# Multiple Logistic Regression
## Claimants Insurance Dataset
### Implementation
getwd()
## [1] "D:/New Volume/DataScience Yogesh/R _Codes/Logistic Regression"
setwd("D:\\New Volume\\DataScience Yogesh\\R _Codes\\Logistic Regression")
claimants <- read.csv("D:\\New Volume\\DataScience Yogesh\\R _Codes\\Logistic Regression\\Claimants.csv")
#View(claimants)
attach(claimants)
summary(claimants)
## CASENUM ATTORNEY CLMSEX CLMINSUR
## Min. : 0 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.: 4177 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:1.0000
## Median : 8756 Median :0.0000 Median :1.0000 Median :1.0000
## Mean :11202 Mean :0.4888 Mean :0.5587 Mean :0.9076
## 3rd Qu.:15702 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :34153 Max. :1.0000 Max. :1.0000 Max. :1.0000
## NA's :12 NA's :41
## SEATBELT CLMAGE LOSS
## Min. :0.00000 Min. : 0.00 Min. : 0.000
## 1st Qu.:0.00000 1st Qu.: 9.00 1st Qu.: 0.400
## Median :0.00000 Median :30.00 Median : 1.069
## Mean :0.01703 Mean :28.41 Mean : 3.806
## 3rd Qu.:0.00000 3rd Qu.:43.00 3rd Qu.: 3.781
## Max. :1.00000 Max. :95.00 Max. :173.604
## NA's :48 NA's :189
# Logistic Regression
a <- na.omit(claimants)
summary(a)
## CASENUM ATTORNEY CLMSEX CLMINSUR
## Min. : 0 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.: 4503 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:1.0000
## Median : 8730 Median :0.0000 Median :1.0000 Median :1.0000
## Mean :11244 Mean :0.4726 Mean :0.5648 Mean :0.9042
## 3rd Qu.:16013 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :34153 Max. :1.0000 Max. :1.0000 Max. :1.0000
## SEATBELT CLMAGE LOSS
## Min. :0.00000 Min. : 0.00 Min. : 0.000
## 1st Qu.:0.00000 1st Qu.: 9.00 1st Qu.: 0.440
## Median :0.00000 Median :30.00 Median : 1.311
## Mean :0.01825 Mean :28.59 Mean : 3.857
## 3rd Qu.:0.00000 3rd Qu.:43.00 3rd Qu.: 3.910
## Max. :1.00000 Max. :95.00 Max. :173.604
colnames(claimants)
## [1] "CASENUM" "ATTORNEY" "CLMSEX" "CLMINSUR" "SEATBELT" "CLMAGE"
## [7] "LOSS"
str(claimants)
## 'data.frame': 1340 obs. of 7 variables:
## $ CASENUM : int 5 3 66 70 96 97 10 36 51 55 ...
## $ ATTORNEY: int 0 1 1 0 1 0 0 0 1 1 ...
## $ CLMSEX : int 0 1 0 0 0 1 0 1 1 0 ...
## $ CLMINSUR: int 1 0 1 1 1 1 1 1 1 1 ...
## $ SEATBELT: int 0 0 0 1 0 0 0 0 0 0 ...
## $ CLMAGE : int 50 18 5 31 30 35 9 34 60 NA ...
## $ LOSS : num 34.94 0.891 0.33 0.037 0.038 ...
str(ATTORNEY)
## int [1:1340] 0 1 1 0 1 0 0 0 1 1 ...
str(CLMSEX)
## int [1:1340] 0 1 0 0 0 1 0 1 1 0 ...
str(as.factor(CLMSEX))
