Analysis of a two by two table
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.
twoby2(exposure, outcome,
alpha = 0.05, print = TRUE, dec = 4,
conf.level = 1-alpha, F.lim = 10000)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- |
F.lim |
If the table total exceeds |
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 |
Mark Myatt. Modified by Bendix Carstensen.
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 roundPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.