ci.pd | 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=NULL, cc=NULL, dd=NULL,
method = "Nc",
alpha = 0.05, conf.level=0.95,
digits = 3,
print = TRUE,
detail.labs = FALSE )
aa |
Numeric vector of successes in sample 1. Can also be a matrix or array (see details). |
bb |
Successes in sample 2. |
cc |
Failures in sample 1. |
dd |
Failures in sample 2. |
method |
Method to use for calculation of confidence interval, see "Details". |
alpha |
Significance level |
conf.level |
Confidence level |
print |
Should an account of the two by two table be printed. |
digits |
How many digits should the result be rounded to if printed. |
detail.labs |
Should the computing of probability differences be reported in the labels. |
Implements method 10 from Newcombe(1998) (method="Nc") or from Agresti & Caffo(2000) (method="AC").
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, Esa Laara. http://bendixcarstensen.com
RG Newcombe: Interval estimation for the difference between independent proportions. Comparison of eleven methods. Statistics in Medicine, 17, pp. 873-890, 1998.
A Agresti & B Caffo: Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures. The American Statistician, 54(4), pp. 280-288, 2000.
twoby2
, binom.test
( 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) ) )
ci.pd( A )
ci.pd( A, detail.labs=TRUE, digits=3 )
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