mosaic (version 1.9.1)

orrr: Odds Ratio and Relative Risk for 2 x 2 Contingency Tables

Description

This function calculates the odds ratio and relative risk for a 2 x 2 contingency table and a confidence interval (default conf.level is 95 percent) for the each estimate. x should be a matrix, data frame or table. "Successes" should be located in column 1 of x, and the treatment of interest should be located in row 2. The odds ratio is calculated as (Odds row 2) / (Odds row 1). The confidence interval is calculated from the log(OR) and backtransformed.

Usage

orrr(
  x,
  conf.level = 0.95,
  verbose = !quiet,
  quiet = TRUE,
  digits = 3,
  relrisk = FALSE
)

oddsRatio(x, conf.level = 0.95, verbose = !quiet, quiet = TRUE, digits = 3)

relrisk(x, conf.level = 0.95, verbose = !quiet, quiet = TRUE, digits = 3)

# S3 method for oddsRatio print(x, digits = 4, ...)

# S3 method for relrisk print(x, digits = 4, ...)

# S3 method for oddsRatio summary(object, digits = 4, ...)

# S3 method for relrisk summary(object, digits = 4, ...)

Value

an odds ratio or relative risk. If verpose is true, more details and the confidence intervals are displayed.

Arguments

x

a 2 x 2 matrix, data frame, or table of counts

conf.level

the confidence interval level

verbose

a logical indicating whether verbose output should be displayed

quiet

a logical indicating whether verbose output should be suppressed

digits

number of digits to display

relrisk

a logical indicating whether the relative risk should be returned instead of the odds ratio

...

additional arguments

object

an R object to print or summarise. Here an object of class "oddsRatio" or "relrisk".

Author

Kevin Middleton (kmm@csusb.edu); modified by R Pruim.

See Also

Examples

Run this code
M1 <- matrix(c(14, 38, 51, 11), nrow = 2)
M1
oddsRatio(M1)

M2 <- matrix(c(18515, 18496, 1427, 1438), nrow = 2)
rownames(M2) <- c("Placebo", "Aspirin")
colnames(M2) <- c("No", "Yes")
M2
oddsRatio(M2)
oddsRatio(M2, verbose = TRUE)
relrisk(M2, verbose = TRUE)
if (require(mosaicData)) {
relrisk(tally(~ homeless + sex, data = HELPrct) )
do(3) * relrisk( tally( ~ homeless + shuffle(sex), data = HELPrct) )
}

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