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Exact statistics

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and confidence intervals are computed under a certain distribution, such as the normal distribution, then the underlying methods are referred to as exact parametric methods. The exact methods that do not make any distributional assumptions are referred to as exact nonparametric methods. The latter
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All classical statistical procedures are constructed using statistics which depend only on observable random vectors, whereas generalized estimators, tests, and confidence intervals used in exact statistics take advantage of the observable random vectors and the observed values both, as in
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has the advantage of making fewer assumptions whereas, the former tend to yield more powerful tests when the distributional assumption is reasonable. For advanced methods such as higher-way ANOVA
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Classical statistical methods do not provide exact tests to many statistical problems such as testing Variance Components and ANOVA under unequal variances. To rectify this situation, the
403: 552:{\displaystyle R={\frac {{\overline {x}}S}{s\sigma }}-{\frac {{\overline {X}}-\mu }{\sigma }}={\frac {\overline {x}}{s}}{\frac {\sqrt {U}}{\sqrt {n}}}~-~{\frac {Z}{\sqrt {n}}}} 615: 588: 173: 146: 50:. Exact statistical methods help avoid some of the unreasonable assumptions of traditional statistical methods, such as the assumption of equal variances in classical 790: 770: 675: 423: 200: 119: 695: 655: 635: 754: 788:
Mehta CR, Patel NR and Gray R. 1985. On computing an exact confidence interval for the common odds ratio in several 2 x 2 contingency tables.
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When the sample size is small, asymptotic results given by some traditional methods may not be valid. In such situations, the asymptotic
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but without having to treat constant parameters as random variables. For example, in sampling from a normal population with mean
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Mehta CR and Patel NR. 1983. A network algorithm for performing Fisher's exact test in rxc contingency tables.
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and approximate statistical methods. The main characteristic of exact methods is that statistical tests and
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are possible because its distribution and the observed value are both free of nuisance parameters.
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Generalized Inference in Repeated Measures: Exact Methods in MANOVA and Mixed Models
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are the sample mean and the sample variance. Then, defining Z and U thus:
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Now suppose the parameter of interest is the coefficient of variation,
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that was developed to provide more accurate results pertaining to
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are based on exact probability statements that are valid for any
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Mehta, C. R. 1995. SPSS 6.1 Exact test for Windows.
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They also allow exact inference on 7: 425:based on the generalized statistic 38:by eliminating procedures based on 398:{\displaystyle \rho =\mu /\sigma } 14: 610:{\displaystyle {\overline {X}}} 583:{\displaystyle {\overline {x}}} 168:{\displaystyle {\overline {X}}} 273: 261: 244: 225: 1: 777:Mehta CR and Patel NR. 1995. 736:Optimal discriminant analysis 741:Classification tree analysis 602: 575: 505: 479: 449: 233: 160: 22:, such as that described in 141:{\displaystyle \sigma ^{2}} 863: 637:is the observed value of 590:is the observed value of 783:Statistics in Medicine 691: 671: 657:. Exact inferences on 651: 631: 611: 584: 553: 419: 399: 361: 280: 196: 169: 142: 115: 847:Statistical inference 818:John Wiley & Sons 810:Weerahandi, S. 2004. 797:Weerahandi, S. 1995. 692: 672: 670:{\displaystyle \rho } 652: 632: 612: 585: 554: 420: 418:{\displaystyle \rho } 400: 362: 281: 197: 195:{\displaystyle S^{2}} 170: 143: 116: 99:the Bayesian approach 752:Fisher, R. A. 1954. 