CEOdata is an R package aimed at facilitating the incorporation of microdata (individual responses) of public opinion polls in Catalonia into R, as performed by the “Centre d’Estudis d’Opinió” (CEO, Opinion Studies Center).
This research examines the working time preferences of women with different stable schedules working 20 hours per week in manufacturing jobs. To this end, qualitative research was employed to identify worker profiles deriving from these women's …
PolicyPortfolios is an R package aimed at providing tools for managing, measuring and visualizing policy portfolios. It simplifies the creation of data structures suitable for dealing with policy portfolios, that is, two-dimensional spaces of policy instruments and policy targets.
Why PolicyPortfolios? A policy portfolio is a collection of simple assessments of the presence or absense of state intervention in a specific area (Target) using a concrete state capacity (Instrument).
ggmcmc is an R package aimed at providing tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis.
Book to be used as a teaching resource for an introductory course on data sources and indicators for international relations and comparative politics.
Introduction This tutorial shows how to process the dataset of institutional characteristics of regulatory agencies in R. It presents the dataset presented at the journal article entitled “Agency proliferation and the globalization of the regulatory state: Introducing a data set on the institutional features of regulatory agencies”, by Jacint Jordana, Xavier Fernández-i-Marín and Andrea C.
This paper asks whether strong bureaucracies can effectively constrain the continuously growing stock of rules in modern democracies through organizational coordination and learning. To answer this question, the paper analyzes the growth of rule …
There is a pdf version of Using the ggmcmc package.
Why ggmcmc? ggplot2, based on the grammar of graphics (Wilkinson et al. 2005), empowers R users by allowing them to flexibly crate graphics (Wickham 2009).