---
title: "Tools to calculate SII and its extensions"
output: rmarkdown::html_vignette
author: Tian-Yuan Huang
vignette: >
  %\VignetteIndexEntry{Tools to calculate SII and its extensions}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

This vignette introduces how to use *siie* package to calculate SII and its extensions introduced in the paper "Superior identification index: Quantifying the capability of academic journals to recognize good research"(<https://doi.org/10.1007/s11192-022-04372-z>). First, we construct a data set manually, suspecting that there are 10,000 papers from 26 journals with their citation counts.

```{r}
set.seed(19960822)
nr_of_rows = 1e4
data.frame(
  Id = 1:1e4,
  Journal = sample(LETTERS,nr_of_rows,replace = TRUE),
  CiteCount = sample(1:100,nr_of_rows,replace = TRUE)
) -> journal_table
```

To get the SII (Superior Identification Index) and SIE (Superior Identification Efficiency) for the 26 journals (represented by letters), we can:

```{r}
library(siie)
library(tidyfst)

journal_table %>% siie(group = "Journal",index = "CiteCount")
```

Note that the default superior cutoff (parameter **p**) is 10, indicating that top 10% papers are regarded as superior. If we want to use a different **p**, say 1, we can:

```{r,eval=FALSE}
journal_table %>% siie(group = "Journal",index = "CiteCount",p = 1)
```


To get the PRP (Paper Rank Percentile) for the 26 journals, we can:

```{r}
prp(journal_table,group = "Journal",index = "CiteCount")
```

Last, if we want to draw p-SIE curve for Journals A, B and C, we can:

```{r,out.width="70%",fig.align = "center",fig.height = 6, fig.width = 6}
library(ggplot2)

p_sie(journal_table,group = "Journal",
      index = "CiteCount",to_compare = c("A","B","C")) -> p_sie_df

p_sie_df

p_sie_df %>%
  ggplot(aes(p/100,sie,color = Journal)) +
  geom_point() +
  geom_line() +
  geom_abline(slope = 1,linetype = "dashed") +
  scale_x_continuous(labels = tidyfst::percent) +
  scale_y_continuous(labels = tidyfst::percent) +
  labs(x = "p",y = "SIE") +
  theme_bw() +
  theme(legend.position = c(0.8, 0.3),
        legend.background = element_rect(linewidth=0.5,
                                         color = "black",linetype="solid"))
```

<br> Notice that we use the `tidyfst::percent` to change the scales of x and y.