{"id":516,"date":"2018-08-14T14:09:51","date_gmt":"2018-08-14T05:09:51","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/multiple-comparison-of-proportion-with-bonferroni-type-p-value-adjustment-in-r\/"},"modified":"2024-10-13T19:30:10","modified_gmt":"2024-10-13T10:30:10","slug":"multiple-comparison-of-proportion-with-bonferroni-type-p-value-adjustment-in-r","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/multiple-comparison-of-proportion-with-bonferroni-type-p-value-adjustment-in-r\/","title":{"rendered":"R \u3067\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u30fb\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a \u3067 3 \u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"\n

\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u3001\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u306e3\u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03\u3092R\u3067\u5b9f\u65bd\u3059\u308b\u65b9\u6cd5\u306e\u89e3\u8aac\u3002<\/p>\n\n\n\n\n\n\n\n

\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u306e3\u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03<\/h2>\n\n\n\n

\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5272\u5408\u306e\u6bd4\u8f03\u306f\u3069\u3046\u3084\u308c\u3070\u3044\u3044\u306e\u304b\uff1f<\/p>\n\n\n\n

Bonferroni\u578b\u306ep\u5024\u8abf\u6574\u3092\u4f7f\u3046\u65b9\u6cd5\u304c\u3042\u308b\u3002<\/p>\n\n\n

\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\u3042\u308f\u305b\u3066\u8aad\u307f\u305f\u3044<\/span>\n\t\t\t\t\t
\"\"<\/figure><\/div>\t\t\t\t\t
\n\t\t\t\t\t\tR \u3067\u30dc\u30f3\u30d5\u30a7\u30ed\u30fc\u30cb\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a>\n\t\t\t\t\t\t\u691c\u8a3c\u8a66\u9a13\u306b\u304a\u3044\u3066\u3001\u4e09\u7fa4\u4ee5\u4e0a\u306e\u5e73\u5747\u5024\u3092\u6bd4\u8f03\u3057\u305f\u3044\u3068\u304d\u306b\u3001\u5358\u7d14\u306b\u4e8c\u7fa4\u6bd4\u8f03\u3092\u7e70\u308a\u8fd4\u3059\u3068\u6709\u610f\u6c34\u6e96\u304c\u7518\u304f\u306a\u308b\u3002 \u6709\u610f\u6c34\u6e96\u306e\u8abf\u6574\u306b\u3088\u3063\u3066\u7c21\u5358\u306b\u51e6\u7406\u3059\u308b\u65b9\u6cd5\u304c\u30dc\u30f3\u30d5\u30a7\u30ed\u30fc\u30cb…<\/span>\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\n\n\n\n\n\n

R\u3067\u884c\u3046\u5834\u5408\u3001pairwise.prop.test()\u3068\u3044\u3046\u95a2\u6570\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n

\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u30003\u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03\u3067\u591a\u91cd\u8abf\u6574\u3057\u306a\u3044\u5834\u5408<\/h3>\n\n\n\n

\u4f8b\u3068\u3057\u3066\u4e0b\u8a18\u306e2×3\u306e\u5206\u5272\u8868\u306e\u30c7\u30fc\u30bf\u3067\u3084\u3063\u3066\u307f\u308b\u3002<\/p>\n\n\n\n

<\/th>Group1<\/th>Group2<\/th>Group3<\/th><\/tr><\/thead>
No<\/td>49 (100%)<\/td>97 (96%)<\/td>63 (86%)<\/td><\/tr>
Yes<\/td>0 (0%)<\/td>4 (4%)<\/td>10 (14%)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u30d1\u30fc\u30bb\u30f3\u30c8\u306f\u5217\u30d1\u30fc\u30bb\u30f3\u30c8\u3092\u8a18\u3057\u3066\u3044\u308b\u3002<\/p>\n\n\n\n

