Investigating Sequences in Ordinal Data: A New Approach with Adapted Evolutionary Models

Patrik Lindenfors, Fredrik Jansson, Yi Ting Wang, Staffan I. Lindberg

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This paper presents a new approach for studying temporal sequences across ordinal variables. It involves three complementary approaches (frequency tables, transitional graphs, and dependency tables), as well as an established adaptation based on Bayesian dynamical systems, inferring a general system of change. The frequency tables count pairs of values in two variables and transitional graphs depict changes, showing which variable tends to attain high values first. The dependency tables investigate which values of one variable are prerequisites for values in another, as a more direct test of causal hypotheses. We illustrate the proposed approaches by analyzing the V-Dem dataset, and show that changes in electoral democracy are preceded by changes in freedom of expression and access to alternative information.

Original languageEnglish
Pages (from-to)449-466
Number of pages18
JournalPolitical Science Research and Methods
Volume6
Issue number3
DOIs
Publication statusPublished - 2018 Jul 1

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science
  • Political Science and International Relations

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