Skewness-corrected asymptotic score ("SCAS") confidence intervals for single binomial or Poisson rate using closed-form calculations.

Closed-form function for computing confidence intervals for a single rate. Note: For associated hypothesis tests, use scoreci() with contrast = "p". This function is vectorised in x, n.

Usage

scaspci(
  x,
  n,
  distrib = "bin",
  level = 0.95,
  bcf = FALSE,
  bign = n,
  xihat = 1,
  cc = FALSE,
  ...
)

Arguments

x

Numeric vector of number of events.

n

Numeric vector of sample sizes (for binomial rates) or exposure times (for Poisson rates).

distrib

Character string indicating distribution assumed for the input data:
"bin" = binomial (default);
"poi" = Poisson.

level

Number specifying confidence level (between 0 and 1, default 0.95).

bcf

Logical (default TRUE) indicating whether to apply bias correction in the score denominator. Applicable to distrib = "bin" only.

bign

Sample size N to be used in the calculation of bcf, if different from n. (Used by transformed SCASp method for paired conditional OR in pairbinci().)

xihat

Number specifying estimated variance inflation factor for a skewness corrected version of the Saha Wilson Score interval for clustered binomial proportions. Need to calculate using BMS and WMS as per Saha 2016. Used by clusterpci() function for data entered per cluster.

cc

Number or logical (default FALSE) specifying (amount of) continuity adjustment. Numeric value is taken as the gamma parameter in Laud 2017, Appendix S2 (default 0.5 for 'conventional' adjustment if cc = TRUE).

...

Other arguments.

Value

A list containing the following components:

estimates

a matrix containing estimated rate(s), the SCAS confidence interval, and the input values x and n.

call

details of the function call.

References

Laud PJ. Equal-tailed confidence intervals for comparison of rates. Pharmaceutical Statistics 2017; 16:334-348. (Appendix A.4)

Author

Pete Laud, p.j.laud@sheffield.ac.uk