{"id":544,"date":"2018-07-14T09:02:05","date_gmt":"2018-07-14T00:02:05","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/forest-plot-in-meta-analysis\/"},"modified":"2024-10-14T08:43:59","modified_gmt":"2024-10-13T23:43:59","slug":"forest-plot-in-meta-analysis","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/forest-plot-in-meta-analysis\/","title":{"rendered":"R \u3067\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9\u306e\u30d5\u30a9\u30ec\u30b9\u30c8\u30d7\u30ed\u30c3\u30c8\u3092\u66f8\u304f\u65b9\u6cd5"},"content":{"rendered":"\n

\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9\u306e\u30d5\u30a9\u30ec\u30b9\u30c8\u30d7\u30ed\u30c3\u30c8\u306e\u66f8\u304d\u65b9\u306e\u89e3\u8aac<\/p>\n\n\n\n

R \u306e metafor \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3046\u65b9\u6cd5<\/p>\n\n\n\n\n\n\n\n

\u7d71\u5408\u5024\u306e\u8a08\u7b97<\/h2>\n\n\n\n

metafor\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n

\u6700\u521d\u4e00\u56de\u3060\u3051\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3002<\/p>\n\n\n\n

install.packages<\/span>(<\/span>\"metafor\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
\u4f7f\u7528\u3059\u308b\u30c7\u30fc\u30bf\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3002<\/p>\n\n\n\n
a <-<\/span> c<\/span>(<\/span>3<\/span>,<\/span>7<\/span>,<\/span>5<\/span>,<\/span>102<\/span>,<\/span>28<\/span>,<\/span>4<\/span>,<\/span>98<\/span>,<\/span>60<\/span>,<\/span>25<\/span>,<\/span>138<\/span>,<\/span>64<\/span>,<\/span>45<\/span>,<\/span>9<\/span>,<\/span>57<\/span>,<\/span>25<\/span>,<\/span>65<\/span>,<\/span>17<\/span>)<\/span>\nn1 <-<\/span> c<\/span>(<\/span>38<\/span>,<\/span>114<\/span>,<\/span>69<\/span>,<\/span>1533<\/span>,<\/span>355<\/span>,<\/span>59<\/span>,<\/span>945<\/span>,<\/span>632<\/span>,<\/span>278<\/span>,<\/span>1916<\/span>,<\/span>873<\/span>,<\/span>263<\/span>,<\/span>291<\/span>,<\/span>858<\/span>,<\/span>154<\/span>,<\/span>1195<\/span>,<\/span>298<\/span>)<\/span>\nc <-<\/span> c<\/span>(<\/span>3<\/span>,<\/span>14<\/span>,<\/span>11<\/span>,<\/span>127<\/span>,<\/span>27<\/span>,<\/span>6<\/span>,<\/span>152<\/span>,<\/span>48<\/span>,<\/span>37<\/span>,<\/span>188<\/span>,<\/span>52<\/span>,<\/span>47<\/span>,<\/span>16<\/span>,<\/span>45<\/span>,<\/span>31<\/span>,<\/span>62<\/span>,<\/span>34<\/span>)<\/span>\nn0 <-<\/span> c<\/span>(<\/span>39<\/span>,<\/span>116<\/span>,<\/span>93<\/span>,<\/span>1520<\/span>,<\/span>365<\/span>,<\/span>52<\/span>,<\/span>939<\/span>,<\/span>471<\/span>,<\/span>282<\/span>,<\/span>1921<\/span>,<\/span>583<\/span>,<\/span>266<\/span>,<\/span>293<\/span>,<\/span>883<\/span>,<\/span>147<\/span>,<\/span>1200<\/span>,<\/span>309<\/span>)<\/span>\ndat <-<\/span> data.frame<\/span>(<\/span>a,<\/span>n1,<\/span>c,<\/span>n0)<\/span>\n<\/code><\/pre>\n\n\n\n
metafor\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u547c\u3073\u51fa\u3059\u3002<\/p>\n\n\n\n
escalc() \u3067\u500b\u3005\u306e\u7814\u7a76\u306e\u63a8\u5b9a\u5024 estimate; yi \u3068\u5206\u6563 variance; vi \u3092\u8a08\u7b97\u3059\u308b\u3002<\/p>\n\n\n\n
measure=\u3067\u6307\u6a19\u3092\u6307\u5b9a\u3002<\/p>\n\n\n\n
\u4eca\u56de\u306e\u30c7\u30fc\u30bf\u306f\u30aa\u30c3\u30ba\u6bd4\u3002<\/p>\n\n\n\n
rma.uni() \u3067\u7d71\u5408\u30aa\u30c3\u30ba\u6bd4\u3092\u8a08\u7b97\u3059\u308b\u3002<\/p>\n\n\n\n
\u7d71\u5408\u3059\u308b\u65b9\u6cd5\u306f\u5236\u9650\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf\uff08REML\uff09\u3002<\/p>\n\n\n\n
REML \u306b\u3064\u3044\u3066\u306f\u3001\u4ee5\u4e0b\u3092\u53c2\u7167\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\u5236\u9650\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf REML \u3067\u30aa\u30c3\u30ba\u6bd4\u3092\u7d71\u5408\u3059\u308b\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9<\/a>\n\t\t\t\t\t\t\u30aa\u30c3\u30ba\u6bd4\u3092\u5236\u9650\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf REML \u3067\u7d71\u5408\u3059\u308b\u65b9\u6cd5\u306e\u89e3\u8aac\u3002 R \u3067\u5b9f\u884c\u3059\u308b\u3002 \u5236\u9650\u4ed8\u304d\u6700\u5c24\u63a8\u5b9a\u91cf\u3067\u30aa\u30c3\u30ba\u6bd4\u3092\u7d71\u5408\u3059\u308b\u610f\u5473 \u30aa\u30c3\u30ba\u6bd4\u306e\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9\u3092\u3059\u308b\u3068\u304d\u306b\u3001\u5bfe\u6570…<\/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 \u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3002<\/p>\n\n\n\n
library<\/span>(<\/span>metafor)<\/span>\ndat.escalc <-<\/span> escalc<\/span>(<\/span>measure=<\/span>\"OR\"<\/span>,<\/span> ai=<\/span>a,<\/span> n1i=<\/span>n1,<\/span> ci=<\/span>c,<\/span> n2i=<\/span>n0,<\/span> data=<\/span>dat)<\/span>\nres.reml <-<\/span> rma.uni<\/span>(<\/span>yi,<\/span> vi,<\/span> method=<\/span>\"REML\"<\/span>,<\/span> data=<\/span>dat.escalc)<\/span>\n<\/code><\/pre>\n\n\n\n
\u30d5\u30a9\u30ec\u30b9\u30c8\u30d7\u30ed\u30c3\u30c8\u306e\u66f8\u304d\u65b9<\/h2>\n\n\n\n
R \u30b9\u30af\u30ea\u30d7\u30c8\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u3068\u3066\u3082\u5358\u7d14\u3060\u3002<\/p>\n\n\n\n
forest<\/span>(<\/span>res.reml)<\/span>\n<\/code><\/pre>\n\n\n\n
\u30c7\u30d5\u30a9\u30eb\u30c8\u306f\u3053\u3046\u306a\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\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>
\u771f\u6570\u306e\u8868\u793a\u3067\u5bfe\u6570\u76ee\u76db\u308a\u306b\u3059\u308b\u65b9\u6cd5<\/h2>\n\n\n\n
X\u8ef8\uff08\u6a2a\u8ef8\uff09\u306e\u5024\u3092\u5bfe\u6570\u304b\u3089\u771f\u6570\u306b\u5909\u66f4\u3059\u308b\u306b\u306f atransf=exp \u3068\u6307\u5b9a\u3059\u308b\u3002<\/p>\n\n\n\n
atransf=exp\u306f\u3001\u6570\u5024\u306f\u771f\u6570\u3060\u304c\u3001\u76ee\u76db\u308a\u306f\u5bfe\u6570\u3068\u3059\u308b\u6307\u5b9a\u3002<\/p>\n\n\n\n
at=\u3067X\u8ef8\u306e\u76ee\u76db\u308a\u306e\u30e9\u30d9\u30eb\u3092\u898f\u5b9a\u3059\u308b\u3002<\/p>\n\n\n\n
0.05, 0.25, 1, 4, 20\u306e5\u3064\u306e\u5024\u3092\u8868\u793a\u3059\u308b\u3088\u3046\u306b\u6307\u793a\u3057\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
0.05, 0.25, 1, 4, 20\u306e\u5bfe\u6570\u306e\u4f4d\u7f6e\u306b\u30010.05, 0.25, 1, 4, 20\u3092\u8868\u793a\u3059\u308b\u3068\u3044\u3046\u6307\u793a\u3060\u3002<\/p>\n\n\n\n
forest<\/span>(<\/span>res.reml,<\/span> atransf=<\/span>exp,<\/span> at=<\/span>log<\/span>(<\/span>c<\/span>(<\/span>.05<\/span>,<\/span>.25<\/span>,<\/span>1<\/span>,<\/span>4<\/span>,<\/span>20<\/span>)))<\/span>\n<\/code><\/pre>\n\n\n\n
\u30b0\u30e9\u30d5\u3092\u898b\u3066\u307f\u308b\u3068\u3001\u6570\u5024\u306f\u771f\u6570\u306e\u30aa\u30c3\u30ba\u6bd40.05, 0.25, 1, 4, 20\u3060\u304c\u3001\u9593\u9694\u306f\u5bfe\u6570\u306b\u306a\u3063\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
0.05\u306820\u30010.25\u30684\u304c\u305d\u308c\u305e\u308c1\u304b\u3089\u540c\u3058\u8ddd\u96e2\u3060\u3002<\/p>\n\n\n\n
\u76ee\u76db\u308a\uff08\u8ddd\u96e2\uff09\u306f\u5bfe\u6570\u3067\u3001\u76ee\u76db\u308a\u306b\u66f8\u3044\u3066\u3042\u308b\u6570\u5024\u306f\u771f\u6570\u3068\u3044\u3046\u3053\u3068\u3060\u3002<\/p>\n\n\n\n
\u63a8\u5b9a\u5024\u306e\u9806\u756a\u306b\u4e26\u3079\u66ff\u3048\u308b\u65b9\u6cd5<\/h2>\n\n\n\n
\u70b9\u63a8\u5b9a\u5024\u306e\u9806\u756a\u306b\u4e26\u3079\u308b\u306b\u306f\u3001order=”obs” \u306e\u6307\u5b9a\u3092\u8ffd\u52a0\u3059\u308b\u3002<\/p>\n\n\n\n
obs\u306fobserved effect size\uff08\u89b3\u5bdf\u3055\u308c\u305f\u52b9\u679c\u306e\u5927\u304d\u3055\uff09\u306e\u7565\u8a9e\u3002<\/p>\n\n\n\n
forest<\/span>(<\/span>res.reml,<\/span> atransf=<\/span>exp,<\/span> at=<\/span>log<\/span>(<\/span>c<\/span>(<\/span>.05<\/span>,<\/span>.25<\/span>,<\/span>1<\/span>,<\/span>4<\/span>,<\/span>20<\/span>)),<\/span> order=<\/span>\"obs\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
\u305d\u3046\u3059\u308b\u3068\u3001\u70b9\u63a8\u5b9a\u5024\u304c\u5c0f\u3055\u3044\uff08\u5de6\uff09\u7814\u7a76\u304b\u3089\u5927\u304d\u3044\uff08\u53f3\uff09\u7814\u7a76\u306e\u9806\u306b\u4e26\u3073\u5909\u308f\u3063\u305f\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u5206\u6563\u304c\u5c0f\u3055\u3044\u9806\u306b\u4e26\u3079\u308b\u65b9\u6cd5<\/h2>\n\n\n\n
\u5206\u6563\u304c\u5c0f\u3055\u3044\u7814\u7a76\u304b\u3089\u5927\u304d\u3044\u7814\u7a76\u306e\u9806\u756a\u306b\u4e26\u3073\u304b\u3051\u308b \u6307\u5b9a\u306forder=”prec”\u3002<\/p>\n\n\n\n
prec\u306fprecision\uff08\u7cbe\u5ea6\uff09\u306e\u7565\u3068\u601d\u308f\u308c\u308b\u3002<\/p>\n\n\n\n
forest<\/span>(<\/span>res.reml,<\/span> atransf=<\/span>exp,<\/span> at=<\/span>log<\/span>(<\/span>c<\/span>(<\/span>.05<\/span>,<\/span>.25<\/span>,<\/span>1<\/span>,<\/span>4<\/span>,<\/span>20<\/span>)),<\/span> order=<\/span>\"prec\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
\u3059\u308b\u3068\u3001\u3053\u306e\u3088\u3046\u306b\u63cf\u753b\u3055\u308c\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u307e\u3068\u3081<\/h2>\n\n\n\n
R \u306e metafor \u30d1\u30c3\u30b1\u30fc\u30b8\u4e2d\u306e\u95a2\u6570 forest() \u3092\u4f7f\u3063\u3066\u3001\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9\u306e\u30d5\u30a9\u30ec\u30b9\u30c8\u30d7\u30ed\u30c3\u30c8\u3092\u66f8\u304f\u65b9\u6cd5\u3092\u89e3\u8aac\u3057\u305f\u3002<\/p>\n\n\n\n
\u53c2\u8003\u306b\u306a\u308c\u3070\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u30e1\u30bf\u30a2\u30ca\u30ea\u30b7\u30b9\u306e\u30d5\u30a9\u30ec\u30b9\u30c8\u30d7\u30ed\u30c3\u30c8\u306e\u66f8\u304d\u65b9\u306e\u89e3\u8aac R \u306e metafor \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3046\u65b9\u6cd5<\/p>\n","protected":false},"author":2,"featured_media":2998,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"swell_btn_cv_data":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[5,95,37,46],"tags":[],"class_list":["post-544","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r","category-95","category-37","category-46"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/best-biostatistics.com\/toukei-er\/wp-content\/uploads\/2018\/07\/20200920212027.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/544","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/comments?post=544"}],"version-history":[{"count":2,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/544\/revisions"}],"predecessor-version":[{"id":3000,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/posts\/544\/revisions\/3000"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/media\/2998"}],"wp:attachment":[{"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/media?parent=544"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/categories?post=544"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/best-biostatistics.com\/toukei-er\/wp-json\/wp\/v2\/tags?post=544"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}