Skyler J Cranmer
Biographic Data
| ID | 635803 |
|---|---|
| NAME | Skyler J Cranmer |
| GIVEN NAMES | Skyler J |
| FAMILY NAME | Cranmer |
| SIGNATURE | CRANMER S J |
| AFFILIATIONS | The Ohio State University |
| VERIFIED | No |
| TOTAL WORKS | 20 |
| TOTAL CITATIONS | 542 |
| AUTHOR COUNT | 20 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 10 |
A Permutation-Based Changepoint Technique for Monitoring Effect Sizes
Across the social sciences, scholars regularly pool effects over substantial periods of time, a practice that produces faulty inferences if the underlying data generating process is dynamic. To help researchers better perform principled analyses of time-varying processes, we develop a two-stage procedure based upon techniques for permutation testing and statistical process monitoring. Given time series cross-sectional data, we break the role of t…
The stochastic actor-oriented model is a theory as much as it is a method and must be subject to theory tests
An abstract is not available for this content. As you have access to this content, full HTML content is provided on this page. A PDF of this content is also available in through the ‘Save PDF’ action button
How teams adapt to exogenous shocks: Experimental evidence with node knockouts of central members
Researchers have found that although external attacks, exogenous shocks, and node knockouts can disrupt networked systems, they rarely lead to the system’s collapse. Although these processes are widely understood, most studies of how exogenous shocks affect networks rely on simulated or observational data. Thus, little is known about how groups of real individuals respond to external attacks. In this article, we employ an experimental design in w…
The contagion of democracy through international networks
A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model
The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several the…
Network Interdependencies and the Evolution of the International Arms Trade
Since few states are able to produce all of their own military hardware, a majority of countries’ military systems rely on weapon imports. The structure of the international defense technology exchange network remains an important puzzle to understand, along with the factors that drive its evolution. Drawing on a political economy model of arms supply, we propose a new network-oriented explanation for the worldwide transactions of major conventio…
Stochastic weighted graphs: Flexible model specification and simulation
Coalition Quality and Multinational Dispute Outcomes 1
Multinational military coalitions are an increasingly common phenomena in international conflict, presumably because coalitions are more likely to secure their conflict aims than single states. Yet what makes a coalition more or less likely to succeed is poorly understood. We argue that the quality of multinational military coalitions—in terms of the coalition’s skill, coordination, and legitimacy—can provide better strategic decisions, more harm…
What To Do About Atheoretic Lags
We examine a problem that is confronted frequently by political science researchers seeking to model longitudinal data: what to do when one suspects a lag between the realization of a regressor and its effect on the outcome variable, but one has no theoretical reason to suspect a particular lag length. We examine the theoretical challenges posed by atheoretic lags, review existing methods for atheoretic lag analysis—most notably distributed lag s…
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
Navigating the Range of Statistical Tools for Inferential Network Analysis
The last decade has seen substantial advances in statistical techniques for the analysis of network data, as well as a major increase in the frequency with which these tools are used. These techniques are designed to accomplish the same broad goal, statistically valid inference in the presence of highly interdependent relationships, but important differences remain between them. We review three approaches commonly used for inferential network ana…
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Kantian fractionalization predicts the conflict propensity of the international system
Significance Many studies in international relations have investigated relationships between pairs of countries and the likelihood of conflict, yet none have connected the overall structure of the network of relationships between countries with the total level of international conflict. Here, we blaze a new path in the study of international conflict by introducing a measure of the overall fractionalization in the network of international relatio…
Reciprocity and the structural determinants of the international sanctions network
We Have to Be Discrete About This: A Non-Parametric Imputation Technique for Missing Categorical Data
Missing values are a frequent problem in empirical political science research. Surprisingly, the match between the measurement of the missing values and the correcting algorithms applied is seldom studied. While multiple imputation is a vast improvement over the deletion of cases with missing values, it is often unsuitable for imputing highly non-granular discrete data. We develop a simple technique for imputing missing values in such situations,…
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks
The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of …
Inferential Network Analysis with Exponential Random Graph Models
Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates …
Demography, Democracy and Disputes: The Search for the Elusive Relationship Between Population Growth and International Conflict
We examine the propensity of states to initiate international conflict conditioned on four primary explanatory variables: (1) changes in population over varying lags, (2) democratic status of the state, (3) the power status of the state, and (4) changes in the state's level of energy consumption. We hypothesize that the responsiveness of a government to the needs of its citizens is sufficiently important that the effect of population growth canno…
