## ----setup, include=FALSE------------------------------------------------
library(ggplot2)
library(ggthemes)
library(ICC)
library(pastecs)
library(threatdemog)
library(viridis)
## ----echo=TRUE-----------------------------------------------------------
summary_all <- stat.desc(FL_all)
summary_all <- t(summary_all[c(1,3,4,5,8:11,13), c(-4,-1)])
summary_all <- data.frame(summary_all)
names(summary_all) <- c("n", "N/A", "min", "max", "median", "mean", "s.e.",
"95% CI", "s.d.")
summary_all
## ----echo = FALSE--------------------------------------------------------
cat("Threat scores:\n")
tapply(FL_all$Threat,
INDEX = FL_all$Recommendation,
FUN = mean, na.rm = T)
table(FL_all$Threat, FL_all$Recommendation)
cat("Demography scores:\n")
tapply(FL_all$Demography,
INDEX = FL_all$Recommendation,
FUN = mean, na.rm = T)
table(FL_all$Demography, FL_all$Recommendation)
## ----echo = FALSE--------------------------------------------------------
cat("Correlation between threat and demography scores:\n")
cor.test(FL_all$Threat, FL_all$Demography, use = "complete")
## ----echo = FALSE--------------------------------------------------------
ggplot(data = FL_all, aes(x = Threat, y = Demography)) +
geom_jitter(height = 0.2, width = 0.2, size = 4, alpha = 0.3) +
geom_vline(xintercept = 0, color = "red", alpha = 0.5) +
geom_hline(yintercept = 0, color = "red", alpha = 0.5) +
theme_hc()
## ----echo = FALSE--------------------------------------------------------
summary_mult <- stat.desc(multi)
summary_mult <- t(summary_mult[c(1,3,4,5,8:11,13),c(-2,-1)])
summary_mult <- data.frame(summary_mult)
names(summary_mult) <- c("n", "N/A", "min", "max", "median", "mean", "s.e.",
"95% CI", "s.d.")
summary_mult
## ----echo = TRUE---------------------------------------------------------
th_m1 <- lm(Threat ~ Person + Species, data = multi)
anova(th_m1)
summary(th_m1)
qplot(resid(th_m1),
geom = "histogram",
xlab = "Residuals",
bins = 5) + theme_hc()
ICC_thr <- ICCest(x = Species, y = Threat, data = multi)
ICC_thr
## ----echo = TRUE---------------------------------------------------------
dem_m1 <- lm(Demography ~ Person + Species, data = multi)
anova(dem_m1)
summary(dem_m1)
qplot(resid(dem_m1),
geom = "histogram",
xlab = "Residuals",
bins = 5) + theme_hc()
ICC_thr <- ICCest(x = Species, y = Demography, data = multi)
ICC_thr
## ----echo = FALSE, fig.width = 8, fig.height = 6-------------------------
tmp <- data.frame(species = c(multi$Species, multi$Species),
person = c(multi$Person, multi$Person),
category = c(rep("Threat", length(multi$Person)),
rep("Demography", length(multi$Person))),
score = c(multi$Threat, multi$Demography))
var_plot <- ggplot(data = tmp, aes(x = species, y = score)) +
geom_violin(fill = "gray87", colour = "gray87") +
geom_jitter(height = 0.05,
width = 0.4,
size = 3,
alpha = 0.8,
aes(colour = person)) +
facet_grid(. ~ category) +
scale_color_viridis(discrete = TRUE) +
coord_flip() +
labs(x = "", y = "\nScore\n") +
theme_hc() +
theme(axis.text.y = element_text(size = 8))
var_plot
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