The Scythe Statistical Library: An Open Source C++ Library for Statistical Computation

The Scythe Statistical Library is an open source C++ library for statistical computation. It includes a suite of matrix manipulation functions, a suite of pseudo-random number generators, and a suite of numerical optimization routines. Programs written using Scythe are generally much faster than those written in commonly used interpreted languages, such as R and \proglang{MATLAB}; and can be compiled on any system with the GNU GCC compiler (and perhaps with other C++ compilers). One of the primary design goals of the Scythe developers has been ease of use for non-expert C++ programmers. Ease of use is provided through three primary mechanisms: (1) operator and function over-loading, (2) numerous pre-fabricated utility functions, and (3) clear documentation and example programs. Additionally, Scythe is quite flexible and entirely extensible because the source code is available to all users under the GNU General Public License.

World Addiction Medicine Reports : formation of the International Society of Addiction Medicine (ISAM) Global Expert Network (ISAM-GEN) and Its global surveys

Funding: All the infrastructure funding of this initiative is supported by the International Society of Addiction Medicine (ISAM). We will be open to fundraising for specific projects within the platform and future collaboration with external partners.Addiction medicine is a dynamic field that encompasses clinical practice and research in the context of societal, economic, and cultural factors at the local, national, regional, and global levels. This field has evolved profoundly during the past decades in terms of scopes and activities with the contribution of addiction medicine scientists and professionals globally. The dynamic nature of drug addiction at the global level has resulted in a crucial need for developing an international collaborative network of addiction societies, treatment programs and experts to monitor emerging national, regional, and global concerns. This protocol paper presents methodological details of running longitudinal surveys at national, regional, and global levels through the Global Expert Network of the International Society of Addiction Medicine (ISAM-GEN). The initial formation of the network with a recruitment phase and a round of snowball sampling provided 354 experts from 78 countries across the globe. In addition, 43 national/regional addiction societies/associations are also included in the database. The surveys will be developed by global experts in addiction medicine on treatment services, service coverage, co-occurring disorders, treatment standards and barriers, emerging addictions and/or dynamic changes in treatment needs worldwide. Survey participants in categories of (1) addiction societies/associations, (2) addiction treatment programs, (3) addiction experts/clinicians and (4) related stakeholders will respond to these global longitudinal surveys. The results will be analyzed and cross-examined with available data and peer-reviewed for publication.Peer reviewe

When and Where Do Elections Matter? A Global Test of the Democratization by Elections Hypothesis, 1900-2012

To date studies assessing the democratizing effects of elections have produced mixed results. While findings suggest that successive uninterrupted election cycles in a global sample (Teorell and Hadenius 2009) and within sub-Saharan Africa (Lindberg 2006, 2009) have a robust positive impact on democratization, tests in other regions have been less encouraging. In particular, negative empirical findings in Latin America (McCoy and Hartlyn 2009) and Postcommunist Europe (Kaya and Bernhard 2013) call into question whether the democratizing effect of elections is isolated to the sub-Saharan region. In addition, the hypothesis has been subject to conceptual criticism (Lust-Okar 2009). This paper poses a comprehensive and global set of tests on the democratizing effect of elections, assessing the scope of the argument both geographically and temporally. We test whether elections have a democratizing effect in specific regions, in specific time periods, and globally. In particular we assess whether the effects are largely confined to Africa, during the third wave, or if this is a more general phenomenon. We find consistent support that the reiteration of contested multiparty elections leads to the improvement of rule of law and the quality of civil rights protections.This research project was supported by Riksbankens Jubileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V- Dem Institute, University of Gothenburg, Sweden; by Swedish Research Council, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden and Jan Teorell, Department of Political Science, Lund University, Sweden; by Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by University of Gothenburg, Grant E 2013/43; by Millennium Nucleus for the Study of Stateness and Democracy in Latin America (RS130002), and the University of Florida Foundation in support of the Miriam and Raymond Ehrlich Eminent Scholar Chair in Political Science

IRT Models for Expert-Coded Panel Data

Data sets quantifying phenomena of social-scientific interest often use multiple experts to code latent concepts. While it remains standard practice to report the average score across experts, experts likely vary in both their expertise and their interpretation of question scales. As a result, the mean may be an inaccurate statistic. Item-response theory (IRT) models provide an intuitive method for taking these forms of expert disagreement into account when aggregating ordinal ratings produced by experts, but they have rarely been applied to cross-national expert-coded panel data. We investigate the utility of IRT models for aggregating expert-coded data by comparing the performance of various IRT models to the standard practice of reporting average expert codes, using both data from the V-Dem data set and ecologically motivated simulated data. We find that IRT approaches outperform simple averages when experts vary in reliability and exhibit differential item functioning (DIF). IRT models are also generally robust even in the absence of simulated DIF or varying expert reliability. Our findings suggest that producers of cross-national data sets should adopt IRT techniques to aggregate expert-coded data measuring latent concepts