Learn R Programming

Epi (version 2.58)

twoby2: Analysis of a two by two table

Description

Computes the usual measures of association in a 2 by 2 table with confidence intervals. Also produces asymtotic and exact tests. Assumes that comparison of probability of the first column level between levels of the row variable is of interest. Output requires that the input matrix has meaningful row and column labels.

Usage

twoby2(exposure, outcome,
       alpha = 0.05, print = TRUE, dec = 4,
       conf.level = 1-alpha, F.lim = 10000)

Value

A list with elements:

table

The analysed 2 x 2 table augmented with probabilities and confidence intervals. The confidence intervals for the probabilities are computed using the normal approximation to the log-odds. Confidence intervals for the difference of proportions are computed using method 10 from Newcombe, Stat.Med. 1998, 17, pp.873 ff.

measures

A table of Odds-ratios and relative risk with confidence intervals.

p.value

Exact p-value for the null hypothesis of OR=1

Arguments

exposure

If a table the analysis is based on the first two rows and first two columns of this. If a variable, this variable is tabulated against

outcome

as the second variable

alpha

Significance level

print

Should the results be printed?

dec

Number of decimals in the printout.

conf.level

1-alpha

F.lim

If the table total exceeds F.lim, Fisher's exact test is not computed

Author

Mark Myatt. Modified by Bendix Carstensen.

Examples

Run this code
Treat <- sample(c("A","B"), 50, rep=TRUE )
Resp <- c("Yes","No")[1+rbinom(50,1,0.3+0.2*(Treat=="A"))]
twoby2( Treat, Resp )                 
twoby2( table( Treat, Resp )[,2:1] ) # Comparison the other way round

Run the code above in your browser using DataLab