Confidence intervals for the single binomial or Poisson rate. Including SCAS or Jeffreys intervals, with or without continuity adjustment, and 'exact' Clopper-Pearson/Garwood or mid-p intervals. This function is vectorised in x, n.
rateci(x, n, distrib = "bin", level = 0.95, cc = FALSE)A list containing, for each method, a matrix containing lower and upper confidence limits and point estimate of p for each value of x and n. Methods shown depend on the cc parameter, which specifies whether the continuity adjustment is applied to the SCAS and Jeffreys methods. The corresponding 'exact' method is Clopper-Pearson/Garwood if cc = TRUE and mid-p if cc = FALSE. The last list item contains details of the function call.
Numeric vector of number of events.
Numeric vector of sample size (for binomial rate) or exposure times (for Poisson rate).
Character string indicating distribution assumed for the input data: "bin" = binomial (default), "poi" = Poisson.
Number specifying confidence level (between 0 and 1, default 0.95).
Number or logical (default FALSE) specifying continuity adjustment.
Pete Laud, p.j.laud@sheffield.ac.uk
Laud PJ. Equal-tailed confidence intervals for comparison of rates. Pharmaceutical Statistics 2017; 16:334-348. (Appendix A.4)
Brown LD, Cai TT and DasGupta A. Interval estimation for a binomial proportion. Statistical Science 2001; 16(2):101-133.