moverci | R Documentation |
Confidence intervals applying the MOVER method ("Method of Variance Estimates Recovery", developed from the Newcombe method for binomial RD) across different contrasts (RD, RR, OR) and distributions (binomial, Poisson) using equal-tailed Jeffreys intervals instead of the Wilson score method for the event rates. Also allows more general Beta and Gamma priors for an approximate Bayesian confidence interval incorporating prior beliefs about the group event rates. This function is vectorised in x1, x2, n1, and n2.
moverci(
x1,
n1,
x2 = NULL,
n2 = NULL,
distrib = "bin",
contrast = "RD",
level = 0.95,
a1 = 0.5,
b1 = 0.5,
a2 = 0.5,
b2 = 0.5,
type = "jeff",
adj = FALSE,
cc = FALSE,
...
)
x1 , x2 |
Numeric vectors of numbers of events in group 1 & group 2 respectively. |
n1 , n2 |
Numeric vectors of sample sizes (for binomial rates) or exposure times (for Poisson rates) in each group. |
distrib |
Character string indicating distribution assumed for the input
data: |
contrast |
Character string indicating the contrast of interest: |
level |
Number specifying confidence level (between 0 and 1, default 0.95). |
a1 , b1 , a2 , b2 |
Numbers defining the Beta(ai,bi) prior distributions for each group (default ai = bi = 0.5 for Jeffreys method). Gamma priors for Poisson rates require only a1, a2. |
type |
Character string indicating the method used for the intervals for
the individual group rates. |
adj |
Logical (default FALSE) indicating whether to apply the boundary
adjustment for Jeffreys intervals recommended on p108 of Brown et al.
( |
cc |
Number or logical specifying (amount of) continuity adjustment
(default FALSE). Numeric value is taken as the gamma parameter in Laud
2017, Appendix S2 (default 0.5 if |
... |
Additional arguments. |
A list containing the following components:
a matrix containing estimates of the rates in each group and of the requested contrast, with its confidence interval.
details of the function call.
Pete Laud, p.j.laud@sheffield.ac.uk
Laud PJ. Equal-tailed confidence intervals for comparison of rates. Pharmaceutical Statistics 2017; 16:334-348.
Newcombe RG. Interval estimation for the difference between independent proportions: comparison of eleven methods. Statistics in Medicine 1998; 17(8):873-890.
Donner A, Zou G. Closed-form confidence intervals for functions of the normal mean and standard deviation. Statistical Methods in Medical Research 2012; 21(4):347-359.
Fagerland MW, Newcombe RG. Confidence intervals for odds ratio and relative risk based on the inverse hyperbolic sine transformation. Statistics in Medicine 2013; 32(16):2823-2836.
Li HQ, Tang ML, Wong WK. Confidence intervals for ratio of two Poisson rates using the method of variance estimates recovery. Computational Statistics 2014; 29(3-4):869-889.
# Binomial RD, MOVER-J method:
moverci(x1 = 5, n1 = 56, x2 = 0, n2 = 29)
# Binomial RD, Newcombe method:
moverci(x1 = 5, n1 = 56, x2 = 0, n2 = 29, type = "wilson")
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