{"id":392,"date":"2021-09-12T19:48:58","date_gmt":"2021-09-12T10:48:58","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/fisher-exact-test-odds-ratio\/"},"modified":"2024-10-03T22:04:05","modified_gmt":"2024-10-03T13:04:05","slug":"fisher-exact-test-odds-ratio","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/fisher-exact-test-odds-ratio\/","title":{"rendered":"EZR \u306e\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u691c\u5b9a\u3067\u8a08\u7b97\u3055\u308c\u308b\u30aa\u30c3\u30ba\u6bd4\u306e\u6ce8\u610f\u70b9"},"content":{"rendered":"\n

EZR\u306eFisher\u306e\u6b63\u78ba\u691c\u5b9a\u306e\u95a2\u6570\u3067\u30aa\u30c3\u30ba\u6bd4\u3092\u8a08\u7b97\u3059\u308b\u3068\u3001\u901a\u5e38\u306e\u624b\u8a08\u7b97\u3067\u8a08\u7b97\u3067\u304d\u308b\u30aa\u30c3\u30ba\u6bd4\u3068\u7570\u306a\u308b\u6570\u5024\u304c\u8a08\u7b97\u3055\u308c\u308b\u3002<\/p>\n\n\n\n

\u3053\u308c\u306f\u306a\u305c\u306a\u306e\u304b\uff1f<\/p>\n\n\n\n\n\n\n\n

EZR\u306eFisher\u306e\u6b63\u78ba\u691c\u5b9a\u3092\u4f7f\u308f\u306a\u3044\u30aa\u30c3\u30ba\u6bd4\u306e\u8a08\u7b97<\/h2>\n\n\n\n

\u30aa\u30c3\u30ba\u6bd4\u306f\u3001\u901a\u5e38\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u5206\u5272\u8868\u3060\u3063\u305f\u5834\u5408\u3001$ \\frac{a\/c}{b\/d} $\u3068\u8a08\u7b97\u3059\u308b\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

a=80, b=20, c=50, d=50\u3060\u3063\u305f\u3068\u3059\u308c\u3070\u3001\u30aa\u30c3\u30ba\u6bd4\u306f\u3001$ \\frac{80\/50}{20\/50} = 4 $ \u3068\u8a08\u7b97\u3055\u308c\u308b\u3002<\/p>\n\n\n\n

EZR\u306eFisher\u306e\u6b63\u78ba\u691c\u5b9a\u3092\u4f7f\u3063\u305f\u5834\u5408\u306e\u30aa\u30c3\u30ba\u6bd4\u306e\u8a08\u7b97<\/h2>\n\n\n\n

EZR \u306e Fisher\u306e\u6b63\u78ba\u691c\u5b9a\u3092\u4f7f\u3063\u305f\u5834\u5408\u3001\u3053\u306e\u30aa\u30c3\u30ba\u6bd4\u304c\u4ee5\u4e0b\u306e\u3088\u3046\u306b3.97\u3068\u306a\u308b\u3002\u3053\u308c\u306f\u3044\u3063\u305f\u3044\u3069\u3046\u3044\u3046\u3053\u3068\u3060\u308d\u3046\u304b\uff1f<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n\n\n\n\n
\"\"<\/figure>\n\n\n\n

\u5206\u5272\u8868\u306b\u76f4\u63a5\u6570\u5024\u3092\u5165\u529b\u3057OK\u3092\u30af\u30ea\u30c3\u30af\uff01<\/p>\n\n\n\n

