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#' @title The 1xc table CIs
#' @param n the observed counts (a 1xc vector, where c is the number of categories)
#' @param alpha the nominal level, e.g. 0.05 for 95# CIs
#' @examples
#' # Genotype counts for SNP rs 6498169 in RA patients
#' the_1xc_table_CIs(n = snp6498169$complete$n)
#' @export
#' @return NULL. This function should be called for its printed output
the_1xc_table_CIs <- function(n, alpha = 0.05) {
validateArguments(mget(ls()))
# ======================================================== #
# Ad-hoc function to print output #
# ======================================================== #
myprint <- function(txt, ...) cat(sprintf(txt, ...), "\n")
# ======================================================== #
# Output #
# ======================================================== #
c0 <- length(n)
myprint("Interval method Simultaneous CIs width")
myprint("----------------------------------------------------------")
res1 <- Gold_Wald_CIs_1xc(n, alpha)
res2 <- Goodman_Wald_CIs_1xc(n, alpha)
res3 <- QuesenberryHurst_Wilson_score_CIs_1xc(n, alpha)
res4 <- Goodman_Wilson_score_CIs_1xc(n, alpha)
for (i in 1:c0) {
myprint("Estimate of pi_%i: %6.4f", i, res1$estimate[i])
myprint(
"Gold Wald %6.4f to %6.4f %6.4f",
res1$lower[i], res1$upper[i], res1$upper[i] - res1$lower[i]
)
myprint(
"Goodman Wald %6.4f to %6.4f %6.4f",
res2$lower[i], res2$upper[i], res2$upper[i] - res2$lower[i]
)
myprint(
"Quesenberry-Hurst Wilson score %6.4f to %6.4f %6.4f",
res3$lower[i], res3$upper[i], res3$upper[i] - res3$lower[i]
)
myprint(
"Goodman Wilson score %6.4f to %6.4f %6.4f",
res4$lower[i], res4$upper[i], res4$upper[i] - res4$lower[i]
)
}
myprint("----------------------------------------------------------")
print(Goodman_Wald_CIs_for_diffs_1xc(n, alpha, "Bonferroni"))
invisible(NULL)
}
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