[R] Improving function that estimates regressions for all variables specified

[Adams, Jean]

You may be able find someone else's function that already does you want.
For example the dredge() function of the MuMIn package.

http://rpackages.ianhowson.com/cran/MuMIn/man/MuMIn-package.html

Jean

On Fri, Aug 26, 2016 at 1:11 PM, Jorge Cimentada <cimentadaj at gmail.com>
wrote:

> Hi, I'd like some feedback on how to make this function more "quicker and
> parsimonious".
>
> I normally run several regressions like this:
> y ~ x1
> y ~ x1 + x2
> y ~ x1 + x2 +xn
>
> Instead, I created a function in which I specify y, x1 and x2 and the
> function automatically generates:
> y ~ x1
> y ~ x1 + x2
> y ~ x1 + x2 +xn
>
> This is the function:
>
> models <- function(dv, covariates, data) {
>     dv <- paste(dv, "~ 1")
>     combinations <- lapply(1:length(covariates), function(i) seq(1:i))
>     formulas <- lapply(combinations, function(p) x <-
> as.formula(paste(c(dv, covariates[p]), collapse=" + ")))
>     results <- lapply(formulas, function(o) lm(o, data=data))
>     return(results)
> }
>
> And an example:
> models("mpg",c("cyl","disp","hp","am"), mtcars)
>
> I'm concerned about the time that it takes when using other regression
> models, such as those with the survey package(I know these models are heavy
> and take time) but I'm sure that the function has room for improvement.
>
> I'd also like to specify the variables as a formula. I managed to do it but
> I get different results when using things like scale() for predictors.
>
> Formula version of the function:
> models2 <- function(formula, data) {
>     dv <- paste(all.vars(formula)[1], " ~ 1")
>     covariates <- all.vars(formula)[-1]
>     combinations <- lapply(1:length(covariates), function(i) seq(1:i))
>     lfo <- lapply(combinations, function(p) x <- as.formula(paste(c(dv,
> covariates[p]), collapse=" + ")))
>     results <- lapply(lfo, function(o) lm(o, data=data))
>     return(results)
> }
>
> models("mpg",c("cyl","scale(disp)"), mtcars)
>
> models2(mpg ~ cyl + scale(disp), mtcars)
>
> See the difference between the disp variables?
>
> Any feedback is appreciated!
>
>
> *Jorge Cimentada*
> *Ph.D. Candidate*
> Dpt. Ciències Polítiques i Socials
> Ramon Trias Fargas, 25-27 | 08005 Barcelona
>
> Office 24.331
> [Tel.] 697 382 009www.jorgecimentada.com
>
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>
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