Relative Risk
Computes the relative risk and it's confidence intervals.
Confidence intervals are calculated using normal approximation ("wald"), ("score") or by
using oddsratio ("use.or")
RelRisk(x, y = NULL, conf.level = NA,
method = c("score", "wald", "use.or"), delta = 0.5, ...)x |
a numeric vector or a 2x2 numeric matrix, resp. table. |
y |
NULL (default) or a vector with compatible dimensions to |
conf.level |
confidence level. Default is NA, meaning no confidence intervals will be reported. |
method |
method for calculating odds ratio and confidence interval. Can be one out of
|
delta |
small constant to be added to the numerator for calculating the log risk ratio (Wald method). Usual choice is 0.5 although there does not seem to be any theory behind this. (Dewey, M. 2006) |
... |
further arguments are passed to the function |
This function expects the following table structure:
disease=0 disease=1
exposed=0 (ref) n00 n01
exposed=1 n10 n11If the table to be provided is not in the
preferred form, use the function Rev() to "reverse" the table rows,
-columns, or both.
If conf.level is not NA then the result will be
a vector with 3 elements for estimate, lower confidence intervall and upper for the upper one.
Else the relative risk will be reported as a single value.
Andri Signorell <andri@signorell.net>, based on code of Yongyi Min and Michael Dewey
Rothman, K. J. and Greenland, S. (1998) Modern Epidemiology. Lippincott-Raven Publishers
Rothman, K. J. (2002) Epidemiology: An Introduction. Oxford University Press
Jewell, N. P. (2004) Statistics for Epidemiology. 1st Edition, 2004, Chapman & Hall, pp. 73-81
Selvin, S. (1998) Modern Applied Biostatistical Methods Using S-Plus. 1st Edition, Oxford University Press
mm <- cbind(c(9,20),c(41,29)) mm RelRisk(t(mm), conf.level=0.95) RelRisk(t(mm), conf.level=0.95, method="wald") RelRisk(t(mm), conf.level=0.95, method="use.or")
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