R user function to run gmm model repeatedly using pgmm function

I have created a function to run gmm model repeatedly using pgmm function from plm package. here is the code.

```
   run.gmm <- function(data,
              predictor,
              dep,
              controls,
              row.name = predictor,
              add.controls = NULL,
              rm.controls = NULL,
              caption = NULL, model, effect, transformation) {
     gmodel <-
              return.model.gmm(data,
                 predictor,
                 dep,
                 controls,
                 add.controls,
                 rm.controls, model, effect, transformation)
    if (Console == T) {
       print(summary(gmodel, robust = TRUE, time.dummies = TRUE))
     }
      invisible(gmodel)
      }

     return.model.gmm <- function(data, predictor, dep, controls, add.controls = NULL, 
                                  rm.controls = NULL, effect, model, mtransformation) {
                 controls <- controls[!controls %in% rm.controls]
                 controls <- paste("lag(", c(controls, add.controls), ",1)", collapse = " + ")
                 predictors <- paste(predictor, controls, sep = " + ")
                 formula <- paste(dep, predictors, sep = " ~ ")
                 gmmodel <- pgmm(formula, paste("|", controls), data = data, effect = effect, 
                             model = model, transformation = transformation)
                 return(gmmodel)
         } 
     ```

with above, now I plugged the arguments:

my.controls <- c("lnPDENS", "GDPGR", "LFSGR", 'GRRAT')
my.predictor = paste("lag(", c("LaPGrowth", "SRate"), ",1)", collapse = " + ")
my.effect <- c("twoways")
my.model <- c("twosteps")
my.transformation <- c("ld")

run.gmm(data=pdata.lbprt, dep="LaPGrowth", predictor = my.predictor, controls = my.controls, effect=my.effect, 
       model=my.model, transformation=my.transformation)

I get the following error:

Error in match.arg(effect) : 'arg' should be one of “twoways”, “individual”

Any idea, where my code is wrong. I believe the error can be detected even without sample data.

Greatly appreciate your help.

Finally, I could solve the problem. It was really worth spending time. Here is the final code:

require(Formula)
require(magrittr)
require(plm)

run.gmm <- function(data,
                  predictor,
                  dep,
                  controls,
                  row.name = predictor,
                  add.controls = NULL,
                  rm.controls = NULL,
                  caption = NULL, effect, model, transformation) {
 gmodel <-
  return.model.gmm(data,
                     predictor,
                     dep,
                     controls,
                     add.controls,
                     rm.controls, effect, model, transformation)
 if (Console == T) {
  print(summary(gmodel, robust = TRUE, time.dummies = TRUE))
 }
 invisible(gmodel)
}

return.model.gmm <- function(data, predictor, dep, controls, add.controls = NULL, 
                         rm.controls = NULL, effect, model, mtransformation) {
  
             controls <- controls[!controls %in% rm.controls]
             controls <- paste("lag(", c(controls, add.controls), ",1)", collapse = " + ")
             predictors <- paste(predictor, paste(controls, sep = " + "), sep='+')
             formula <- paste(dep, predictors, sep = " ~ ")
             multipart <- paste(formula, "|", controls)
             multipartformula <- Formula::Formula(as.formula(multipart))
             gmmodel <- pgmm(multipartformula, data = data, effect = effect, model = 
                         model, transformation = transformation)
    
       return(gmmodel)
}

Notice the changes. I have used Formula function from Formula package to incorporate multipart formula object. Also, note the changes in 'predictors'. The function works perfectly.