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Kendall's W

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When tied values occur, they are each given the average of the ranks that would have been given had no ties occurred. For example, the data set {80,76,34,80,73,80} has values of 80 tied for 4th, 5th, and 6th place; since the mean of {4,5,6} = 5, ranks would be assigned to the raw data values as
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is 1, then all the judges or survey respondents have been unanimous, and each judge or respondent has assigned the same order to the list of objects or concerns. If
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Suppose, for instance, that a number of people have been asked to rank a list of political concerns, from the most important to the least important. Kendall's
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is 0, then there is no overall trend of agreement among the respondents, and their responses may be regarded as essentially random. Intermediate values of
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is 0, then there is no overall trend of agreement among the respondents, and their responses may be regarded as essentially random. Intermediate values of
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is 1, then all the survey respondents have been unanimous, and each respondent has assigned the same order to the list of concerns. If
2906:"Large-scale group decision-making (LSGDM) for performance measurement of healthcare construction projects: Ordinal Priority Approach" 3240: 3173: 2974: 204: 1708: 3235: 2453: 1976:
In case of tie rank, we need to consider it in the above formula. To correct for ties, we should compute the correction factors,
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Kendall, M. G., & Gibbons, J. D. (1990). Rank correlation methods. New York, NY : Oxford University Press.
3060: 1281:{\displaystyle W={\frac {12\sum _{i=1}^{n}(R_{i}^{2})-3m^{2}n(n+1)^{2}}{m^{2}n(n^{2}-1)-m\sum _{j=1}^{m}(T_{j})}},} 128: 1539: 2827: 84: 30: 2614: 1375:
In some cases, the importance of the raters (experts) might not be the same as each other. In this case, the
839:{\displaystyle W={\frac {12\sum _{i=1}^{n}(R_{i}^{2})-3r^{2}n\left(p+1\right)^{2}}{\lambda ^{2}n(n^{2}-1)}}.} 1305: 42: 1536:(in real-world situation, the importance of each rater can be different). Indeed, the weight of judges is 2352:
against a null hypothesis of no agreement (i.e. random rankings) is given by Kendall and Gibbons (1990)
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If the weights of the raters are equal (the distribution of the weights is uniform), the value of
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test performs approximately as well as the permutation test method, and may be preferred to when
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Legendre, P (2005) Species Associations: The Kendall Coefficient of Concordance Revisited.
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th group of tied ranks, (where a group is a set of values having constant (tied) rank,) and
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indicate a greater or lesser degree of unanimity among the various judges or respondents.
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and each pair of objects is presented together to some judge a total of exactly λ times,
3085:"Kendall's coefficient of concordance W – generalized for randomly incomplete datasets" 2963: 2938: 2905: 2793: 2186: 2139: 2119: 1784: 1605: 1492: 1472: 1452: 1432: 1382: 3229: 3161: 3046: 2854: 38: 603: 3038: 2316:{\displaystyle W_{w}={\frac {12S}{(n^{3}-n)-\sum _{j=1}^{m}\vartheta _{j}T_{j}}}} 2921: 2076:{\displaystyle T_{j}=\sum _{i=1}^{n}(t_{ij}^{3}-t_{ij})\;\;\;\;\;\;\;\forall j} 3128: 3107: 68:
indicate a greater or lesser degree of unanimity among the various responses.
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Marozzi, Marco (2014). "Testing for concordance between several criteria".
2947: 41:, and can be used for assessing agreement among raters and in particular 3149:
Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach
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is the number of groups of ties in the set of ranks (ranging from 1 to
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values and compare two sequences of outcomes simultaneously, Kendall's
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In the case of complete ranks, a commonly used significance test for
2969:. Gibbons, Jean Dickinson, 1938- (5th ed.). London: E. Arnold. 2904:
Mahmoudi, Amin; Abbasi, Mehdi; Yuan, Jingfeng; Li, Lingzhi (2022).
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Legendre compared via simulation the power of the chi-square and
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The above formula is suitable when we do not have any tie rank.
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is the correction factor required for the set of ranks for judge
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Journal of Agricultural, Biological and Environmental Statistics
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th set of ranks. Note that if there are no tied ranks for judge
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Where the test statistic takes a chi-squared distribution with
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test, as proposed in the original publication introducing the
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objects, the formula above is equivalent to the original one.
270:{\displaystyle {\bar {R}}={\frac {1}{n}}\sum _{i=1}^{n}R_{i}.} 2447:
In the case of incomplete rankings (see above), this becomes
1771:{\displaystyle {\bar {R}}={\frac {1}{n}}\sum _{i=1}^{n}R_{i}} 3211:(4th ed.). New York: Marcel Dekker. pp. 476–482. 2518:{\displaystyle \chi ^{2}={\frac {\lambda (n^{2}-1)}{k+1}}W} 1018:{\displaystyle T_{j}=\sum _{i=1}^{g_{j}}(t_{i}^{3}-t_{i}),} 3207:
Gibbons, Jean Dickinson; Chakraborti, Subhabrata (2003).
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Kendall, Maurice G. (Maurice George), 1907-1983. (1990).
