Issue with do.call specification of second argument

Question

I created a function that should evaluate the performance of two statistical tests. within this function I am using the call-function within the first function to create my data generations. (already sorry for the amount of code) Thank you for your help! The problem arises in the first if else statement in the first for loop. the Error says: Error in [.data.frame(Design, RowDesign, ) : object 'RowDesign' not found Here is the Function:

SimStudy <- function(Design, RowDesign, K){
  #Design = Design Matrix
  #RowDesign = Number that indicates which row of Design Matrix is used
  #K = number that indicates amount of generated data sets for each row
  Results <- matrix(NA, nrow=K, ncol=4)
  for(k in 1:K){
    if(normal) {
      SimuDat <- call("DataGeneration1", x=Design[RowDesign, ])
    }else{
      SimuDat <- call("DataGeneration2", x=Design[RowDesign, ])
    }
    #Analysis with both methods
    #Analysis with Welchs´s T-test
    Analysis_old <- Method_old(SimData=SimuDat)
    #Analysis with Trimmed F-test
    Analysis_new <- Method_new(SimData=SimuDat)
    P_old <- Analysis_old$p.value
    P_new <- Analysis_new$p.value
    #store in Vector (optional)
    ResultsAnalysis <- c(P_old, P_new)
    #Evaluation
    Hyp <- ifelse(Design[RowDesign,"ef"] == 0, TRUE, FALSE)
    TypeIerror_old <- 0
    TypeIerror_new <- 0
    TypeIIerror_old <- 0
    TypeIIerror_new <- 0
    if(Hyp==TRUE) {#i do not need to write ==TRUE necessarily
      #Type I error
      if(P_old < 0.05){
        TypeIerror_old <- TypeIerror_old + 1
      }
      if(P_new < 0.05){
        TypeIerror_new <- TypeIerror_new + 1
      }
      #Type II error
      if(P_old >= 0.05){
        TypeIIerror_old <- TypeIIerror_old + 1
      }
      if(P_new >= 0.05){
        TypeIIerror_new <- TypeIIerror_new + 1
      }
    }#end if hyp
    Results[k, ] <- c(TypeIerror_old, TypeIerror_new, TypeIIerror_old, TypeIIerror_new)
  }#end for 1
  return(Results)
}

And this is the code part with which i call the function:

totalcells <- nrow(Design1)
magic_for(put,silent=TRUE)
for(i in 1:totalcells){
  RowDesign <- i
  MyResult <- SimStudy(Design=Design1, RowDesign=RowDesign, K=4) 
}#end loop Sim All rows
Result <- magic_result()

Finally, the functions and packages necessary to run the code:

#Packages necessary
install.packages("stats") 
install.packages("PearsonDS")
install.packages("dplyr")
install.packages("magicfor")
library(stats)
library(PearsonDS)
library(dplyr)
library(magicfor)
#Preperation to creat fulfactorial Design Matrix
samp1 <- c(1,2,3,4)
samp2 <- c(1,2,3,4)
ef <- c(0,0.2,0.5,0.8)
vari1 <- c(3)
vari2 <- c(3,9)
Design1 <- expand.grid(samp1=samp1, samp2=samp2, ef=ef, vari1=vari1, vari2=vari2)
#Functions necessary
DataGeneration1 <- function(samp1, samp2, ef, vari1, vari2){
  gen1 <- rnorm(n=samp1, mean=1, sd=sqrt(vari1))
  gen2 <- rnorm(n=samp2, mean=1+ef, sd=sqrt(vari2))
  Y <- c(gen1, gen2)
  group <- as.factor(c(rep(1, times=length(gen1)), rep(2, times=length(gen2))))
  SimData <- data.frame(Y,group)
  return(SimData)
}
DataGeneration2 <- function(samp1, samp2, ef, vari1, vari2){
  gen1 <- rnorm(n=samp1, mean=1, sd=sqrt(vari1)+2)
  gen2 <- rnorm(n=samp2, mean=1+ef, sd=sqrt(vari2)+1)
  Y <- c(gen1, gen2)
  group <- as.factor(c(rep(1, times=length(gen1)), rep(2, times=length(gen2))))
  SimData <- data.frame(Y,group)
  return(SimData)
}
Method_old<- function(SimData){
  formula <- Y~group
  res <- t.test(formula, data = SimData)
  return <- res
}
Method_new<- function(SimData){
  formula <- Y~group
  res <- wilcox.test(formula, data = SimData)
  return <- res
}

Please share your data to [make your code reproducible](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example). `dput()` is a great function for easily including data — Jan Boyer, Apr 17 '20 at 15:56
what is a full factorial matrix? can you elaborate on that? do.call only works with list — StupidWolf, Apr 17 '20 at 20:19
@JanBoyer, I took your tipp and added my script. Maybe this way it is easier to understand my problem — Lena, Apr 19 '20 at 12:51

score 0 · Answer 1 · answered Apr 17 '20 at 10:19

0

Maybe you can try

if(normal){
      SimData <- do.call(MyDataGeneration1, as.list(x[y, ]))
    }else{
      SimData <- do.call(MyDataGeneration2, as.list(x[y, ]))
    }

answered Apr 17 '20 at 10:19

ThomasIsCoding

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Thank you for the tipp! I tried that and unfortunately it does still give me the same error. – Lena Apr 17 '20 at 10:49

Issue with do.call specification of second argument

1 Answers1