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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,120 +1,120 @@ | ||
| #X = number of successes | ||
| #n = number of trials | ||
| #alpha = pvalues threshold | ||
| #Details: https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Agresti-Coull_interval | ||
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| estimate_binconf = function(X, n, alpha = 0.05){ | ||
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| z = 1-(alpha/2) | ||
| zsqrd = z^2 | ||
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| nt = n + zsqrd | ||
| #pr = X/n | ||
| pr = (1/nt) * (X + (zsqrd/2)) | ||
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| pr_ci_up = pr + z*(sqrt((pr/nt) * (1-pr))) | ||
| pr_ci_low = pr - z*(sqrt((pr/nt) * (1-pr))) | ||
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| data.table::data.table(ci_up = pr_ci_up, ci_low = pr_ci_low) | ||
| } | ||
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| #From https://raw.githubusercontent.com/harrelfe/Hmisc/master/R/binconf.s | ||
| binconf <- function(x, n, alpha = 0.05, | ||
| method = c("wilson","exact","asymptotic","all"), | ||
| include.x = FALSE, include.n = FALSE, | ||
| return.df = FALSE){ | ||
| ## ..modifications for printing and the addition of a | ||
| ## method argument and the asymptotic interval | ||
| ## and to accept vector arguments were | ||
| ## made by Brad Biggerstaff on 10 June 1999 | ||
|
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| method <- match.arg(method) | ||
| bc <- function(x, n, alpha, method) | ||
| { | ||
| nu1 <- 2 * (n - x + 1) | ||
| nu2 <- 2 * x | ||
| ll <- if(x > 0) | ||
| x/(x + qf(1 - alpha/2, nu1, nu2) * (n - x + 1)) | ||
| else | ||
| 0 | ||
|
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||
| nu1p <- nu2 + 2 | ||
| nu2p <- nu1 - 2 | ||
| pp <- if(x < n) | ||
| qf(1 - alpha/2, nu1p, nu2p) | ||
| else | ||
| 1 | ||
|
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| ul <- ((x + 1) * pp)/(n - x + (x + 1) * pp) | ||
| zcrit <- - qnorm(alpha/2) | ||
| z2 <- zcrit * zcrit | ||
| p <- x/n | ||
| cl <- (p + z2/2/n + c(-1, 1) * zcrit * | ||
| sqrt((p * (1 - p) + z2/4/n)/n))/(1 + z2/n) | ||
|
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| if(x == 1) | ||
| cl[1] <- - log(1 - alpha)/n | ||
|
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| if(x == (n - 1)) | ||
| cl[2] <- 1 + log(1 - alpha)/n | ||
|
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| asymp.lcl <- x/n - qnorm(1 - alpha/2) * | ||
| sqrt(((x/n) * (1 - x/n))/n) | ||
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| asymp.ucl <- x/n + qnorm(1 - alpha/2) * sqrt(((x/n) * (1 - x/n) | ||
| )/n) | ||
| res <- rbind(c(ll, ul), cl, c(asymp.lcl, asymp.ucl)) | ||
| res <- cbind(rep(x/n, 3), res) | ||
|
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| ##dimnames(res) <- list(c("Exact", "Wilson", "Asymptotic"), c( | ||
| ## "Point Estimate", "Lower", "Upper")) | ||
| switch(method, | ||
| wilson = res[2, ], | ||
| exact = res[1, ], | ||
| asymptotic = res[3, ], | ||
| all = res, | ||
| res) | ||
| } | ||
|
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||
| if((length(x) != length(n)) & length(x) == 1) | ||
| x <- rep(x, length(n)) | ||
| if((length(x) != length(n)) & length(n) == 1) | ||
| n <- rep(n, length(x)) | ||
| if((length(x) > 1 | length(n) > 1) & method == "all") { | ||
| method <- "wilson" | ||
| warning("method=all will not work with vectors...setting method to wilson") | ||
| } | ||
| if(method == "all" & length(x) == 1 & length(n) == 1) { | ||
| mat <- bc(x, n, alpha, method) | ||
| dimnames(mat) <- list(c("Exact", "Wilson", "Asymptotic"), | ||
| c("PointEst", "Lower", "Upper")) | ||
| if(include.n) | ||
| mat <- cbind(N = n, mat) | ||
|
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| if(include.x) | ||
| mat <- cbind(X = x, mat) | ||
|
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| if(return.df) | ||
| mat <- as.data.frame(mat) | ||
|
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| return(mat) | ||
| } | ||
|
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| mat <- matrix(ncol = 3, nrow = length(x)) | ||
| for(i in 1:length(x)) | ||
| mat[i, ] <- bc(x[i], n[i], alpha = alpha, method = method) | ||
|
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||