1692:{\displaystyle R_{i}=\sum _{j=1}^{m}\vartheta _{j}r_{ij}} 56:
can be calculated from these data. If the test statistic
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Rank correlation statistic used for inter-rater agreement
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Kendall's W and Weighted Kendall's W are implemented in
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Where the test statistic follows an F distribution with
365:{\displaystyle S=\sum _{i=1}^{n}(R_{i}-{\bar {R}})^{2},} 49:
ranges from 0 (no agreement) to 1 (complete agreement).
1879:{\displaystyle S=\sum _{i=1}^{n}(R_{i}-{\bar {R}})^{2}} 602:
objects, and when the correspondent block design is a
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approaches to determining significance for Kendall's
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every object is ranked exactly the same total number
620: 528: 493: 388: 293: 207: 131: 3192:(2nd ed.). New York: McGraw-Hill. p. 266. 3190:
Nonparametric Statistics for the Behavioral Sciences
604:(n, m, r, p, λ)-design (note the different notation) 2608:statistic by Kendall & Babington Smith (1939): 2962: 2802: 2778: 2723: 2661: 2592: 2555: 2517: 2436: 2398: 2315: 2195: 2175: 2148: 2128: 2108: 2075: 1957: 1878: 1793: 1770: 1691: 1614: 1594: 1528: 1501: 1481: 1461: 1441: 1421: 1391: 1348: 1280: 1017: 899: 867: 838: 668: 632: 583:{\displaystyle {\bar {r}}_{s}={\frac {mW-1}{m-1}}} 582: 511: 446: 364: 269: 187: 3027:Journal of Statistical Computation and Simulation 598:When the judges evaluate only some subset of the 505: 488: 83:makes no assumptions regarding the nature of the 3106:Kendall, M. G.; Babington Smith, B. (Sep 1939). 2600:. Marozzi extended this by also considering the 2203:. With the correction for ties, the formula for 447:{\displaystyle W={\frac {12S}{m^{2}(n^{3}-n)}}.} 87:and can handle any number of distinct outcomes. 37:. It is a normalization of the statistic of the 3188:Siegel, Sidney; Castellan, N. John Jr. (1988). 2873:Dodge (2003): see "concordance, coefficient of" 1958:{\displaystyle W_{w}={\frac {12S}{(n^{3}-n)}}} 1083:With the correction for ties, the formula for 923:The effect of ties is to reduce the value of 476:is linearly related to the mean value of the 188:{\displaystyle R_{i}=\sum _{j=1}^{m}r_{i,j},} 8: 2997:: CS1 maint: multiple names: authors list ( 2830:, and other statistical software packages. 2810:is small, as it is computationally simpler. 2116:represents the number of tie ranks in judge 1702:and the mean value of these total ranks is, 118:judges. Then the total rank given to object 1595:{\displaystyle \vartheta _{j}(j=1,2,...,m)} 198:and the mean value of these total ranks is 3166:The Oxford Dictionary of Statistical Terms 3001:) CS1 maint: numeric names: authors list ( 2066: 2065: 2064: 2063: 2062: 2061: 2060: 519:possible pairs of rankings between judges 3127: 2937: 2795: 2770: 2742: 2736: 2710: 2683: 2677: 2624: 2616: 2579: 2533: 2483: 2470: 2461: 2455: 2414: 2366: 2360: 2304: 2294: 2284: 2273: 2251: 2233: 2224: 2218: 2188: 2167: 2161: 2141: 2121: 2097: 2091: 2048: 2035: 2027: 2014: 2003: 1990: 1984: 1937: 1919: 1910: 1904: 1870: 1855: 1854: 1845: 1832: 1821: 1809: 1786: 1762: 1752: 1741: 1727: 1713: 1712: 1710: 1680: 1670: 1660: 1649: 1636: 1630: 1607: 1547: 1541: 1520: 1514: 1494: 1474: 1454: 1434: 1410: 1404: 1384: 1337: 1324: 1313: 1307: 1263: 