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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,105 @@ | ||
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| ###------------------------MICE.IMPUTE.NORM.BB---------------------- | ||
| mice.impute.norm.bb <- function(y, ry, x, ridge=0.00001, ...) | ||
| { | ||
| # mice.impute.norm.bb | ||
| # Regression imputations of y given x, with a fixed regression | ||
| # line, and with random draws of the residuals around the line. | ||
| # Bayesian bootstrap | ||
| # | ||
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| x <- cbind(1, as.matrix(x)) | ||
| xobs <- x[ry,] | ||
| yobs <- y[ry] | ||
| n1 <- sum(ry) | ||
| n0 <- sum(!ry) | ||
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| # do here the Bayesian bootstap Rubin p. 124 | ||
| u <- runif(n1-1) | ||
| u <- diff(c(0,u[order(u)],1)) | ||
| s <- sample(n1, n1, replace=TRUE, prob=u) | ||
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| dotxobs <- xobs[s,] | ||
| dotyobs <- yobs[s] | ||
| xtx <- t(dotxobs) %*% dotxobs | ||
| pen <- ridge * diag(xtx) | ||
| if (length(pen)==1) pen <- matrix(pen) | ||
| v <- solve(xtx + diag(pen)) | ||
| coef <- t(dotyobs %*% dotxobs %*% v) | ||
| residuals <- dotyobs - dotxobs %*% coef | ||
| sigma <- sqrt((sum(residuals^2))/(n1-ncol(x)-1)) | ||
| parm <- list(coef, sigma) | ||
| names(parm) <- c("beta", "sigma") | ||
| return(x[!ry, ] %*% parm$beta + rnorm(n0) * parm$sigma) | ||
| } | ||
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| mice.impute.normdump <- function (y, ry, x, ...) | ||
| { | ||
| x <- cbind(1, as.matrix(x)) | ||
| parm <- .norm.draw(y, ry, x, ...) | ||
| betadump <<- c(betadump,parm$beta) | ||
| return(x[!ry, ] %*% parm$beta + rnorm(sum(!ry)) * parm$sigma) | ||
| } | ||
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| mice.impute.pmmdump <- function (y, ry, x, ...) | ||
| { | ||
| x <- cbind(1, as.matrix(x)) | ||
| parm <- .norm.draw(y, ry, x, ...) | ||
| yhatobs <- x[ry, ] %*% parm$coef | ||
| yhatmis <- x[!ry, ] %*% parm$beta | ||
| betadump <<- c(betadump,parm$beta) | ||
| return(apply(as.array(yhatmis), 1, .pmm.match, yhat = yhatobs, | ||
| y = y[ry], ...)) | ||
| } | ||
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| #-------------------------MICE.IMPUTE.2L.NORM.BOOT-------------------- | ||
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| mice.impute.2L.norm.boot <- function(y, ry, x, type, intercept=FALSE, ...) | ||
| { | ||
| # | ||
| # Bootstrap version of mice.impute.2L.norm | ||
| # | ||
| # Author: Stef van Buuren, 2011 | ||
| # | ||
| n.class <- length(unique(x[, type==(-2)])) | ||
| s1 <- sample(n.class, n.class, replace=TRUE) | ||
| dotx <- | ||
| gf.full <- factor(x[,type==(-2)], labels=1:n.class) | ||
| gf <- gf.full[ry] | ||
| n.g <- tabulate(gf) | ||
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| ## draw a bootstrap sample for yobs and xobs | ||
| xobs <- x[ry,] | ||
| yobs <- y[ry] | ||
| n1 <- sum(ry) | ||
| n0 <- sum(!ry) | ||
| s <- sample(n1, n1, replace=TRUE) | ||
| doty <- y | ||
| doty[ry] <- yobs[s] | ||
| dotx <- x | ||
| dotx[ry,] <- xobs[s,] | ||
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| x <- dotx | ||
| y <- doty | ||
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| ## append intercept | ||
| if (intercept) { | ||
| x <- cbind(1, as.matrix(x)) | ||
| type <- c(2, type) | ||
| } | ||
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| expr <- expression(glm.fit(x[ry, ], y[ry], | ||
| family = binomial(link = logit))) | ||
| fit <- suppressWarnings(eval(expr)) | ||
| beta.star <- beta <- coef(fit) | ||
| p <- 1/(1 + exp(-(x[!ry,] %*% beta.star))) | ||
| vec <- (runif(nrow(p)) <= p) | ||
| vec[vec] <- 1 | ||
| if (is.factor(y)) { | ||
| vec<-factor(vec,c(0,1),levels(y))} | ||
| return(vec) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,9 +1,11 @@ | ||
| book_filename: "FIMD-bookdown" | ||
| delete_merged_file: true | ||
| language: | ||
| label: | ||
| def: 'Algorithm ' | ||
| ui: | ||
| chapter_name: "Chapter " | ||
| rmd_files: ["index.Rmd", "01-introduction.Rmd", "02-multiple-imputation.Rmd", "05-analysis.Rmd", "13-references.Rmd"] | ||
| rmd_files: ["index.Rmd", "01-introduction.Rmd", "02-multiple-imputation.Rmd", "03-univariate-missing.Rmd", "05-analysis.Rmd", "13-references.Rmd"] | ||
| before_chapter_script: "R/before_chapter_script.R" | ||
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| # rmd_files: ["index.Rmd", "01-introduction.Rmd", "02-multiple-imputation.Rmd", "05-analysis.Rmd"] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,14 +1,24 @@ | ||
| p.caption { | ||
| color: #777; | ||
| margin-top: 10px; | ||
| } | ||
| p code { | ||
| white-space: inherit; | ||
| } | ||
| pre { | ||
| word-break: normal; | ||
| word-wrap: normal; | ||
| } | ||
| pre code { | ||
| white-space: inherit; | ||
| } | ||
| h1 { | ||
| color: #006CC2B3; | ||
| } | ||
| h2 { | ||
| color: #006CC2B3; | ||
| } | ||
| h3 { | ||
| color: #006CC2B3; | ||
| } | ||
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| .caption { | ||
| color: #006CC2B3; | ||
| margin-top: 10px; | ||
| } | ||
| p code { | ||
| white-space: inherit; | ||
| } | ||
| pre { | ||
| word-break: normal; | ||
| word-wrap: normal; | ||
| } | ||
| pre code { | ||
| white-space: inherit; | ||
| } |
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