03-additional-analyses.Rmd

---
title: "03-additional-investigations"
author: "Thomas Klebel"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output: 
  html_document:
    keep_md: true
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, dpi = 300)
library(janitor)

df <- readd(merged)
metadata <- readd(metadata)

extrafont::loadfonts(device = "win")

theme_set(hrbrthemes::theme_ipsum(base_family = "Hind"))
```

# Relationship pub quality, citations, journal metrics
What are the propensities for universities mentioning pub quality also mentioning
citations and jourmal metrics?


```{r}
df_pub <- df %>% 
  filter(code_legible %in% c("Journal metrics", "Citations", 
                             "Publication quality")) %>% 
  group_by(country, university, code_legible) %>%
  summarise(uni_has_indicator = any(quant_indicator > 0, na.rm = TRUE)) %>% 
  ungroup() %>% 
  pivot_wider(names_from = "code_legible", values_from = "uni_has_indicator")
df_pub



```

```{r}
df_pub %>% 
  tabyl(`Publication quality`, Citations) %>% 
  adorn_percentages() %>% 
  adorn_totals("col") %>% 
  adorn_pct_formatting()
```

```{r}
df_pub %>% 
  tabyl(`Publication quality`, `Journal metrics`) %>% 
  adorn_percentages() %>% 
  adorn_totals("col") %>% 
  adorn_pct_formatting()
```
```{r}
df_pub %>% 
  tabyl(Citations, `Journal metrics`) %>% 
  adorn_percentages() %>% 
  adorn_totals("col") %>% 
  adorn_pct_formatting()
```


```{r}
metadata %>% 
  mutate(across(c("research", "citations"), .fns = as.numeric)) %>% 
  select(country, citations, research) %>% 
  pivot_longer(-country) %>% 
  ggplot(aes(value, country)) +
  geom_boxplot() +
  geom_jitter(height = .05, alpha = .6, colour = "#3288BD") +
  facet_wrap(vars(name)) +
  labs(y = NULL, x = "Ranking value")

```