將模擬結果存儲在R中

Question

我想估計Mantel-Haenszel差異項功能（DIF）賠率和HMDDIF指數。 我在下面編寫了函數。 在我看來，存儲結果時我犯了一個錯誤。 您能看看這個並給我反饋嗎？ 這是示例數據：

# generate dataset
r <- 1000
c <- 16
test <- matrix(rbinom(r*c,1,0.5),r,c)
# create sum scores for each student using first 15 columns
test <- cbind(test, apply(test[,1:15],1,sum))
colnames(test) <- c("v1","v2","v3","v4","v5","v6","v7","v8","v9","v10","v11","v12","v13","v14","v15","group","score")
test <- as.data.frame(test)

前15列是學生對項目/問題的正確/錯誤答案。 組成員資格列是第16列。 學生的“得分”變量是最后一列（第17列）的項目得分總和。 在我從Wikipedia（ https://en.wikipedia.org/wiki/Differential_item_functioning ）獲得的圖片中，可以找到該公式。

對於每個分數類別，我想估計這張圖中的最后兩個公式。 行是10個學生，列是六個項目/問題。 同樣，第16列是組成員身份（1-焦點，0引用）這是我的功能代碼。

    library(dplyr)

# this function first starts with the first item and loop k scores from 1-15. Then move to the second item.
# data should only contain the items, grouping variable, and person score.

Mantel.Haenszel <- function (data) { 
  # browser() #runs with debug
  for (item in 1:15) { #item loop not grouping/scoring

    item.incorrect <- data[,item] == 0 
    item.correct   <- data[,item] == 1
    Results <-  c() 

    for (k in 1:15) { # for k scores

        Ak <- nrow(filter(data, score == k, group == 0, item.correct)) #  freq of ref group & correct

        Bk <- nrow(filter(data, score == k, group == 0, item.incorrect)) #  freq of ref group & incorrect

        Ck <- nrow(filter(data, score == k, group == 1, item.correct)) #  freq of foc group & correct

        Dk <- nrow(filter(data, score == k, group == 1, item.incorrect)) #  freq of foc group & incorrect

        nrk <- nrow(filter(data, score == k, group == 0)) #sample size for ref

        nfk <- nrow(filter(data, score == k, group == 1)) #sample size for focal

        if (Bk == 0 | Ck == 0) { 

          next
        }

      nominator   <-sum((Ak*Dk)/(nrk + nfk))
      denominator <-sum((Bk*Ck)/(nrk + nfk))
      odds.ratio  <- nominator/denominator

       if (odds.ratio == 0) { 

        next
      }

      MH.D.DIF <- (-2.35)*log(odds.ratio) #index

      # save the output
      out <- list("Odds Ratio" = odds.ratio, "MH Diff" = MH.D.DIF)
      results <- rbind(Results, out)
      return(results)

    } # close score loop

  } # close item loop

 } #close function

這就是我得到的

# test funnction
Mantel.Haenszel(test)

> Mantel.Haenszel(test)
    Odds Ratio MH Diff 
out 0.2678571  3.095659

我想要得到的是

> Mantel.Haenszel(test)
    Odds Ratio MH Diff 
out 0.2678571  3.095659
    ##         ##
    ..         ..
    (15 rows here for 15 score categories in the dataset)

Answer 1

您不應該為item和k每種組合期望結果，最大輸出行數為225，除非有break任何實例？ 如果是這樣，我認為您只需要更改一些小事情。 首先，在函數開始時只聲明一次Results 。 然后，確保您正在rbind並返回Results或results, but not both. Then, move your返回results, but not both. Then, move your results, but not both. Then, move your返回值results, but not both. Then, move your到實際功能級別，而不是循環。 在下面的示例中，我還包括了當前item和k進行演示：

Mantel.Haenszel <- function (data) {
  # browser() #runs with debug

  Results <-  c()

  for (item in 1:15) {
    #item loop not grouping/scoring

    item.incorrect <- data[, item] == 0
    item.correct   <- data[, item] == 1

    for (k in 1:15) {
      # for k scores

      Ak <-
        nrow(filter(data, score == k, group == 0, item.correct)) #  freq of ref group & correct

      Bk <-
        nrow(filter(data, score == k, group == 0, item.incorrect)) #  freq of ref group & incorrect

      Ck <-
        nrow(filter(data, score == k, group == 1, item.correct)) #  freq of foc group & correct

      Dk <-
        nrow(filter(data, score == k, group == 1, item.incorrect)) #  freq of foc group & incorrect

      nrk <-
        nrow(filter(data, score == k, group == 0)) #sample size for ref

      nfk <-
        nrow(filter(data, score == k, group == 1)) #sample size for focal

      if (Bk == 0 | Ck == 0) {
        next
      }

      nominator   <- sum((Ak * Dk) / (nrk + nfk))
      denominator <- sum((Bk * Ck) / (nrk + nfk))
      odds.ratio  <- nominator / denominator

      if (odds.ratio == 0) {
        next
      }

      MH.D.DIF <- (-2.35) * log(odds.ratio) #index

      # save the output
      out <-
        list(
          item = item,
          k = k,
          "Odds Ratio" = odds.ratio,
          "MH Diff" = MH.D.DIF
        )
      Results <- rbind(Results, out)
    } # close score loop

  } # close item loop

  return(Results)

} #close function

test.output <- Mantel.Haenszel(test)

給出類似的輸出：

> head(test.output, 20)
    item k  Odds Ratio MH Diff    
out 1    3  2          -1.628896  
out 1    4  4.666667   -3.620046  
out 1    5  0.757085   0.6539573  
out 1    6  0.5823986  1.27041    
out 1    7  0.9893293  0.02521097 
out 1    8  1.078934   -0.1785381 
out 1    9  1.006237   -0.01461145
out 1    10 1.497976   -0.9496695 
out 1    11 1.435897   -0.8502066 
out 1    12 1.5        -0.952843  
out 2    3  0.8333333  0.4284557  
out 2    4  2.424242   -2.08097   
out 2    5  1.368664   -0.7375117 
out 2    6  1.222222   -0.4715761 
out 2    7  0.6288871  1.089938   
out 2    8  1.219512   -0.4663597 
out 2    9  1          0          
out 2    10 2.307692   -1.965183  
out 2    11 0.6666667  0.952843   
out 2    12 0.375      2.304949 

那是您要找的東西嗎？