1250: 1239: 1214: 1198: 1186: 1161: 1142: 1137: 1124: 1113: 1103: 1095: 1003: 990: 985: 970: 965: 954: 941: 935: 880: 854: 815: 799: 787: 758: 739: 734: 721: 710: 700: 692: 655: 619: 551: 542: 531: 530: 527: 504: 498: 487: 485: 423: 410: 395: 387: 353: 338: 337: 328: 315: 304: 292: 258: 248: 237: 223: 209: 208: 206: 170: 160: 149: 136: 130: 2183:shows the total number of ties in judge 478:Spearman's rank correlation coefficients 3089:The R Project for Statistical Computing 2866: 2850:Spearman's rank correlation coefficient 2662:{\displaystyle F={\frac {W(m-1)}{1-W}}} 1602:. Then, the total rank given to object 2990: 2786:degrees of freedom. Marozzi found the 1349:{\displaystyle \sum _{j=1}^{m}(T_{j})} 3116:The Annals of Mathematical Statistics 2891:Siegel & Castellan (1988, p. 266) 472:Kendall and Gibbons (1990) also show 7: 3147:Corder, G.W., Foreman, D.I. (2009). 2899: 2897: 1379:should be used. Suppose that object 27:Kendall's coefficient of concordance 3209:Nonparametric Statistical Inference 1298:is the sum of the ranks for object 1035:is the number of tied ranks in the 2067: 1489:judges. Also, the weight of judge 492: 14: 2399:{\displaystyle \chi ^{2}=m(n-1)W} 610:each judge ranks the same number 2882:Gibbons & Chakraborti (2003) 2779:{\displaystyle v_{2}=(m-1)v_{1}} 2724:{\displaystyle v_{1}=n-1-(2/m)} 1781:The sum of squared deviations, 280:The sum of squared deviations, 73:Pearson correlation coefficient 71:While tests using the standard 2763: 2751: 2718: 2704: 2642: 2630: 2495: 2476: 2390: 2378: 2263: 2244: 2057: 2020: 1949: 1930: 1867: 1860: 1838: 1718: 1589: 1553: 1529:{\displaystyle \vartheta _{j}} 1343: 1330: 1269: 1256: 1226: 1207: 1183: 1170: 1148: 1130: 1009: 978: 827: 808: 745: 727: 669:{\displaystyle \lambda \geq 1} 536: 435: 416: 350: 343: 321: 214: 1: 1371:Steps of Weighted Kendall's W 907:so that each judge ranks all 512:{\displaystyle m \choose {2}} 3039:10.1080/00949655.2013.766189 1356:is the sum of the values of 900:{\displaystyle \lambda =r=m} 1449:, where there are in total 676:, a constant for all pairs. 110:, where there are in total 3262: 2922:10.1007/s10489-022-04094-y 3241:Nonparametric statistics 3182:, 10(2), 226–245. 2965:Rank correlation methods 920:follows: {5,3,1,5,2,5}. 85:probability distribution 31:non-parametric statistic 3236:Inter-rater reliability 3129:10.1214/aoms/1177732186 2593:{\displaystyle m<20} 2528:Where again, there are 606:. In other words, when 43:inter-rater reliability 3061:"Weighted Kendall's W" 2804: 2780: 2725: 2663: 2594: 2557: 2556:{\displaystyle df=n-1} 2519: 2438: 2437:{\displaystyle df=n-1} 2400: 2317: 2289: 2197: 2177: 2150: 2130: 2110: 2109:{\displaystyle t_{ij}} 2077: 2019: 1959: 1880: 1837: 1795: 1772: 1757: 1693: 1665: 1616: 1596: 1530: 1503: 1483: 1463: 1443: 1423: 1422:{\displaystyle r_{ij}} 1393: 1350: 1329: 1282: 1255: 1129: 1019: 977: 901: 869: 840: 726: 670: 634: 633:{\displaystyle p<n} 584: 513: 457:If the test statistic 448: 366: 320: 271: 253: 189: 165: 2805: 2781: 2726: 2664: 2595: 2558: 2520: 2439: 2401: 2318: 2269: 2198: 2178: 2176:{\displaystyle T_{j}} 2151: 2131: 2111: 2078: 1999: 1960: 1881: 1817: 1796: 1773: 1737: 1694: 1645: 1617: 1597: 1531: 1504: 1484: 1464: 1444: 1424: 1394: 1351: 1309: 1283: 1235: 1109: 1020: 950: 902: 870: 841: 706: 671: 635: 585: 514: 449: 367: 300: 272: 233: 190: 145: 2910:Applied Intelligence 2794: 2735: 2676: 2615: 2578: 2563:degrees of freedom. 