自舉以獲得置信區間使用R

Question

我試圖使用非參數引導來引導可靠性估計 我已經寫了下面的代碼創建模型，然後引導1000次以獲得兩個可靠性統計信息Alpha和Omega 我是能夠與置信區間得到Alpha和歐米茄爲第一構建：visual =~ x1 + x2 + x3但看到沒有辦法訪問它的其他結構textual和speed 當我運行的引導功能，我看到的結果爲所有的

# 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 

下面是我承認shodd嘗試。誰能幫

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

你首先需要了解一下什麼是從reliability返回與完整數據集：

> 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 

然後，你需要看到的是返回什麼from your boot-call：

> 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" 

.... so results$t0有三個模型參數估計值。