Quantitative empirical inquiry in international relations often relies on dyadic data. Standard analytic techniques do not account for the fact that dyads are not generally independent of one another. That is, when dyads share a constituent member (e.g., a common country), they may be statistically dependent, or "clustered." Recent work has developed dyadic clustering robust standard errors (DCRSEs) that account for this dependence. Using these DCRSEs, we reanalyzed all empirical articles published in International Organization between January 2014 and January 2020 that feature dyadic data. We find that published standard errors for key explanatory variables are, on average, approximately half as large as DCRSEs, suggesting that dyadic clustering is leading researchers to severely underestimate uncertainty. However, most (67% of) statistically significant findings remain statistically significant when using DCRSEs. We conclude that accounting for dyadic clustering is both important and feasible, and offer software in R and Stata to facilitate use of DCRSEs in future research.

This study includes event summaries derived from The Conflict and Peace Data Bank (COPDAB) Project (see also CONFLICT AND PEACE DATA BANK (COPDAB), 1948-1978 [ICPSR 7767]). Part 1 contains yearly summaries of events directed by one international actor toward another. There are both conflict and cooperation summaries, including measures of the frequency and intensity of events, and a measure of the dimension of interaction, which combines frequency and intensity. Event summaries are included only for dyads involving the following political entities as actors and targets: Algeria, Canada, China, Cyprus, Federal Republic of Germany, German Democratic Republic, Egypt, France, Greece, India, Indonesia, Iran, Iraq, Israel, Italy, Japan, Jordan, Kuwait, Lebanon, Libya, Morocco, Pakistan, Palestine Liberation Organization, Saudi Arabia, Sudan, Syria, Tunisia, Turkey, United Kingdom, United States, and Soviet Union. Data are recorded for each dyad for each year between 1948-1973. Part 2 contains domestic event summaries for the same 31 political entities. The variables measure frequency, intensity, and dimension of interaction (frequency and intensity) for both conflictive and cooperative domestic events. Data are recorded by year for each entity. In Part 3, a variable records the total number of international events initiated by each actor in each year, while a second variable calculates this yearly total as a percentage of all events initiated by the same actor during the 26-year period. Part 4 provides similar information, but with the dyad actor-target as a unit of analysis. One variable records the total number of events initiated by the actor toward the target over the whole time period, while a second variable calculates the number of events directed at one target as a percentage of the events directed at all targets.

This dataset provides dyad-year counts of transnational terror events and fatalities. These data were calculated using the GTD data, using a process described in "All Politics is Local: The Domestic Agenda of Terror Groups and the Study of Transnational Attacks," published in the Journal of Global Security Studies.

This dataset includes triaxial acceleration data collected from 60 children (2- and 4-year-olds) across three childcare facilities during a 15-minute free play session. Dyadic (two-person) and triadic (three-person) peer relationships were analyzed using a novel-directed network analysis method, offering insights into age and sex differences in peer interactions. The dataset includes normalized connection counts, demographic details, and detailed analyses of interaction directionality. This research validates the application of network analysis in early childhood studies, reducing observational biases and labor-intensive manual coding, and provides a framework for exploring complex social dynamics in naturalistic play settings., Participants:The study involved 60 children, with equal representation of 2- and 4-year-olds, across three childcare facilities. Informed consent was obtained from the participants' legal guardians following ethical guidelines. Data Collection:Participants wore wristwatch-style triaxial accelerometers (Silmee W22, TDK) during a 15-minute free play session. Acceleration data were recorded at 20 Hz to measure individual movement intensity and calculate dyadic and triadic peer relationships. Data Processing:

Normalization: Acceleration data were aggregated into 1-second intervals and normalized using Sturges’ formula to account for individual variability.

Network Analysis: Connections were quantified using directed graph analysis, identifying dyads and triads based on movement entropy thresholds. Entropy values ranged from 0 to 1, representing interaction strength.

