Odds ratio estimation and confidence intervals using mid-p method

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Description

Calculates odds ratio by median-unbiased estimation and exact confidence interval using the mid-p method (Rothman 1998).

Usage

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or.midp(x, conf.level = 0.95, byrow = TRUE, interval = c(0, 1000))

Arguments

x

input data can be 2x2 matrix or vector of length 4

conf.level

confidence level (default is 0.95)

byrow

integer vectors are read in row-wise (default)

interval

interval for the uniroot that finds the odds ratio median-unbiased estimate and mid-p exact confidence interval for oddsratio.midp

Details

Calculates odds ratio by median-unbiased estimation and exact confidence interval using the mid-p method (Rothman 1998, p. 251).

This function expects the following 2x2 table struture:

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              exposed   not exposed
    disease  	 a1	    a0	      			
    no disease   b1	    b0
  

or a numeric vector of the form c(a1, a0, b1, b0).

This function is used by oddsratio.midp.

Value

x

table that was used in analysis

data

same table as x but with marginal totals

estimate

median unbiased odds ratio

conf.level

confidence level used

Note

Visit http://medepi.com for the latest.

Author(s)

Tomas Aragon, aragon@berkeley.edu, http://www.medepi.com

References

Kenneth J. Rothman and Sander Greenland (1998), Modern Epidemiology, Lippincott-Raven Publishers

See Also

oddsratio

Examples

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##rothman p. 243
z1 <- matrix(c(12,2,7,9),2,2,byrow=TRUE)
z2 <- z1[2:1,2:1]
##jewell p. 79
z3 <- matrix(c(347,555,20,88),2,2,byrow=TRUE)
z4 <- z3[2:1,2:1]
or.midp(z1)
or.midp(z2)
or.midp(z3)
or.midp(z4)

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