geographic_tarsiers:

## This is the code to create the coefficient plot
library(ggplot2)

model1 <- as.data.frame(precis(n.notes.gp.only.female.indiv ))
model1 <-model1[c(2:3),] # This is different because doesn't have extra sigmasq parameter

model2 <- as.data.frame(precis(notefreq.gp.cov.female.indiv))
model2 <-model2[c(2:7),]

model3 <- as.data.frame(precis(notedur.gp.only.female.indiv))
model3 <-model3[c(2:4),]

model5 <- as.data.frame(precis(noterate.gp.only.male.indiv))
model5 <-model5[c(2:4),]

# N notes spatial
1.09/ (1.09+0.07)

# Note freq spatial
0.56 /(0.56+0.56)

# Note duration spatial
2.23 /(2.23+0.38)

# Note rate spatial
0.77 / (0.77+1.56)




# Put model estimates into temporary data.frames:
model1Frame <- data.frame(Variable = rownames(model1),
                          Coefficient = model1$mean,
                          ymin = model1$`5.5%`,
                          ymax =model1$`94.5%`,
                          modelName = "Female Number of Notes")

model2Frame <- data.frame(Variable = rownames(model2),
                          Coefficient = model2$mean,
                          ymin = model2$`5.5%`,
                          ymax =model2$`94.5%`,
                          modelName = "Female Note 1 Max Frequency")

model3Frame <- data.frame(Variable = rownames(model3),
                          Coefficient = model3$mean,
                          ymin = model3$`5.5%`,
                          ymax =model3$`94.5%`,
                          modelName = "Female Note 1 Duration")

model5Frame <- data.frame(Variable = rownames(model5),
                          Coefficient = model5$mean,
                          ymin = model5$`5.5%`,
                          ymax =model5$`94.5%`,
                          modelName = "Male Note Rate")

# Combine these data.frames
allModelFrame <- data.frame(rbind(model1Frame,model2Frame,model3Frame,model5Frame))  # etc.


# Plot
zp1 <- ggplot(allModelFrame, aes(colour = modelName))
zp1 <- zp1 + geom_hline(yintercept = 0, colour = gray(1/2), lty = 2)
# zp1 <- zp1 + geom_linerange(aes(x = Variable, ymin = Coefficient - SE*interval1,
#                                 ymax = Coefficient + SE*interval1),
#                             lwd = 1, position = position_dodge(width = 1/2))
zp1 <- zp1 + geom_pointrange(aes(x = Variable, y = Coefficient, ymin = ymin,
                                 ymax = ymax),
                             lwd = 1/2, position = position_dodge(width = 1/2),
                             shape = 21, fill = "WHITE") + scale_color_manual(values=c(viridis::viridis(4,end=0.8)))
zp1 <- zp1 + coord_flip() + theme_bw()+ theme(legend.title=element_blank())+ xlab("")
zp1 <- zp1 + ggtitle("")
zp1 <- zp1 + scale_x_discrete(labels=c("Eta-squared", "Rho-squared", "Mainland (0) or Island (1)","Temperature (C)","Rainfall (mm)",  "Sigma-squared"))
print(zp1)  # The trick to these is position_dodge().