Inferential Network Analysis with Exponential Random Graph Models
Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates …
Navigating the Range of Statistical Tools for Inferential Network Analysis
The last decade has seen substantial advances in statistical techniques for the analysis of network data, as well as a major increase in the frequency with which these tools are used. These techniques are designed to accomplish the same broad goal, statistically valid inference in the presence of highly interdependent relationships, but important differences remain between them. We review three approaches commonly used for inferential network ana…
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks
The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of …
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
Network Interdependencies and the Evolution of the International Arms Trade
Since few states are able to produce all of their own military hardware, a majority of countries’ military systems rely on weapon imports. The structure of the international defense technology exchange network remains an important puzzle to understand, along with the factors that drive its evolution. Drawing on a political economy model of arms supply, we propose a new network-oriented explanation for the worldwide transactions of major conventio…
We Have to Be Discrete About This: A Non-Parametric Imputation Technique for Missing Categorical Data
Missing values are a frequent problem in empirical political science research. Surprisingly, the match between the measurement of the missing values and the correcting algorithms applied is seldom studied. While multiple imputation is a vast improvement over the deletion of cases with missing values, it is often unsuitable for imputing highly non-granular discrete data. We develop a simple technique for imputing missing values in such situations,…
A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model
The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several the…
Coalition Quality and Multinational Dispute Outcomes 1
Multinational military coalitions are an increasingly common phenomena in international conflict, presumably because coalitions are more likely to secure their conflict aims than single states. Yet what makes a coalition more or less likely to succeed is poorly understood. We argue that the quality of multinational military coalitions—in terms of the coalition’s skill, coordination, and legitimacy—can provide better strategic decisions, more harm…
Demography, Democracy and Disputes: The Search for the Elusive Relationship Between Population Growth and International Conflict
We examine the propensity of states to initiate international conflict conditioned on four primary explanatory variables: (1) changes in population over varying lags, (2) democratic status of the state, (3) the power status of the state, and (4) changes in the state's level of energy consumption. We hypothesize that the responsiveness of a government to the needs of its citizens is sufficiently important that the effect of population growth canno…
The stochastic actor-oriented model is a theory as much as it is a method and must be subject to theory tests
An abstract is not available for this content. As you have access to this content, full HTML content is provided on this page. A PDF of this content is also available in through the ‘Save PDF’ action button
What To Do About Atheoretic Lags
We examine a problem that is confronted frequently by political science researchers seeking to model longitudinal data: what to do when one suspects a lag between the realization of a regressor and its effect on the outcome variable, but one has no theoretical reason to suspect a particular lag length. We examine the theoretical challenges posed by atheoretic lags, review existing methods for atheoretic lag analysis—most notably distributed lag s…
A Permutation-Based Changepoint Technique for Monitoring Effect Sizes
Across the social sciences, scholars regularly pool effects over substantial periods of time, a practice that produces faulty inferences if the underlying data generating process is dynamic. To help researchers better perform principled analyses of time-varying processes, we develop a two-stage procedure based upon techniques for permutation testing and statistical process monitoring. Given time series cross-sectional data, we break the role of t…
How teams adapt to exogenous shocks: Experimental evidence with node knockouts of central members
Researchers have found that although external attacks, exogenous shocks, and node knockouts can disrupt networked systems, they rarely lead to the system’s collapse. Although these processes are widely understood, most studies of how exogenous shocks affect networks rely on simulated or observational data. Thus, little is known about how groups of real individuals respond to external attacks. In this article, we employ an experimental design in w…
Demography, Democracy and Disputes: The Search for the Elusive Relationship Between Population Growth and International Conflict
We examine the propensity of states to initiate international conflict conditioned on four primary explanatory variables: (1) changes in population over varying lags, (2) democratic status of the state, (3) the power status of the state, and (4) changes in the state's level of energy consumption. We hypothesize that the responsiveness of a government to the needs of its citizens is sufficiently important that the effect of population growth canno…
Inferential Network Analysis with Exponential Random Graph Models
Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates …
Complex Dependencies in the Alliance Network
The multifaceted and strategic interactions inherent in the formation of international military pacts render the alliance decisions of states highly interdependent. Our aim here is to model the network of alliances in such a way as to capture the effects of covariates and account for the complex dependencies inherent in the network. Regression analysis, due to its foundational assumption of conditional independence, cannot be used to analyze alli…
