Basic Analysis and Graphing - SAS

More documents

Recommendations

Info

232 Performing Simple Logistic Regression Chapter 7 Additional Examples of Logistic Regression 8. Move the cross-hair intersection to the prediction line, and read the In(dose) value that shows on the horizontal axis. In this example, a rabbit with a In(dose) of approximately -0.9 is equally likely to be cured as it is to die. Figure 7.10 Example of Crosshair Tool on Logistic Plot Example of Inverse Prediction Using the Inverse Prediction Option If your response has exactly two levels, the Inverse Prediction option enables you to request an exact inverse prediction. You are given the x value corresponding to a given probability of the lower response category, as well as a confidence interval for that x value. To use the Inverse Prediction option, proceed as follows: 1. Open the Penicillin.jmp sample data table. 2. Select Analyze > Fit Y by X. 3. Select Response and click Y, Response. 4. Select In(Dose) and click X, Factor. Notice that JMP automatically fills in Count for Freq. Count was previously assigned the role of Freq. 5. Click OK. 6. From the red triangle menu, select Inverse Prediction. See Figure 7.11. 7. Type 0.95 for the Confidence Level. 8. Select Two sided for the confidence interval. 9. Request the response probability of interest. Type 0.5 and 0.9 for this example, which indicates you are requesting the values for ln(Dose) that correspond to a 0.5 and 0.9 probability of being cured. 10. Click OK. The Inverse Prediction plot appears.
Chapter 7 Performing Simple Logistic Regression 233 Statistical Details for the Logistic Platform Figure 7.11 Inverse Prediction Window Figure 7.12 Example of Inverse Prediction Plot The estimates of the x values and the confidence intervals are shown in the report as well as in the probability plot. For example, the value of ln(Dose) that results in a 90% probability of being cured is estimated to be between -0.526 and 0.783. Statistical Details for the Logistic Platform Statistical Details for the Whole Model Test Report Chi-Square The Chi-Square statistic is sometimes denoted G 2 and is written as follows: G 2 = 2( –lnp( background) – –ln p( model) )
Page 1 and 2:
Version 10 Basic Analysis and Graph
Page 3:
USE, DATA OR PROFITS, WHETHER IN AN
Page 6 and 7:
6 Options for Categorical Variables
Page 8 and 9:
8 Nonparametric Bivariate Density R
Page 10 and 11:
10 Example of the Power Option . .
Page 12 and 13:
12 Statistical Details for the Logi
Page 14 and 15:
14 Use Categorical Variables . . .
Page 16 and 17:
16 Control Animation for Dynamic Bu
Page 18 and 19:
18 Launch the Scatterplot Matrix Pl
Page 20 and 21:
Contents Book Conventions. . . . .
Page 22 and 23:
22 Learn about JMP Chapter 1 Book C
Page 24 and 25:
24 Learn about JMP Chapter 1 Book C
Page 26 and 27:
26 Learn about JMP Chapter 1 Additi
Page 28 and 29:
28 Learn about JMP Chapter 1 Additi
Page 30 and 31:
Contents Overview of the Distributi
Page 32 and 33:
32 Performing Univariate Analysis C
Page 34 and 35:
Page 36 and 37:
Page 38 and 39:
Page 40 and 41:
Page 42 and 43:
Page 44 and 45:
Page 46 and 47:
Page 48 and 49:
Page 50 and 51:
Page 52 and 53:
Page 54 and 55:
Page 56 and 57:
Page 58 and 59:
Page 60 and 61:
Page 62 and 63:
Page 64 and 65:
Page 66 and 67:
Page 68 and 69:
Page 70 and 71:
Page 72 and 73:
Page 74 and 75:
Page 76 and 77:
Page 78 and 79:
Page 80 and 81:
Page 82 and 83:
Page 84 and 85:
Page 86 and 87:
Page 88 and 89:
Contents Overview of the Fit Y by X
Page 90 and 91:
90 Introduction to the Fit Y by X P
Page 92 and 93:
Contents Example of Bivariate Analy
Page 94 and 95:
94 Performing Bivariate Analysis Ch
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
100 Performing Bivariate Analysis C
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Contents Overview of Oneway Analysi
Page 130 and 131:
130 Performing Oneway Analysis Chap
Page 132 and 133:
Page 134 and 135:
Page 136 and 137:
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
Page 152 and 153:
Page 154 and 155:
Page 156 and 157:
Page 158 and 159:
Page 160 and 161:
Page 162 and 163:
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
Page 176 and 177:
Page 178 and 179:
Page 180 and 181:
Page 182 and 183: 182 Performing Oneway Analysis Chap
Page 184 and 185: Contents Example of Contingency Ana
Page 186 and 187: 186 Performing Contingency Analysis
Page 216 and 217: Contents Overview of Logistic Regre
Page 218 and 219: 218 Performing Simple Logistic Regr
Page 236 and 237: Contents Overview of the Matched Pa
Page 238 and 239: 238 Comparing Paired Data Chapter 8
Page 248 and 249: Contents Example of Bootstrapping .
Page 250 and 251: 250 Bootstrapping Chapter 9 Example
Page 252 and 253: 252 Bootstrapping Chapter 9 Unstack
Page 254 and 255: 254 Bootstrapping Chapter 9 Analysi
Page 256 and 257: Contents Overview of Graph Builder
Page 258 and 259: 258 Interactive Data Visualization
Page 282 and 283:
282 Interactive Data Visualization
Page 284 and 285:
Page 286 and 287:
Page 288 and 289:
Page 290 and 291:
Page 292 and 293:
Page 294 and 295:
Page 296 and 297:
Page 298 and 299:
Page 300 and 301:
Page 302 and 303:
Page 304 and 305:
Page 306 and 307:
Page 308 and 309:
Page 310 and 311:
Page 312 and 313:
Contents Example of the Chart Platf
Page 314 and 315:
314 Creating Summary Charts Chapter
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
Page 322 and 323:
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
Page 336 and 337:
Page 338 and 339:
Contents Example of an Overlay Plot
Page 340 and 341:
340 Creating Overlay Plots Chapter
Page 342 and 343:
Page 344 and 345:
Page 346 and 347:
Page 348 and 349:
Page 350 and 351:
Page 352 and 353:
Contents Example of a 3D Scatterplo
Page 354 and 355:
354 Creating Three-Dimensional Scat
Page 356 and 357:
Page 358 and 359:
Page 360 and 361:
Page 362 and 363:
Page 364 and 365:
Page 366 and 367:
Page 368 and 369:
Page 370 and 371:
Page 372 and 373:
Contents Example of a Contour Plot
Page 374 and 375:
374 Creating Contour Plots Chapter
Page 376 and 377:
Page 378 and 379:
Page 380 and 381:
Page 382 and 383:
Contents Example of a Dynamic Bubbl
Page 384 and 385:
384 Creating Bubble Plots Chapter 1
Page 386 and 387:
Page 388 and 389:
Page 390 and 391:
Page 392 and 393:
Page 394 and 395:
Page 396 and 397:
Page 398 and 399:
Page 400 and 401:
Page 402 and 403:
Page 404 and 405:
Contents Overview of Mapping . . .
Page 406 and 407:
406 Creating Maps Chapter 16 Exampl
Page 408 and 409:
Page 410 and 411:
Page 412 and 413:
Page 414 and 415:
Page 416 and 417:
Page 418 and 419:
418 Creating Maps Chapter 16 Backgr
Page 420 and 421:
Page 422 and 423:
Page 424 and 425:
Page 426 and 427:
Page 428 and 429:
Page 430 and 431:
Page 432 and 433:
Page 434 and 435:
Page 436 and 437:
Page 438 and 439:
Page 440 and 441:
Page 442 and 443:
Page 444 and 445:
Page 446 and 447:
Page 448 and 449:
Contents Example of a Parallel Plot
Page 450 and 451:
450 Creating Parallel Plots Chapter
Page 452 and 453:
Page 454 and 455:
Page 456 and 457:
Page 458 and 459:
Contents Example of a Cell Plot. .
Page 460 and 461:
460 Creating Cell Plots Chapter 18
Page 462 and 463:
Page 464 and 465:
Page 466 and 467:
Contents Example of Tree Maps . . .
Page 468 and 469:
468 Creating Tree Maps Chapter 19 E
Page 470 and 471:
470 Creating Tree Maps Chapter 19 E
Page 472 and 473:
472 Creating Tree Maps Chapter 19 T
Page 474 and 475:
474 Creating Tree Maps Chapter 19 A
Page 476 and 477:
Page 478 and 479:
Page 480 and 481:
Page 482 and 483:
Page 484 and 485:
Contents Example of a Scatterplot M
Page 486 and 487:
486 Creating Scatterplot Matrices C
Page 488 and 489:
Page 490 and 491:
Page 492 and 493:
Page 494 and 495:
Contents Example of a Ternary Plot
Page 496 and 497:
496 Creating Ternary Plots Chapter
Page 498 and 499:
Page 500 and 501:
Page 502 and 503:
Page 504 and 505:
504 References Becker, R.A. and Cle
Page 506 and 507:
506 References Dunnett, C.W. (1955)
Page 508 and 509:
508 References Hosmer, D.W. and Lem
Page 510 and 511:
510 References McLachlan, G.J. and
Page 512 and 513:
512 References Robertson, T., Wrigh
Page 514 and 515:
514 References Wadsworth, H. M., St
Page 516 and 517:
516 Index examples 459, 463-464 lau
Page 518 and 519:
518 Index Horizontal option 268, 32
Page 520 and 521:
520 Index Proportion of Densities o
Page 522:
522 Index examples 467-468, 473-482
show all

Basic Analysis and Graphing - SAS

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?