><\/span> fisher.test<\/span>(<\/span>.Table)<\/span>\nFisher's Exact Test for Count Data<\/span>\ndata:  .Table<\/span>\np-value = 0.00001389<\/span>\nalternative hypothesis: true odds ratio is not equal to 1<\/span>\n95 percent confidence interval:<\/span>\n 2.049148 7.919959<\/span>\nsample estimates:<\/span>\nodds ratio <\/span>\n  3.970815<\/span>\n<\/code><\/pre>\n\n\n\n
\uff1e\uff1e\u3082\u3046\u7d71\u8a08\u3067\u60a9\u3080\u306e\u306f\u7d42\u308f\u308a\u306b\u3057\u307e\u305b\u3093\u304b\uff1f\u00a0<\/a><\/strong><\/span><\/p>\r\n\"\"<\/a>\r\n
\u21911\u4e07\u4eba\u4ee5\u4e0a\u306e\u533b\u7642\u5f93\u4e8b\u8005\u304c\u8cfc\u8aad\u4e2d<\/span><\/strong><\/span><\/p><\/div>
EZR\u306eFisher\u306e\u6b63\u78ba\u691c\u5b9a\u3067\u4f7f\u3063\u3066\u3044\u308b\u30aa\u30c3\u30ba\u6bd4\u306e\u8a08\u7b97\u65b9\u6cd5<\/h2>\n\n\n\n
\u3053\u308c\u306f\u3001EZR\u306eFisher\u306e\u6b63\u78ba\u691c\u5b9a\u3067\u4f7f\u3063\u3066\u3044\u308b\u30aa\u30c3\u30ba\u6bd4\u8a08\u7b97\u306e\u65b9\u6cd5\u304c\u3001\u5358\u7d14\u306a\u30aa\u30c3\u30ba\u6bd4\u8a08\u7b97\u3068\u306f\u7570\u306a\u308b\u304b\u3089\u3060\u3002<\/p>\n\n\n\n
\u6761\u4ef6\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf\uff08Conditional Maximum Likelihood Estimate\uff09\u3092\u8a08\u7b97\u3057\u3066\u3044\u308b\u306e\u3067\u3001\u30b5\u30f3\u30d7\u30eb\u304b\u3089\u5358\u7d14\u306b\u8a08\u7b97\u3059\u308b\u30aa\u30c3\u30ba\u6bd4\u3068\u7570\u306a\u308b\u3053\u3068\u306b\u306a\u308b\u3002<\/p>\n\n\n\n
\u901a\u5e38\u8a08\u7b97\u3059\u308b\u5358\u7d14\u306a\u30aa\u30c3\u30ba\u6bd4\u306f\u3001\u6761\u4ef6\u306a\u3057\u306e\u6700\u5c24\u63a8\u5b9a\u91cf\uff08Unconditional Maximum Likelihood Estimate\uff09\u3067\u3001\u3053\u306e\u30aa\u30c3\u30ba\u6bd4\u306fWald\u306e\u30aa\u30c3\u30ba\u6bd4\u3068\u3082\u547c\u3070\u308c\u308b\u3002<\/p>\n\n\n\n
\u4eca\u56de\u306e 2×2 \u306e\u30c7\u30fc\u30bf\u304c\u5f97\u3089\u308c\u305f\u3068\u3044\u3046\u6761\u4ef6\u3067\u3001\u6700\u5c24\u63a8\u5b9a\u91cf\u3092\u6c42\u3081\u3066\u3044\u308b\u306e\u304cFisher\u306e\u30aa\u30c3\u30ba\u6bd4\u306a\u306e\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\u4e09\u91cd\u5927\u5b66\u540d\u8a89\u6559\u6388\u306e\u5965\u6751\u5148\u751f\u306e\u8aac\u660e\u306f\u3068\u3066\u3082\u308f\u304b\u308a\u3084\u3059\u3044\u306e\u3067\u3001\u305c\u3072\u4e00\u8aad\u3092\u3002<\/p>\n\n\n\n
\u4e0b\u6bb5\u306e\u300c\u30aa\u30c3\u30ba\u6bd4\u300d\u3068\u3044\u3046\u30bb\u30af\u30b7\u30e7\u30f3\u304c\u8a72\u5f53\u7b87\u6240\u3002<\/p>\n\n\n\n
https:\/\/okumuralab.org\/~okumura\/stat\/fishertest.html<\/a><\/p>\n\n\n\n
\u3061\u306a\u307f\u306b\u3001\u6700\u5c24\u63a8\u5b9a\u91cf\u3068\u3044\u3046\u306e\u306f\u3001\u3042\u308b\u73fe\u8c61\u3092\u30e2\u30c7\u30eb\u5316\u3057\u3001\uff08\u4eca\u56de\u306f 2×2 \u306e\u5206\u5272\u8868\u306a\u306e\u3067\u3001\u4e8c\u9805\u5206\u5e03\u3067\u30e2\u30c7\u30eb\u5316\u3057\u3001\uff09\u5f97\u3089\u308c\u305f\u30c7\u30fc\u30bf\u304b\u3089\u305d\u306e\u30e2\u30c7\u30eb\u306e\u5c24\u5ea6\uff08\u3082\u3063\u3068\u3082\u3089\u3057\u3055\uff09\u304c\u6700\u5927\u306b\u306a\u308b\u3088\u3046\u306b\u3057\u305f\u3068\u304d\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u3053\u3068\u3092\u8a00\u3046\u3002<\/p>\n\n\n\n
