prop.comb.RR (version 1.1)

prop.RR: prop.RR

Description

Main function for making inferences (confidence intervals and tests) about the relative risk using optimal methods from the literature and score method.

Usage

prop.RR(x, n, rho = NULL, alternative = c("two.sided", "less", "greater"), conf.level = 0.95)

Arguments

x

a vector of counts of successes.

n

a vector of counts of samples sizes.

rho

hypothesized true value of the relative risk.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

conf.level

confidence level of the returned confidence interval.

Value

Returns a list with the following components:

estimate

a vector with the sample proportions x/n.

RR

estimated relative risk.

inference

confidence intervals (lower limit, upper limit) and p-values of the test (with z-values of statistics.

alternative

a character string describing the alternative hypothesis.

rho

hypothesized true value of the relative risk.

x

number of successes.

n

number of trials.

conf.level

confidence level of the confidence interval.

recommendation

recommended method by references.

References

Woolf, B. (1955). "On estimating the realtion between blood group disease." Annals of Human Genetics 19, 25-352.

Martin, A. & Alvarez, M. (2014). "Two-tailed approximate confidence intervals for the ratio of proportions." Statistics and Computing 24, 65 - 75.

Alvarez, M. & Martin, A. (2015). "New asymptotic inferences about the difference, ratio and linear combination of two independent proportions." Communications in Statistics - Simulation and Computation (in press).

See Also

prop.comb for inferences about a linear combination of K proportions

Examples

# The Relative Risk was used by Maxwell (1961) for the following data related to 
# the rate of occurrence of virus infection among the group of the non-inoculated 
# and the group of the inoculated. The objetive is to obtain an approximate 
# confidence interval for RR.

prop.RR(x=c(11, 48), n=c(46, 102), conf.level=0.99)

# Price and Bonnet (2008) reviewed a study in which the aim is to prove if
# the effect of the beta-blocker could be highly beneficial or slightly detrimental.

x=c(7, 14); n=c(114, 116); prop.RR(x, n, rho=2)