Statistical Analysis:Chi-square tests and ANOVAs were performed to analyze age, sex, and directional differences in peer r..., , # Directed network analysis of 2-year-old and 4-year-old children

https://doi.org/10.5061/dryad.63xsj3vbx

Description of the data and file structure

Dataset Overview: This dataset contains information about directed networks among 2-year-old and 4-year-old children. The data reflects interactions in terms of directed connections from one child to another, categorized by their unique identifiers and demographics.

Files and variables

File: Directed_network_of_2_and_4_YO_childlen.xlsx

The Excel file consists of four sheets as follows:

Sheet1: Dyad

Sheet2: Triad

Sheet3: Directed NW

Sheet4: Directed NW among individuals

Sheet description and variables

Sheet 1:Â Dyad

This sheet includes each child's age, gender, and the number of Dyads for each facility. Using this data, comparisons of the number of Dyads were conducted between different ages and genders.

Variables in each column

• Facility...

Abstract (en): This study contains export and import trade data for 207 nations in the period 1958-1968. The data were collected on a country by country, dyadic, or directional basis and provide information for the imports and exports of a nation dyad in units of millions of United States dollars. Imports and exports for 207 nations in the period 1958-1968.

The rationale for generating a dyadic version of the Militarized Interstate Dispute (MID) dataset (Bremer, Jones, and Singer, 1996) is based on the following observations: There is a need for such a version in light of the growing number of studies on international conflict employing the dyadic unit of analysis, and utilizing the MID dataset. The existing versions of the dataset (e.g., the version, which is downloadable through the PSSI Website or the EUGENE Website) consist of two types of observations: (a) The dispute level. This level includes general information about the dispute such as its start dates and end dates, the numb er of participants, its name, the highest level of hostility reached, the outcome of the dispute, etc. (b) The individual participant level. This level provides entry and exit dates for each participant, the side it took in the dispute, the highest level of hostility reached, and so forth. Extrapolation from the individual level to the dyadic level by simple computerized means may cause considerable errors. Some of these are enumerated in the Dyadic MID Codebook. In strictly bilateral disputes, it is easy to transform the participation records for a specific dispute into a dyadic record, includ ing the combination of data from the dispute profile record in the dispute dataset. However, performing such a combination on multilateral dispute may cause a great number of errors. Here are some examples of such errors. Beyond these problems of extrapolation, there is a need to redefine certain variables at the dyadic level. For example, for some analyses, it makes sense to have an annual record of ongoing MIDs, while for others it is only necessary to look at the start year of the dispute. The minimum and maximum duration variables that are listed at the dispute level are not very useful when it comes to dyadic analyses, as each dyad may have a different duration from each other dyad within the same dispute. Likewise, the outcome and settlement of the dispute may not apply to all dyads.

The ICOW project is currently collecting data on territorial issues in all regions of the world since 1816, compiled into several related data files. The first file identifies territorial claims, or explicit claims by official government representatives of at least two sovereign nation-states to the same piece of territory, and includes basic claim-level information such as the overall beginning and ending of the claim and the form of claim termination. The second file is organized by claim-dyad-years and includes one data point for each year of each claimant dyad, with information on details such as the characteristics of the claimed territory. The third and final data file covers attempts to settle these territorial claims through bilateral negotiations or with third party assistance (good offices, mediation, inquiry, conciliation, arbitration, or adjudication), and includes details such as the beginning, ending, and effectiveness of each settlement attempt.

International relations scholars frequently rely on datasets 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 correct p-values associated with the trade hypotheses. Our results show that typical statistical tests for significance are severely overconfident when applied to dyadic data.

Over the history of modern international relations research, we have moved from systemic and regional studies to empirical explorations of dyadic interactions. However, our statistical models have put the details of dyadic interactions under a microscope at the expense of ignoring the relevant regional context that these dyads interact in. This development has been in part due to computational limitations, but do we really believe that decision makers interact with one another while ignoring the regional power balance and the wishes of regional powers? In this article, I take a look at the well-researched relationship between democracy and peace by using a multilevel approach to dyadic interactions and the regions they are embedded in. The findings suggest that when the regional power balance favors democracies, it influences conflict between dyads, especially mixed dyads, by increasing the costs of aggression by autocracies and establishing regional norms of cooperation and compromise.