## Factor w/ 2 levels "0","1": 1 2 1 1 1 2 1 2 2 1 ...
age <- log(a$CLMAGE)
m2 <- glm(ATTORNEY ~ factor(CLMSEX)+factor(CLMINSUR)+(SEATBELT) + sqrt(a$CLMAGE) + sqrt(LOSS), family = binomial,data = a)
#m2 <- glm(ATTORNEY ~ . , family=binomial,data = claimants)
coef(m2)
## (Intercept) factor(CLMSEX)1 factor(CLMINSUR)1 SEATBELT
## 0.31489803 0.43657274 0.56979673 -0.71399974
## sqrt(a$CLMAGE) sqrt(LOSS)
## 0.08551318 -1.22867052
summary(m2)
##
## Call:
## glm(formula = ATTORNEY ~ factor(CLMSEX) + factor(CLMINSUR) +
## (SEATBELT) + sqrt(a$CLMAGE) + sqrt(LOSS), family = binomial,
## data = a)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.9793 -0.9354 -0.1419 0.9253 2.2955
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.31490 0.28361 1.110 0.26686
## factor(CLMSEX)1 0.43657 0.13828 3.157 0.00159 **
## factor(CLMINSUR)1 0.56980 0.23520 2.423 0.01541 *
## SEATBELT -0.71400 0.57743 -1.237 0.21627
## sqrt(a$CLMAGE) 0.08551 0.03227 2.650 0.00804 **
## sqrt(LOSS) -1.22867 0.09687 -12.684 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1516.1 on 1095 degrees of freedom
## Residual deviance: 1256.1 on 1090 degrees of freedom
## AIC: 1268.1
##
## Number of Fisher Scoring iterations: 5
exp(coef(m2)) # odds ratio
## (Intercept) factor(CLMSEX)1 factor(CLMINSUR)1 SEATBELT
## 1.3701196 1.5473948 1.7679077 0.4896817
## sqrt(a$CLMAGE) sqrt(LOSS)
## 1.0892759 0.2926814
prob <- predict(m2,a)
(prob)
## 1 2 3 4 5
## -5.773315435 -0.045504000 0.370090563 0.410472754 1.113557752
## 6 7 8 9 11
## 1.144179765 -1.169842375 -0.894609250 0.834990640 -1.215472846
## 12 13 14 15 16
## -4.008697489 -0.480649426 0.854141089 1.376797916 0.725149115
## 17 18 19 20 22
## 1.697777388 0.466223907 1.032807932 -0.830546454 1.412293675
## 23 25 26 27 28
## -4.097310531 -2.380074668 0.379389941 1.076711989 0.102773629
## 29 31 33 34 35
## 0.643606456 -0.792177133 0.187133859 0.237952529 -0.850936896
## 36 37 38 39 40
## -0.637229301 -0.893732962 -0.437457954 0.612571113 -0.583286962
## 41 42 43 44 45
## 0.215111394 -2.251991809 -1.593452297 -2.491590321 0.242583149
## 47 48 50 51 52
## -0.963776987 0.970207941 -0.737770101 -0.693849586 0.299870789
## 55 56 58 59 60
## 0.396332954 -5.772477834 -2.157023258 1.430416168 -0.065546864
## 64 65 66 68 69
## 1.006491888 0.337091449 0.933873180 1.005549227 0.419955847
## 70 71 72 73 74
## 0.382750558 -6.631016426 0.009275634 0.356500602 0.655010134
## 75 76 77 79 80
## 0.065069294 -1.222724029 0.240400593 -0.256898815 -0.892700462
## 81 82 84 85 86
## 0.041518003 0.523333254 -0.571609292 0.303461429 0.344114351
## 87 88 89 90 92
## -1.008042804 1.351308243 -0.888138003 -0.925649226 -1.286873298
## 93 94 95 96 98
## 0.423713128 -0.773682596 0.001201266 1.657179640 -6.254019506
## 99 100 101 102 103
## -2.396893328 0.307909404 0.058862230 0.983319904 0.355327618
## 105 106 107 108 109
## 0.167981765 -1.156613974 -6.548633679 -1.427762632 0.849634450
## 111 112 113 115 118
## 0.336007934 1.025770314 -1.574477268 0.805731920 -0.460799922
## 119 121 122 123 124
## -0.257071886 0.913128443 -1.384537724 1.626507017 -0.185738961
## 125 126 128 129 131
## -0.791735526 -0.532877535 -2.046969979 0.451156088 1.192039656
## 132 135 136 138 139
## 1.635180474 -0.797409173 0.622687437 -1.061043350 1.090451768
## 140 141 142 144 145
## -0.085407416 0.553125616 -0.511408010 -2.550798382 -0.502859163
## 146 147 148 149 150
## 1.715477340 -0.067430482 -7.555542453 -7.615163563 0.773902379
## 151 153 154 155 156
## -1.770278667 1.194245877 0.704545377 0.324892925 -1.156826708
## 157 158 160 161 162
## -5.868967359 -6.185759390 0.650845196 -0.703181752 0.402707215
## 164 166 167 168 169
## -0.800459375 0.761827710 0.452976765 0.825773990 -1.344561557
## 170 171 172 173 174
## 1.431350999 0.284228483 -0.834256144 -1.059758327 0.111562915
## 175 176 177 178 179
## -0.426198083 -1.414837608 0.555532774 0.575839919 -1.000726773
## 180 181 182 183 186
## -2.649645157 -1.029599612 1.075908043 0.069686939 0.342318827
## 188 190 191 192 193
## 0.871797424 0.690505192 0.089499854 -1.685483668 1.530731158
## 194 195 196 197 198
## -0.527632193 0.847390635 0.069403395 -1.002968074 1.458073191
## 199 201 202 203 204
## 0.715982515 1.388330143 1.086648949 -0.474338102 -0.647929846
## 205 206 208 209 210
## 0.240400993 0.316242115 0.336729563 -3.044917097 -1.985499370
## 211 212 213 214 215
## 0.961811840 0.435166174 1.492293862 -0.517209907 1.144907723
## 216 217 218 219 220
## 0.877870466 -0.685503682 -1.294415309 1.075533400 0.536791082
## 221 222 224 225 226
## -0.384667691 1.222061810 -0.302126757 0.111221997 -0.317945630
## 227 228 229 230 231
## 0.045614575 0.128004947 -0.809179896 -0.644549638 1.007424964
## 232 233 234 236 237
## 0.165721395 -0.664941623 -0.704465363 0.110487846 0.346214193
## 238 239 240 241 242
## -0.031650819 0.454468260 1.401867107 0.385141340 -1.286269260
## 243 244 245 246 247
## -6.338548434 -0.749194872 1.135777535 -0.501294610 0.426997976
## 248 250 251 252 253
## 0.678712849 1.113368038 1.042413492 -1.232487200 0.762472961
## 254 256 258 259 260
## -1.675368127 -1.104271318 -0.936918795 -0.149872085 -1.749669994
## 261 262 263 264 265
## 0.639013682 0.931007545 -0.425774878 0.718512342 0.479908403
## 266 267 269 270 271
## 0.073283074 -0.587350759 1.593555916 -0.670433193 1.219139718
## 272 273 274 276 277
## -1.017094269 0.137132096 -0.550312734 0.427348359 -0.621439998
## 279 280 281 282 284
## 0.628179371 0.995081530 0.757088220 0.164263829 -1.387850942
## 286 287 288 289 290
## -1.806103769 -0.407282418 -8.479499846 0.060321422 -1.517132729
## 291 292 293 294 296
## 1.674517680 -0.571629949 -0.395525426 -0.650429390 -0.601459165
## 297 298 300 301 303
## 0.015893503 1.045865254 0.411562257 0.333861896 -0.803123827
## 304 305 306 307 308
## 1.174595563 0.535155785 0.219412828 -0.962611869 0.661503842
## 309 310 311 312 313
## 1.358484527 -2.307884414 0.371027667 0.210667290 -0.202811766
## 314 315 316 317 318
## -0.313950956 -0.122093550 1.241049919 0.797814637 1.284997053
## 320 321 322 323 324
## 0.106792459 1.071386110 0.281976716 0.559064287 -1.505866348
## 326 327 328 329 330
## 1.814365973 1.027926438 -0.657225360 -0.046096921 -1.230089049
## 331 332 334 335 337
## -0.239237130 0.056709426 -7.087340478 -1.840110704 -1.041031415
## 338 339 340 341 342
## 0.727370890 0.082227844 -0.910143206 1.071004744 -0.792323645
## 343 344 345 346 347
## 0.163915480 0.523235786 0.347997277 -0.781634913 