\u305d\u306e\u6700\u5c24\u63a8\u5b9a\u91cf\u3092\u6c42\u3081\u308b\u969b\u306b\u3001\u6761\u4ef6\u3092\u4ed8\u3051\u305f\u3068\u3044\u3046\u3053\u3068\u3002<\/p>\n\n\n\n
\u53c2\u8003\uff1a\u5c24\u5ea6\u3068\u306f\uff1f<\/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\t\u5c24\u5ea6\u3068\u306f\uff1f\u308f\u304b\u308a\u3084\u3059\u304f\u89e3\u8aac<\/a>\n\t\t\t\t\t\t\u8aad\u307f\u65b9\u3082\u610f\u5473\u3057\u3066\u3044\u308b\u3068\u3053\u308d\u3082\u5206\u304b\u308a\u306b\u304f\u3044\u5c24\u5ea6\uff08\u3086\u3046\u3069\uff09\u3002 \u308f\u304b\u308a\u3084\u3059\u304f\u89e3\u8aac\u3002 \u5c24\u5ea6\u3068\u4f3c\u3066\u3044\u308b\u78ba\u7387\u3068\u306f\u4f55\u304b\uff1f \u307e\u305a\u5c24\u5ea6\u306f\u78ba\u7387\u306b\u4f3c\u3066\u3044\u308b\u3082\u306e\u3060\u304c\u3001\u78ba\u7387\u3068\u306f\u9055\u3046\u3002 \u307e…<\/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
EZR\u3067Fisher\u306e\u30aa\u30c3\u30ba\u6bd4\u3067\u306a\u3044\u30aa\u30c3\u30ba\u6bd4\u3092\u6c42\u3081\u308b\u306b\u306f\uff1f<\/h2>\n\n\n\n
epitools \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u3001oddsratio.wald() \u3092\u4f7f\u3046\u3068\u3088\u3044\u3002<\/p>\n\n\n\n
R\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u7a93\u306b\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u66f8\u3044\u3066\u3001\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u3001\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3048\u308b\u3088\u3046\u306b\u3059\u308b\u3002<\/p>\n\n\n\n
install.packages<\/span>(<\/span>\"epitools\"<\/span>)<\/span> #\u4e00\u56de\u306e\u307f\u3002\u5b9f\u884c\u3059\u308b\u3068\u30d1\u30c3\u30b1\u30fc\u30b8\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3059\u308b\u30b5\u30fc\u30d0\u30fc\u3092\u9078\u3076\u7a93\u304c\u958b\u304f\u306e\u3067Japan\u3092\u9078\u629e\u3002<\/span>\nlibrary<\/span>(<\/span>epitools)<\/span> #\u30d1\u30c3\u30b1\u30fc\u30b8\u4f7f\u7528\u6642\u306b\u4e8b\u524d\u306b\u4e00\u56de\u5b9f\u884c\u3002<\/span>\n<\/code><\/pre>\n\n\n\n
\u5148\u307b\u3069\u306e\u7d50\u679c\u3092\u4e00\u90e8\u6d41\u7528\u3057\u3066\u3001Wald\u306e\u30aa\u30c3\u30ba\u6bd4\uff08\u901a\u5e38\u306e\u30aa\u30c3\u30ba\u6bd4\uff09\u3092\u8a08\u7b97\u3057\u3066\u307f\u308b\u3068\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308b\u3002<\/p>\n\n\n\n
odds ratio\u3068\u3042\u308b\u500b\u6240\u306eestimate\u304c\uff14\u306b\u306a\u3063\u3066\u3044\u308b\u306e\u304c\u308f\u304b\u308b\u3002<\/p>\n\n\n\n
><\/span> oddsratio.wald<\/span>(<\/span>.Table)<\/span>\n$<\/span>data\n1<\/span>  2<\/span> Total\n1<\/span>      80<\/span> 20<\/span>   100<\/span>\n2<\/span>      50<\/span> 50<\/span>   100<\/span>\nTotal 130<\/span> 70<\/span>   200<\/span>\n$<\/span>measure\nNA<\/span>\nodds ratio with 95<\/span>% C.I. estimate    lower   upper\n1<\/span>        1<\/span>       NA<\/span>      NA<\/span>\n2<\/span>        4<\/span> 2.135711<\/span> 7.49165<\/span>\n$<\/span>p.value\nNA<\/span>\ntwo-<\/span>sided   midp.exact  fisher.exact     chi.square\n1<\/span>           NA<\/span>            NA<\/span>             NA<\/span>\n2<\/span> 0.0000085777<\/span> 0.00001388917<\/span> 0.000008687712<\/span>\n$<\/span>correction\n[<\/span>1<\/span>]<\/span> FALSE<\/span>\nattr<\/span>(,<\/span>\"method\"<\/span>)<\/span>\n[<\/span>1<\/span>]<\/span> \"Unconditional MLE & normal approximation (Wald) CI\"<\/span>\n<\/code><\/pre>\n\n\n\n
\u3053\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3063\u3066\u3001Fisher\u306e\u30aa\u30c3\u30ba\u6bd4\u3092\u8a08\u7b97\u3057\u3066\u307f\u308b\u5834\u5408\u306f\u3001oddsratio.fisher() \u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n
fisher.test() \u3068\u540c\u3058\u7d50\u679c\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308b\u3002<\/p>\n\n\n\n
><\/span> oddsratio.fisher<\/span>(<\/span>.Table)<\/span>\n$<\/span>data\n1<\/span>  2<\/span> Total\n1<\/span>      80<\/span> 20<\/span>   100<\/span>\n2<\/span>      50<\/span> 50<\/span>   100<\/span>\nTotal 130<\/span> 70<\/span>   200<\/span>\n$<\/span>measure\nNA<\/span>\nodds ratio with 95<\/span>% C.I. estimate    lower    upper\n1<\/span> 1.000000<\/span>       NA<\/span>       NA<\/span>\n2<\/span> 3.970815<\/span> 2.049148<\/span> 7.919959<\/span>\n$<\/span>p.value\nNA<\/span>\ntwo-<\/span>sided   midp.exact  fisher.exact     chi.square\n1<\/span>           NA<\/span>            NA<\/span>             NA<\/span>\n2<\/span> 0.0000085777<\/span> 0.00001388917<\/span> 0.000008687712<\/span>\n$<\/span>correction\n[<\/span>1<\/span>]<\/span> FALSE<\/span>\nattr<\/span>(,<\/span>\"method\"<\/span>)<\/span>\n[<\/span>1<\/span>]<\/span> \"Conditional MLE & exact CI from 'fisher.test'\"<\/span>\n<\/code><\/pre>\n\n\n\n
\u307e\u3068\u3081<\/h2>\n\n\n\n
EZR\u3067\u3001Fisher\u306e\u6b63\u78ba\u691c\u5b9a\u3092\u4f7f\u3063\u3066\u30aa\u30c3\u30ba\u6bd4\u3092\u8a08\u7b97\u3059\u308b\u3068\u3001\u624b\u8a08\u7b97\u3067\u884c\u3063\u305f\u30aa\u30c3\u30ba\u6bd4\u3068\u7570\u306a\u308b\u6570\u5024\u304c\u793a\u3055\u308c\u308b\u304c\u3001\u305d\u308c\u306f\u306a\u305c\u304b\u3068\u3044\u3046\u8a71\u3092\u3057\u305f\u3002<\/p>\n\n\n\n
\u901a\u5e38\u306e\u624b\u8a08\u7b97\u3067\u3067\u304d\u308b\u30aa\u30c3\u30ba\u6bd4\u306f\u3001\u6761\u4ef6\u306a\u3057\u306e\u6700\u5c24\u63a8\u5b9a\u91cf\uff08Unconditional Maximum Likelihood Estimate\uff09\u3067\u3042\u308a\u3001fisher.test()\u3067\u8a08\u7b97\u3055\u308c\u308b\u30aa\u30c3\u30ba\u6bd4\u306f\u3001\u6761\u4ef6\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf\uff08Conditional Maximum Likelihood Estimate\uff09\u3067\u3042\u308b\u305f\u3081\u3001\u6570\u5024\u304c\u7570\u306a\u308b\u3002<\/p>\n\n\n\n
\u3069\u3061\u3089\u3092\u4f7f\u3063\u3066\u3044\u308b\u304b\u3092\u65ad\u308c\u3070\u3001\u3069\u3061\u3089\u3092\u4f7f\u3063\u3066\u3082\u9593\u9055\u3044\u3067\u306f\u306a\u3044\u3068\u8a00\u3048\u308b\u3002<\/p>\n\n\n\n
\u53c2\u8003\u30b5\u30a4\u30c8<\/h2>\n\n\n\n
https:\/\/okumuralab.org\/~okumura\/stat\/fishertest.html<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
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