2532: 2454: 2444:degrees of freedom. 2413: 2359: 2217: 2187: 2160: 2140: 2120: 2090: 1983: 1903: 1808: 1785: 1709: 1629: 1606: 1540: 1513: 1493: 1473: 1453: 1433: 1403: 1383: 1377:Weighted Kendall's W 1306: 1094: 934: 879: 853: 691: 654: 618: 614:of objects for some 526: 484: 386: 291: 205: 129: 95:Suppose that object 91:Steps of Kendall's W 77:normally distributed 2916:(12): 13781–13802. 2568:permutation testing 2328:Weighted Kendall's 2205:Weighted Kendall's 2040: 1972:Correction for Ties 1891:Weighted Kendall's 1147: 995: 915:Correction for Ties 868:{\displaystyle p=n} 744: 375:and then Kendall's 2800: 2776: 2721: 2659: 2590: 2553: 2515: 2434: 2396: 2344:Significance Tests 2313: 2193: 2173: 2146: 2126: 2106: 2073: 2023: 1955: 1876: 1791: 1768: 1689: 1612: 1592: 1526: 1499: 1479: 1459: 1439: 1419: 1399:is given the rank 1389: 1346: 1278: 1133: 1015: 981: 897: 865: 836: 730: 666: 630: 580: 497: 444: 362: 267: 185: 99:is given the rank 3218:978-0-8247-4052-8 3199:978-0-07-057357-4 3157:978-0-470-45461-9 3065:www.mathworks.com 2803:{\displaystyle m} 2657: 2510: 2311: 2196:{\displaystyle j} 2149:{\displaystyle i} 2129:{\displaystyle j} 1953: 1863: 1801:, is defined as, 1794:{\displaystyle S} 1735: 1721: 1615:{\displaystyle i} 1502:{\displaystyle j} 1482:{\displaystyle m} 1462:{\displaystyle n} 1442:{\displaystyle j} 1392:{\displaystyle i} 1370: 1273: 831: 594:Incomplete Blocks 578: 539: 503: 439: 346: 231: 217: 90: 3253: 3222: 3203: 3141: 3131: 3108:"The Problem of 3093: 3092: 3081: 3075: 3074: 3072: 3071: 3057: 3051: 3050: 3033:(9): 1843–1850. 3022: 3016: 3013: 3007: 3006: 2996: 2988: 2968: 2958: 2952: 2951: 2941: 2901: 2892: 2889: 2883: 2880: 2874: 2871: 2809: 2807: 2806: 2801: 2785: 2783: 2782: 2777: 2775: 2774: 2747: 2746: 2730: 2728: 2727: 2722: 2714: 2688: 2687: 2668: 2666: 2665: 2660: 2658: 2656: 2645: 2625: 2599: 2597: 2596: 2591: 2562: 2560: 2559: 2554: 2524: 2522: 2521: 2516: 2511: 2509: 2498: 2488: 2487: 2471: 2466: 2465: 2443: 2441: 2440: 2435: 2405: 2403: 2402: 2397: 2371: 2370: 2322: 2320: 2319: 2314: 2312: 2310: 2309: 2308: 2299: 2298: 2288: 2283: 2256: 2255: 2242: 2234: 2229: 2228: 2202: 2200: 2199: 2194: 2182: 2180: 2179: 2174: 2172: 2171: 2155: 2153: 2152: 2147: 2135: 2133: 2132: 2127: 2115: 2113: 2112: 2107: 2105: 2104: 2082: 2080: 2079: 2074: 2056: 2055: 2039: 2034: 2018: 2013: 1995: 1994: 1964: 1962: 1961: 1956: 1954: 1952: 1942: 1941: 1928: 1920: 1915: 1914: 1885: 1883: 1882: 1877: 1875: 1874: 1865: 1864: 1856: 1850: 1849: 1836: 1831: 1800: 1798: 1797: 1792: 1777: 1775: 1774: 1769: 1767: 1766: 1756: 1751: 1736: 1728: 1723: 1722: 1714: 1698: 1696: 1695: 1690: 1688: 1687: 1675: 1674: 1664: 1659: 1641: 1640: 1621: 1619: 1618: 1613: 1601: 1599: 1598: 1593: 1552: 1551: 1535: 1533: 1532: 1527: 1525: 1524: 1508: 1506: 1505: 1500: 1488: 1486: 1485: 1480: 1468: 1466: 1465: 1460: 1448: 1446: 1445: 1440: 1429:by judge number 1428: 1426: 1425: 1420: 1418: 1417: 1398: 1396: 1395: 1390: 1355: 1353: 1352: 1347: 1342: 1341: 1328: 1323: 1287: 1285: 1284: 1279: 1274: 1272: 1268: 1267: 1254: 1249: 1219: 1218: 1203: 1202: 1192: 1191: 1190: 1166: 1165: 1146: 1141: 1128: 1123: 1104: 1024: 1022: 1021: 1016: 1008: 1007: 994: 989: 976: 975: 974: 964: 946: 945: 906: 904: 903: 898: 874: 872: 871: 866: 845: 843: 842: 837: 832: 830: 820: 819: 804: 803: 793: 792: 791: 786: 782: 763: 762: 743: 738: 725: 