0.299977930
## 348 349 350 351 352
## -0.170120027 -0.020886157 -0.742410251 -1.484068372 -1.432013927
## 353 355 356 357 358
## 0.863730651 -1.100362212 -1.314195137 -0.444425114 -1.892106432
## 359 360 361 362 364
## 0.862358592 -0.472769637 0.786510019 -0.309071441 -14.287577974
## 365 366 368 369 370
## 0.781214165 -0.299132799 0.458136430 -0.044199197 0.654831556
## 371 372 373 375 376
## 1.541533949 -0.552578693 0.735472967 -1.743786782 -1.003627157
## 377 378 379 380 381
## 0.632629113 -0.867230400 0.771235696 -1.027507663 0.341241148
## 382 383 384 385 387
## -0.351512241 -1.756674396 0.464689948 -0.074694136 0.687748121
## 388 390 391 392 393
## 1.000558969 -0.990437460 0.406231794 0.772586011 0.666284820
## 394 397 401 403 404
## 1.239517468 0.358541996 -1.154815234 -3.564810064 -7.532901420
## 406 407 409 411 412
## -1.492127197 -1.029323530 -0.084274880 -6.707102659 0.740034172
## 413 414 415 416 417
## -1.048047627 -0.109252003 -1.519559203 -8.695472843 0.384935083
## 418 419 420 421 422
## -1.224113040 1.049335865 -1.449887831 -0.132837342 0.552393130
## 423 424 425 426 427
## 0.320974106 0.747450173 -0.256795604 0.298787949 0.829313907
## 430 431 433 434 436
## 1.296772566 -0.572712375 -1.425727302 -7.109986383 -1.073351100
## 437 438 439 440 443
## -0.758028432 -0.595240717 -0.890404561 -0.892700462 0.724667263
## 444 445 447 448 449
## 0.630527407 -0.559016008 -0.116857882 -0.346952856 -0.715668076
## 450 451 452 454 457
## -0.747923562 -0.407655805 0.025993284 0.286885786 -1.954289693
## 458 461 462 463 464
## 1.495250082 0.321331285 0.973747001 -0.049545752 -0.075758040
## 465 467 469 470 471
## 0.484268471 1.665296610 -0.861106813 0.184610216 -1.156003364
## 473 474 475 476 477
## -0.532939419 -1.788638849 -2.707102945 1.293708017 -8.895195111
## 478 479 480 481 482
## 0.654707547 -0.969453700 1.138121445 1.102342420 1.112356741
## 483 486 487 488 490
## 0.613955357 0.435674343 0.729201996 -0.699986853 -0.505039267
## 493 494 495 497 498
## 0.948680862 -0.505598939 0.241114654 0.001944286 0.765592975
## 499 500 501 502 503
## 1.080840940 -1.285030562 -1.696861035 -0.985144807 -1.983894749
## 504 505 507 508 509
## 0.297237379 -0.800817136 -0.657823184 0.995081530 -0.570604625
## 511 512 513 514 515
## 0.055474209 -0.595271999 0.248947971 1.701913698 0.301756680
## 516 517 518 519 520
## 0.145659998 1.560668879 -0.961416476 -1.206611561 0.843821885
## 521 522 525 526 527
## 1.283575444 0.429719201 0.762657294 0.834800976 -1.495069969
## 529 530 532 533 534
## -0.635350299 -0.175625526 1.115573121 0.591506252 -0.194709903
## 535 536 537 538 540
## 1.566574086 0.341276446 -1.280531790 -0.292650024 -2.351303542
## 541 542 543 544 545
## -0.779685818 -0.489035964 -0.607046896 -0.900586022 -0.880238609
## 546 549 550 552 553
## -0.462620787 -1.894454858 0.809074294 -0.462421373 -1.429111216
## 554 556 557 558 559
## -0.035336638 -1.741134759 0.373566862 0.429521323 -1.215986537
## 561 562 564 565 566
## -1.324948250 -0.775696234 -0.193717899 0.972622603 -1.454618923
## 567 568 569 570 571
## 1.855297133 -2.269993458 0.237988525 -0.543421910 0.856104192
## 572 573 574 575 576
## -0.347885114 0.081083837 -0.456509880 -1.181407849 -0.765161089
## 577 578 