scholarly journals Taking dyads seriously

2021 ◽  
pp. 1-19
Author(s):  
Shahryar Minhas ◽  
Cassy Dorff ◽  
Max B. Gallop ◽  
Margaret Foster ◽  
Howard Liu ◽  
...  
Keyword(s):  
International Relations ◽  
Standard Errors ◽  
Dyadic Data ◽  
Modeling Approaches ◽  
Modeling Approach ◽  
Out Of Sample ◽  
Data Generating Process ◽  
Key Variables ◽  
Conventional Methods ◽  
Multiplicative Effects

Abstract International relations scholarship concerns dyads, yet standard modeling approaches fail to adequately capture the data generating process behind dyadic events and processes. As a result, they suffer from biased coefficients and poorly calibrated standard errors. We show how a regression-based approach, the Additive and Multiplicative Effects (AME) model, can be used to account for the inherent dependencies in dyadic data and glean substantive insights in the interrelations between actors. First, we conduct a simulation to highlight how the model captures dependencies and show that accounting for these processes improves our ability to conduct inference on dyadic data. Second, we compare the AME model to approaches used in three prominent studies from recent international relations scholarship. For each study, we find that compared to AME, the modeling approach used performs notably worse at capturing the data generating process. Further, conventional methods misstate the effect of key variables and the uncertainty in these effects. Finally, AME outperforms standard approaches in terms of out-of-sample fit. In sum, our work shows the consequences of failing to take the dependencies inherent to dyadic data seriously. Most importantly, by better modeling the data generating process underlying political phenomena, the AME framework improves scholars’ ability to conduct inferential analyses on dyadic data.

Dyadic Analysis in International Relations: A Cautionary Tale

2014 ◽  
Vol 22 (4) ◽  
pp. 457-463 ◽  
Author(s):  
Robert S. Erikson ◽  
Pablo M. Pinto ◽  
Kelly T. Rader
Keyword(s):  
International Relations ◽  
Statistical Tests ◽  
Standard Errors ◽  
Dyadic Analysis ◽  
Data Sets ◽  
Cautionary Tale ◽  
Randomization Tests ◽  
Dyadic Data ◽  
Independent Events ◽  
Trading Partners

International relations scholars frequently rely on data sets with country pairs, or dyads, as the unit of analysis. Dyadic data, with its thousands and sometimes hundreds of thousands of observations, may seem ideal for hypothesis testing. However, dyadic observations are not independent events. Failure to account for this dependence in the data dramatically understates the size of standard errors and overstates the power of hypothesis tests. We illustrate this problem by analyzing a central proposition among IR scholars, the democratic trade hypothesis, which claims that democracies seek out other democracies as trading partners. We employ randomization tests to infer the correctp-values associated with the trade hypotheses. Our results show that typical statistical tests for significance are severely overconfident when applied to dyadic data.

(Mis)Using Dyadic Data to Analyze Multilateral Events

2010 ◽  
Vol 18 (4) ◽  
pp. 403-425 ◽  
Author(s):  
Paul Poast
Keyword(s):  
International Relations ◽  
Rare Events ◽  
Model Misspecification ◽  
Data Sets ◽  
Alliance Formation ◽  
Dyadic Data ◽  
Political Analysis ◽  
Data Generating Process ◽  
State Pair ◽  
Substantial Bias

Dyadic (state-pair) data is completely inappropriate for analyzing multilateral events (such as large alliances and major wars). Scholars, particularly in international relations, often divide the actors in a multilateral event into a series of dyadic relations. Though this practice can dramatically increase the size of data sets, using dyadic data to analyze what are, in reality, k-adic events leads to model misspecification and, inevitably, statistical bias. In short, one cannot recover a k-adic data generating process using dy-adic data. In this paper, I accomplish three tasks. First, I use Monte Carlo simulations to confirm that analyzing k-adic events with dyadic data produces substantial bias. Second, I show that choice-based sampling, as popularized by King and Zeng (2001a, Explaining rare events in international relations. International Organization 55:693–715, and 2001b, Logistic regression in rare events data. Political Analysis 9:137–63), can be used to create feasibly sized k-adic data sets. Finally, I use the study of alliance formation by Gibler and Wolford (2006, Alliances, then democracy: An examination of the relationship between regime type and alliance formation. The Journal of Conflict Resolution 50:1–25) to illustrate how to apply this choice-based sampling solution and explain how to code independent variables in a k-adic context.

