bda (version 10.1.9)

oddsratio: Odds Ratio and Relative Risk

Description

To compute the odds ratio and relative risk based on a 2 X 2 table.

Usage

oddsratio(x,alpha=0.05,n,...)

Arguments

x

A vector of length 2 of the number of events from the case and control studies.

n

A vector of length 2 of the sample sizes.

alpha

The significance level. Default: 0.05.

...

Controls

Value

OR

an estimate of odds ratio;

RR

an estimate of realtive risk;

ORCI

A table showing various (1-alpha)% confidence limits for OR;

RRCI

A table showing various (1-alpha)% confidence limits for RR;

Details

x can be a matrix or a data.frame: the first columns showing the number of events and the second column showing the sample sizes.

Exact confidence limits for the odds ratio by using an algorithm based on Thomas (1971). See also Gart (1971). If the sample sizes are too large, the exact confidence interval may not work due to overflow problem.

Asymptotic confidence limits are computed according to SAS/STAT(R) 9.2 User's Guide, Second Edition.

Score method: code has been published for generating confidence intervals by inverting a score test. It is available from http://web.stat.ufl.edu/~aa/cda/R/two_sample/R2/

See also "riskratio" and "oddsratio" in R package epitools.

References

Agresti, A. (1990) _Categorical data analysis_. New York: Wiley. Pages 59-66.

Agresti, A. (1992), A Survey of Exact Inference for Contingency Tables Statistical Science, Vol. 7, No. 1. (Feb., 1992), pp. 131-153.

Agresti, A. (2002), Categorical Data Analysis, Second Edition, New York: John Wiley \& Sons.

Fisher, R. A. (1935) The logic of inductive inference. _Journal of the Royal Statistical Society Series A_ *98*, 39-54.

Fisher, R. A. (1962) Confidence limits for a cross-product ratio. _Australian Journal of Statistics_ *4*, 41.

Fisher, R. A. (1970) _Statistical Methods for Research Workers._ Oliver & Boyd.

Mehta, C. R. and Patel, N. R. (1986) Algorithm 643. FEXACT: A Fortran subroutine for Fisher's exact test on unordered r*c contingency tables. _ACM Transactions on Mathematical Software_, *12*, 154-161.

Clarkson, D. B., Fan, Y. and Joe, H. (1993) A Remark on Algorithm 643: FEXACT: An Algorithm for Performing Fisher's Exact Test in r x c Contingency Tables. _ACM Transactions on Mathematical Software_, *19*, 484-488.

Patefield, W. M. (1981) Algorithm AS159. An efficient method of generating r x c tables with given row and column totals. _Applied Statistics_ *30*, 91-97.

Stokes, M. E., Davis, C. S., and Koch, G. G. (2000), Categorical Data Analysis Using the SAS System, Second Edition, Cary, NC: SAS Institute Inc.

See Also

fisher.test, chisq.test

Examples

# NOT RUN {
#  library(bstats)
x = c(1,0)
n = c(72370,73058)
oddsratio(x,n=n)

Convictions <-
     matrix(c(2, 10, 15, 3),
            nrow = 2,
            dimnames =
            list(c("Dizygotic", "Monozygotic"),
                 c("Convicted", "Not convicted")))
     Convictions
     fisher.test(Convictions, conf.level = 0.95)$conf.int

x = matrix(c(2,10,17,13), ncol=2)
oddsratio(x)

Convictions <-
     matrix(c(8, 492, 0, 500), nrow = 2, byrow=TRUE)
fisher.test(Convictions, conf.level = 0.95)$conf.int

x = c(8,0)
n = c(500,500)
oddsratio(x,n=n)

# }