blob: 5410b3bfe0712298e0176594f8234b953b97522a [file] [log] [blame]
#' Add confidence interval and relative frequency variables
#'
#' Using \code{\link{prop.test}}, \code{ci} adds three columns to a data frame:
#' 1. relative frequency (\code{f})
#' 2. lower bound of a confidence interval (\code{ci.low})
#' 3. upper bound of a confidence interval
#'
#'
#' @seealso
#' \code{ci} is alread included in \code{\link{frequencyQuery}}
#'
#' @param df table with columns for absolute and total frequencies.
#' @param x column with the observed absolute frequency.
#' @param N column with the total frequncies
#' @param conf.level confidence level of the returned confidence interval. Must
#' be a single number between 0 and 1.
#'
#' @export
#' @importFrom stats prop.test
#' @importFrom tibble remove_rownames
#' @importFrom dplyr enquo rename starts_with
#' @examples
#' library(ggplot2)
#' kco <- new("KorAPConnection", verbose=TRUE)
#' expand_grid(year=2015:2018, alternatives=c("Hate Speech", "Hatespeech")) %>%
#' bind_cols(corpusQuery(kco, .$alternatives, sprintf("pubDate in %d", .$year))) %>%
#' mutate(total=corpusStats(kco, vc=vc)$tokens) %>%
#' ci() %>%
#' ggplot(aes(x=year, y=f, fill=query, color=query, ymin=conf.low, ymax=conf.high)) +
#' geom_point() + geom_line() + geom_ribbon(alpha=.3)
#'
ci <- function(df, x = totalResults, N = total, conf.level = 0.95) {
x <- enquo(x)
N <- enquo(N)
df %>%
rowwise %>%
mutate(tst = list(broom::tidy(prop.test(!!x, !!N, conf.level = conf.level)) %>%
select("estimate", "conf.low", "conf.high") %>%
rename(f = estimate)
)) %>%
tidyr::unnest(tst)
}
## Mute notes: "Undefined global functions or variables:"
globalVariables(c("totalResults", "total", "estimate", "tst"))
# ci.old <- function(df, x = totalResults, N = total, conf.level = 0.95) {
# x <- deparse(substitute(x))
# N <- deparse(substitute(N))
# df <- data.frame(df)
# df$f <- df[,x] / df[,N]
# df[, c("conf.low", "conf.high")] <- t(sapply(Map(function(a, b) prop.test(a, b, conf.level = conf.level), df[,x], df[,N]), "[[","conf.int"))
# return(df)
# }