681: 661: 641: 621: 594: 567: 432: 409: 375: 296: 209: 179: 152: 125: 114:{\displaystyle \mu } 105: 44:confidence intervals 794:, 80(392): 969–973. 774:, 78(382): 427–434. 731:Fisher's exact test 356: 75:regression analysis 56:variance components 36:interval estimation 32:statistical testing 758:. Oliver and Boyd. 687: 667: 647: 627: 607: 580: 549: 415: 395: 357: 336: 276: 192: 165: 138: 111: 690:{\displaystyle R} 650:{\displaystyle s} 630:{\displaystyle S} 605: 578: 547: 546: 536: 530: 526: 525: 520: 512: 508: 494: 482: 466: 452: 236: 223: 163: 26:, is a branch of 16:Type of statistic 854: 785:, 14: 2143–2160. 696: 694: 693: 688: 676: 674: 673: 668: 656: 654: 653: 648: 636: 634: 633: 628: 616: 614: 613: 608: 606: 598: 589: 587: 586: 581: 579: 571: 558: 556: 555: 550: 548: 542: 538: 534: 528: 527: 521: 516: 515: 513: 501: 500: 495: 490: 483: 475: 472: 467: 465: 457: 453: 445: 442: 424: 422: 421: 416: 404: 402: 401: 396: 391: 366: 364: 363: 358: 355: 350: 332: 331: 322: 317: 316: 285: 283: 282: 277: 251: 237: 229: 224: 219: 201: 199: 198: 193: 191: 190: 174: 172: 171: 166: 164: 156: 147: 145: 144: 139: 137: 136: 120: 118: 117: 112: 20:Exact statistics 862: 861: 857: 856: 855: 853: 852: 851: 837: 836: 827: 805:Springer-Verlag 749: 727: 707: 679: 678: 659: 658: 639: 638: 619: 618: 592: 591: 565: 564: 473: 458: 443: 430: 429: 407: 406: 373: 372: 323: 308: 294: 293: 207: 206: 182: 177: 176: 150: 149: 128: 123: 122: 103: 102: 94: 17: 12: 11: 5: 860: 858: 850: 849: 839: 838: 835: 834: 826: 825:External links 823: 822: 821: 808: 795: 786: 775: 766: 759: 748: 745: 744: 743: 738: 733: 726: 723: 706: 699: 686: 666: 646: 626: 604: 601: 577: 574: 561: 560: 545: 541: 533: 524: 519: 511: 507: 504: 498: 493: 489: 486: 481: 478: 470: 464: 461: 456: 451: 448: 440: 437: 414: 394: 390: 386: 383: 380: 369: 368: 354: 349: 346: 343: 339: 335: 330: 326: 321: 315: 311: 307: 304: 301: 287: 286: 275: 272: 269: 266: 263: 260: 257: 254: 250: 246: 243: 240: 235: 232: 227: 222: 217: 214: 189: 185: 162: 159: 135: 131: 110: 93: 90: 15: 13: 10: 9: 6: 4: 3: 2: 859: 848: 845: 844: 842: 832: 829: 828: 824: 819: 815: 814: 809: 806: 802: 801: 796: 793: 792: 787: 784: 780: 776: 773: 772: 767: 764: 763:Prentice Hall 760: 757: 756: 751: 750: 746: 742: 739: 737: 734: 732: 729: 728: 724: 722: 720: 716: 714: 704: 700: 698: 684: 664: 644: 624: 599: 572: 543: 539: 531: 522: 517: 509: 502: 496: 491: 487: 484: 476: 468: 462: 459: 454: 446: 438: 435: 428: 427: 426: 412: 392: 388: 384: 381: 378: 352: 347: 344: 341: 337: 333: 328: 324: 319: 313: 309: 305: 302: 299: 292: 291: 290: 270: 267: 264: 258: 255: 252: 248: 241: 238: 230: 220: 215: 212: 205: 204: 203: 187: 183: 157: 133: 129: 121:and variance 108: 100: 91: 89: 87: 83: 78: 76: 71: 69: 63: 61: 57: 53: 49: 45: 41: 37: 33: 29: 25: 21: 811: 798: 789: 782: 769: 753: 718: 712: 711:generalized 708: 702: 701:Generalized 562: 370: 288: 95: 92:The approach 85: 81: 79: 67: 64: 60:mixed models 19: 18: 65:When exact 48:sample size 747:References 289:and that 148:, suppose 40:asymptotic 28:statistics 24:exact test 665:ρ 603:¯ 576:¯ 532:− 506:¯ 492:σ 488:μ 485:− 480:¯ 469:− 463:σ 450:¯ 413:ρ 393:σ 385:μ 379:ρ 345:− 338:χ 334:∼ 325:σ 256:∼ 253:σ 242:μ 239:− 234:¯ 161:¯ 130:σ 109:μ 841:Category 725:See also 715:-values 705:-values 70:-values 563:where 535:  529:  52:ANOVA 831:XPro 617:and 175:and 34:and 58:of 843:: 816:. 803:. 781:. 62:. 820:. 807:. 765:. 719:p 713:p 703:p 685:R 645:s 625:S 600:X 573:x 559:, 544:n 540:Z 523:n 518:U 510:s 503:x 497:= 477:X 460:s 455:S 447:x 439:= 436:R 389:/ 382:= 367:. 353:2 348:1 342:n 329:2 320:/ 314:2 310:S 306:n 303:= 300:U 274:) 271:1 268:, 265:0 262:( 259:N 249:/ 245:) 231:X 226:( 221:n 216:= 213:Z 188:2 184:S 158:X 134:2 86:p 82:p 68:p

Index

exact test
statistics
statistical testing
interval estimation
asymptotic
confidence intervals
sample size
ANOVA
variance components
mixed models
p-values
regression analysis
the Bayesian approach
generalized p-values
Fisher's exact test
Optimal discriminant analysis
Classification tree analysis
Statistical Methods for Research Workers
Prentice Hall
Journal of the American Statistical Association
Exact logistic regression: theory and examples
Journal of the American Statistical Association
Exact Statistical Method for Data Analysis
Springer-Verlag
Generalized Inference in Repeated Measures: Exact Methods in MANOVA and Mixed Models
John Wiley & Sons
XPro
Category
Statistical inference

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