579 581 582
## 0.476555701 -0.969536945 0.027201029 -1.458245216 0.591690454
## 583 585 586 587 588
## 1.189775292 1.472966377 -1.361333117 -6.235012314 -0.352086436
## 590 591 592 593 594
## 0.670270352 1.142191423 0.696995708 -0.892658393 -0.606690513
## 595 596 597 598 599
## 1.779216964 -1.533743845 1.632939749 1.215108499 0.666600592
## 600 601 603 604 605
## -7.938747205 0.301296392 1.153727607 -0.566757171 -0.726355778
## 608 609 610 611 613
## 0.497905369 0.408832715 -1.303680756 0.427384196 1.140257753
## 614 616 617 618 619
## -1.504109241 0.537418080 -0.433462458 -3.044264539 0.906353516
## 620 621 622 623 624
## -1.114144078 -0.274498026 -0.979185961 -0.188917513 -0.469374249
## 626 627 628 629 630
## -1.583908883 -1.883264354 -1.230880961 1.617817137 0.405123887
## 632 633 634 635 636
## 0.796700465 -0.860108110 0.169799665 -2.609013475 1.370653622
## 637 638 639 640 641
## 0.807277748 -0.974504851 0.877083921 0.703668799 -0.123937736
## 642 643 644 646 647
## -0.968095266 -1.852795145 1.342897099 -1.542346348 -0.551578813
## 648 649 650 651 652
## 1.735760501 -1.166577679 -0.311018838 0.740344734 0.605680559
## 653 654 655 657 658
## 0.902797404 -1.766011677 0.663521039 -0.861592724 -0.415960311
## 659 660 662 663 664
## -1.395659280 0.134789431 -1.849812771 1.234387379 1.038715060
## 665 666 669 670 672
## -0.264497822 -1.131470006 -0.303110164 1.672817948 1.742638232
## 673 674 675 676 678
## 1.242706587 -1.384954800 -1.060327011 0.735250895 -1.134765928
## 679 680 681 682 684
## -0.228754355 -0.954376872 0.780322631 -0.072000572 0.712757720
## 685 687 688 689 690
## -1.730958208 0.525660686 1.197920119 -0.507260671 -2.308839742
## 691 692 693 695 696
## 0.386318421 -1.550343964 0.730900934 0.532626588 -1.701915602
## 697 699 700 701 702
## -0.783925889 1.158537259 -1.698036673 0.769176051 0.777469531
## 703 704 705 706 708
## -0.459404264 1.046528424 -1.677364823 0.600045995 0.729288139
## 709 710 711 712 713
## 0.190701469 0.290017130 -1.823428792 -1.139227659 0.544700415
## 715 716 717 718 719
## 1.241483320 -2.052859941 0.498076547 -0.903554408 -3.530257538
## 720 721 722 724 725
## 0.726675515 -0.701335149 -2.241988854 -0.910264309 1.071652061
## 726 727 728 729 730
## 0.378682897 1.114912636 -1.294230494 -1.022063393 0.299508630
## 731 732 734 735 736
## 0.609955681 -1.108567909 -0.074457401 1.351102028 0.739316506
## 737 738 739 740 741
## -2.268259393 1.093272252 -1.422285042 -1.386417526 1.806858879
## 742 743 744 745 746
## -0.960494360 0.785085085 -1.312057668 -0.910179007 -2.560268040
## 747 749 750 751 753
## 0.743772661 -0.717704651 1.281211913 0.955321265 -0.631053607
## 754 756 757 758 759
## 0.724417669 0.619367910 -0.198447420 -0.957728962 0.152800463
## 760 761 762 763 764
## -3.084405389 -0.299132799 0.107615293 -1.345143238 1.547076994
## 765 766 767 768 770
## -1.061404703 0.298127755 0.571444014 -0.541928003 0.652624128
## 772 775 776 778 779
## 1.381416485 1.125083766 -0.693849586 1.267210689 1.364678070
## 781 782 783 786 787
## -0.593089602 0.676705383 0.564619370 -0.034101462 -0.719318302
## 788 791 793 794 795
## -7.297648916 -2.233756598 0.722882659 0.199672773 -0.441362071
## 796 797 798 799 800
## -1.469940527 -0.683080272 -1.357845264 0.133435776 1.673847372
## 801 802 803 804 805
## 0.031846454 1.159352961 -0.762660579 -0.703988814 -0.840973231
## 807 808 810 812 813
## -0.322227919 -11.741693843 0.596545983 0.819692617 1.171852009
## 814 815 816 817 818
## -9.777983527 0.006277229 -0.673951606 -1.139542569 0.709842945
## 819 820 821 822 823
## -1.462101738 -1.552188408 0.741432794 0.711596123 -1.219820121
## 826 827 829 830 831
## -0.519252076 0.325191260 -1.890015371 0.672418830 -1.203986996
## 832 833 834 835 836
## -0.071168211 -0.602209829 -5.249815708 0.654707547 1.116671911
## 838 839 841 842 843
## 1.031946073 -1.094870841 0.646072535 -0.452464396 0.898129389
## 845 847 848 849 852
## -1.087542747 -0.715188000 -1.100762705 -1.215410092 1.040851485
## 853 854 856 857 858
## -0.012784646 0.199159739 -1.003258170 -1.382232870 -0.755146265
## 859 861 863 864 865
## 0.180776705 -0.248524507 -0.044765380 1.127238764 0.740884657
## 866 867 868 870 871
## 0.606705980 1.116671911 0.583832791 -0.900139057 0.415392112
## 872 874 876 878 879
## -0.355143673 -0.469138078 -2.439901928 -2.086605940 0.516093605
## 880 883 885 886 887
## 0.622111075 0.374213413 -1.973936103 -0.887532386 -2.470642959
## 888 889 890 891 892
## 1.360330776 1.338244553 1.170786713 -0.876651008 -0.461779582
## 893 894 896 897 898
## 0.598235794 0.223773963 -0.421687012 -1.149388232 -3.089058090
## 899 900 901 902 904
## -0.609059489 -1.333848252 -0.012679657 0.795885906 -0.824931091
## 905 908 909 911 912
## 0.724374030 -2.229206466 0.753651688 -0.207397516 -2.088777170
## 913 914 915 916 917
## -1.223085787 0.947735607 -0.117615950 0.004841959 0.536319559
## 918 919 920 922 924
## -0.906674394 0.311209670 1.255992077 -0.553745107 0.637469026
## 925 926 927 928 929
## 0.501001955 0.008386009 0.791107970 1.526986087 -1.051656734
## 930 931 932 934 935
## -1.374802253 0.994964089 1.297607317 0.329186357 1.189129770
## 936 937 939 940 941
## 0.809762785 1.038935532 1.252731375 0.299615708 1.507240098
## 943 945 946 948 949
## 1.174595563 -1.234305092 -1.006368934 -1.636239670 -0.421241022
## 951 952 953 954 955
## 0.468263736 1.419271726 0.856668143 0.799895823 -0.087587095
## 956 958 959 960 961
## 0.261399141 0.518871654 -0.962713454 1.171202337 -1.121981734
## 962 963 964 966 969
## -5.524958695 1.168016060 0.572683245 -1.184371465 -0.271262329
## 970 971 972 973 974
## -2.846045660 0.299508630 -2.097794940 -0.628193868 0.517476522
## 975 976 977 978 979
## 0.919972846 -0.836585115 -1.619729082 -10.089067497 -1.112652701
## 980 981 982 984 986
## -1.635075409 0.461717191 0.581668206 -1.514485632 0.745753829
## 987 988 989 990 991
## -1.938233648 -0.322018628 0.767385875 -1.195879303 -1.698036673
## 993 994 995 996 997
## 0.272433038 0.813641795 0.239165233 -1.128208564 -1.568369665
## 1000 1001 1003 1004 1005
## 0.369688933 1.265185465 0.019666901 -0.048682506 -0.174767087
## 1006 1007 1008 1009 1012
## -0.095993235 1.011317476 0.207106783 -0.167639672 1.654488624
## 1013 1014 1015 1016 1017
## 1.926018655 0.167158362 -2.181345442 -0.704987487 -1.390427611
## 1018 1019 1020 1021 1022
## -0.555932883 0.384843117 -0.525127767 -0.714367473 0.052617362
## 1023 1025 1026 1027 1028
## 0.283675033 