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使用glmer，我可以很好地运行逻辑回归混合模型。但是当我尝试使用 做同样的事情时glmulti，我得到了错误（如下所述）。我认为问题出在我指定用于glmulti. 我想要一个函数，使用 logit 链接为包含连续固定协变量和分类随机效应的数据指定逻辑回归模型。响应变量是二进制 0/1。

样本数据：

library(lme4)
library(rJava)
library(glmulti)

set.seed(666)
x1 = rnorm(1000)  # some continuous variables 
x2 = rnorm(1000)
x3 = rnorm(1000)
r1 = rep(c("red", "blue"), times = 500)  #categorical random effects
r2 = rep(c("big", "small"), times = 500)
z = 1 + 2*x1 + 3*x2 +2*x3       
pr = 1/(1+exp(-z))         
y = rbinom(1000,1,pr)      # bernoulli response variable
df = data.frame(y=y,x1=x1,x2=x2, x3=x3, r1=r1, r2=r2)

单个 glmer 逻辑回归工作得很好：

model1<-glmer(y~x1+x2+x3+(1|r1)+(1|r2),data=df,family="binomial")

但是当我尝试通过 glmulti 使用相同的模型结构时会出现错误：

# create a function - I think this is where my problem is 

glmer.glmulti<-function(formula, data, family=binomial(link ="logit"), random="", ...){
  glmer(paste(deparse(formula),random),data=data,...)
}

# run glmulti models
glmulti.logregmixed <-
  glmulti(formula(glmer(y~x1+x2+x3+(1|r1)+(1|r2), data=df),   fixed.only=TRUE), #error w/o fixed.only=TRUE
      data=df,
      level = 2,              
      method = "g",            
      crit = "aicc",           
      confsetsize = 128,       
      plotty = F, report = F,  
      fitfunc = glmer.glmulti,
      family = binomial(link ="logit"),
      random="+(1|r1)","+(1|r2)",  # possibly this line is incorrect?
      intercept=TRUE)

#Errors returned:
singular fit
Error in glmulti(formula(glmer(y ~ x1 + x2 + x3 + (1 | r1) + (1 | r2),  : 
  Improper call of glmulti.
In addition: Warning message:
In glmer(y ~ x1 + x2 + x3 + (1 | r1) + (1 | r2), data = df) :
  calling glmer() with family=gaussian (identity link) as a shortcut     to lmer() is deprecated; please call lmer() directly

我已经尝试了对该函数以及 glmulti 代码的formulaandfitfunc部分的各种更改。我试过代替lmer，glmer我想我不明白这个错误。我也担心调用lmer可能会改变模型结构，因为在我的一次尝试summary()中，模型声明"Linear mixed model fit by REML ['lmerMod']."我需要 glmulti 模型与我model1使用时获得的相同glmer（即summary(model1)给出"Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']"

许多类似的问题仍未得到解答。提前致谢！

信用：

在此处的帮助下创建的示例数据集： https ://stats.stackexchange.com/questions/46523/how-to-simulate-artificial-data-for-logistic-regression

glmulti 代码改编自这里： Model selection using glmulti

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