University league table of good research practice

Creating an international university league table based on a good research practice.

The key R files are:

• data.management.R takes the raw data from Scopus and attempts to create consistent names for institutions.
• WhoCitesEquator.Rmd is the Rmarkdown file for the complete analyses.
• ui.R and server.R make the Shiny page with the interactive results.

The two key data sets (both available in csv and RData format) are:

1. Papers.for.Analysis.500 which are a random sample of 500 of the 47,876 papers used to create the league tables, with the variables:

• doi
• affiliation
• affid, Scopus affiliation ID number
• country
• year, 2016 or 2017
• Region
• weight, fraction count of authors in the range (0,1]

2. Processed.papers.for.Shiny which is the summary data used to create the interactive league tables in Shiny, with the variables:

• year, 2016 or 2017
• country
• Region
• affiliation
• wsum, sum of fractional papers per university which determines the rank
• n, number of papers
• rank, rank per year
• cluster.member, estimated cluster based on wsum from 1 (lowest) to 5 (highest)
• p10, bootstrap probability of being in the top 10
• rlower, bootstrap lower 95% confidence interval
• rupper, bootstrap upper 95% confidence interval

3. pubmed.frame which details the EQUATOR papers used to count citations:

• type, type of EQUATOR paper: CONSORT, PRIMSA or STROBE
• title, paper title
• journal, journal title
• date, date of publication
• pmid, pubmed ID number
• year, year published