Epi (version 0.1)

ci.pd: Compute confidence limits for a difference of two independent proportions.

Description

The usual formula for the c.i. of at difference of proportions is inaccurate. Newcombe has compared 11 methods and method 10 in his paper looks like a winner. It is implemented here.

Usage

ci.pd(aa, bb, cc, dd, alpha = 0.05, print = TRUE)

Arguments

aa

Numeric vector of successes in sample 1. Can also be a matrix (see details).

bb

Successes in sample 2.

cc

Failures in sample 1.

dd

Failures in sample 2.

alpha

Significance level

print

Should an account of the two by two table be printed. Ignored if more than difference is computed, i.e. if aa, bb, cc and dd are vectors or if aa is a 3-dimensional matrix.

Value

• A matrix with three columns: probability difference, lower and upper limit. The number of rows equals the length of the vectors aa, bb, cc and dd or, if aa is a 3-way matrix, dim(aa)[3].

Details

aa, bb, cc and dd can be vectors. If aa is a matrix, the elements [1:2,1:2] are used, with successes aa[,1:2]. If aa is a three-way table or array, the elements aa[1:2,1:2,] are used.

References

RG Newcombe: Interval estimation for the difference between independent proportions. Comparison of eleven methods. Statistics in Medicine, 17, pp. 873-890, 1998.

See Also

twoby2, binom.test

Examples

( a <- matrix( sample( 10:40, 4 ), 2, 2 ) )
ci.pd( a )
twoby2( t(a) )
prop.test( t(a) )
( A <- array( sample( 10:40, 20 ), dim=c(2,2,5) ) )
print( ci.pd( A ) )