[R] creating functions question

[Dimitris Rizopoulos]

try this:

MRfit <- function (...) {
     models <- list(...)
     do.call(anova, models)
}


I hope it helps.

Best,
Dimitris


AC Del Re wrote:
> Hi All,
> 
> I am interested in creating a function that will take x number of  lm
> objects and automate the comparison of each model (using anova). Here
> is a simple example (the actual function will involve more than what
> Im presenting but is irrelevant for the example):
> 
> # sample data:
> 
> id<-rep(1:20)
> n<-c(10,20,13,22,28,12,12,36,19,12,36,75,33,121,37,14,40,16,14,20)
> r<-c(.68,.56,.23,.64,.49,-.04,.49,.33,.58,.18,-.11,.27,.26,.40,.49,
> .51,.40,.34,.42,.16)
> mod2<-factor(c(rep(c(1,2,3,4),5)))
> da<-data.frame(id, n, r, mod1, mod2)
> 
> 
> reg0<-lm(da$r ~ 1)
> reg1<-lm(da$r ~ da$mod1)
> reg2<-lm(da$r ~ da$mod1 + da$mod2)
> 
> # This is as far as I get with the function:
> 
> MRfit <- function( ...) {
>  models <- list(...)
>  fit<- anova(models)
>  return(fit)
> }
> 
> MRfit(reg0,reg1,reg2)
> 
> # This is what I get from R:
> 
> #  Error in UseMethod("anova") :
> #  no applicable method for 'anova' applied to an object of class "list"
> 
> # which makes sense, but Im not sure how to work with this list
> considering the desired output.
> # Ideally I would like to get:
> 
> MRfit(reg0,reg1,reg2)   # I know that I could just do anova(reg0,reg1,
> reg2) but the actual function will have additional functions
> integrated
> 
> Analysis of Variance Table
> 
> Model 1: da$r ~ 1
> Model 2: da$r ~ da$mod1
> Model 3: da$r ~ da$mod1 + da$mod2
> 
>  Res.Df     RSS Df Sum of Sq      F Pr(>F)
> 1     19 0.83848
> 2     18 0.78668  1  0.051803 1.1230 0.3060
> 3     15 0.69193  3  0.094747 0.6847 0.5752
> 
> 
> Any help is much appreciated!
> 
> Thank you,
> 
> AC
> 
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> and provide commented, minimal, self-contained, reproducible code.
> 

-- 
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center

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