| dimnames(mat) <- list(rep("", dim(mat)[1]), | ||
| c("PointEst", "Lower", "Upper")) | ||
| if(include.n) | ||
| mat <- cbind(N = n, mat) | ||
|
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||
| if(include.x) | ||
| mat <- cbind(X = x, mat) | ||
|
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| if(return.df) | ||
| mat <- as.data.frame(mat, row.names=NULL) | ||
|
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||
| mat | ||
| } | ||
| #X = number of successes | ||
| #n = number of trials | ||
| #alpha = pvalues threshold | ||
| #Details: https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Agresti-Coull_interval | ||
|
|
||
| estimate_binconf = function(X, n, alpha = 0.05){ | ||
|
|
||
| z = 1-(alpha/2) | ||
| zsqrd = z^2 | ||
|
|
||
| nt = n + zsqrd | ||
| #pr = X/n | ||
| pr = (1/nt) * (X + (zsqrd/2)) | ||
|
|
||
| pr_ci_up = pr + z*(sqrt((pr/nt) * (1-pr))) | ||
| pr_ci_low = pr - z*(sqrt((pr/nt) * (1-pr))) | ||
|
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||
| data.table::data.table(ci_up = pr_ci_up, ci_low = pr_ci_low) | ||
| } | ||
|
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||
|
|
||
| #From https://raw.githubusercontent.com/harrelfe/Hmisc/master/R/binconf.s | ||
| binconf <- function(x, n, alpha = 0.05, | ||
| method = c("wilson","exact","asymptotic","all"), | ||
| include.x = FALSE, include.n = FALSE, | ||
| return.df = FALSE){ | ||
| ## ..modifications for printing and the addition of a | ||
| ## method argument and the asymptotic interval | ||
| ## and to accept vector arguments were | ||
| ## made by Brad Biggerstaff on 10 June 1999 | ||
|
|
||
| method <- match.arg(method) | ||
| bc <- function(x, n, alpha, method) | ||
| { | ||
| nu1 <- 2 * (n - x + 1) | ||
| nu2 <- 2 * x | ||
| ll <- if(x > 0) | ||
| x/(x + qf(1 - alpha/2, nu1, nu2) * (n - x + 1)) | ||
| else | ||
| 0 | ||
|
|
||
| nu1p <- nu2 + 2 | ||
| nu2p <- nu1 - 2 | ||
| pp <- if(x < n) | ||
| qf(1 - alpha/2, nu1p, nu2p) | ||
| else | ||
| 1 | ||
|
|
||
| ul <- ((x + 1) * pp)/(n - x + (x + 1) * pp) | ||
| zcrit <- - qnorm(alpha/2) | ||
| z2 <- zcrit * zcrit | ||
| p <- x/n | ||
| cl <- (p + z2/2/n + c(-1, 1) * zcrit * | ||
| sqrt((p * (1 - p) + z2/4/n)/n))/(1 + z2/n) | ||
|
|
||
| if(x == 1) | ||
| cl[1] <- - log(1 - alpha)/n | ||
|
|
||
| if(x == (n - 1)) | ||
| cl[2] <- 1 + log(1 - alpha)/n | ||
|
|
||
| asymp.lcl <- x/n - qnorm(1 - alpha/2) * | ||
| sqrt(((x/n) * (1 - x/n))/n) | ||
|
|
||
| asymp.ucl <- x/n + qnorm(1 - alpha/2) * sqrt(((x/n) * (1 - x/n) | ||
| )/n) | ||
| res <- rbind(c(ll, ul), cl, c(asymp.lcl, asymp.ucl)) | ||
| res <- cbind(rep(x/n, 3), res) | ||
|
|
||
| ##dimnames(res) <- list(c("Exact", "Wilson", "Asymptotic"), c( | ||
| ## "Point Estimate", "Lower", "Upper")) | ||
| switch(method, | ||
| wilson = res[2, ], | ||
| exact = res[1, ], | ||
| asymptotic = res[3, ], | ||
| all = res, | ||
| res) | ||
| } | ||
|
|
||
| if((length(x) != length(n)) & length(x) == 1) | ||
| x <- rep(x, length(n)) | ||
| if((length(x) != length(n)) & length(n) == 1) | ||
| n <- rep(n, length(x)) | ||
| if((length(x) > 1 | length(n) > 1) & method == "all") { | ||
| method <- "wilson" | ||
| warning("method=all will not work with vectors...setting method to wilson") | ||
| } | ||
| if(method == "all" & length(x) == 1 & length(n) == 1) { | ||
| mat <- bc(x, n, alpha, method) | ||
| dimnames(mat) <- list(c("Exact", "Wilson", "Asymptotic"), | ||
| c("PointEst", "Lower", "Upper")) | ||
| if(include.n) | ||
| mat <- cbind(N = n, mat) | ||
|
|
||
| if(include.x) | ||
| mat <- cbind(X = x, mat) | ||
|
|
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| if(return.df) | ||
| mat <- as.data.frame(mat) | ||
|
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| return(mat) | ||
| } | ||
|
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||
| mat <- matrix(ncol = 3, nrow = length(x)) | ||
| for(i in 1:length(x)) | ||
| mat[i, ] <- bc(x[i], n[i], alpha = alpha, method = method) | ||
|
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||
| dimnames(mat) <- list(rep("", dim(mat)[1]), | ||
| c("PointEst", "Lower", "Upper")) | ||
| if(include.n) | ||
| mat <- cbind(N = n, mat) | ||
|
|
||
| if(include.x) | ||
| mat <- cbind(X = x, mat) | ||
|
|
||
| if(return.df) | ||
| mat <- as.data.frame(mat, row.names=NULL) | ||
|
|
||
| mat | ||
| } |
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