East Asia International Relations and International Relations Theory: Where Does a Poor Fit Exist, and What to Do about It

2018 ◽  
Vol 53 (8) ◽  
pp. 1202-1218 ◽  
Author(s):  
Min-hyung Kim
Keyword(s):  
International Relations ◽  
East Asia ◽  
International Relations Theory ◽  
Power Politics ◽  
Indigenous Theory ◽  
Core Concepts ◽  
Great Power Politics ◽  
Key Variables ◽  
Many Core ◽  
Central Claim

This article seeks to critically assess the relevance of International Relations Theory (IRT) for East Asia International Relations (IR). After identifying the shortcomings of IRT in explaining East Asia IR, the article provides several ways to modify it with a goal to make it more suitable for East Asia IR. Its central claim is that the IRT’s bias toward European experiences and great power politics generates unsatisfactory accounts for and inaccurate predictions about East Asia IR. This does not mean, however, that we should treat IRT as completely irrelevant and develop an indigenous theory of East Asia IR. Given that no single theory is complete and perfectly relevant across time and space and that many core concepts and key variables of IRT are also pertinent for East Asia IR, our efforts should instead be made to refine the existing IRT and make it more suitable for East Asia IR by problematising its major assumptions and central claims on the basis of East Asian experiences. This will save IRT from being a region-specific and a country-specific theory of IR.

Damage mechanics-based modeling approaches for cyclic analysis of precast concrete structures: A comparative study

2020 ◽  
Vol 29 (6) ◽  
pp. 965-987 ◽  
Author(s):  
De-Cheng Feng ◽  
Zhun Wang ◽  
Xu-Yang Cao ◽  
Gang Wu
Keyword(s):  
Damage Mechanics ◽  
Precast Concrete ◽  
Concrete Structures ◽  
Cyclic Tests ◽  
Bond Slip ◽  
Concrete Frame ◽  
Modeling Approaches ◽  
Modeling Approach ◽  
Key Issues ◽  
Precast Structures

Precast concrete frame structures are widely adopted around the world due to their various advantages, so it is important to study their seismic performance. The development of damage mechanics has enabled us to accurately investigate the typical failure mechanisms of precast structures. This paper presents three of the most commonly used modeling approaches based on damage mechanics for analysis of precast reinforced concrete structures under cyclic loading and compares the performance of the three models. Particularly, the shear behavior of the joint panel and the bond-slip behavior of the beam–column interfaces are especially considered, which are the key issues for precast concrete structures. First, the fundamental assumptions, formulations, and modeling strategies are given in detail for each approach. Then, the unified damage mechanics for concrete is introduced, and the model for reinforcement bars and the consideration of the bond-slip effect are also presented. Several benchmark cyclic tests of precast beam-to-column connections are chosen to evaluate the accuracy and efficiency of the modeling approaches. The numerical results, e.g. the capacities, deformations, and energy dissipation of the connections, are compared to the experimental results to show the ability of each approach. With this study, we can gain a further understanding of the characteristics and applicability of each modeling approach, helping us make a better decision in choosing which modeling approach is appropriate.

The Song Remains the Same: International Relations After COVID-19

2020 ◽  
pp. 1-18 ◽  
Author(s):  
Daniel W. Drezner
Keyword(s):  
International Relations ◽  
Inflection Point ◽  
World Politics ◽  
The Novel ◽  
Critical Junctures ◽  
Ex Post ◽  
Key Variables ◽  
Distribution Of Power ◽  
Novel Coronavirus

Abstract Since the onset of COVID-19, there has been a surfeit of commentary arguing that 2020 will have transformative effects on world politics. This paper asks whether, decades from now, the pandemic will be viewed as an inflection point. Critical junctures occur when an event triggers a discontinuous shift in key variables or forces a rapid acceleration of preexisting trends. Pandemics have undeniably had this effect in the far past. A welter of economic and medical developments, however, have strongly muted the geopolitical impact of pandemics in recent centuries. A review of how the novel coronavirus has affected the distribution of power and interest in its first six months suggests that COVID-19 will not have transformative effects on world politics. Absent a profound ex post shift in hegemonic ideas, 2020 is unlikely to be an inflection point.

