在 R 中提取 glmer() 函数的结果

Question

我想模拟多级逻辑分布 1000 次和每次估计参数的数据并计算估计值的平均值。但似乎，在glmer() 函数中的结果不能像lm() 函数那样提取，比如lm(y~x)$coef。如何从glmer() 函数中提取结果？

这里是 R 代码：

#Simulating data from multilevel logistic distribution 

library(mvtnorm)
library(lme4)

set.seed(1234)

## J               = number of groups
## n               = group size
## g00,g10,g01,g11 = fixed effect parameters .
## s2_0,s2_1,s01   = variance values for the group level random effect .

simu <- function(J,n,g00,g10,g01,g11,s2_0,s2_1,s01){

  n_j <- rep(n,J)     ## number of individuals in jth group
  N <- sum(n_j)       ## sample size

  #Simulate the covariate value for this sample size .
  z <- rnorm(J)
  x <- rnorm(N)

  #Generate (u_0j,u_1j) from a bivariate normal .
  mu <- c(0,0)
  sig <- matrix(c(s2_0,s01,s01,s2_1),ncol=2)
  u <- rmvnorm(J,mean=mu,sigma=sig,method="chol")

  #Now form the linear predictor .
  pi_0 <- g00 +g01*z + u[,1]
  pi_1 <- g10 + g11*z + u[,2]

  eta <- rep(pi_0,n_j)+rep(pi_1,n_j)*x

  #Transform back to the probability scale .
  p <- exp(eta)/(1+exp(eta))

  #Simulate a bernoulli from each individual distribution .
  y <- rbinom(N,1,p)

  # estimating parameters 

  sim_data_mat <- matrix(c(y,x,rep(z,n_j),rep(1:30,n_j)),ncol=4)
  sim_data <- data.frame(sim_data_mat)
  colnames(sim_data) <- c("Y","X","Z","cluster")

  res <-summary(glmer(Y~X*Z+(1|cluster),family=binomial,data=sim_data,nAGQ=10))
  res$coef
}


out <- replicate(10,simu(30,5,-1,.3,.3,.3,.13,1,0))
##Error in res$coef : $ operator not defined for this S4 class

如何从glmer() 函数中提取结果？

sessionInfo()
R version 2.14.0 (2011-10-31)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] lme4_0.999999-0  Matrix_1.0-1     lattice_0.20-10  mvtnorm_0.9-9994

loaded via a namespace (and not attached):
[1] grid_2.14.0   nlme_3.1-102  stats4_2.14.0 tools_2.14.0 

Answer 1

在混合效应模型中，您有两种类型的系数（因此是“混合”）：固定系数和随机系数。两者都可以使用专用函数从 lmer/glmer 对象中提取。例如：

lmer_obj = glmer(Y ~ X1 + X2 + (1|Subj), data = D, family = binomial)
fixef(lmer_obj) ## returns fixed effects 
ranef(lmer_obj) ## returns random effects