From 6a2bf3f8738829e9821e0a197f0698c00aa1d9bf Mon Sep 17 00:00:00 2001 From: Ken Kellner Date: Tue, 10 Jul 2018 16:50:23 -0400 Subject: Add benchmark app post --- src/webapp-scholar-benchmarks.Rmd | 37 +++++++++++++++++++++++++++++++++++++ 1 file changed, 37 insertions(+) create mode 100644 src/webapp-scholar-benchmarks.Rmd diff --git a/src/webapp-scholar-benchmarks.Rmd b/src/webapp-scholar-benchmarks.Rmd new file mode 100644 index 0000000..ff4f1aa --- /dev/null +++ b/src/webapp-scholar-benchmarks.Rmd @@ -0,0 +1,37 @@ +--- +title: Web App for Benchmarking Scholarly Performance +date: 2018-07-10 +output: + html_document: + css: style.css + highlight: pygments +--- + +A paper I co-authored titled "Benchmarking Scholarly Performance by Faculty in Forestry and Forest Products" was recently [published](https://academic.oup.com/jof/article/116/4/320/4930773) in *Journal of Forestry*. + +Here's the abstract: + +> Measures of scholarly performance have proliferated, without corresponding efforts to standardize comparisons among faculty. +> An exception was a recent use of regression to model sources of variation in scholarly performance by fisheries and wildlife faculty. +> We applied this model-based method to data for 404 forestry and forest products faculty from 33 doctoral-degree-granting institutional members of the National Association of University Forest Resources Programs. +> Regression models were developed for h-index, the number of publications with at least h citations, and m quotient, the annual rate of change in h-index since conferral of the Ph.D. Years since Ph.D. and percent of appointment allocated to research were important predictors for h-index and m quotient. +> We also noted positive subdisciplinary effects for research foci in conservation, ecology, disease, and quantitative methods, and negative effects for management and social science. +> Standardized residuals enabled relative performance to be compared among faculty who differ in academic age, research appointment, and subdisciplinary focus. +> Model-based benchmarking provides much-needed context for interpretation of quantitative performance metrics and can supplement comprehensive peer evaluation. +> An interactive web application is provided to facilitate such benchmarking. + +My main contribution to the paper was development of the [Shiny](https://shiny.rstudio.com/) web application. +We hope it's a useful tool for faculty and administrators to assess one metric of the impact of a scientist's scholarly work (i.e., citations). +You can try out the app below. + +
+
+ +
Load Shiny app
+
+
+ +The R source code for the app is [here](https://github.com/kenkellner/naufrp-benchmark). -- cgit v1.2.3