QBmover function

Confidence intervals for ratios of proportions based on the quasibinomial assumption

Confidence intervals for ratios of proportions based on the quasibinomial assumption

Confidence intervals for ratios of proportions with overdispersed binomial data in a one-factor quasibinomial generalized linear model. Intervals are computed using the MOVER-R method on profile deviance intervals (as implemented in mcprofile) for the single proportions.

QBmover(succ, fail, trt, conf.level = 0.95, alternative = "two.sided", grid = NULL)

Arguments

  • succ: vector of counts of successes
  • fail: vector of counts of failures
  • trt: factor variable distinguishing the treatment groups
  • conf.level: a single numeric value, the confidence level
  • alternative: a character string, "two.sided" for two-sided intervals, "less" for upper limits, "greater" for lower limits only
  • grid: optional, a numeric vector to be supplied to the profiling used internally in quasibin.ratio to obtain profile deviance intervals for each samples proportion on the logit-scale.

Returns

A data.frame with three columns - est: estimated ratios

  • lower: lower confidence limits

  • upper: upper confidence limits

References

Donner and Zou (2012): Closed-form confidence intervals for functions of the normal mean and standard deviation. Statistical Methods in Medical Research 21(4):347-359. Gerhard (2014): Simultaneous Small Sample Inference For Linear Combinations Of Generalized Linear Model Parameters. Communications in Statistics - Simulation and Computation. DOI:10.1080/03610918.2014.895836

Author(s)

Frank Schaarschmidt

Note

Experimental

Examples

QBmover(succ=c(0,0,1, 0,6,8), fail=c(20,20,18, 20,14,12), trt=factor(rep(c("A", "B"), c(3,3))), conf.level = 0.95, alternative = "two.sided", grid = NULL)
  • Maintainer: Frank Schaarschmidt
  • License: GPL-2
  • Last published: 2019-03-11

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