| ci.pd {Epi} | R Documentation |
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.
ci.pd(aa, bb, cc, dd, alpha = 0.05, print = TRUE)
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. |
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.
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].
Bendix Carstensen, http://www.biostat.ku.dk/~bxc
RG Newcombe: Interval estimation for the difference between independent proportions. Comparison of eleven methods. Statistics in Medicine, 17, pp. 873-890, 1998.
( 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 ) )