glmSeries {Publish} | R Documentation |
Run a series of generalized linear regression analyses
Description
Run a series of generalized linear regression analyses for a list of predictor variables and summarize the results in a table. The regression models can be adjusted for a fixed set of covariates.
Usage
glmSeries(formula, data, vars, ...)
Arguments
formula |
The fixed part of the regression formula. For
univariate analyses this is simply |
data |
A |
vars |
A list of variable names, the changing part of the regression formula. |
... |
passed to glm |
Value
Matrix with regression coefficients, one for each element of vars
.
Author(s)
Thomas Alexander Gerds
Examples
data(Diabetes)
Diabetes$hyper1 <- factor(1*(Diabetes$bp.1s>140))
## collect odds ratios from three univariate logistic regression analyses
uni.odds <- glmSeries(hyper1~1,vars=c("chol","hdl","location"),data=Diabetes,family=binomial)
uni.odds
## control the logistic regression analyses for age and gender
## but collect only information on the variables in `vars'.
controlled.odds <- glmSeries(hyper1~age+gender,
vars=c("chol","hdl","location"),
data=Diabetes, family=binomial)
controlled.odds
[Package Publish version 2023.01.17 Index]