Influence within friend dyads: Results from longitudinal actor-partner interdependence models.

[This is a post-publication review symposium] To what extent are international relations scholars constrained in their ability to answer important questions by what has become the workhorse unit of observation for analyzing relational data: the dyad? Skyler Cranmer and Bruce Desmarais argue that focusing on dyadic data has led scholarship to fail at properly characterizing relationships of interest in international relations data, while Paul Diehl and Thorin Wright (2016)and Paul Poast (2016) offer conditional defenses of using dyadic data. However, all three acknowledge that many of the problems identified in Cranmer and Desmarais (2016) carry with them both inferential and substantive merit. Journal space prevents a fuller exploration of this debate in the pages of International Studies Quarterly. Thus, to facilitate this important discussion, we invited eight scholars to weigh in on the question of dyadic data. [...]

The UCDP, Uppsala Conflict Data Program, contains information on a large number data on organised violence, armed violence, and peacemaking. There is information from 1946 up to today, and the datasets are updated continuously. The data can be downloaded for free.

The UCDP Battle-Related Deaths Dataset is a conflict-year and dyad-year dataset with information on the number of battle-related deaths in the conflicts from 1989-2013 that appear in the UCDP/PRIO Armed Conflict Dataset.

Purpose:

The Uppsala Conflict Data Program (UCDP) collects information on a large number of aspects of armed violence since 1946.

Cite as: UCDP Battle-Related Deaths Dataset v.5-2013, Uppsala Conflict Data Program, www.ucdp.uu.se, Uppsala University

This data collection is gathered from interviews with parent-youth dyads in Arizona, Colorado, and Florida across two election cycles: 2002 and 2004. Adolescent respondents were juniors and seniors in high school during a midterm campaign, and old enough to vote during the subsequent presidential election. The civics curriculum Kids Voting USA (KVUSA) provided conditions for a quasi-experimental field intervention in the three selected states. Measures of civic engagement include student and parent voting, political knowledge, and deliberative activities like news media attention, active political discussion, and willingness to listen and to disagree with others.

The dataset contains harmonized variables from four studies of men who have sex with men (MSM) conducted at Emory University from 2009-2013. The variables include the age and race/ethnicity of participants and their recent male sexual partners. The objective of the analysis was to examine racial differences in age mixing, including whether age mixing was related to prevalent HIV infection.Two of the four studies were Internet-based samples in the US. The two other studies sampled MSM in the Atlanta area, of which one used a mixture of online and offline recruitment methods and the other used offline methods exclusively. For all studies, participants were eligible if they were male at birth, aged 18 years or older, and had a male sex partner within a specified period prior to enrollment in the study. In order to examine differences in age mixing between Black and White MSM, we restricted our analytic samples to those who reported being Black or White and not Hispanic. All studies were reviewed and approved by the Emory University Institutional Review Board.

Governments often fight multiple civil conflicts simultaneously and each conflict can have multiple groups. Prior research on civil war termination and recurrence has been conducted at either the conflict level, once all the groups have been terminated, or the dyadic level, which examines group terminations in a conflict separately as more or less independent processes. Hence, conflict-level studies mostly tell us how to preserve peace once a civil war has already ended, while dyadic studies mostly tell us about the durability of specific group-level terminations within the larger process that led to that ending. As a result, our understanding of how ongoing civil wars are brought to a close is limited, particularly, with respect to multiparty conflicts. In this study, we put forth a systems approach that treats dyadic terminations as connected processes where group terminations influence the future behavior of other groups, incentivizing the system toward greater aggregate peace or conflict. Analyzing 264 dyadic terminations, the findings suggest that the most effective strategy for governments to reduce systemic conflict is to demonstrate to other groups that they have the political will and capacity to implement security, political, and social reforms as part of a larger reform-oriented peace process. Viable implementation can be followed by the concomitant use of military victories against remaining groups with great success. However, military victories achieved in isolation, that is, outside of a reform-process, do not reduce future levels of conflict even if they themselves are durable.