\u5206\u5272\u8868\u4f5c\u6210\u3068\u691c\u5b9a\u306e\u305f\u3081\u306eR\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3002<\/p>\n\n\n\n

tab <-<\/span> matrix<\/span>(<\/span>c<\/span>(<\/span>49<\/span>,<\/span>0<\/span>,<\/span>97<\/span>,<\/span>4<\/span>,<\/span>63<\/span>,<\/span>10<\/span>),<\/span>nr=<\/span>2<\/span>)<\/span>\ndimnames<\/span>(<\/span>tab)<\/span> <-<\/span> list<\/span>(<\/span>c<\/span>(<\/span>\"No\"<\/span>,<\/span>\"Yes\"<\/span>),<\/span>c<\/span>(<\/span>paste<\/span>(<\/span>\"Group\"<\/span>,<\/span>1<\/span>:<\/span>3<\/span>,<\/span>sep=<\/span>\"\"<\/span>)))<\/span>\ntab\nround<\/span>(<\/span>prop.table<\/span>(<\/span>tab,<\/span> 2<\/span>),<\/span>2<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
><\/span> tab\n    Group1 Group2 Group3\nNo      49<\/span>     97<\/span>     63<\/span>\nYes      0<\/span>      4<\/span>     10<\/span>\n><\/span>\n><\/span> round<\/span>(<\/span>prop.table<\/span>(<\/span>tab,<\/span> 2<\/span>),<\/span>2<\/span>)<\/span>\n    Group1 Group2 Group3\nNo       1<\/span>   0.96<\/span>   0.86<\/span>\nYes      0<\/span>   0.04<\/span>   0.14<\/span>\n<\/code><\/pre>\n\n\n\n
\u591a\u91cd\u6bd4\u8f03\u306e\u7d50\u679c\u3001Group1\u30683\u3001Group2\u30683\u304c\u305d\u308c\u305e\u308c0.05\u3092\u4e0b\u56de\u3063\u3066\u3001\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306b\u7570\u306a\u308b\u3088\u3046\u306b\u898b\u3048\u308b\u3002<\/p>\n\n\n\n
><\/span> pairwise.prop.test<\/span>(<\/span>t<\/span>(<\/span>tab),<\/span> p.adj=<\/span>\"none\"<\/span>)<\/span>\nPairwise comparisons using Pairwise comparison of proportions\ndata:<\/span>  t<\/span>(<\/span>tab)<\/span>\nGroup1 Group2\nGroup2 0.383<\/span>  -<\/span>\nGroup3 0.018<\/span>  0.041<\/span>\nP value adjustment method:<\/span> none\nWarning messages:<\/span>\n1<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n2<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n<\/code><\/pre>\n\n\n\n
\u4f8b\u984c\u306f\u671f\u5f85\u5024\u304c5\u4ee5\u4e0b\u306e\u30de\u30b9\u76ee\u304c20%\u4ee5\u4e0a\u306a\u306e\u3067\u3001$ \\chi^2 $ \u691c\u5b9a\u304c\u4e0d\u9069\u5207\u3067\u3042\u308b\u30e1\u30c3\u30bb\u30fc\u30b8\u304c\u51fa\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
$ \\chi^2 $ \u691c\u5b9a\u304c\u4e0d\u9069\u5207\u306a\u5834\u5408\u306f\u3001\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\uff08\u5f8c\u8ff0\uff09\u3092\u884c\u3046\u3002<\/p>\n\n\n\n
\u4ee5\u4e0b\u306f\u3001\u671f\u5f85\u5024\u3092\u8a08\u7b97\u3057\u305f\u5206\u5272\u8868\u3002<\/p>\n\n\n\n
<\/th>Group1<\/th>Group2<\/th>Group3<\/th>Total<\/th><\/tr><\/thead>