A Look Behind Conceptual Modeling Constructs in Information System Analysis and Design

2010 ◽  
Vol 1 (1) ◽  
pp. 79-108 ◽  
Author(s):  
Remigijus Gustas
Keyword(s):  
Information System ◽  
System Analysis ◽  
Conceptual Modeling ◽  
Technical System ◽  
Single Type ◽  
System Analysis And Design ◽  
Analysis And Design ◽  
Object Oriented Design ◽  
Modeling Approaches ◽  
Modeling Approach

Information systems can be conceptualized in a number of ways. Most methodologies propose to analyze separately process and data semantics by projecting them into totally different diagram types. This system analysis and design tradition is very strong in most modeling approaches such as structured analysis as well as object-oriented design. Structural and behavioral aspects are complementary. They cannot be analyzed in isolation. Lack of a conceptual modeling approach, which can be used for verification of semantic integrity among various types of diagrams, is the cornerstone of frustration for information system architects. Inconsistency, incompleteness and ambiguity of conceptual views create difficulties in verification and validation of technical system architectures by business experts, who determine the organizational strategies. Consequently, the traditional information system methodologies are not able to bridge a communication gap among business experts and IT-system designers. Various interpretations of semantic relations in conceptual modeling approaches make the system analysis and design process more art than science. It creates difficulties to formulate comprehensible principles of decomposition and separation of concerns. Unambiguous definition of aggregation and generalization is necessary for breaking down information system functionality into coherent non-overlapping components. This article concentrates on conceptual modeling enhancements, which help to avoid semantic integrity problems in conceptualizations on various levels of abstraction. The presented conceptual modeling approach is based on a single type of diagram, which can be used for reasoning on semantic integrity between business process and data across organizational and technical system boundaries.

Threat Modeling

2010 ◽  
pp. 228-246
Author(s):  
Nishtha Srivastava ◽  
Sumeet Gupta ◽  
Mayank Mathur
Keyword(s):  
Web 2.0 ◽  
Research Work ◽  
Complete Analysis ◽  
New Approach ◽  
Threat Modeling ◽  
Commercial Use ◽  
Modeling Approaches ◽  
Modeling Approach ◽  
Public Networks ◽  
Informal Method

This research work proposes a threat modeling approach for Web 2.0 applications. The authors’ approach is based on applying informal method of threat modeling for Web 2.0 applications. Traditional enterprises are skeptical in adopting Web 2.0 applications for internal and commercial use in public-facing situations, with customers and partners. One of the prime concerns for this is lack of security over public networks. Threat modeling is a technique for complete analysis and review of security aspects of application. The authors will show why existing threat modeling approaches cannot be applied to Web 2.0 applications, and how their new approach is a simple way of applying threat modeling to Web 2.0 applications.

A Note on Borders, Dyads and the Distribution of Democracy in Sub-Saharan Africa

2018 ◽  
Vol 24 (2) ◽  
Author(s):  
Nicola Pontarollo ◽  
Roberto Ricciuti
Keyword(s):  
International Relations ◽  
Sub Saharan Africa ◽  
Political Regimes ◽  
Dyadic Data ◽  
Dependent Observations ◽  
Binary Relationship ◽  
Sub Saharan ◽  
Differentiated Effects

AbstractIn this note we use dyadic data to address the issue of the spread of political regimes in Sub-Saharan Africa from 1977 to 2014. Dyadic data are binary relationship between countries and provide a data-rich environment for the study of international relations. We address the issue of correlation between these dyadic observations, which generates a cluster of dependent observations associated with that country. We find that borders matter, since often the effect of home- and foreign-grown variables have differentiated effects on democracy in one country.

scholarly journals A Bayesian forecasting model of international conflict

2019 ◽  
Vol 17 (3) ◽  
pp. 235-242
Author(s):  
George W Williford ◽  
Douglas B Atkinson
Keyword(s):  
International Relations ◽  
Bayesian Methods ◽  
International Conflict ◽  
Rare Events ◽  
Forecasting Model ◽  
Bayesian Forecasting ◽  
Strong Interest ◽  
Out Of Sample ◽  
Cross National

Scholars and practitioners in international relations have a strong interest in forecasting international conflict. However, due to the complexity of forecasting rare events, existing attempts to predict the onset of international conflict in a cross-national setting have generally had low rates of success. In this paper, we apply Bayesian methods to develop a forecasting model designed to predict the onset of international conflict at the yearly level. We find that this model performs substantially better at producing accurate predictions both in and out of sample.

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