720: 701: 675: 673: 672: 667: 639: 637: 636: 631: 589: 587: 586: 581: 579: 577: 566: 552: 547: 546: 541: 540: 532: 518: 516: 515: 510: 509: 508: 502: 491: 453: 451: 450: 445: 440: 438: 428: 427: 415: 414: 404: 396: 371: 369: 368: 363: 358: 357: 348: 347: 339: 333: 332: 319: 314: 284:, is defined as 276: 274: 273: 268: 263: 262: 252: 247: 232: 224: 219: 218: 210: 194: 192: 191: 186: 181: 180: 164: 159: 141: 140: 106:by judge number 35:rank correlation 3261: 3260: 3256: 3255: 3254: 3252: 3251: 3250: 3226: 3225: 3219: 3206: 3200: 3187: 3105: 3102: 3097: 3096: 3083: 3082: 3078: 3069: 3067: 3059: 3058: 3054: 3024: 3023: 3019: 3015:Legendre (2005) 3014: 3010: 2989: 2977: 2960: 2959: 2955: 2903: 2902: 2895: 2890: 2886: 2881: 2877: 2872: 2868: 2863: 2840:Maurice Kendall 2836: 2816: 2792: 2791: 2766: 2738: 2733: 2732: 2679: 2674: 2673: 2646: 2626: 2613: 2612: 2576: 2575: 2530: 2529: 2499: 2479: 2472: 2457: 2452: 2451: 2411: 2410: 2362: 2357: 2356: 2346: 2300: 2290: 2247: 2243: 2235: 2220: 2215: 2214: 2185: 2184: 2163: 2158: 2157: 2138: 2137: 2118: 2117: 2093: 2088: 2087: 2044: 1986: 1981: 1980: 1974: 1933: 1929: 1921: 1906: 1901: 1900: 1896:is defined as, 1866: 1841: 1806: 1805: 1783: 1782: 1758: 1707: 1706: 1676: 1666: 1632: 1627: 1626: 1604: 1603: 1543: 1538: 1537: 1516: 1511: 1510: 1491: 1490: 1471: 1470: 1451: 1450: 1431: 1430: 1406: 1401: 1400: 1381: 1380: 1373: 1367:sets of ranks. 1361: 1333: 1304: 1303: 1296: 1259: 1210: 1194: 1193: 1182: 1157: 1105: 1092: 1091: 1078: 1059: 1044: 1033: 999: 966: 937: 932: 931: 917: 877: 876: 851: 850: 811: 795: 794: 772: 768: 767: 754: 702: 689: 688: 684:is defined as 680:Then Kendall's 652: 651: 616: 615: 596: 567: 553: 529: 524: 523: 486: 482: 481: 419: 406: 405: 397: 384: 383: 349: 324: 289: 288: 254: 203: 202: 166: 132: 127: 126: 104: 93: 25:(also known as 17: 12: 11: 5: 3259: 3257: 3249: 3248: 3243: 3238: 3228: 3227: 3224: 3223: 3217: 3204: 3198: 3185: 3176: 3159: 3145: 3142: 3122:(3): 275–287. 3101: 3098: 3095: 3094: 3076: 3052: 3017: 3008: 2975: 2953: 2893: 2884: 2875: 2865: 2864: 2862: 2859: 2858: 2857: 2852: 2847: 2842: 2835: 2832: 2815: 2812: 2799: 2773: 2769: 2765: 2762: 2759: 2756: 2753: 2750: 2745: 2741: 2720: 2717: 2713: 2709: 2706: 2703: 2700: 2697: 2694: 2691: 2686: 2682: 2670: 2669: 2655: 2652: 2649: 2644: 2641: 2638: 2635: 2632: 2629: 2623: 2620: 2589: 2586: 2583: 2552: 2549: 2546: 2543: 2540: 2537: 2526: 2525: 2514: 2508: 2505: 2502: 2497: 2494: 2491: 2486: 2482: 2478: 2475: 2469: 2464: 2460: 2433: 2430: 2427: 2424: 2421: 2418: 2407: 2406: 2395: 2392: 2389: 2386: 2383: 2380: 2377: 2374: 2369: 2365: 2345: 2342: 2324: 2323: 2307: 2303: 2297: 2293: 2287: 2282: 2279: 2276: 2272: 2268: 2265: 2262: 2259: 2254: 2250: 2246: 2241: 2238: 2232: 2227: 2223: 2192: 2170: 2166: 2145: 2125: 2103: 2100: 2096: 2084: 2083: 2072: 2069: 2059: 2054: 2051: 2047: 2043: 2038: 2033: 2030: 2026: 2022: 2017: 2012: 2009: 2006: 2002: 1998: 1993: 1989: 1973: 1970: 1966: 1965: 1951: 1948: 1945: 1940: 1936: 1932: 1927: 1924: 1918: 1913: 1909: 1887: 1886: 1873: 1869: 1862: 1859: 1853: 1848: 1844: 1840: 1835: 1830: 1827: 1824: 1820: 1816: 1813: 1790: 1779: 1778: 1765: 1761: 1755: 1750: 1747: 1744: 1740: 1734: 1731: 1726: 1720: 1717: 1700: 1699: 1686: 1683: 1679: 1673: 1669: 1663: 1658: 1655: 1652: 1648: 1644: 1639: 1635: 1611: 1591: 1588: 1585: 1582: 1579: 1576: 1573: 1570: 1567: 1564: 1561: 1558: 1555: 1550: 