No<\/td>45.9<\/td>97.4<\/td>68.4<\/td>209<\/td><\/tr>
Yes<\/td>3.1<\/span><\/td>6.3<\/td>4.6<\/span><\/td>14<\/td><\/tr>
Total<\/td>49<\/td>101<\/td>73<\/td>223<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\u8d64\u3067\u793a\u3057\u305f\u4e8c\u3064\u306e\u30bb\u30eb\u304c\u671f\u5f85\u50245\u672a\u6e80\u3060\u3002<\/p>\n\n\n\n
\u3069\u306e\u30b0\u30eb\u30fc\u30d7\u9593\u6bd4\u8f03\u3067\u3082\u3001\u671f\u5f85\u50245\u672a\u6e80\u306e\u30bb\u30eb\u304c\u4e00\u3064\u307e\u305f\u306f\u4e8c\u3064\u542b\u307e\u308c\u308b\u3002<\/p>\n\n\n\n
\u4e00\u3064\u306e\u30bb\u30eb\u3060\u3051\u3067\u3082 1\/4 = 25 % \u3001\u4e8c\u3064\u306e\u30bb\u30eb\u306a\u3089 2\/4 = 50 % \u306a\u306e\u3067\u3001\u3044\u305a\u308c\u306e\u5834\u5408\u3082 20 % \u3092\u8d85\u3048\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
\u3086\u3048\u306b\u3001$ \\chi^2 $ \u691c\u5b9a\u3092\u4f7f\u3046\u306e\u306f\u9069\u5207\u3067\u306f\u306a\u3044\u3002<\/p>\n\n\n\n
\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u3000\u30db\u30eb\u30e0\u306e\u591a\u91cd\u8abf\u6574<\/h3>\n\n\n\n
\u30db\u30eb\u30e0\u306e\u65b9\u6cd5\u306f\u3001\u3082\u3063\u3068\u3082\u5c0f\u3055\u3044p\u5024\u306b\u6700\u5927\u6bd4\u8f03\u30da\u30a2\u6570\u3092\u304b\u3051\u308b\u3002<\/p>\n\n\n\n
\u4f8b\u306f\u30da\u30a2\u6570\u306f3\u306a\u306e\u3067\u30013\u3092\u304b\u3051\u308b\u3002<\/p>\n\n\n\n
2\u756a\u76ee\u306ep\u5024\u306b2\u3092\u304b\u3051\u308b\u3002\u4e00\u756a\u5927\u304d\u3044p\u5024\u306f\u305d\u306e\u307e\u307e\u3002\u3068\u8a08\u7b97\u3055\u308c\u308b\u3002<\/p>\n\n\n\n
1\u30683\uff1a$ 0.018 \\times 3 = 0.054 $<\/p>\n\n\n\n
2\u30683\uff1a$ 0.041 \\times 2 = 0.081 $<\/p>\n\n\n\n
\u3082\u3063\u3068\u3082\u5c0f\u3055\u3044p\u5024\u306e3\u500d\u304c0.05\u3092\u4e0b\u56de\u3089\u306a\u304b\u3063\u305f\u6642\u70b9\u3067\u3001\u8a08\u7b97\u306f\u7d42\u4e86\u3060\u3002<\/p>\n\n\n\n
\u591a\u91cd\u6bd4\u8f03\u8abf\u6574\u3059\u308b\u3068\u3069\u306e\u7fa4\u9593\u3082\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306b\u7570\u306a\u3089\u306a\u3044\u3002<\/p>\n\n\n\n
><\/span> pairwise.prop.test<\/span>(<\/span>t<\/span>(<\/span>tab))<\/span>\nPairwise comparisons using Pairwise comparison of proportions\ndata:<\/span>  t<\/span>(<\/span>tab)<\/span>\nGroup1 Group2\nGroup2 0.383<\/span>  -<\/span>\nGroup3 0.054<\/span>  0.081<\/span>\nP value adjustment method:<\/span> holm\nWarning messages:<\/span>\n1<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n2<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n<\/code><\/pre>\n\n\n\n
