دورية أكاديمية

An Alternative to the Carnegie Classifications: Identifying Similar Doctoral Institutions With Structural Equation Models and Clustering

التفاصيل البيبلوغرافية
العنوان: An Alternative to the Carnegie Classifications: Identifying Similar Doctoral Institutions With Structural Equation Models and Clustering
المؤلفون: Paul Harmon, Sarah McKnight, Laura Hildreth, Ian Godwin, Mark Greenwood
المصدر: Statistics and Public Policy, Vol 6, Iss 1, Pp 87-97 (2019)
بيانات النشر: Taylor & Francis Group, 2019.
سنة النشر: 2019
المجموعة: LCC:Political institutions and public administration (General)
LCC:Probabilities. Mathematical statistics
مصطلحات موضوعية: carnegie classification, clustering, institutional research, multivariate statistics, structural equation modeling, Political institutions and public administration (General), JF20-2112, Probabilities. Mathematical statistics, QA273-280
الوصف: The Carnegie Classification of Institutions of Higher Education is a commonly used framework for institutional classification that classifies doctoral-granting schools into three groups based on research productivity. Despite its wide use, the Carnegie methodology involves several shortcomings, including a lack of thorough documentation, subjectively placed thresholds between institutions, and a methodology that is not completely reproducible. We describe the methodology of the 2015 and 2018 updates to the classification and propose an alternative method of classification using the same data that relies on structural equation modeling (SEM) of latent factors rather than principal component-based indices of productivity. In contrast to the Carnegie methodology, we use SEM to obtain a single factor score for each school based on latent metrics of research productivity. Classifications are then made using a univariate model-based clustering algorithm as opposed to subjective thresholding, as is done in the Carnegie methodology. Finally, we present a Shiny web application that demonstrates sensitivity of both the Carnegie Classification and SEM-based classification of a selected university and generates a table of peer institutions in line with the stated goals of the Carnegie Classification.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2330-443X
2330443X
Relation: https://doaj.org/toc/2330-443X
DOI: 10.1080/2330443X.2019.1666761
URL الوصول: https://doaj.org/article/f007412b430f421281526df5ebf677ca
رقم الأكسشن: edsdoj.f007412b430f421281526df5ebf677ca
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2330443X
DOI:10.1080/2330443X.2019.1666761