gm.or, gm.rr {gmvalid}R Documentation

Stratified odds ratios or risk ratios

Description

Computes (stratified) odds ratios or risk ratios and their asymptotic confidence interval.

Usage

gm.or(X, Y, data = 0, conditions = 0,
        reference = c("last", "biggest", "first"), conf.level = 0.95)

gm.rr(X, Y, data = 0, conditions = 0,
        reference = c("last", "biggest", "first"), conf.level = 0.95)

Arguments

X Index of the variable's position in data or a vector.
Y Index of the variable's position in data or a vector.
data Data frame or a table
conditions Variable indices in data or a data frame of the conditioning variables.
reference Character string specifying the reference category, must be one of "last" (default), "biggest" (largest) or "first". May be abbreviated.
conf.level confidence level of the interval (default is 0.95).

Details

Calculates odds ratios by conditional maximum likelihood estimation (Fisher) for stratified odds ratios and odds ratios by unconditional maximum likelihood estimation (Wald) for marginal odds ratios. Confidence intervals are calculated using exact methods.

Calculates risk ratios by unconditional maximum likelihood estimation (Wald). Confidence intervals are calculated using normal approximation.

Is based on the functions oddsratio.fisher, oddsratio.wald and riskratio.wald (package: epitools).

Value

A matrix containing the estimate(s), confidence interval(s) and p-value(s).

Author(s)

Ronja Foraita, Fabian Sobotka
Bremen Institute for Prevention Research and Social Medicine
(BIPS) http://www.bips.uni-bremen.de

References

Rothman KJ, Greenland S (1998) Modern Epidemiology. (2nd) Lippincott-Raven Publisher

http://www.epitools.net

See Also

oddsratio, riskratio

Examples

  group  <- c("treatment","placebo1","placebo2")
  target <- c("low","medium","high")
  mat    <- matrix(c(78,35,53,77,10,89,16,119,32),nrow=3,ncol=3,byrow=TRUE, 
                    dimnames=list("group"=group,"target"=target))
  treat  <- data.frame(expand.table(mat))
  table(treat)
  
  ### Marginal OR
  gm.or(1,2,treat,reference="f")
  gm.or(treat$target,treat$group)
  
  ### Stratified OR
  data <- gm.modelsim(1000,"ab,bcd",list(c(1,1),c(1,1),c(1,1),c(1,1)))  
  gm.or(1,2,conditions=c(3,4),data=data)
  
  ### Marginal RR
  gm.rr(1,2,treat,reference="f")
  gm.rr(treat$target,treat$group)
  
  ### Stratified RR
  data <- gm.modelsim(1000,"ab,bcd",list(c(1,1),c(1,1),c(1,1),c(1,1)))  
  gm.rr(1,2,conditions=c(3,4),data=data)
  
  ### ALSO
  gm.or(X=data$a,Y=data$b,conditions=data$d)


[Package gmvalid version 1.0 Index]