How can I handle multiple parameters without using nested if else statements? - r

Question

I am trying to write a function that has up to 6 potential conditions. The function creates a linear model that could have up to three parameters and is either scaled or not scaled. I tried using nested if else statements, but have run into issues because I have too many conditions (scaled or not X 3ivs possible = 6 potential conditions). How can I simplify my code so it is easier to read?
This is what I tried to write, but it does not currently work.
test<-data.frame(a=sample.int(20,10,replace=T),b=sample.int(20,10,replace=T),c=sample.int(20,10,replace=T),d=sample.int(20,10,replace=T))
lm3iv<-function(dv,iv1,iv2=NA,iv3=NA,df,scale=F){
dn<-dv;in1<-iv1;in2<-iv2;in3<-iv3 #stores the names of variables/elements specified in function
dv<-eval(parse(text=paste0(df,"$",dv))) #Store output of (df,"$",dv) as variable dv; parse=trun string into text; eval=return the values given by an expression that is passed to eval (by parse in this case).
#return(dv)
iv1<-eval(parse(text=paste0(df,"$",iv1)))
if(!is.na(iv2)){iv2<-eval(parse(text=paste0(df,"$",iv2)))}
if(!is.na(iv3)){iv3<-eval(parse(text=paste0(df,"$",iv3)))}
ifelse(scale,
ifelse(!is.na(iv3),
{
x<-lm(scale(dv)~scale(iv1)+scale(iv2)+scale(iv3))
names(x$coefficients)<-c(dn,in1,in2,in3) #set names of coefficients (element of x) from x (object defined in above line); names=pulling specific elements of coefficients
return(summary(x))
},
ifelse(!is.na(iv2),{
x<-lm(scale(dv)~scale(iv1)+scale(iv2))
names(x$coefficients)<-c(dn,in1,in2)
return(summary(x))
},
{
x<-lm(scale(dv)~scale(iv1))
names(x$coefficients)<-c(dn,in1)
return(summary(x))
},
ifelse(!is.na(iv3),
return(summary(lm((dv)~(iv1)+(iv2)+(iv3)))),
ifelse(!is.na(iv2),
return(summary(lm((dv)~(iv1)+(iv2)))),
return(summary(lm((dv)~(iv1)))))))
) #format=ifelse(cond,if_true,if_false)
)
}
#tried adding list() before the first summary to return model outpot and the model its self; have to add the model again after the comma after summary() - e.g., lm(scale(dv)~scale(iv1)+scale(iv2)+scale(iv3))) (same model being summarized). Have to create a variable when passing the data into the model. When reading output -> model.output(model.std.el.ns.tw[[1]],model.std.el.ns.tw[[2]]).
lm3iv("a","b","c","d",df="test",scale=F)
This is the error I'm getting, but I am trying to simplify my code, not just solve the error:
Error in ifelse(scale, ifelse(!is.na(iv3), { :
argument "no" is missing, with no default

Answer 1

Here is you function organised. I hope it works because I didn't care for what the function do, just for the arguments of the ifelse(test, yes, no)
lm3iv<-function(dv,iv1,iv2=NA,iv3=NA,df,scale=F){
dn<-dv;in1<-iv1;in2<-iv2;in3<-iv3 #stores the names of variables/elements specified in function
dv<-eval(parse(text=paste0(df,"$",dv))) #Store output of (df,"$",dv) as variable dv; parse=trun string into text; eval=return the values given by an expression that is passed to eval (by parse in this case).
#return(dv)
iv1<-eval(parse(text=paste0(df,"$",iv1)))
if(!is.na(iv2)){iv2<-eval(parse(text=paste0(df,"$",iv2)))}
if(!is.na(iv3)){iv3<-eval(parse(text=paste0(df,"$",iv3)))}
ifelse(test = scale,
yes = ifelse(test = !is.na(iv3),
yes = {
x<-lm(scale(dv)~scale(iv1)+scale(iv2)+scale(iv3))
names(x$coefficients)<-c(dn,in1,in2,in3) #set names of coefficients (element of x) from x (object defined in above line); names=pulling specific elements of coefficients
return(summary(x))
},
no = ifelse(test = !is.na(iv2),
yes = {
x<-lm(scale(dv)~scale(iv1)+scale(iv2))
names(x$coefficients)<-c(dn,in1,in2)
return(summary(x))
},
no = {
x<-lm(scale(dv)~scale(iv1))
names(x$coefficients)<-c(dn,in1)
return(summary(x))
})),
no = ifelse(test = !is.na(iv3),
yes = return(summary(lm((dv)~(iv1)+(iv2)+(iv3)))),
no = ifelse(test = !is.na(iv2),
yes = return(summary(lm((dv)~(iv1)+(iv2)))),
no = return(summary(lm((dv)~(iv1))))))
) #format=ifelse(cond,if_true,if_false)
}

Answer 2

Instead of using a bunch of ifelse statements, perhaps you should build a formula from the function arguments and then pass it to lm?
library(tidyverse)
lm2 <- function(dep_var, ind_var, ..., data, scaled = FALSE) {
if (scaled) {
data <- mutate_if(data, is.numeric, scale)
}
form <- paste(dep_var, '~',
paste(ind_var, ..., sep = '+')) %>%
as.formula()
lm(form, data = data) %>% summary()
}
# tests
# 1 independent var
lm(Petal.Width ~ Sepal.Width, data = iris) %>% summary()
lm2('Petal.Width', 'Sepal.Width', data = iris)
# 2 independent var
lm(Petal.Width ~ Sepal.Width + Sepal.Length, data = iris) %>% summary()
lm2('Petal.Width', 'Sepal.Width', 'Sepal.Length', data = iris)
# test scale option
iris_scaled <- mutate(iris,
Petal.Width = scale(Petal.Width),
Sepal.Width = scale(Sepal.Width))
lm(Petal.Width ~ Sepal.Width, data = iris_scaled) %>% summary()
lm2('Petal.Width', 'Sepal.Width', data = iris, scaled = TRUE)