text:
Q: Error in eval(parse()) - r unable to find argument input I am very new to R, and this is my first time of encountering the eval() function. So I am trying to use the med and boot.med function from the following package: mma. I am using it to conduct mediation analysis. med and boot.med take in models such as linear models, and dataframes that specify mediators and predictors and then estimate the mediation effect of each mediator.
The author of the package gives the flexible option of specifying one's own custom.function. From the source code of med, it can be seen that the custom.function is passed to the eval(). So I tried insert the gbmt function as the custom function. However, R kept giving me error message: Error during wrapup: Number of trees to be used in prediction must be provided. I have been searching online for days and tried many ways of specifying the number of trees parameter n.trees, but nothing works (I believe others have raised similar issues: post 1, post 2).
The following codes are part of the source code of the med function:
cf1 = gsub("responseY", "y[,j]", custom.function[j])
cf1 = gsub("dataset123", "x2", cf1)
cf1 = gsub("weights123", "w", cf1)
full.model[[j]] <- eval(parse(text = cf1))

One custom function example the author gives in the package documentation is as follows:
temp1<-med(data=data.bin,n=2,custom.function = 'glm(responseY~.,data=dataset123,family="quasibinomial",
           weights=weights123)')

Here the glm is the custom function. This example code works and you can replicate it easily (if you have mma installed and loaded). However when I am trying to use the gbmt function on a survival object, I got errors and here is what my code looks like:
temp1 <- med(data = data.surv,n=2,type = "link",
                    custom.function = 'gbmt(responseY ~.,
                                       data = dataset123,
                                       distribution = dist,
                                       train_params = start_stop,
                                       cv_folds=10,
                                       keep_gbm_data = TRUE,
                                       )')

Anyone has any idea how the argument about number of trees n.trees can be added somewhere in the above code?
Many thanks in advance!
Update: in order to replicate the example code, please install mma and try the following:
library("mma")

data("weight_behavior") ##binary x #binary y

x=weight_behavior[,c(2,4:14)]
pred=weight_behavior[,3]
y=weight_behavior[,15]

data.bin<-data.org(x,y,pred=pred,contmed=c(7:9,11:12),binmed=c(6,10), binref=c(1,1),catmed=5,catref=1,predref="M",alpha=0.4,alpha2=0.4)

temp1<-med(data=data.bin,n=2) #or use self-defined final function

temp1<-med(data=data.bin,n=2, custom.function = 'glm(responseY~.,data=dataset123,family="quasibinomial",
weights=weights123)')

I changed the custom.function to gbmt and used a survival object as responseY and the error occurs. When I use the gbmt function on my data outside the med function, there is no error.