attribrisk: Calculate attributable risk estimates for one or more...

In attribrisk: Population Attributable Risk

Description

Calculate attributable risk estimates for one or more exposure characteristics. The attributable risk, or etiologic fraction, is an estimate of the reduction in an outcome were a risk factor to change.

Usage

  attribrisk(formula, data, weights, subset, na.action,
    varmethod = c("jackknife", "bootstrap", "none"),
    conf=.95, baseline, k=20, control,
    model = FALSE, x = FALSE, y = FALSE, ...)

Arguments

formula	an object of class 'formula'. A symbolic description of the model to be fitted.
data	a data frame used for the formula.
weights	optional weights for the fitting criterion.
subset	an optional vector specifying a subset of observations to be used.
na.action	a missing-data filter function. This is applied to the model.frame after any subset argument has been used. Default is options()\$na.action.
varmethod	A string that specifies the resampling technique used to estimate confidence intervals and standard errors. bootstrap: indicates that the CI and standard error should be estimated using a bootstrap. jackknife: indicates that the CI and standard error should be estimated using a grouped jackknife. none: do not estimate standard error or CI.
k	the number of groups to use for the jackknife. The parameter is ignored for bootstrap variance. Setting this to 0 or to a value >= the sample size will leads to leaving out each observation one at a time, i.e., the ordinary jackknife. Optionally, k can be a vector with one element per observation that directly specifies the grouping of the observation, the jackknife estimate will leave out one group at a time. If the model has strata then they will not be broken, either all or none of the observations in a strata are left out of each jackknife subsample.
conf	The confidence level for confidence intervals
control	a list of optional parameters, see attribrisk.control.
baseline	Must be either NULL or a data frame containing values for the exposure variable(s) of the formula, which specifies the desired baseline value for each individual.
model	a logical value indicating whether model frame should be included as a component of the returned value.
x,y	logical values indicating whether the model matrix and/or response used in the fitting process should be returned.
...	other arguments such as nboot, normally passed to the attribrisk.control rountine.

Value

an object of class "attribrisk" with the following components:

attribrisk

attributable risk estimate

var

variance of the attributable risk

fit

results from the underlying coxph or glm fit

boot

results of the boot function, optional

boot.ci

results of the boot.ci function, optional

call

A copy of the call to the function

Details

None.

See Also

attribrisk.fit, attribrisk.control, and benichou

Examples

data(benichou)

# Use the Benichou (1991) data to estimate attributable risk of oesophageal
# cancer due to alcohol greater than or equal to 80g/day 
attribrisk(cases ~ expos(alcohol80), data=benichou)

attribrisk documentation built on May 30, 2017, 7:34 a.m.