\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u3000\u30db\u30c3\u30af\u30d0\u30fc\u30b0 \u306e\u591a\u91cd\u8abf\u6574<\/h3>\n\n\n\n
\u3082\u3046\u4e00\u3064\u306e\u65b9\u6cd5\u306f\u30db\u30c3\u30af\u30d0\u30fc\u30b0\u306e\u65b9\u6cd5\u3002<\/p>\n\n\n\n
\u3053\u3061\u3089\u306e\u307b\u3046\u304c\u691c\u51fa\u529b\u304c\u9ad8\u304f\u3001\u304a\u3059\u3059\u3081\u3002<\/p>\n\n\n\n
\u30db\u30eb\u30e0\u3068\u540c\u69d8\u306b\u3001\u5927\u304d\u3044p\u5024\u306f\u305d\u306e\u307e\u307e\u30012\u756a\u76ee\u306b\u5927\u304d\u3044p\u5024\u30922\u500d\u3057\u3066\u3001\u4e00\u756a\u5c0f\u3055\u3044p\u5024\u30923\u500d\u3059\u308b\u3002<\/p>\n\n\n\n
\u30c1\u30a7\u30c3\u30af\u306e\u4ed5\u65b9\u304c\u30db\u30eb\u30e0\u306e\u6642\u3068\u9006\u3067\u3001\u5927\u304d\u3044p\u5024\u304b\u3089\u59cb\u3081\u308b\u3002<\/p>\n\n\n\n
\u3082\u3057\u3082\u3063\u3068\u3082\u5927\u304d\u3044p\u5024\u304c0.05\u3092\u4e0b\u56de\u3063\u3066\u3044\u305f\u3089\u3001\u305d\u308c\u4ee5\u5916\u306ep\u5024\u304c\u3069\u3046\u3067\u3042\u308c\u3001\u3059\u3079\u3066\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306b\u7570\u306a\u308b\u3068\u5224\u65ad\u3059\u308b\u3002<\/p>\n\n\n\n
\u3082\u3063\u3068\u3082\u5927\u304d\u3044p\u5024\u304c0.05\u3092\u4e0b\u56de\u3063\u3066\u3044\u306a\u304b\u3063\u305f\u3089\u3001\u6b21\u306b2\u756a\u76ee\u306b\u5927\u304d\u3044p\u5024\u306e2\u500d\u30680.05\u3092\u6bd4\u8f03\u3059\u308b\u3002<\/p>\n\n\n\n
\u3053\u3053\u3067\u3082\u30570.05\u3088\u308a\u5c0f\u3055\u3051\u308c\u3070\u3001\u6700\u3082\u5c0f\u3055\u3044p\u5024\u306f\u4e0d\u554f\u3067\u3001\u3068\u3082\u306b\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306b\u7570\u306a\u308b\u3068\u5224\u65ad\u3059\u308b\u3002<\/p>\n\n\n\n
\u4eca\u56de\u306e\u4f8b\u306f\u3001\u3069\u306e\u30ec\u30d9\u30eb\u3067\u30820.05\u3092\u4e0b\u56de\u3089\u306a\u304b\u3063\u305f\u306e\u3067\u3001\u3069\u306e\u7fa4\u9593\u306b\u3082\u7d71\u8a08\u5b66\u7684\u6709\u610f\u5dee\u306f\u306a\u304b\u3063\u305f\u3002<\/p>\n\n\n\n
><\/span> pairwise.prop.test<\/span>(<\/span>t<\/span>(<\/span>tab),<\/span>p.adjust=<\/span>\"hochberg\"<\/span>)<\/span>\nPairwise comparisons using Pairwise comparison of proportions\ndata:<\/span>  t<\/span>(<\/span>tab)<\/span>\nGroup1 Group2\nGroup2 0.383<\/span>  -<\/span>\nGroup3 0.054<\/span>  0.081<\/span>\nP value adjustment method:<\/span> hochberg\nWarning messages:<\/span>\n1<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n2<\/span>:<\/span> In prop.test<\/span>(<\/span>x[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> n[<\/span>c<\/span>(<\/span>i,<\/span> j)],<\/span> ...)<\/span> :<\/span>\nChi-<\/span>squared approximation may be incorrect\n<\/code><\/pre>\n\n\n\n
