printmRR {logisticRR}

Print adjusted relative risk using multinomial logistic regression under binary or ordinal exposure variable.

Description

Print adjusted relative risk using multinomial logistic regression under binary or ordinal exposure variable.

Usage

printmRR(formula, basecov = 0, fixcov = NULL, data)

Arguments

formula

a formula term that is passed into multinom() where response should be a factor having K different levels. Every term appearing in the formula should be well-defined as a column of data. Reference response should be specified as the first level.

basecov

a baseline value of exposure variable. Defaults to 0.

fixcov

a data frame of fixed value for each of adjusted confounders. If there is no confounder other than the exposure variable of interest, fixcov = NULL; if fixcov is missing for existing covariates, they are all set to 0 (for numerical covariates) or to the first level (for factor covariates).

data

a data frame containing response variable and all the terms used in formula.

Value

fit

an object of class multinom.

RRR

(adjusted) relative risk ratio of K different responses compared to reference response under exposure at baseline (basecov) and basecov + 1.

RR

(adjusted) relative risk of K different responses under exposure at baseline (basecov) and basecov + 1.

delta.var

estimated variance of relative risk (RR) using Delta method.

fix.cov

a data frame of fixed value for each of adjsuted confounders.

Author(s)

Youjin Lee

Examples

n <- 500
set.seed(1234)
X <- rbinom(n, 1, 0.3)
W <- rbinom(n, 1, 0.3)
W[sample(1:n, n/3)] = 2
Y <- rbinom(n, 1, plogis(X - W))
dat <- as.data.frame(cbind(Y, X, W))
result <- printmRR(W ~ X + Y, basecov = 0, data = dat)