43    0.8153
44    0.8612
45    0.8696
46    0.5746
47    0.7892
48    0.7822
50    0.8611
51    0.7357
52    0.8061
53    0.8642
54    0.7581
55    0.8185
56    0.8667
57    0.6055
58    0.7018
59    0.6536
60    0.7465
62    0.5365
63    0.3506
64    0.8129
65    0.7369
66    1.0000
67    0.8225
68    0.8262
70    0.7166
71    0.6660
72    0.6077
73    0.8154
74    0.8672
75    0.7149
76    0.4253
77    0.5297
78    0.8931
79    0.5658
80    0.4217
81    0.8822
82    0.8569
83    0.7761
84    0.7059
85    0.7880
86    0.8975
87    0.7176
89    0.8317
91    0.7891
92    0.6865
94    0.8983
95    0.8605
96    0.7961
97    0.8265
98    0.7916
99    0.8348
100   0.6257
101   0.8911
102   0.7508
103   0.8241
104   0.6020
106   0.7508
107   0.8483
108   0.7239
109   0.6566
110   0.7217
111   0.7986
112   0.7707
113   0.7207
114   0.9360
115   0.7638
116   0.7690
117   0.6815
118   0.5685
119   0.7530
120   0.7419
121   0.9286
122   0.8246
123   0.8135
124   0.5968
125   0.6742
127   0.8210
128   0.9134
129   0.9373
130   0.8591
131   0.7217
132   0.8081
133   0.4426
134   0.7944
135   0.8878
136   0.6561
137   1.0000
138   0.6790
139   0.9632
140   1.0000
141   0.8745
142   0.7747
143   0.6923
144   0.7176
145   0.7244
146   0.8388
147   0.6866
148   0.5957
149   0.9018
150   0.5905
151   0.8971
152   0.8387
153   0.7881
154   0.5580
155   0.8546
156   0.8591
157   0.4407
158   0.6284
159   0.7015
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162   0.5545
163   0.7857
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165   0.5891
166   0.5529
167   0.2593
168   0.7431
170   0.8992
171   0.8254
172   0.8997
173   0.7135
174   0.7285
175   0.3029
177   0.9314
178   0.7932
179   0.6525
180   0.8664
181   1.0000
182   0.8010
183   0.8495
184   0.8061
185   0.8632
186   0.6898
187   0.7644
188   0.9501
189   0.8228
190   0.5783
191   0.9235
192   0.2593
193   1.0000
194   0.8330
195   0.4645
196   0.8649
197   0.6060
198   0.8541
199   0.8137
200   0.6940
202   0.8262
203   0.6768
204   0.6636
205   0.6983
206   0.7891
207   0.6707
208   0.7456
209   0.9245
210   0.6788
211   0.8353
212   0.8240
214   1.0000
215   0.7182
216   0.7578
217   0.9815
218   0.5973
219   0.4161
220   0.6494
221   0.9402
222   0.6990
223   0.8205
224   0.7351
225   0.7486
226   0.5467
227   0.8776
228   0.8571
229   0.2386
231   0.7121
232   0.5812
233   0.7993
234   0.5916
235   0.9065
236   0.4703
237   0.7427
238   0.6423
239   0.7104
240   0.6970
241   0.7475
242   0.6239
243   0.9240
244   0.8501
245   0.7727
246   1.0000
247   0.8875
248   0.5914
249   0.5751
250   0.4645
251   1.0000
252   0.8106
253   0.9526
254   0.4219
255   0.4055
256   0.7768
257   0.3421
258   0.8731
259   0.8262
260   0.6439
261   0.4169
262   0.5880
263   0.7426
264   0.8096
265   0.9472
266   0.8546
267   0.5892
268   0.9502
270   0.7388
271   0.7808
272   0.6260
273   0.9122
274   0.8106
275   0.9322
276   0.8350
277   0.5799
278   0.7880
279   1.0000
281   0.8868
282   0.8544
283   0.6390
284   0.6794
285   0.7176
286   0.8077
287   0.8430
288   0.8983
289   0.9103
290   0.6820
291   0.8861
292   0.5399
293   0.7901
294   0.9112
295   0.5530
296   0.7785
297   0.9030
298   0.7105
299   0.5266
300   0.3869
301   0.6077
302   0.5030
303   0.5892
304   0.8066
305   1.0000
306   0.7941
307   0.6574
308   0.6809
309   0.6294
310   0.8289
311   0.8983
312   0.7241
315   0.8981
316   0.9987
317   0.7331
318   0.5812
319   0.4842
321   0.6516
322   0.2593
323   0.7672
324   0.6156
325   0.8974