\u30db\u30eb\u30e0\u306f\u5c0f\u3055\u3044p\u5024\u304b\u30890.05\u3092\u4e0b\u56de\u308a\u7d9a\u3051\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u70b9\u3067\u53b3\u3057\u304f\u3001\u30db\u30c3\u30af\u30d0\u30fc\u30b0\u306f\u3001\u5927\u304d\u3044p\u5024\u304c\u4e00\u56de0.05\u3092\u4e0b\u56de\u3063\u305f\u6bb5\u968e\u3067\u305d\u308c\u3088\u308a\u5c0f\u3055\u3044p\u5024\u306f\u4e0d\u554f\u3067\u5168\u90e8\u6709\u610f\u3068\u3044\u3046\u3068\u3053\u308d\u304c\u3001\u691c\u51fa\u529b\u304c\u9ad8\u3044\u3086\u3048\u3093\u3060\u3002<\/p>\n\n\n\n
\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u306e3\u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03<\/h2>\n\n\n\n
\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u30923\u7fa4\u4ee5\u4e0a\u306e\u6bd4\u8f03\u3067\u4f7f\u3046\u65b9\u6cd5\u3002<\/p>\n\n\n\n
RVAideMemoire\u30d1\u30c3\u30b1\u30fc\u30b8\u306efisher.multcomp()\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n
RVAideMemoire\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3002<\/p>\n\n\n\n
\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306f\u4e00\u56de\u3060\u3051\u3002<\/p>\n\n\n\n
install.packages<\/span>(<\/span>\"RVAideMemoire\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
p.method\u3067\u591a\u91cd\u6bd4\u8f03\u8abf\u6574\u306e\u65b9\u6cd5\u3092\u6307\u5b9a\u3059\u308b\u3002<\/p>\n\n\n\n
library<\/span>(<\/span>RVAideMemoire)<\/span>\nfisher.multcomp<\/span>(<\/span>tab,<\/span> p.method=<\/span>\"none\"<\/span>)<\/span>\nfisher.multcomp<\/span>(<\/span>tab,<\/span> p.method=<\/span>\"holm\"<\/span>)<\/span>\nfisher.multcomp<\/span>(<\/span>tab,<\/span> p.method=<\/span>\"hochberg\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u3068\u30ab\u30a4\u4e8c\u4e57\u691c\u5b9a\u306e\u7d50\u679c\u306e\u6bd4\u8f03<\/h3>\n\n\n\n
\u3053\u306e\u30c7\u30fc\u30bf\u306f\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u78ba\u7387\u691c\u5b9a\u3092\u4f7f\u3046\u3053\u3068\u304c\u9069\u5207\u3067\u3042\u308b\u5178\u578b\u4f8b\u3068\u601d\u3046\u3002<\/p>\n\n\n\n
<\/th>\"<\/th>\" with Holm\/Hochberg<\/th>Fisher<\/th>Fisher with Holm\/Hochberg<\/th><\/tr><\/thead>
Group1:Group2<\/td>0.383<\/td>0.383<\/td>0.3038<\/td>0.3038<\/td><\/tr>
Group1:Group3<\/td>0.018<\/td>0.054<\/td>0.005656<\/td>0.01697<\/span><\/td><\/tr>
Group2:Group3<\/td>0.041<\/td>0.081<\/td>0.02481<\/td>0.04962<\/span><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Group1\u30683\u3001Group2\u30683\u306ep\u5024\u304c\u3001$ \\chi^2$  \u306b\u6bd4\u3079\u308b\u3068Fisher\u306e\u307b\u3046\u304c\u65ad\u7136\u4f4e\u3044\u3002<\/p>\n\n\n\n