1.290722334 -0.419148505 1.005246291 1.255488649
## 1029 1030 1031 1032 1033
## 0.396647865 -0.813283781 -1.481704419 -2.175083258 0.910965512
## 1034 1035 1036 1037 1038
## 0.619375561 1.020305920 0.154668512 0.524185013 0.352928676
## 1039 1040 1041 1042 1044
## 1.440723531 1.530731158 0.199965374 0.851848931 -1.004546524
## 1045 1046 1047 1048 1049
## 0.767692612 0.653356008 1.174495007 -0.416307125 0.832365833
## 1051 1052 1053 1054 1055
## -0.884453389 -0.090892262 -0.863185868 -1.811509493 0.728793730
## 1057 1058 1059 1061 1062
## 1.104585322 0.515123271 -0.037063438 -0.607554607 1.056268410
## 1063 1064 1065 1066 1067
## 0.411195250 1.364309841 0.062972656 -11.100443403 1.296777702
## 1068 1069 1070 1071 1072
## -1.950887248 0.962535548 1.028410069 0.193037657 -0.048633450
## 1073 1074 1075 1076 1077
## -0.326230588 0.137810294 -0.219382846 0.128004947 0.826075321
## 1078 1079 1080 1081 1082
## -1.044753297 -0.172558098 1.291492953 0.973544409 0.842972076
## 1083 1084 1085 1086 1089
## 0.424206477 0.219066331 -1.244244921 -2.208107292 0.746654990
## 1090 1091 1092 1093 1094
## 1.031079888 -1.243725667 -2.125974182 -1.021937031 -1.387683765
## 1095 1096 1097 1098 1099
## 0.365106682 1.123423074 -0.672188146 -0.612450036 -0.818114429
## 1100 1101 1102 1103 1104
## 0.500943354 -0.513104869 0.605669233 -0.889669918 -1.385225862
## 1105 1106 1107 1108 1109
## -0.559164709 -2.179324787 -1.154491607 -0.901339404 0.450445529
## 1110 1111 1112 1114 1115
## 1.775220206 -0.397385973 0.363125267 -1.220453353 -1.968496390
## 1116 1117 1118 1119 1120
## 0.371626324 0.956728797 -1.325444739 -0.302674925 1.310679175
## 1123 1124 1125 1126 1128
## -1.745453890 -1.782117062 0.851469542 -0.796357491 1.229769574
## 1129 1130 1131 1132 1134
## 0.729534754 0.766571441 -1.116624357 -1.176662192 -0.856761085
## 1135 1136 1137 1138 1139
## -0.151520748 -0.464213757 1.221842282 0.409546580 -0.267442683
## 1140 1141 1143 1144 1145
## -1.607895387 0.560971948 -1.174385173 -0.767735146 -0.620710245
## 1146 1147 1148 1149 1151
## 0.750013455 1.026384368 -6.900767277 -0.826714843 -0.973403919
## 1152 1154 1155 1156 1157
## -0.537299368 -0.862741553 -1.644428383 0.952666348 -0.311333772
## 1158 1159 1160 1161 1163
## 1.008795105 -0.292396379 -0.777731174 1.028752716 -2.730161787
## 1165 1166 1168 1169 1171
## 1.108578911 1.154319321 0.657963294 -0.946495328 1.090678985
## 1172 1173 1174 1175 1177
## -1.182869968 0.131798312 1.948719292 -0.470864397 -3.234162303
## 1178 1179 1180 1182 1184
## -1.351992604 0.075430714 -2.721065087 -1.811042972 0.201704237
## 1185 1186 1188 1189 1190
## -1.039364550 0.811182914 0.250235030 -2.541536817 -0.308909261
## 1191 1192 1193 1195 1196
## -0.837519129 0.422572494 1.005886950 0.596583447 -0.309088967
## 1197 1198 1199 1201 1203
## -0.730412990 -0.751031558 0.807656437 -0.588098007 0.793587847
## 1204 1205 1206 1207 1208
## 0.312877071 -0.858077363 1.161891707 1.738155776 -0.902470738
## 1209 1210 1211 1212 1213
## 0.512120954 -0.292714698 0.925778550 -0.046177506 -0.530603614
## 1214 1215 1216 1217 1218
## 0.812362430 1.246552524 -2.006865379 0.876306399 -1.080717902
## 1219 1220 1221 1222 1223
## 0.739361672 1.022337976 0.955792224 0.011406631 0.494619025