1546: 1523: 1519: 1498: 1478: 1458: 1438: 1416: 1413: 1409: 1388: 1372: 1369: 1359: 1345: 1340: 1336: 1332: 1327: 1322: 1319: 1316: 1312: 1294: 1289: 1288: 1277: 1271: 1266: 1262: 1258: 1253: 1248: 1245: 1242: 1238: 1234: 1231: 1228: 1225: 1222: 1217: 1213: 1209: 1206: 1201: 1197: 1189: 1185: 1181: 1178: 1175: 1172: 1169: 1164: 1160: 1156: 1153: 1150: 1145: 1140: 1136: 1132: 1127: 1122: 1119: 1116: 1112: 1108: 1102: 1099: 1076: 1057: 1042: 1031: 1026: 1025: 1014: 1011: 1006: 1002: 998: 993: 988: 984: 980: 973: 969: 963: 960: 957: 953: 949: 944: 940: 916: 913: 896: 893: 890: 887: 884: 864: 861: 858: 847: 846: 835: 829: 826: 823: 818: 814: 810: 807: 802: 798: 790: 785: 781: 778: 775: 771: 766: 761: 757: 753: 750: 747: 742: 737: 733: 729: 724: 719: 716: 713: 709: 705: 699: 696: 678: 677: 665: 662: 659: 648: 641: 629: 626: 623: 595: 592: 591: 590: 576: 573: 570: 565: 562: 559: 556: 550: 545: 538: 535: 507: 501: 496: 490: 455: 454: 443: 437: 434: 431: 426: 422: 418: 413: 409: 403: 400: 394: 391: 379:is defined as 373: 372: 361: 356: 352: 345: 342: 336: 331: 327: 323: 318: 313: 310: 307: 303: 299: 296: 278: 277: 266: 261: 257: 251: 246: 243: 240: 236: 230: 227: 222: 216: 213: 196: 195: 184: 179: 176: 173: 169: 163: 158: 155: 152: 148: 144: 139: 135: 102: 92: 89: 15: 13: 10: 9: 6: 4: 3: 2: 3258: 3247: 3244: 3242: 3239: 3237: 3234: 3233: 3231: 3220: 3214: 3210: 3205: 3201: 3195: 3191: 3186: 3184: 3181: 3177: 3175: 3174:0-19-920613-9 3171: 3167: 3163: 3160: 3158: 3154: 3150: 3146: 3143: 3139: 3135: 3130: 3125: 3121: 3117: 3113: 3111: 3104: 3103: 3099: 3090: 3086: 3080: 3077: 3066: 3062: 3056: 3053: 3048: 3044: 3040: 3036: 3032: 3028: 3021: 3018: 3012: 3009: 3004: 3000: 2994: 2986: 2982: 2978: 2976:0-19-520837-4 2972: 2967: 2966: 2957: 2954: 2949: 2945: 2940: 2935: 2931: 2927: 2923: 2919: 2915: 2911: 2907: 2900: 2898: 2894: 2888: 2885: 2879: 2876: 2870: 2867: 2860: 2856: 2855:Friedman test 2853: 2851: 2848: 2846: 2845:Kendall's tau 2843: 2841: 2838: 2837: 2833: 2831: 2829: 2825: 2821: 2813: 2811: 2797: 2789: 2771: 2767: 2760: 2757: 2754: 2748: 2743: 2739: 2715: 2711: 2707: 2701: 2698: 2695: 2692: 2689: 2684: 2680: 2653: 2650: 2647: 2639: 2636: 2633: 2627: 2621: 2618: 2611: 2610: 2609: 2607: 2603: 2587: 2584: 2581: 2573: 2569: 2564: 2550: 2547: 2544: 2541: 2538: 2535: 2512: 2506: 2503: 2500: 2492: 2489: 2484: 2480: 2473: 2467: 2462: 2458: 2450: 2449: 2448: 2445: 2431: 2428: 2425: 2422: 2419: 2416: 2393: 2387: 2384: 2381: 2375: 2372: 2367: 2363: 2355: 2354: 2353: 2351: 2343: 2341: 2339: 2338: 2332: 2331: 2305: 2301: 2295: 2291: 2285: 2280: 2277: 2274: 2270: 2266: 2260: 2257: 2252: 2248: 2239: 2236: 2230: 2225: 2221: 2213: 2212: 2211: 2209: 2208: 2190: 2168: 2164: 2143: 2123: 2101: 2098: 2094: 2070: 2052: 2049: 2045: 2041: 2036: 2031: 2028: 2024: 2015: 2010: 2007: 2004: 2000: 1996: 1991: 1987: 1979: 1978: 1977: 1971: 1969: 1946: 1943: 1938: 1934: 1925: 1922: 1916: 1911: 1907: 1899: 1898: 1897: 1895: 1894: 1871: 1857: 1851: 1846: 1842: 1833: 1828: 1825: 1822: 1818: 1814: 1811: 1804: 1803: 1802: 1788: 1763: 1759: 1753: 1748: 1745: 1742: 1738: 1732: 1729: 1724: 1715: 1705: 1704: 1703: 1684: 1681: 1677: 1671: 1667: 1661: 1656: 1653: 1650: 1646: 1642: 1637: 1633: 1625: 1624: 1623: 1609: 1586: 1583: 1580: 1577: 1574: 1571: 1568: 1565: 1562: 1559: 1556: 1548: 1544: 1521: 1517: 1496: 1476: 1456: 1436: 1414: 1411: 1407: 1386: 1378: 1368: 1366: 1362: 