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  1. # your code goes here
  2. n1 <- 200
  3. rep = 10
  4. result1 = matrix(NA, rep, 5)
  5. result2 = matrix(NA, rep, 5)
  6. result3 = matrix(NA, rep, 5)
  7. result4 = matrix(NA, rep, 5)
  8. total = 0
  9. set.seed(888)
  10.  
  11. for (i in 1 : rep){
  12.         mydata <- simulateData(popmodel3.5,sample.nobs=n1)
  13.         fit1 <- cfa(mismodel1.5, data = mydata, std.lv = T)
  14.         fit2 <- cfa(mismodel2.5, data = mydata, std.lv = T)
  15.         fit3 <- cfa(truemodel3.5, data = mydata, std.lv = T)
  16.         fit4 <- cfa(mismodel4.5, data = mydata, std.lv = T)
  17.         fit5 <- cfa(mismodel5.5, data = mydata, std.lv = T)
  18.         if(
  19.                 fit1@Fit@converged == 'TRUE' && 
  20.                 min(eigen(fit1@Model@GLIST$theta)$values) > 0 &&
  21.                 min(eigen(fit1@Model@GLIST$psi)$values) > 0 &&
  22.                 min(eigen(inspect(fit1,"cov.ov"))$values) > 0 &&
  23.                 fit2@Fit@converged == 'TRUE' &&
  24.                 min(eigen(fit2@Model@GLIST$theta)$values) > 0 &&
  25.                 min(eigen(fit2@Model@GLIST$psi)$values) > 0 &&
  26.                 min(eigen(inspect(fit2,"cov.ov"))$values) > 0 &&
  27.                 fit3@Fit@converged == 'TRUE' &&
  28.                 min(eigen(fit3@Model@GLIST$theta)$values) > 0 &&
  29.                 min(eigen(fit3@Model@GLIST$psi)$values) > 0 &&
  30.                 min(eigen(inspect(fit3,"cov.ov"))$values) > 0 &&        
  31.                 fit4@Fit@converged == 'TRUE' &&
  32.                 min(eigen(fit4@Model@GLIST$theta)$values) > 0 &&
  33.                 min(eigen(fit4@Model@GLIST$psi)$values) > 0 &&
  34.                 min(eigen(inspect(fit4,"cov.ov"))$values) > 0 &&  
  35.                 fit5@Fit@converged == 'TRUE' &&
  36.                 min(eigen(fit5@Model@GLIST$theta)$values) > 0 &&
  37.                 min(eigen(fit5@Model@GLIST$psi)$values) > 0 &&
  38.                 min(eigen(inspect(fit5,"cov.ov"))$values) > 0 ){
  39.                 for(n in 1 : 5){
  40.                         z <- paste("fit", n, sep = "")
  41.                         z <- fi
  42.                         result1[i, n] <- fitmeasures(z, c("ecvi"))
  43.                         result2[i, n] <- fitmeasures(z, c("aic"))
  44.                         result3[i, n] <- fitmeasures(z, c("bic"))    
  45.                         result4[i, n] <- fitmeasures(z, c("bic2")) 
  46.                 }
  47.  
  48.         }
  49.         else{
  50.                 total = total + i
  51.         }
  52. }
Runtime error #stdin #stdout #stderr 0.3s 22832KB
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Standard output is empty
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Error: could not find function "simulateData"
Execution halted
https://ideone.com/D3dX0Y
language:
R (R 3.5.2)
created:
11 years ago
visibility:
public

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