## 1225 1226 1229 1231 1233
## 0.780127576 -0.479045452 -0.186963311 0.661524999 -1.253733046
## 1234 1236 1237 1238 1239
## -0.261502541 0.248025384 0.119818338 1.658020397 1.086965995
## 1240 1241 1242 1243 1244
## 1.412654506 -0.968434866 -1.018897539 -1.554957879 0.002466157
## 1246 1248 1249 1252 1253
## 1.037921869 1.563135298 0.251512992 -0.486371017 0.648296943
## 1254 1255 1256 1257 1258
## 0.052193864 -1.148301396 0.648363862 -6.162040343 0.283981295
## 1259 1260 1261 1262 1263
## -1.394977306 -1.129101037 0.069686939 0.224708819 0.744604769
## 1264 1265 1267 1269 1271
## 0.666594118 0.522912102 1.301647212 -0.068675247 0.724213171
## 1272 1273 1274 1275 1276
## -0.949019261 1.344028687 0.551290943 0.648296943 0.976915720
## 1278 1279 1280 1281 1282
## -2.245976584 -1.544805375 -0.817604783 0.559932240 -1.021477121
## 1283 1284 1285 1286 1287
## 1.003234025 -1.718814292 0.270892550 1.587361251 -7.996109799
## 1288 1289 1290 1292 1293
## 0.339580343 0.166126295 -1.038746130 0.170756646 -0.051240568
## 1294 1296 1297 1299 1300
## 0.362177313 -0.506964214 -1.193526967 0.220001145 -1.646753160
## 1301 1303 1307 1308 1309
## 0.053512944 0.836520471 1.761526013 1.422323375 -0.982131773
## 1310 1311 1312 1313 1314
## -0.787075413 0.693247780 -1.367638058 -2.845277424 0.327474593
## 1315 1316 1318 1320 1323
## 0.709032739 -0.165003369 -1.199155275 0.310075872 1.059260180
## 1324 1325 1326 1327 1328
## -1.293183497 -1.992780114 -0.609433563 0.528383938 1.163587626
## 1329 1330 1331 1332 1333
## 0.427576308 0.913808304 -1.832052638 0.271820783 1.577807040
## 1334 1335 1337 1338 1339
## 1.483287011 1.362358634 -0.463745193 1.468704978 -1.196661089
## 1340
## 0.770512302
#pvprob <- as.data.frame(prob)
#final <- cbind(pvprob,claimants)
#dim(final)
table(a$ATTORNEY)
##
## 0 1
## 578 518
table(prob > 0.5)
##
## FALSE TRUE
## 727 369
confusion <- table(prob > 0.5,a$ATTORNEY)
confusion
##
## 0 1
## FALSE 484 243
## TRUE 94 275
Acc = sum(diag(confusion)) / sum(confusion)
Acc
## [1] 0.6925182
library(MASS)
library(caret)
## Loading required package: lattice
## Loading required package: ggplot2
library(car)
## Loading required package: carData
stepAIC(m2)
## Start: AIC=1268.11
## ATTORNEY ~ factor(CLMSEX) + factor(CLMINSUR) + (SEATBELT) + sqrt(a$CLMAGE) +
## sqrt(LOSS)
##
## Df Deviance AIC
## - SEATBELT 1 1257.7 1267.7
## <none> 1256.1 1268.1
## - factor(CLMINSUR) 1 1262.1 1272.1
## - sqrt(a$CLMAGE) 1 1263.2 1273.2
## - factor(CLMSEX) 1 1266.2 1276.2
## - sqrt(LOSS) 1 1494.0 1504.0
##
## Step: AIC=1267.72
## ATTORNEY ~ factor(CLMSEX) + factor(CLMINSUR) + sqrt(a$CLMAGE) +
## sqrt(LOSS)
##
## Df Deviance AIC
## <none> 1257.7 1267.7
## - factor(CLMINSUR) 1 1263.6 1271.6
## - sqrt(a$CLMAGE) 1 1265.2 1273.2
## - factor(CLMSEX) 1 1268.0 1276.0
## - sqrt(LOSS) 1 1498.4 1506.4
##
## Call: glm(formula = ATTORNEY ~ factor(CLMSEX) + factor(CLMINSUR) +
## sqrt(a$CLMAGE) + sqrt(LOSS), family = binomial, data = a)
##
## Coefficients:
## (Intercept) factor(CLMSEX)1 factor(CLMINSUR)1
## 0.30022 0.44037 0.56370
## sqrt(a$CLMAGE) sqrt(LOSS)
## 0.08731 -1.22990
##
## Degrees of Freedom: 1095 Total (i.e. Null); 1091 Residual
## Null Deviance: 1516
## Residual Deviance: 1258 AIC: 1268