如何使用glmer（）解释GLMM泊松回归中的不同采样努力-easy Reproducted exampled inc

我一直在努力处理我的数据集，似乎已经有很长一段时间了。希望有人能给我指出正确的方向

我想知道如何使用glmer（）解释我的GLMM泊松回归中不同的采样努力

我们从绘图中收集计数数据，有时3晚，有时2晚

我不确定我是否应该：

创建每个图的平均丰度，四舍五入平均值（泊松数的整数），然后运行我的模型-这消除了在我的完整数据集中发现的过度分散

添加采样工作量的偏移量（二进制2或3）- 偏移量（对数（采样工作量））

添加位置（1 | Loc/Plot）和日期（1 | Date）内嵌套的绘图的随机效果，并希望glmer解释采样工作

以上全部或部分

任何帮助都将不胜感激。我有一个物种丰富度、多样性和特定丰富度的完整数据集要检查，但这或多或少只涉及复制模型。干杯

下面的例子。只需运行代码

# obtain data

dl_from_dropbox <- function(x, key) {
  require(RCurl)
  bin <- getBinaryURL(paste0("https://dl.dropboxusercontent.com/s/", key, "/", x),
                      ssl.verifypeer = FALSE)
  con <- file(x, open = "wb")
  writeBin(bin, con)
  close(con)
  message(noquote(paste(x, "read into", getwd())))                        
}

dl_from_dropbox("Reproducible_example.csv", "4z97tlkfedmutqr")
shell.exec("Reproducible_example.csv")

# read data

data<-read.csv("Reproducible_example.csv")

# run models

library(lme4)

glmer_offset_no_date<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot) + offset(log(Sampling_effort)), data = data, family = poisson(link = "log"))

glmer_no_offset_no_date<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot) , data = data, family = poisson(link = "log"))

glmer_offset_date<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot) + (1|Date) + offset(log(Sampling_effort)), data = data, family = poisson(link = "log"))

glmer_no_offset_date<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot) + (1|Date), data = data, family = poisson(link = "log"))

AIC(glmer_no_offset,glmer_offset,glmer_no_offset_date,glmer_offset_date)

# or take mean abundance per plot and run the model with/without an offset #

# tidy data
library(plyr)
Mean_abundance_per_plot<-ddply(data, c("Plot", "Loc", "Habitat", "latitude", "longitude"), colwise(mean))
Mean_abundance_per_plot<-Mean_abundance_per_plot[,-6]
library(dplyr)
Mean_abundance_per_plot_rounded<-Mean_abundance_per_plot %>% mutate_each(funs(round(.,0)), -c(Loc, Plot, Habitat,latitude, longitude)) 

# run models 

glmer_avg_offset<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot) + offset(log(Sampling_effort)), data = Mean_abundance_per_plot_rounded, family = poisson(link = "log"))

glmer_avg_no_offset<- glmer(Total_abundance ~ Habitat + (1|Loc/Plot), data = Mean_abundance_per_plot_rounded, family = poisson(link = "log")) # fails to converge

#获取数据
来自dropbox的dl_