# This example code is written for analyses of the ovarian cancer dataset adopted in Royston and White (2011; Journal of Statistical Software 45: Issue 4).
# The article page of Journal of Statistical Software: https://www.jstatsoft.org/article/view/v045i04/
# The ovarian cancer dataset ("ovariancancer.dta") can be downloaded from https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v045i04/ovariancancer.dta

require(mice)
require(survival)
require(foreign)

tgc <- read.dta(file="ovariancancer.dta")

head(tgc)
N <- dim(tgc)[1]

attach(tgc)

log_ca125 <- log(ca125)
log_alp <- log(alp)

grade <- factor(grade, levels=c("well differentiated", "moderately differentiated", "poorly differentiated"))
histol <- factor(histol, levels=c("Serous papillary", "Adenocarcinoma", "Endometrioid", "Mesonephroid (clear cell)", "Mixed mesodermal", "Mucinous", "Undifferentiated" ))
resdis <- factor(resdis, levels=c(">5 cm",  "2-5 cm", "<2 cm"))

t <- tgc[,20] - tgc[,21]
d <- tgc[,19]

tgce <- data.frame(patno, age, figo, grade, histol, ascites, ps, resdis, log_ca125, log_alp, d, t)

detach(tgc)

####

# Model 1: Complete-Case Analysis

ph1 <- coxph(Surv(t, d) ~ age + figo + grade + histol + ascites + ps + resdis + log_ca125 + log_alp, data=tgce)
summary(ph1)

# Model 2: mice

predmt1 <- (1 - diag(1, ncol(tgce)))
predmt1[c(1,11,12),] <- predmt1[,c(1,11,12)] <- 0

imp.tgce <- mice(tgce, m=200, predictorMatrix=predmt1, seed=34871)
	# m は、代入値の組の数（デフォルトでは5であるが、ここでは200としている）
	# predictorMatrixで、予測モデルに含める変数の組を指定している
	# methodで、代入値の生成方法を指定できる。特に指定しなければ、デフォルトの方法を採用。
	# seedは、乱数のシード

print(imp.tgce)

complete(imp.tgce, 5)   # 5番目のimputed datasetを出力

ph2 <- with(imp.tgce, coxph(Surv(t, d) ~ age + figo + grade + histol + ascites + ps + resdis + log_ca125 + log_alp))
  # 補完後のデータセット（M組）の解析；Cox回帰

pool2 <- pool(ph2)
round(summary(pool2),3)
  # M組の解析結果の統合と結果の表⽰