presize (version 0.3.9)

prec_or: Sample size or precision for an odds ratio

Description

prec_or returns the sample size or the precision for the provided proportions.

Usage

prec_or(
  p1,
  p2,
  n1 = NULL,
  r = 1,
  conf.width = NULL,
  conf.level = 0.95,
  method = c("gart", "woolf", "indip_smooth"),
  ...
)

Value

Object of class "presize", a list of arguments (including the computed one) augmented with method and note elements.

Arguments

p1

risk among exposed.

p2

risk among unexposed.

n1

number of patients in exposed group.

r

allocation ratio (relative size of unexposed and exposed cohort (n2 / n1)).

conf.width

precision (the full width of the confidence interval).

conf.level

confidence level.

method

Exactly one of indip_smooth (default), gart, or woolf. Methods can be abbreviated.

...

other arguments to uniroot (e.g. tol).

Details

Exactly one of the parameters n1 or conf.width must be passed as NULL, and that parameter is determined from the other.

Woolf (woolf), Gart (gart), and Independence-smoothed logit (indip_smooth) belong to a general family of adjusted confidence intervals, adding 0 (woolf) to each cell, 0.5 (gart) to each cell, or an adjustment for each cell based on observed data (independence-smoothed). In gart and indip_smooth, estimate of the CI is not possible if \(p1 = 0\), in which case the OR becomes 0, but the lower level of the CI is > 0. Further, if \(p1 = 1\) and \(p2 < 1\), or if \(p1 > 0\) and \(p2 = 0\), the OR becomes \(\infty\), but the upper limit of the CI is finite. For the approximate intervals, gart and indip_smooth are the recommended intervals (Fagerland et al. 2011).

uniroot is used to solve n for the woolf, gart, and indip_smooth method.

References

Fagerland MW, Lydersen S, Laake P (2015). Recommended confidence intervals for two independent binomial proportions. Statistical Methods in Medical Research, 24(2):224-254. tools:::Rd_expr_doi("10.1177/0962280211415469").

Examples

# 10\% events in one group, 15\% in the other, 200 participants total
#  (= 100 in each group), estimate confidence interval width
prec_or(p1 = .1, p2 = .15, n1 = 200/2)
# formula by Gart
prec_or(p1 = .1, p2 = .15, n1 = 200/2, method = "gart")
# formula by Woolf
prec_or(p1 = .1, p2 = .15, n1 = 200/2, method = "woolf")

# 10\% odds in one group, 15\% in the other, desired CI width of 0.1,
#  estimate N
prec_or(p1 = .1, p2 = .15, conf.width = .1)
# formula by Gart
prec_or(p1 = .1, p2 = .15, conf.width = .1, method = "gart")
# formula by Woolf
prec_or(p1 = .1, p2 = .15, conf.width = .1, method = "woolf")