326   0.8391
327   0.8196
328   0.7993
329   0.9017
330   0.7384
331   0.7263
332   0.7168
333   0.4415
334   0.7001
335   0.5685
336   0.6372
337   0.7720
338   0.7722
339   0.8950
340   0.6155
341   0.8503
342   0.6509
343   0.7136
345   0.4161
346   0.5631
347   0.6973
348   0.5685
349   0.7285
350   0.8904
351   0.7694
352   0.8169
353   0.8382
354   0.6946
355   1.0000
356   0.8765
357   1.0000
358   0.6863
359   0.6863
360   0.4929
362   0.6440
364   0.8212
365   0.7241
366   0.9093
367   0.7722
368   0.6219
369   0.6973
370   0.9082
371   0.7241
373   0.6884
375   0.8983
376   0.9088
377   0.5454
378   0.7144
379   0.7890
380   0.6994
381   0.8454
382   0.6916
383   0.7220
384   0.7574
385   0.8247
386   0.7703
387   0.4798
388   0.7508
389   0.7957
390   0.6722
391   0.6591
392   0.7071
393   0.7794
394   0.8979
395   0.8821
396   0.6994
397   0.9069
398   0.9194
399   0.8026
400   0.9071
401   0.7452
402   0.8181
403   0.9274
404   0.7907
405   1.0000
406   0.8490
407   0.9162
408   0.7508
409   0.5749
410   0.7774
411   0.7190
412   0.7373
413   0.5685
414   0.6612
415   0.6077
416   0.8983
417   0.7141
418   0.7481
419   0.9100
420   0.9119
421   0.5798
422   0.7149
423   0.8983
424   0.7094
425   0.2593
426   0.7334
427   0.8074
428   0.7168
429   0.5807
431   0.7265
432   0.8262
433   0.8275
434   0.8931
435   0.8600
436   0.8546
437   0.8983
438   0.6021
439   0.9208
440   0.5955
441   0.8293
442   1.0000
443   0.7356
444   0.6768
445   0.7663
446   0.8876
447   0.9297
448   0.7151
449   0.9321
450   0.5892
453   0.9114
454   0.6809
456   0.8072
457   0.6353
458   0.9323
459   0.9111
460   0.8116
462   0.8423
463   0.7101
464   0.7033
465   0.7294
466   0.7538
467   0.9987
468   0.8546
469   0.8203
471   0.6784
472   0.9395
473   0.5556
475   0.6852
476   0.7160
477   0.8109
478   0.8822
479   0.7880
480   0.6940
481   0.8584
482   0.6973
483   0.7892
484   0.6368
485   0.8283
486   0.6923
487   0.8212
489   0.8795
490   0.6452
491   1.0000
492   0.3465
493   1.0000
495   0.7514
496   0.7724
497   0.8743
498   0.7727
499   0.8577
500   0.7369
502   0.7115
503   0.7632
504   0.7783
505   0.8620
506   0.5523
507   1.0000
508   0.8539
509   0.7239
510   0.5555
511   0.8500
513   0.9332
514   0.8751
515   0.8188
516   0.8149
517   0.6353
518   0.9146
519   0.8983
520   0.7947
522   0.7819
524   0.8354
526   0.7241
527   0.8321
528   0.8354
529   0.7579
530   0.7303
531   0.6098
533   0.5454
534   0.8069
535   0.8426
536   0.8702
537   1.0000
538   0.7090
539   0.5892
540   0.4315
541   0.8836
542   0.7640
543   0.6606
544   0.8878
545   0.7579
546   0.8228
547   0.8983
548   0.4494
549   0.8477
550   0.8393
551   0.7855
553   0.5685
554   1.0000
555   0.5987
556   0.4744
557   0.5934
558   0.7458
559   0.8150
560   0.9138
563   0.7770
564   0.8206
565   0.9003
566   1.0000
567   0.7532
568   0.7906
569   0.7094
570   0.8983
571   0.7176
572   0.7818
573   0.1660
574   0.4979
575   0.5311
576   0.7863
577   0.9123
578   0.7623
579   1.0000
580   0.9126
581   1.0000
582   0.9082
583   0.7500
585   0.7942
586   0.8983
587   0.8212
588   0.7672
589   0.8983
590   0.5058
591   0.8615
592   0.2593
593   0.7508
594   0.7961
595   0.6968
596   0.7944
598   0.4253
599   0.4979
601   0.7854
602   0.8983
603   0.7961
604   0.3191
605   0.6748
606   0.6494
607   0.3423
608   0.8821
609   0.7174
611   0.7263
612   0.5185
613   0.8372
614   0.3506
615   0.5892
616   0.7508
617   0.9248
618   1.


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO