{"id":269,"date":"2022-08-12T18:39:45","date_gmt":"2022-08-12T09:39:45","guid":{"rendered":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/correlateion-coefficient-difference-test\/"},"modified":"2025-01-05T20:40:42","modified_gmt":"2025-01-05T11:40:42","slug":"correlateion-coefficient-difference-test","status":"publish","type":"post","link":"https:\/\/best-biostatistics.com\/toukei-er\/entry\/correlateion-coefficient-difference-test\/","title":{"rendered":"R \u3067\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092\u884c\u3046\u65b9\u6cd5"},"content":{"rendered":"\n

\u76f8\u95a2\u4fc2\u6570\u306e\u6bd4\u8f03\u306f\u3069\u3046\u3084\u308b\u304b\uff1f<\/p>\n\n\n\n

\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3068\u306f\uff1f<\/p>\n\n\n\n\n\n\n\n

\u76f8\u95a2\u4fc2\u6570\u306e\u6bd4\u8f03\u3000\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a<\/h2>\n\n\n\n

\uff08\u3053\u306e\u8a18\u4e8b\u3067\u8a00\u3046\u76f8\u95a2\u4fc2\u6570\u306f\u3001\u3059\u3079\u3066Pearson\u306e\u7a4d\u7387\u76f8\u95a2\u4fc2\u6570\u3092\u6307\u3057\u3066\u3044\u308b\uff09<\/p>\n\n\n\n

\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u306f\u3001\u4ee5\u4e0b\u306e\u691c\u5b9a\u7d71\u8a08\u91cf T \u3092\u8a08\u7b97\u3057\u3001\u6a19\u6e96\u6b63\u898f\u5206\u5e03\u3067\u6709\u610f\u78ba\u7387\u3092\u6c42\u3081\u308b\u3002<\/p>\n\n\n\n

\u5e30\u7121\u4eee\u8aac\u306f\u300c\uff12\u3064\u306e\u6bcd\u76f8\u95a2\u4fc2\u6570\u306f\u7b49\u3057\u3044\u300d \u3060\u3002<\/p>\n\n\n\n

$$ T = \\frac{\\frac{1}{2}\\log{\\frac{1+r_A}{1-r_A}} – \\frac{1}{2}\\log{\\frac{1+r_B}{1-r_B}}}{\\sqrt{\\frac{1}{n_A – 3} + \\frac{1}{n_B – 3}}} $$<\/p>\n\n\n\n\n\n\n\n

\u3053\u3053\u3067 $ r_A $, $ n_A $ \u306f\u3001\u76f8\u95a2\u4fc2\u6570A\u3068\u305d\u306e\u30b5\u30f3\u30d7\u30eb\u30b5\u30a4\u30ba\u3001$ r_B $, $ n_B $ \u306f\u3001\u76f8\u95a2\u4fc2\u6570B\u3068\u305d\u306e\u30b5\u30f3\u30d7\u30eb\u30b5\u30a4\u30ba\u3067\u3042\u308b\u3002<\/p>\n\n\n\n

\u5206\u5b50\u306f\u3001\u5404\u7fa4\u306e\u76f8\u95a2\u4fc2\u6570\u3092Fisher\u306e\uff5a\u5909\u63db\u3092\u3057\u305f\u3082\u306e\u540c\u58eb\u306e\u5f15\u304d\u7b97\u306b\u306a\u3063\u3066\u3044\u308b\u3002<\/p>\n\n\n\n

Fisher\u306e\uff5a\u5909\u63db\u306f\u3001\u76f8\u95a2\u4fc2\u6570\u3092\u6b63\u898f\u8fd1\u4f3c\u3055\u305b\u308b\u305f\u3081\u306e\u5909\u63db\u3067\u3042\u308b\u3002<\/p>\n\n\n\n

\u3053\u306e\u691c\u5b9a\u7d71\u8a08\u91cf\u304c\u3001\u6a19\u6e96\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3046\u3068\u3057\u3066\u3001\u6709\u610f\u78ba\u7387\u3092\u6c42\u3081\u308b\u3002<\/p>\n\n\n\n

R\u3067function\u3092\u4f5c\u3063\u3066\u307f\u308b\u3068\u4ee5\u4e0b\u306e\u901a\u308a\u3002<\/p>\n\n\n\n

cor.diff.test <- function(nA, rA, nB, rB,\n                          alternative=c(\"two.sided\",\"one.sided\")){\n  data.name <- sprintf(\"\\nnA=%s, rA=%s\\nnB=%s, rB=%s\",\n                       nA, rA, nB, rB)\n  alternative <- match.arg(alternative)\n  tside <- switch(alternative, one.sided=1, two.sided=2)\n  zA <- 1\/2*log((1+rA)\/(1-rA))\n  zB <- 1\/2*log((1+rB)\/(1-rB))\n  ZTRANS <- c(zA, zB)\n  names(ZTRANS) <- c(\"Fisher z-transformation: zA\",\n                     \"Fisher z-transformation: zB\")\n  STATISTICS <- abs((zA-zB)\/sqrt(1\/(nA-3)+1\/(nB-3)))\n  names(STATISTICS) <- \"T\"\n  PVAL <- pnorm(STATISTICS, lower.tail=F)*tside\n  METHOD <- \"Correlation Coefficients Difference Test\"\n  structure (list(statistics=STATISTICS, p.value=PVAL,\n                  estimate=ZTRANS, alternative=alternative,\n                  data.name=data.name, method=METHOD), class=\"htest\")\n}\n<\/code><\/pre>\n\n\n\n
nA=30, rA=-0.459, nB=24, rB=-0.097\u3068\u3057\u305f\u6642\u306e\u691c\u5b9a\u7d50\u679c\u306f\u4ee5\u4e0b\u306e\u901a\u308a\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u6709\u610f\u6c34\u6e965\uff05\u3068\u3059\u308b\u3068\u3001\u7d71\u8a08\u5b66\u7684\u6709\u610f\u306b\u5dee\u304c\u3042\u308b\u3068\u306f\u8a00\u3048\u306a\u304b\u3063\u305f\u3002<\/p>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092\u30a8\u30af\u30bb\u30eb\u3067\u3067\u304d\u306a\u3044\u304b\uff1f<\/h2>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092\u30a8\u30af\u30bb\u30eb\u3067\u8a08\u7b97\u3067\u304d\u308b\u3088\u3046\u306b\u30a8\u30af\u30bb\u30eb\u30d5\u30a1\u30a4\u30eb\u3092\u4f5c\u6210\u3057\u305f\u3002<\/p>\n\n\n\n
\u3088\u3051\u308c\u3070\u3069\u3046\u305e\u3002<\/p>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3010\u30a8\u30af\u30bb\u30eb\u8a08\u7b97\u6a5f\u3011 | TKER SHOP<\/a><\/p>\n\n\n\n
Reference: Fisher, R. A. (1925). Statistical methods for research workers<\/em>. Edinburgh, Scotland: Oliver and Boyd. <\/a><\/p>\n\n\n\n
\u5177\u4f53\u7684\u306b\u306f\u3001\u3053\u3061\u3089\u306e\u66f8\u7c4d\u3092\u53c2\u8003\u306b\u3057\u3066\u3044\u308b \u2192 \u533b\u5b66\u3078\u306e\u7d71\u8a08\u5b66 (\u7d71\u8a08\u30e9\u30a4\u30d6\u30e9\u30ea\u30fc)<\/a><\/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>
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092R\u3067\u3082\u3063\u3068\u7c21\u5358\u306b\u3067\u304d\u306a\u3044\u304b\uff1f<\/h2>\n\n\n\n
\u7d71\u8a08\u30bd\u30d5\u30c8R\u306e cocor \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3046\u3068\u3001\u6bd4\u8f03\u7684\u7c21\u5358\u306b\u3067\u304d\u308b\u3002<\/p>\n\n\n\n
\u307e\u305a\u3001cocor \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3002<\/p>\n\n\n\n
\u7d71\u8a08\u30bd\u30d5\u30c8R\u306e\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u4ee5\u4e0b\u3092\u66f8\u3044\u3066\u30a8\u30f3\u30bf\u30fc\u3002<\/p>\n\n\n\n
install.packages<\/span>(<\/span>\"cocor\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
Japan\u3092\u9078\u3093\u3067OK\u3092\u30af\u30ea\u30c3\u30af\u3059\u308b\u3068\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3055\u308c\u308b\u3002<\/p>\n\n\n\n
cocor \u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u3046\u3068\u304d\u306f\u3001library(cocor)\u3067\u547c\u3073\u51fa\u3059\u3002<\/p>\n\n\n\n
library<\/span>(<\/span>cocor)<\/span>\n<\/code><\/pre>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092\u3059\u308b\u3068\u304d\u306f\u3001cocor.indep.groups()\u95a2\u6570\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n
\u4e0a\u8a18\u306e\u8a2d\u5b9a\u3068\u540c\u3058\u8a2d\u5b9a\u3067\u8a08\u7b97\u3057\u3066\u307f\u308b\u3068\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
fisher1925\u3068\u3042\u308b\u3068\u3053\u308d\u304c\u540c\u3058\u7d50\u679c\uff08p-value = 0.1706\uff09\u306b\u306a\u3063\u3066\u3044\u308b\u306e\u304c\u308f\u304b\u308b\u3002<\/p>\n\n\n\n
95\uff05\u4fe1\u983c\u533a\u9593\u3082\u8a08\u7b97\u3055\u308c\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
\u3053\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u30de\u30cb\u30e5\u30a2\u30eb\u3092\u898b\u3066\u3044\u305f\u3068\u3053\u308d\u3001\u3053\u306e\u8a08\u7b97\u306f\u3001\u5b8c\u5168\u306b\u72ec\u7acb\u306a\u76f8\u95a2\u4fc2\u6570\u306e\u691c\u5b9a\u306e\u5834\u5408\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u3063\u305f\u3002<\/p>\n\n\n\n
Reference: Fisher, R. A. (1925). Statistical methods for research workers<\/em>. Edinburgh, Scotland: Oliver and Boyd. <\/a><\/p>\n\n\n\n
psych \u30d1\u30c3\u30b1\u30fc\u30b8\u306e r.test \u3092\u4f7f\u3046\u65b9\u6cd5<\/h3>\n\n\n\n
\u4e0a\u8a18\u3068\u540c\u3058\u3053\u3068\u3092 psych \u30d1\u30c3\u30b1\u30fc\u30b8\u306e r.test \u3092\u4f7f\u3046\u3068\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308b<\/p>\n\n\n\n
install.packages(\"psych\") # \u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306f\u6700\u521d\u306e\u4e00\u56de\u3060\u3051\nlibrary(psych)\nr.test(n=30, r12=-0.459, n2=24, r34=-0.097)<\/code><\/pre>\n\n\n\n
\u7d50\u679c\u306f\u4ee5\u4e0b\u306e\u3068\u304a\u308a\u3001\u691c\u5b9a\u7d71\u8a08\u91cf z \u3068 P \u5024\u304c\u540c\u3058\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308b<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u306e\u30d1\u30c3\u30b1\u30fc\u30b8 cocor \u3092\u4f7f\u3044\u3053\u306a\u3059<\/h2>\n\n\n\n
cocor \u30d1\u30c3\u30b1\u30fc\u30b8\u306f\u3001\u96c6\u8a08\u5024\u3092\u4f7f\u3046\u65b9\u6cd5\u3082\u3067\u304d\u308c\u3070\u3001\u751f\u30c7\u30fc\u30bf\u304b\u3089\u306e\u89e3\u6790\u3082\u3067\u304d\u308b\u512a\u308c\u3082\u306e\u3060\u3002<\/p>\n\n\n\n
\u5834\u5408\u5206\u3051\u3092\u3057\u3066\u3001\u4f7f\u3044\u65b9\u3092\u307e\u3068\u3081\u3066\u307f\u3088\u3046\u3068\u601d\u3046\u3002<\/p>\n\n\n\n
\u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\u306f\u3001cocor \u30d1\u30c3\u30b1\u30fc\u30b8\u306b\u542b\u307e\u308c\u3066\u3044\u308b aptitude \u3068\u3044\u3046\u30c7\u30fc\u30bf\u3092\u7528\u3044\u308b\u3002<\/p>\n\n\n\n
data<\/span>(<\/span>\"aptitude\"<\/span>)<\/span>\n<\/code><\/pre>\n\n\n\n
\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f\u3001\u5185\u90e8\u7684\u306b\u4e8c\u3064\u306b\u5206\u304b\u308c\u3066\u304a\u308a\u3001\u7279\u6b8a\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u308a\u65b9\u306f\u8abf\u3079\u305f\u304c\u308f\u304b\u3089\u306a\u304b\u3063\u305f\u3002<\/p>\n\n\n\n
\u3057\u304b\u3057\u3001\u96c6\u8a08\u3057\u305f\u5f8c\u306b\u3001\u96c6\u8a08\u5024\u3092\u4f7f\u3046\u95a2\u6570 cocor.indep.groups() \u306b\u5165\u529b\u3059\u308c\u3070\u8a08\u7b97\u53ef\u80fd\u3060\uff08\u6b21\u306e\u30bb\u30af\u30b7\u30e7\u30f3\u306b\u8a18\u8f09\u3042\u308a\uff09\u3002<\/p>\n\n\n\n
\u540c\u3058\u9805\u76ee\u306e\u76f8\u95a2\u4fc2\u6570\u3092\u7fa4\u9593\u6bd4\u8f03\u3057\u305f\u3044\u5834\u5408<\/h3>\n\n\n\n
apitude\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306elogic\u3068intelligence.a\u306e\u76f8\u95a2\u4fc2\u6570\u3092\u3001sample1\u3068sample2\u3067\u6bd4\u8f03\u3059\u308b\u5f62\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
Sample1\u306e\u76f8\u95a2\u4fc2\u6570\u304c0.3213, Sample2\u306e\u76f8\u95a2\u4fc2\u6570\u304c0.2024\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\u305d\u308c\u305e\u308c\u306e\u30b5\u30f3\u30d7\u30eb\u30b5\u30a4\u30ba\u306f\u3001n1=291, n2=334\u3067\u3042\u308b\u3002<\/p>\n\n\n\n
\u3053\u308c\u306f\u72ec\u7acb\uff12\u7fa4\uff08Sample1\u3068Sample2\uff09\u3067\u3042\u308b\u306e\u3067\u3001fisher1925\u306e\u65b9\u6cd5\u3067\u8a08\u7b97\u3055\u308c\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
\u3053\u308c\u3092 cocor.indep.groups()\u3092\u4f7f\u3063\u3066\u307f\u308b\u3068\u3001\u307b\u307c\u540c\u3058\u7d50\u679c\u306b\u306a\u308b\u3002<\/p>\n\n\n\n
\u5c0f\u6570\u70b9\u4ee5\u4e0b\uff14\u6841\u3088\u308a\u4e0b\u3092\u7aef\u6298\u3063\u3066\u3044\u308b\u306e\u3067\u5c11\u3057\u3060\u3051\u6570\u5024\u306f\u7570\u306a\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u540c\u3058\u30b5\u30f3\u30d7\u30eb\u306e\u7570\u306a\u308b\u76f8\u95a2\u4fc2\u6570\u3092\u6bd4\u8f03\u3057\u305f\u3044\u5834\u5408\uff08\uff12\u3064\u306e\u5909\u6570\u306e\u3046\u3061\uff11\u3064\u306f\u540c\u3058\uff09<\/h3>\n\n\n\n
\u540c\u3058\u30b5\u30f3\u30d7\u30eb\u3067\u3001\u7570\u306a\u308b\u76f8\u95a2\u4fc2\u6570\u3092\u6bd4\u8f03\u3057\u305f\u3044\u304c\u3001\u5b8c\u5168\u306b\u72ec\u7acb\u3067\u306f\u306a\u304f\u3001\u76f8\u95a2\u4fc2\u6570\u3092\u8a08\u7b97\u3057\u3066\u3044\u308b\uff12\u3064\u306e\u5909\u6570\u306e\u3046\u3061\uff11\u3064\u306f\u540c\u3058\u5834\u5408\u306f\u3069\u3046\u3059\u308c\u3070\u3088\u3044\u304b\uff1f<\/p>\n\n\n\n
\u4f8b\u3068\u3057\u3066\u3001intelligence.a \u3068 knowledge\u3001intelligence.a \u3068 logic \u3092\u6bd4\u8f03\u3059\u308b\u3002<\/p>\n\n\n\n
intelligence.a \u304c\u91cd\u8907\u3057\u3066\u3044\u308b\u3002<\/p>\n\n\n\n
\u751f\u30c7\u30fc\u30bf\u304b\u3089\u8a08\u7b97\u3059\u308b\u5834\u5408\u306f\u3001cocor()\u3067\u8a08\u7b97\u3067\u304d\u308b\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
\u8a08\u7b97\u3059\u308b\u3068\u9a5a\u304f\u3053\u3068\u306b\u3001\u5408\u8a08\uff19\u3064\u306e\u691c\u5b9a\u7d50\u679c\u304c\u51fa\u3066\u304f\u308b\u3002<\/p>\n\n\n\n
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\u3053\u308c\u3092\u96c6\u8a08\u5024\u3067\u8a08\u7b97\u3059\u308b\u5834\u5408\u306f\u3001cocor.dep.groups.overlap()\u95a2\u6570\u3092\u4f7f\u3046\u3002<\/p>\n\n\n\n
\"\"<\/figure>\n\n\n\n
<\/span><\/p>\n\n\n\n
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\"\"<\/figure>\n\n\n\n
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\"\"<\/figure>\n\n\n\n
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\"\"<\/figure>\n\n\n\n
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\"\"<\/figure>\n\n\n\n
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Pearson\u304c\u767a\u8868\u3057\u305f1898\u5e74\u304b\u3089100\u5e74\u4ee5\u4e0a\u3082\u7d4c\u904e\u3057\u3066\u3044\u308b\u89e3\u6790\u624b\u6cd5\u306b\u3082\u304b\u304b\u308f\u3089\u305a\u3001EZR\u3084SPSS\u306b\u5b9f\u88c5\u3055\u308c\u3066\u3044\u306a\u3044\u3002<\/p>\n\n\n\n
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Fisher\u304c1925\u5e74\u306b\u767a\u8868\u3057\u305f\u72ec\u7acb\u306a\uff12\u3064\u306e\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3067\u3001\u3069\u306e\u3068\u304d\u3082\u5927\u5dee\u306a\u3044\u7d50\u679c\u304c\u5f97\u3089\u308c\u308b\u306e\u3067\u3001\u3069\u308c\u3092\u4f7f\u3048\u3070\u3088\u3044\u306e\u304b\u60a9\u3080\u3068\u304d\u306f\u3001Fisher\u306e\u65b9\u6cd5\u3092\u63a1\u7528\u3059\u308c\u3070\u3088\u3044\u306e\u304b\u3082\u3057\u308c\u306a\u3044\u3002<\/p>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u3092\u30a8\u30af\u30bb\u30eb\u3067\uff08Fisher 1925 \u306e\u65b9\u6cd5\uff09<\/h2>\n\n\n\n
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\u3088\u3051\u308c\u3070\u3069\u3046\u305e\u3002<\/p>\n\n\n\n
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Reference: Fisher, R. A. (1925). Statistical methods for research workers<\/em>. Edinburgh, Scotland: Oliver and Boyd. <\/a><\/p>\n\n\n\n
\u5177\u4f53\u7684\u306b\u306f\u3001\u3053\u3061\u3089\u306e\u66f8\u7c4d\u3092\u53c2\u8003\u306b\u3057\u3066\u3044\u308b \u2192 \u533b\u5b66\u3078\u306e\u7d71\u8a08\u5b66 (\u7d71\u8a08\u30e9\u30a4\u30d6\u30e9\u30ea\u30fc)<\/a><\/p>\n\n\n\n
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\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u30a2\u30d7\u30ea\u3010Win \u7248\u3011<\/a><\/p>\n\n\n\n
\u76f8\u95a2\u4fc2\u6570\u306e\u5dee\u306e\u691c\u5b9a\u30a2\u30d7\u30ea\u3010Mac \u7248\u3011<\/a><\/p>\n\n\n\n
\u53c2\u8003PDF\uff08cocor\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u30de\u30cb\u30e5\u30a2\u30eb\uff09<\/h2>\n\n\n\n
https:\/\/cran.r-project.org\/web\/packages\/cocor\/cocor.pdf<\/a><\/p>\n\n\n\n
\u53c2\u8003\u66f8\u7c4d<\/h2>\n\n\n\n
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