\u30db\u30eb\u30e0\u306a\u3089\u3001Group1\u30683\u304c\u6709\u610f\u3001Group2\u30683\u304c\u6709\u610f\u3001Group1\u30682\u306f\u6709\u610f\u3067\u306a\u304f\u8a08\u7b97\u7d42\u4e86\u3002<\/p>\n\n\n\n
\u30db\u30c3\u30af\u30d0\u30fc\u30b0\u306a\u3089\u3001Group1\u30682\u306f\u6709\u610f\u3067\u306a\u3044\u304c\u3001Group2\u30683\u304c\u6709\u610f\u3067\u3001Group1\u30683\u3092\u78ba\u8a8d\u3059\u308b\u524d\u306b\u7d42\u4e86\u3002<\/p>\n\n\n\n
\u7d50\u679c\u3068\u3057\u3066\u3001Group1\u30683\u3001Group2\u30683\u306e\u7fa4\u9593\u306b\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306a\u5dee\u3092\u8a8d\u3081\u305f\uff08\u8d64\u3067\u793a\u3057\u305f\u6709\u610f\u78ba\u7387\uff09\u3002<\/p>\n\n\n\n
\u3064\u307e\u308a\u3001Group3\u304c\u30c0\u30f3\u30c8\u30c4\u3067Yes\u306e\u5272\u5408\u304c\u9ad8\u3044\u3068\u3044\u3046\u7d50\u8ad6\u3060\u3002<\/p>\n\n\n\n
\u4ee5\u4e0b\u306f\u3001\u4e0a\u8a18\u306e\u7d50\u679c\u3092\u8a08\u7b97\u3059\u308b\u305f\u3081\u306eR\u30b9\u30af\u30ea\u30d7\u30c8\u3002<\/p>\n\n\n\n
><\/span> library<\/span>(<\/span>RVAideMemoire)<\/span>\n><\/span>\n><\/span> fisher.multcomp<\/span>(<\/span>tab,<\/span> p.method=<\/span>\"none\"<\/span>)<\/span>\nPairwise comparisons using Fisher's exact test for count data<\/span>\ndata:  tab<\/span>\n       Group1:Group2 Group1:Group3 Group2:Group3<\/span>\nNo:Yes        0.3038      0.005656       0.02481<\/span>\nP value adjustment method: none<\/span>\n> <\/span>\n> fisher.multcomp(tab, p.method=\"holm\")<\/span>\n        Pairwise comparisons using Fisher'<\/span>s exact test for<\/span> count data\ndata:<\/span>  tab\nGroup1:<\/span>Group2 Group1:<\/span>Group3 Group2:<\/span>Group3\nNo:<\/span>Yes        0.3038<\/span>       0.01697<\/span>       0.04962<\/span>\nP value adjustment method:<\/span> holm\n><\/span>\n><\/span> fisher.multcomp<\/span>(<\/span>tab,<\/span> p.method=<\/span>\"hochberg\"<\/span>)<\/span>\nPairwise comparisons using Fisher's exact test for count data<\/span>\ndata:  tab<\/span>\n       Group1:Group2 Group1:Group3 Group2:Group3<\/span>\nNo:Yes        0.3038       0.01697       0.04962<\/span>\nP value adjustment method: hochberg<\/span>\n<\/code><\/pre>\n\n\n\n
\u3061\u306a\u307f\u306b\u3001fisher.multcomp()\u306f $ 2 \\times n $ \u3092\u8d85\u3048$ m \\times n $ \u306e\u5206\u5272\u8868\u306b\u9069\u7528\u3067\u304d\u308b\u3002<\/p>\n\n\n\n
\u4e0b\u8a18\u306e\u7d50\u679c\u304b\u3089\u629c\u304d\u51fa\u3059\u3068\u3001\u691c\u8a0e\u306b\u5024\u3059\u308b\u7d44\u307f\u5408\u308f\u305b\u306f\u4ee5\u4e0b\u306e5\u901a\u308a\u3002<\/p>\n\n\n\n