1338: 1334: 1325: 1320: 1317: 1314: 1310: 1301: 1297: 1275: 1264: 1260: 1251: 1246: 1243: 1240: 1236: 1232: 1229: 1223: 1220: 1215: 1211: 1204: 1199: 1195: 1187: 1179: 1176: 1173: 1167: 1162: 1158: 1154: 1151: 1143: 1138: 1134: 1125: 1120: 1117: 1114: 1110: 1106: 1100: 1097: 1090: 1089: 1088: 1086: 1081: 1079: 1072: 1068: 1064: 1060: 1053: 1049: 1045: 1038: 1034: 1012: 1004: 1000: 996: 991: 986: 982: 971: 967: 961: 958: 955: 951: 947: 942: 938: 930: 929: 928: 926: 921: 914: 912: 910: 894: 891: 888: 885: 882: 862: 859: 856: 833: 824: 821: 816: 812: 805: 800: 796: 788: 783: 779: 776: 773: 769: 764: 759: 755: 751: 748: 740: 735: 731: 722: 717: 714: 711: 707: 703: 697: 694: 687: 686: 685: 683: 663: 660: 657: 649: 646: 642: 627: 624: 621: 613: 609: 608: 607: 605: 601: 593: 574: 571: 568: 563: 560: 557: 554: 548: 543: 533: 522: 521: 520: 499: 494: 479: 475: 470: 468: 464: 460: 441: 432: 429: 424: 420: 411: 407: 401: 398: 392: 389: 382: 381: 380: 378: 359: 354: 340: 334: 329: 325: 316: 311: 308: 305: 301: 297: 294: 287: 286: 285: 283: 264: 259: 255: 249: 244: 241: 238: 234: 228: 225: 220: 211: 201: 200: 199: 182: 177: 174: 171: 167: 161: 156: 153: 150: 146: 142: 137: 133: 125: 124: 123: 121: 117: 113: 109: 105: 98: 88: 86: 82: 78: 74: 69: 67: 63: 59: 55: 50: 48: 44: 40: 39:Friedman test 36: 32: 28: 24: 23: 3208: 3189: 3179: 3165: 3148: 3119: 3115: 3109: 3088: 3079: 3068:. Retrieved 3064: 3055: 3030: 3026: 3020: 3011: 2964: 2956: 2913: 2909: 2887: 2878: 2869: 2817: 2787: 2671: 2605: 2601: 2571: 2565: 2527: 2446: 2408: 2349: 2347: 2336: 2334: 2329: 2327: 2325: 2206: 2204: 2085: 1975: 1967: 1892: 1890: 1888: 1780: 1701: 1509:is shown by 1469:objects and 1376: 1374: 1364: 1357: 1299: 1292: 1290: 1084: 1082: 1074: 1070: 1066: 1062: 1055: 1051: 1050:) for judge 1047: 1040: 1036: 1029: 1027: 924: 922: 918: 908: 848: 681: 679: 644: 611: 599: 597: 480:between all 473: 471: 466: 462: 458: 456: 376: 374: 281: 279: 197: 119: 115: 114:objects and 111: 107: 100: 96: 94: 80: 70: 65: 61: 57: 53: 51: 46: 45:. Kendall's 26: 21: 19: 18: 2340:are equal. 2136:for object 1065:, i.e. the 3230:Categories 3100:References 3070:2022-10-06 2335:Kendall's 2210:becomes, 1080:equals 0. 20:Kendall's 3162:Dodge, Y. 3112:Rankings" 3047:119577430 2993:cite book 2930:1573-7497 2758:− 2702:− 2696:− 2651:− 2637:− 2548:− 2490:− 2474:λ 2459:χ 2429:− 2385:− 2364:χ 2292:ϑ 2271:∑ 2267:− 2258:− 2068:∀ 2042:− 2001:∑ 1944:− 1889:and then 1861:¯ 1852:− 1819:∑ 1739:∑ 1719:¯ 1668:ϑ 1647:∑ 1545:ϑ 1518:ϑ 1363:over all 1311:∑ 1237:∑ 1230:− 1221:− 1152:− 1111:∑ 997:− 952:∑ 883:λ 822:− 797:λ 749:− 708:∑ 661:≥ 658:λ 647:of times, 572:− 561:− 537:¯ 430:− 344:¯ 335:− 302:∑ 235:∑ 215:¯ 147:∑ 3246:Rankings 3164:(2003). 2985:21195423 2948:36091930 2834:See also 2814:Software 1087:becomes 1054:. Thus, 3168:, OUP. 3151:Wiley, 3138:2235668 2939:9449288 75:assume 29:) is a 3215:  3196:  3172:  3155:  3136:  3045:  2983:  2973:  2946:  2936:  2928:  2820:MATLAB 2086:where 1302:, and 1291:where 1028:where 3134:JSTOR 3043:S2CID 2861:Notes 3213:ISBN 3194:ISBN 3170:ISBN 3153:ISBN 3003:link 2999:link 2981:OCLC 2971:ISBN 2944:PMID 2926:ISSN 2824:SPSS 2731:and 2585:< 2333:and 875:and 625:< 33:for 3124:doi 3035:doi 2934:PMC 2918:doi 1622:is 849:If 122:is 103:i,j 3232:: 3132:. 3120:10 3118:. 3114:. 3087:. 3063:. 3041:. 3031:84 3029:. 2995:}} 2991:{{ 2979:. 2942:. 2932:. 2924:. 2914:52 2912:. 2908:. 