如何绘制 lmer 模型的一些术语

Question

I am trying to plot only a few terms of random effects from a lmer object. I will borrow the dataset posted by oshun here .

Make up data:

tempEf <- data.frame(
  N = rep(c("Nlow", "Nhigh"), each=300),
  Myc = rep(c("AM", "ECM"), each=150, times=2),
  TRTYEAR = runif(600, 1, 15),
  site = rep(c("A","B","C","D","E"), each=10, times=12)   #5 sites
)

Make up some response data

tempEf$r <- 2*tempEf$TRTYEAR +                   
  -8*as.numeric(tempEf$Myc=="ECM") +
  4*as.numeric(tempEf$N=="Nlow") +
  0.1*tempEf$TRTYEAR * as.numeric(tempEf$N=="Nlow") +
  0.2*tempEf$TRTYEAR*as.numeric(tempEf$Myc=="ECM") +
  -11*as.numeric(tempEf$Myc=="ECM")*as.numeric(tempEf$N=="Nlow")+ 
  0.5*tempEf$TRTYEAR*as.numeric(tempEf$Myc=="ECM")*as.numeric(tempEf$N=="Nlow")+ 
  as.numeric(tempEf$site) +  #Random intercepts; intercepts will increase by 1
  tempEf$TRTYEAR/10*rnorm(600, mean=0, sd=2)    #Add some noise

library(lme4)
model <- lmer(r ~ Myc * N * TRTYEAR + (1|site), data=tempEf)

I can plot random effects by using type = "re" as follows:

plot_model(model, type = "re")

I would like to show only A and E so I add the 'terms' argument as follows:

plot_model(model, type = "re", terms = c("A", "E"))

But this does not work. Any guidance on how I can show "A" and "E" only??

Answer 1

For some reason, the terms option doesn't work. Should be reflected to the authors of sjplot. Here's two workarounds:

1) manually define the terms using ggplot2:

library(ggplot2)
library(sjPlot)

plot_model(model, type = "re") + scale_x_discrete(limits=c("A","D"))

You get the following warnings because you throw out data

Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing scale. Warning messages: 1: Removed 3 rows containing missing values (geom_point). 2: Removed 3 rows containing missing values (geom_errorbar).

2) Plot it from get_model()

    df = get_model_data(model,type="re")
    df = subset(df,term %in% c("A","D"))
    ggplot(df,aes(x=term,y=estimate,col=group)) +
    geom_point(show.legend=FALSE) + 
    geom_segment(aes(xend=term,y=conf.low,yend=conf.high),show.legend=FALSE)+
    scale_colour_brewer(palette = "Set1")+
    coord_flip()+ggtitle("Random Effects")