Hello Tim,
This function will do it where the covariates are provided as separate
arguments. It would be easy to modify this to handle a list too.
function(outcome, ...) {
arg.names <- as.character(match.call())[-1]
nargs <- length(arg.names)
f <- as.formula(paste(arg.names[1], "~", paste(arg.names[2:nargs],
collapse="+")))
model <- lm(f)
# rest of your code here
}
Hope that helps you get started.
Michael
On 12 October 2010 14:35, Tim Elwell-Sutton <tesut...@hku.hk> wrote:
> Hello all
> I have what seems like a simple question but have not been able to find an
> answer on the forum. I'm trying to define a function which involves
> regression models and a large number of covariates.
>
> I would like the function to accept any number of covariates and, ideally, I
> would like to be able to enter the covariates in a group (e.g. as a list)
> rather than individually. Is there any way of doing this?
>
> Example:
>
> #define function involving regression model with several covariates
> custom <- function(outcome, exposure, covar1, covar2, covar3){
> model <- lm(outcome ~ exposure + covar1 + covar2 + covar3)
> expected <- predict(model)
> summary(expected)
> }
>
> library(MASS)
> attach(birthwt)
>
> custom(bwt, lwt, low, age, race) #Works when 3 covariates are specified
>
> custom(bwt,lwt,low,age) # Does not work with < or > 3 covariates
>
> varlist <- list(low,age,race)
> custom(bwt,lwt, varlist) #Does not work if covariates are included as a list
>
>
>
> Thanks very much for your help
>
> Tim
>
> --
> Tim Elwell-Sutton
> University of Hong Kong
>
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