Passing a function argument with dots - r

Question

I'm trying to write a function to compute sample sizes in R.
The function uses a couple of smaller functions. I'd like to pass arguments into the smaller functions using the dots. Here is my function so far:
log_reg_var<-function(p){
if(p<=0|p>=1) stop('p must be between 0 and 1')
var<-1/(p*(1-p))
return(var)
}
samplesize<-function(method_name, beta, sigma_x, mult_cor, power= 0.8,fpr = 0.05,...){
if(method_name=='linear regression'){
var_func <- lin_reg_var
}
else if(method_name=='logistic regression'){
var_func <- log_reg_var
}
else if(method_name=='cox regression'){
var_func <- cox_reg_var
}
else if(method_name=='poisson regression'){
var_func <- pois_reg_var
}
else{
stop('method_name not recognized. method_name accepts one of: "linear regression",
"logistic regression","cox regression", or "poisson regression"')
}
top = (qnorm(1-fpr/2) + qnorm(power))^2
bottom = (beta*sigma_x)^2*(1-mult_cor)
n = (top/bottom)*var_func(...)
return(ceiling(n))
}
I should be able to do
samplesize(method_name = 'logreg',1,1,0,p=0.5)
>>>32
But instead I am thrown the following error:
Error in var_func(...) : argument "p" is missing, with no default
Clearly there is something wrong with me passing p through the dots, but I'm not sure what is wrong.
What is my problem here?

Answer 1

You need to add the additional parameter p as an argument and you need to pass it into your log_reg_var() function. You also have to be careful with some other syntax:
log_reg_var<-function(p){
if(p<=0|p>=1) stop('p must be between 0 and 1')
var<-1/(p*(1-p))
return(var)
}
# specify that you pass a parameter `p`
samplesize<-function(method_name, beta, sigma_x, mult_cor, power= 0.8,fpr = 0.05, p, ...){
# Initialize `var_func` to a NULL value
var_func = NULL
if(method_name=='linear regression'){
var_func <- lin_reg_var(p)
}
else if(method_name=='logistic regression'){
# pass parameter `p` into log_reg_var since there is no default
var_func <- log_reg_var(p)
}
else if(method_name=='cox regression'){
var_func <- cox_reg_var(p)
}
else if(method_name=='poisson regression'){
var_func <- pois_reg_var(p)
}
else{
stop('method_name not recognized. method_name accepts one of: "linear regression",
"logistic regression","cox regression", or "poisson regression"')
}
top = (qnorm(1-fpr/2) + qnorm(power))^2
bottom = (beta*sigma_x)^2*(1-mult_cor)
n = (top/bottom)*var_func
return(ceiling(n))
}
> samplesize(method_name ='logistic regression', 1, 1, 0, p=0.5)
[1] 32