The final column contains the Spearman rank correlation of each feature with the Closest Friend target variable. Interaction counts represent the total interactions in the six months prior to an online survey that asked users to identify their closest friends in real life.

Chronic conditions are an increasing concern in the United States, where they affect nearly half of the adult population and their prevalence has increased in recent years. These conditions result in numerous adverse health outcomes, increased health care needs, and subsequently higher medical costs. This dataset provides co-morbidity dyads illustrated by the combinations of the 19 chronic conditions for the year 2014.

Dyad leadership in healthcare : when one plus one is greater than two is a book. It was written by Kathleen Sanford and published by Lippincott Williams&Wilkins in 2015.

The new FJSRC linking system, implemented with the 2008 FJSRC data, includes sets of agency dyad linked files created by improved methods of algorithmic matching. There are both inter-agency linked files and intra-agency dyad linked files. The inter-agency matched pair files (or "dyads") permit the linking of records from two different source agencies for adjacent stages of federal case processing by providing a crosswalk of the agency-specific key ID variables for the two agency data files in the pair. These agency ID variables (sequential ID numbers) may be used to link records from one agency's standard analysis file (SAF) to the next. The system enables users to track individual defendant-cases through stages of the federal criminal justice system (from arrest to prosecution, adjudication, sentencing, and corrections) sequentially, one agency dyad pair at a time. Each inter-agency paired linked file relates the sequential record numbers (i.e. SEQ_NUM) included in the SAFs from one agency/stage to another. The intra-agency matched pair files (also dyads) permit the same type of linking as described above except that the linkages are within the same federal agency. The linkages are to different stages of case processing withing a particular agency. The system covers all data years from 1994-2022. These data are part of a series designed by the Urban Institute (Washington, D.C.) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute through 2012. Data from 2013 and on were prepared by Abt Associates.

This dataset examines the complexity of network structures in professional and collegiate women’s soccer teams using directed network analysis based on tri-axial acceleration data. The study involved one professional team and one university-level team, with data collected from matches during their respective seasons. Directed network analysis identified dyads and triads, representing cooperative interactions among players, while movement entropy quantified the influence of individual movements within the team. Network diversity, defined as the variability in activation probabilities of dyads and triads, was calculated to evaluate the tactical dynamics and cooperative behaviors of the teams. Data were collected using GNSS devices equipped with tri-axial accelerometers, ensuring precise measurement of movement intensity. The findings provide insights into the structural and functional differences in team coordination between professional and collegiate levels. The dataset is anonymized an..., Participants Prior to participant recruitment, we calculated the minimum required number of matches using G*Power 3.1.9.4 (Heinrich Heine Universität Düsseldorf, Germany). This study employs a two-way analysis of variance (ANOVA) to primarily examine the interaction effects between the period of the match (the first half and second half of the match) and three team groups (professional teams during the first half of the season, professional teams during the second half of the season, and collegiate teams). Thus, the calculation for the F-test with ANOVA was conducted a priori, given an effect size of 0.40, an α error probability of 0.05, a power of 0.80, and a numerator df of 2 with six groups. The effect size (0.40) for this analysis was set based on findings from a previous study that examined changes in team coordination states during matches and reported a large effect size (η² = 0.240 to 0.263) for differences influenced by the level of the opposing team. The total required sample ..., , # Accelerometer-based network analysis in female soccer: performance levels and injuries

https://doi.org/10.5061/dryad.sf7m0cgh6

Description of the data and file structure

Dataset Overview

This dataset investigates the complexity of network structures in professional and collegiate women’s soccer teams, focusing on cooperative interactions and tactical dynamics. Data were collected during matches using GNSS devices equipped with tri-axial accelerometers, providing precise measurements of player movements and interactions.

Data Content

The dataset includes:

1. Player Movement Data: Tri-axial acceleration data recorded at 10 Hz for all players during each match. Data capture spans from match entry to exit, with segmentation into 45-minute halves. Stoppage time is excluded, and substitutions are handled by segmenting data accordingly.
2. Network Analysis Results: Quantitative results of directed network analysis, includ...