使用Owls数据和glmmTMB
包,我想直观地比较来自不同零膨胀模型的回归系数,这些模型在所用系列(ZIPOISS,ZINB1,ZINB2)和带偏移(out)之外不同( logBroodSize)。
然而,我的第一个问题是得到系数。包tidy
中的broom
函数应该为您提供系数,以便稍后使用ggplot
绘制它们,但是当我尝试获取它们时出现以下错误:
modList= list(zipoiss, zinb1, zinb2, zinb1_bs, zinb2_bs)
coefs= ldply(modList,tidy,effect="fixed",conf.int=TRUE,
.id="model") %>%
mutate(term=abbfun(term)) %>%
select(model,term,estimate,conf.low,conf.high) %>%
filter(!term %in% c("Intercept","Intercept.1","NCalls","zi_NCalls"))
Error in as.data.frame.default(x) :
cannot coerce class ""glmmTMB"" to a data.frame
Also: Warning message:
In tidy.default(X[[i]], ...) :
No method for tidying an S3 object of class glmmTMB , using as.data.frame
任何可能出错的想法?我已经被告知没有正确版本的broom
可能是原因,但是我已经安装了正确的版本...接下来提供了可重现示例的代码:
# Packages and dataset
library(glmmTMB)
library(broom) # devtools::install_github("bbolker/broom")
library(plyr)
library(dplyr)
data(Owls,package="glmmTMB")
Owls = plyr::rename(Owls, c(SiblingNegotiation="NCalls"))
Owls = transform(Owls,
ArrivalTime=scale(ArrivalTime, center=TRUE, scale=FALSE),
obs=factor(seq(nrow(Owls))))
# Models
zipoiss<-glmmTMB(NCalls~(FoodTreatment+ArrivalTime)*SexParent+
offset(logBroodSize)+(1|Nest),
data=Owls,
ziformula = ~ 1,
family="poisson")
zinb2<- glmmTMB(NCalls~(FoodTreatment+ArrivalTime)*SexParent+
offset(logBroodSize)+(1|Nest),
data=Owls,
ziformula = ~ 1,
family="nbinom2")
zinb1 <- glmmTMB(NCalls~(FoodTreatment+ArrivalTime)*SexParent+
offset(logBroodSize)+(1|Nest),
data=Owls,
ziformula = ~ 1,
family="nbinom1")
zinb1_bs<- glmmTMB(NCalls~(FoodTreatment+ArrivalTime)*SexParent+
BroodSize+(1|Nest),
data=Owls,
ziformula = ~ 1,
family="nbinom1")
zinb2_bs<- glmmTMB(NCalls~(FoodTreatment+ArrivalTime)*SexParent+
BroodSize+(1|Nest),
data=Owls,
ziformula = ~ 1,family="nbinom2")
# Get coefficients ("coefs" does not work yet...)
modList = list(zipoiss, zinb1, zinb2, zinb1_bs, zinb2_bs)
coefs = ldply(modList,tidy,effect="fixed",conf.int=TRUE,
.id="model") %>%
mutate(term=abbfun(term)) %>%
select(model,term,estimate,conf.low,conf.high) %>%
filter(!term %in% c("Intercept","Intercept.1","NCalls","zi_NCalls"))
答案 0 :(得分:0)
现在可以使用新的/开发不足的broom.mixed软件包(截至今天),例如
devtools::install_github("bbolker/broom.mixed")
希望很快就会出现在CRAN上,但它只是中等优先级 对我而言,我不想将它发布到CRAN,直到它至少有90%被烘焙。拉请求欢迎!
最后一步改变了一点(首先,我似乎没有abbfun
):
modList = lme4:::namedList(zipoiss, zinb1, zinb2, zinb1_bs, zinb2_bs)
coefs = ldply(modList,tidy,effect="fixed",conf.int=TRUE,
.id="model") %>%
select(model,term,component,estimate,conf.low,conf.high) %>%
filter(!term %in% c("(Intercept)","NCalls"))
警告:glmmTMB
模型的这些工具的开发是相当新的/实验性的;您应该(1)仔细检查您的结果,并且(2)report an issue如果某些事情没有按预期工作。