Odds Ratio and Relative Risk for 2 x 2 Contingency Tables

Source: R/oddsRatio.R

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.

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, ...)

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".

Value

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

Author

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

Examples

M1 <- matrix(c(14, 38, 51, 11), nrow = 2)
M1
#>      [,1] [,2]
#> [1,]   14   51
#> [2,]   38   11
oddsRatio(M1)
#> [1] 12.58442

M2 <- matrix(c(18515, 18496, 1427, 1438), nrow = 2)
rownames(M2) <- c("Placebo", "Aspirin")
colnames(M2) <- c("No", "Yes")
M2
#>            No  Yes
#> Placebo 18515 1427
#> Aspirin 18496 1438
oddsRatio(M2)
#> [1] 0.9913321
oddsRatio(M2, verbose = TRUE)
#> 
#> Odds Ratio
#> 
#> Proportions
#> 	   Prop. 1:	 0.9284 
#> 	   Prop. 2:	 0.9279 
#> 	 Rel. Risk:	 0.9994 
#> 
#> Odds
#> 	    Odds 1:	 12.97 
#> 	    Odds 2:	 12.86 
#> 	Odds Ratio:	 0.9913 
#> 
#> 95 percent confidence interval:
#> 	 0.9939 < RR < 1.005 
#> 	 0.9188 < OR < 1.07 
#> NULL
#> [1] 0.9913321
relrisk(M2, verbose = TRUE)
#> 
#> Odds Ratio
#> 
#> Proportions
#> 	   Prop. 1:	 0.9284 
#> 	   Prop. 2:	 0.9279 
#> 	 Rel. Risk:	 0.9994 
#> 
#> Odds
#> 	    Odds 1:	 12.97 
#> 	    Odds 2:	 12.86 
#> 	Odds Ratio:	 0.9913 
#> 
#> 95 percent confidence interval:
#> 	 0.9939 < RR < 1.005 
#> 	 0.9188 < OR < 1.07 
#> NULL
#> [1] 0.9993747
if (require(mosaicData)) {
relrisk(tally(~ homeless + sex, data = HELPrct) )
do(3) * relrisk( tally( ~ homeless + shuffle(sex), data = HELPrct) )
}
#> Using parallel package.
#>   * Set seed with set.rseed().
#>   * Disable this message with options(`mosaic:parallelMessage` = FALSE)
#>          RR
#> 1 1.0934775
#> 2 1.0528518
#> 3 0.8098361