For the dataset shown below, the variable "score" shows the scores of students. The variable "frequency" specifies the frequency of each value of the "score" variable. For instance, the first value of the "score" variable is 710 and the corresponding frequency is 13. This means that 13 students got a score 710. Similarly, the second value of the "score" variable is 709 and the corresponding frequency is 3. This means that 3 students got a score 709.
I want to find the corresponding percentile for each value of the "score" variable with 2 decimal digits (e.g., 99.23 percentile, 81.23 percentile). The standard -xtile and -pctile syntax only create variables that give the value of the "score" variable corresponding to specific percentiles (10%, 20%, etc), not the opposite (the value of percentiles corresponding to each value of the "score" variable", which is the variable I try to create).
Any help with this will be much appreciated.
Thanks a lot!
I want to find the corresponding percentile for each value of the "score" variable with 2 decimal digits (e.g., 99.23 percentile, 81.23 percentile). The standard -xtile and -pctile syntax only create variables that give the value of the "score" variable corresponding to specific percentiles (10%, 20%, etc), not the opposite (the value of percentiles corresponding to each value of the "score" variable", which is the variable I try to create).
Any help with this will be much appreciated.
Thanks a lot!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input int(score frequency year) 710 13 2019 709 3 2019 708 1 2019 707 1 2019 706 3 2019 704 2 2019 703 2 2019 702 3 2019 701 4 2019 700 4 2019 699 6 2019 698 4 2019 697 9 2019 696 3 2019 695 5 2019 694 13 2019 693 3 2019 692 8 2019 691 5 2019 690 12 2019 689 6 2019 688 16 2019 687 9 2019 686 9 2019 685 19 2019 684 19 2019 683 22 2019 682 18 2019 681 17 2019 680 16 2019 679 9 2019 678 21 2019 677 18 2019 676 22 2019 675 21 2019 674 25 2019 673 29 2019 672 25 2019 671 32 2019 670 33 2019 669 39 2019 668 29 2019 667 37 2019 666 33 2019 665 28 2019 664 36 2019 663 35 2019 662 37 2019 661 46 2019 660 63 2019 659 46 2019 658 43 2019 657 51 2019 656 60 2019 655 64 2019 654 71 2019 653 67 2019 652 56 2019 651 62 2019 650 69 2019 649 68 2019 648 73 2019 647 91 2019 646 75 2019 645 83 2019 644 71 2019 643 67 2019 642 83 2019 641 93 2019 640 67 2019 639 85 2019 638 85 2019 637 107 2019 636 111 2019 635 87 2019 634 89 2019 633 106 2019 632 95 2019 631 117 2019 630 108 2019 629 102 2019 628 121 2019 627 138 2019 626 128 2019 625 104 2019 624 122 2019 623 134 2019 622 134 2019 621 141 2019 620 122 2019 619 127 2019 618 133 2019 617 153 2019 616 154 2019 615 133 2019 614 156 2019 613 146 2019 612 171 2019 611 143 2019 610 159 2019 609 172 2019 608 182 2019 607 168 2019 606 179 2019 605 179 2019 604 199 2019 603 176 2019 602 196 2019 601 169 2019 600 201 2019 599 196 2019 598 214 2019 597 198 2019 596 196 2019 595 199 2019 594 197 2019 593 219 2019 592 197 2019 591 214 2019 590 211 2019 589 208 2019 588 218 2019 587 236 2019 586 242 2019 585 239 2019 584 254 2019 583 246 2019 582 241 2019 581 264 2019 580 264 2019 579 229 2019 578 254 2019 577 261 2019 576 259 2019 575 266 2019 574 264 2019 573 286 2019 572 254 2019 571 296 2019 570 289 2019 569 281 2019 568 263 2019 567 291 2019 566 313 2019 565 287 2019 564 310 2019 563 342 2019 562 323 2019 561 327 2019 560 307 2019 559 314 2019 558 305 2019 557 327 2019 556 341 2019 555 349 2019 554 377 2019 553 318 2019 552 333 2019 551 329 2019 550 343 2019 549 312 2019 548 357 2019 547 378 2019 546 351 2019 545 346 2019 544 375 2019 543 393 2019 542 395 2019 541 375 2019 540 385 2019 539 391 2019 538 365 2019 537 360 2019 536 401 2019 535 376 2019 534 419 2019 533 399 2019 532 381 2019 531 396 2019 530 395 2019 529 391 2019 528 380 2019 527 411 2019 526 367 2019 525 421 2019 524 419 2019 523 423 2019 522 417 2019 521 403 2019 520 458 2019 519 461 2019 518 443 2019 517 444 2019 516 439 2019 515 443 2019 514 436 2019 513 376 2019 512 435 2019 511 422 2019 510 441 2019 509 463 2019 end
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