2896:^ 2826:, 2822:, 2588:20 2237:12 2156:. 1923:12 1107:12 1073:, 704:12 399:12 3221:. 3202:. 3140:. 3126:: 3110:m 3091:. 3073:. 3049:. 3037:: 3005:) 2987:. 2950:. 2920:: 2828:R 2798:m 2788:F 2772:1 2768:v 2764:) 2761:1 2755:m 2752:( 2749:= 2744:2 2740:v 2719:) 2716:m 2712:/ 2708:2 2705:( 2699:1 2693:n 2690:= 2685:1 2681:v 2654:W 2648:1 2643:) 2640:1 2634:m 2631:( 2628:W 2622:= 2619:F 2606:W 2602:F 2582:m 2572:W 2551:1 2545:n 2542:= 2539:f 2536:d 2513:W 2507:1 2504:+ 2501:k 2496:) 2493:1 2485:2 2481:n 2477:( 2468:= 2463:2 2432:1 2426:n 2423:= 2420:f 2417:d 2394:W 2391:) 2388:1 2382:n 2379:( 2376:m 2373:= 2368:2 2350:W 2337:W 2330:W 2306:j 2302:T 2296:j 2286:m 2281:1 2278:= 2275:j 2264:) 2261:n 2253:3 2249:n 2245:( 2240:S 2231:= 2226:w 2222:W 2207:W 2191:j 2169:j 2165:T 2144:i 2124:j 2102:j 2099:i 2095:t 2071:j 2058:) 2053:j 2050:i 2046:t 2037:3 2032:j 2029:i 2025:t 2021:( 2016:n 2011:1 2008:= 2005:i 1997:= 1992:j 1988:T 1950:) 1947:n 1939:3 1935:n 1931:( 1926:S 1917:= 1912:w 1908:W 1893:W 1872:2 1868:) 1858:R 1847:i 1843:R 1839:( 1834:n 1829:1 1826:= 1823:i 1815:= 1812:S 1789:S 1764:i 1760:R 1754:n 1749:1 1746:= 1743:i 1733:n 1730:1 1725:= 1716:R 1685:j 1682:i 1678:r 1672:j 1662:m 1657:1 1654:= 1651:j 1643:= 1638:i 1634:R 1610:i 1590:) 1587:m 1584:, 1581:. 1578:. 1575:. 1572:, 1569:2 1566:, 1563:1 1560:= 1557:j 1554:( 1549:j 1522:j 1497:j 1477:m 1457:n 1437:j 1415:j 1412:i 1408:r 1387:i 1365:m 1360:j 1358:T 1344:) 1339:j 1335:T 1331:( 1326:m 1321:1 1318:= 1315:j 1300:i 1295:i 1293:R 1276:, 1270:) 1265:j 1261:T 1257:( 1252:m 1247:1 1244:= 1241:j 1233:m 1227:) 1224:1 1216:2 1212:n 1208:( 1205:n 1200:2 1196:m 1188:2 1184:) 1180:1 1177:+ 1174:n 1171:( 1168:n 1163:2 1159:m 1155:3 1149:) 1144:2 1139:i 1135:R 1131:( 1126:n 1121:1 1118:= 1115:i 1101:= 1098:W 1085:W 1077:j 1075:T 1071:j 1067:j 1063:j 1058:j 1056:T 1052:j 1048:n 1043:j 1041:g 1037:i 1032:i 1030:t 1013:, 1010:) 1005:i 1001:t 992:3 987:i 983:t 979:( 972:j 968:g 962:1 959:= 956:i 948:= 943:j 939:T 925:W 909:n 895:m 892:= 889:r 886:= 863:n 860:= 857:p 834:. 828:) 825:1 817:2 813:n 809:( 806:n 801:2 789:2 784:) 780:1 777:+ 774:p 770:( 765:n 760:2 756:r 752:3 746:) 741:2 736:i 732:R 728:( 723:n 718:1 715:= 712:i 698:= 695:W 682:W 664:1 645:r 640:, 628:n 622:p 612:p 600:n 575:1 569:m 564:1 558:W 555:m 549:= 544:s 534:r 506:) 500:2 495:m 489:( 474:W 467:W 463:W 459:W 442:. 436:) 433:n 425:3 421:n 417:( 412:2 408:m 402:S 393:= 390:W 377:W 360:, 355:2 351:) 341:R 330:i 326:R 322:( 317:n 312:1 309:= 306:i 298:= 295:S 282:S 265:. 260:i 256:R 250:n 245:1 242:= 239:i 229:n 226:1 221:= 212:R 183:, 178:j 175:, 172:i 168:r 162:m 157:1 154:= 151:j 143:= 138:i 134:R 120:i 116:m 112:n 108:j 101:r 97:i 81:W 66:W 62:W 58:W 54:W 47:W 22:W

Index

non-parametric statistic
rank correlation
Friedman test
inter-rater reliability
Pearson correlation coefficient
normally distributed
probability distribution
Spearman's rank correlation coefficients
(n, m, r, p, λ)-design (note the different notation)
permutation testing
MATLAB
SPSS
R
Maurice Kendall
Kendall's tau
Spearman's rank correlation coefficient
Friedman test


"Large-scale group decision-making (LSGDM) for performance measurement of healthcare construction projects: Ordinal Priority Approach"
doi
10.1007/s10489-022-04094-y
ISSN
1573-7497
PMC
9449288
PMID
36091930
Rank correlation methods
ISBN

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