引導以使用R獲得置信區間

Question

我試圖使用非參數引導程序來引導可靠性估計，我在下面的代碼中創建了一個模型，然后將其引導了1000次，以便獲得兩個可靠性統計信息Alpha和Omega。我能夠獲得第一個構造的Alpha和Omega具有置信區間： visual =~ x1 + x2 + x3但是看不到其他構造的textual和speed訪問方法當我運行啟動功能時，我看到了所有結果

# bootstrapping with 1000 replications
results <- boot(data=data, statistic=reliability, R=500, formula=HS.model,parallel = 'snow')

> results$t0

        visual   textual     speed     total
alpha  0.6261171 0.8827069 0.6884550 0.7604886
omega  0.6253180 0.8851754 0.6877600 0.8453351
omega2 0.6253180 0.8851754 0.6877600 0.8453351
omega3 0.6120052 0.8850608 0.6858417 0.8596204
avevar 0.3705589 0.7210163 0.4244883 0.5145874

以下是我公認的偽劣嘗試。 誰能幫忙

library(lavaan)
library(semTools)
library(boot)

data <- HolzingerSwineford1939

HS.model <- 'visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9 '

# function to reliability stats
reliability <- function(formula, data, indices) {
  data = data
  d <- data[indices,] # allows boot to select sample
  fit <- cfa(HS.model, data=d)
  semTools::reliability(fit)
}

# bootstrapping with 500 replications
results <- boot(data=data, statistic=reliability, R=500, formula=HS.model,parallel = 'snow')

# Get the confidence intervals
conf_interval_alpha <- boot.ci(results, type="bca", index = 1)

# Retrieve the Alpha and confidence intervals
alpha <- conf_interval_alpha$t0
alpha.ci <- conf_interval_alpha$bca[,c(4,5)]

# Retrieve the Omega and confidence intervals  
conf_interval_omega <- boot.ci(results, type="bca", index = 2)
omega <- conf_interval_omega$t0
omega.ci <- conf_interval_omega$bca[,c(4,5)]

謝謝您的幫助

Answer 1

首先，您需要查看完整數據集的reliability返回的結果：

> reliability(data=data)
          visual   textual     speed     total
alpha  0.6261171 0.8827069 0.6884550 0.7604886
omega  0.6253180 0.8851754 0.6877600 0.8453351
omega2 0.6253180 0.8851754 0.6877600 0.8453351
omega3 0.6120052 0.8850608 0.6858417 0.8596204
avevar 0.3705589 0.7210163 0.4244883 0.5145874

然后，您需要查看boot調用返回的內容：

> str(results)
List of 11
 $ t0       : num [1:5, 1:4] 0.626 0.625 0.625 0.612 0.371 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:5] "alpha" "omega" "omega2" "omega3" ...
  .. ..$ : chr [1:4] "visual" "textual" "speed" "total"
 $ t        : num [1:500, 1:20] 0.594 0.607 0.613 0.669 0.621 ...
 $ R        : num 500
 $ data     :'data.frame':  301 obs. of  15 variables:
  ..$ id    : int [1:301] 1 2 3 4 5 6 7 8 9 11 ...
  ..$ sex   : int [1:301] 1 2 2 1 2 2 1 2 2 2 ...
  ..$ ageyr : int [1:301] 13 13 13 13 12 14 12 12 13 12 ...
  ..$ agemo : int [1:301] 1 7 1 2 2 1 1 2 0 5 ...
  ..$ school: Factor w/ 2 levels "Grant-White",..: 2 2 2 2 2 2 2 2 2 2 ...
  ..$ grade : int [1:301] 7 7 7 7 7 7 7 7 7 7 ...
  ..$ x1    : num [1:301] 3.33 5.33 4.5 5.33 4.83 ...
  ..$ x2    : num [1:301] 7.75 5.25 5.25 7.75 4.75 5 6 6.25 5.75 5.25 ...
  ..$ x3    : num [1:301] 0.375 2.125 1.875 3 0.875 ...
  ..$ x4    : num [1:301] 2.33 1.67 1 2.67 2.67 ...
  ..$ x5    : num [1:301] 5.75 3 1.75 4.5 4 3 6 4.25 5.75 5 ...
  ..$ x6    : num [1:301] 1.286 1.286 0.429 2.429 2.571 ...
  ..$ x7    : num [1:301] 3.39 3.78 3.26 3 3.7 ...
  ..$ x8    : num [1:301] 5.75 6.25 3.9 5.3 6.3 6.65 6.2 5.15 4.65 4.55 ...
  ..$ x9    : num [1:301] 6.36 7.92 4.42 4.86 5.92 ...
 $ seed     : int [1:626] 403 330 1346657232 1136157038 -874329217 857221657 1850455833 952027245 2020402269 -1198488986 ...
 $ statistic:function (formula, data, indices)  
  ..- attr(*, "srcref")=Class 'srcref'  atomic [1:8] 1 16 6 1 16 1 1 6
  .. .. ..- attr(*, "srcfile")=Classes 'srcfilecopy', 'srcfile' <environment: 0x7fa57918d430> 
 $ sim      : chr "ordinary"
 $ call     : language boot(data = data, statistic = reliability, R = 500, formula = HS.model, parallel = "snow")
 $ stype    : chr "i"
 $ strata   : num [1:301] 1 1 1 1 1 1 1 1 1 1 ...
 $ weights  : num [1:301] 0.00332 0.00332 0.00332 0.00332 0.00332 ...
 - attr(*, "class")= chr "boot"

....因此results$t0包含所有三個模型參數估計值。