Toward a Network Theory of Alliance Formation
We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network—where i is allied with j is allied with k is allied with i — produce synergy effects in which state-level ut…
Micro‐Level Interpretation of Exponential Random Graph Models with Application to Estuary Networks
The exponential random graph model (ERGM) is an increasingly popular method for the statistical analysis of networks that can be used to flexibly analyze the processes by which policy actors organize into a network. Often times, interpretation of ERGM results is conducted at the network level, such that effects are related to overall frequencies of network structures (e.g., the number of closed triangles in a network). This limits the utility of …
Reciprocity and the structural determinants of the international sanctions network
We Have to Be Discrete About This: A Non-Parametric Imputation Technique for Missing Categorical Data
Missing values are a frequent problem in empirical political science research. Surprisingly, the match between the measurement of the missing values and the correcting algorithms applied is seldom studied. While multiple imputation is a vast improvement over the deletion of cases with missing values, it is often unsuitable for imputing highly non-granular discrete data. We develop a simple technique for imputing missing values in such situations,…
Kantian fractionalization predicts the conflict propensity of the international system
Significance Many studies in international relations have investigated relationships between pairs of countries and the likelihood of conflict, yet none have connected the overall structure of the network of relationships between countries with the total level of international conflict. Here, we blaze a new path in the study of international conflict by introducing a measure of the overall fractionalization in the network of international relatio…
Navigating the Range of Statistical Tools for Inferential Network Analysis
The last decade has seen substantial advances in statistical techniques for the analysis of network data, as well as a major increase in the frequency with which these tools are used. These techniques are designed to accomplish the same broad goal, statistically valid inference in the presence of highly interdependent relationships, but important differences remain between them. We review three approaches commonly used for inferential network ana…
A Critique of Dyadic Design
Dyadic research designs concern data that comprise interactions among actors. They are, without a doubt, the most frequent designs employed in the empirical analysis of international politics. But what do such designs carry with them in terms of theoretical claims and statistical problems? These two issues closely intertwine. When testing hypotheses empirically, the statistical model must be a careful operationalization of the theory under consid…
Stochastic weighted graphs: Flexible model specification and simulation
Coalition Quality and Multinational Dispute Outcomes 1
Multinational military coalitions are an increasingly common phenomena in international conflict, presumably because coalitions are more likely to secure their conflict aims than single states. Yet what makes a coalition more or less likely to succeed is poorly understood. We argue that the quality of multinational military coalitions—in terms of the coalition’s skill, coordination, and legitimacy—can provide better strategic decisions, more harm…
What To Do About Atheoretic Lags
We examine a problem that is confronted frequently by political science researchers seeking to model longitudinal data: what to do when one suspects a lag between the realization of a regressor and its effect on the outcome variable, but one has no theoretical reason to suspect a particular lag length. We examine the theoretical challenges posed by atheoretic lags, review existing methods for atheoretic lag analysis—most notably distributed lag s…
What Can We Learn from Predictive Modeling
The large majority of inferences drawn in empirical political research follow from model-based associations (e.g., regression). Here, we articulate the benefits of predictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-util…
A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model
The temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several the…
Network Interdependencies and the Evolution of the International Arms Trade
Since few states are able to produce all of their own military hardware, a majority of countries’ military systems rely on weapon imports. The structure of the international defense technology exchange network remains an important puzzle to understand, along with the factors that drive its evolution. Drawing on a political economy model of arms supply, we propose a new network-oriented explanation for the worldwide transactions of major conventio…
The contagion of democracy through international networks
A Permutation-Based Changepoint Technique for Monitoring Effect Sizes
Across the social sciences, scholars regularly pool effects over substantial periods of time, a practice that produces faulty inferences if the underlying data generating process is dynamic. To help researchers better perform principled analyses of time-varying processes, we develop a two-stage procedure based upon techniques for permutation testing and statistical process monitoring. Given time series cross-sectional data, we break the role of t…
The stochastic actor-oriented model is a theory as much as it is a method and must be subject to theory tests
An abstract is not available for this content. As you have access to this content, full HTML content is provided on this page. A PDF of this content is also available in through the ‘Save PDF’ action button
How teams adapt to exogenous shocks: Experimental evidence with node knockouts of central members
Researchers have found that although external attacks, exogenous shocks, and node knockouts can disrupt networked systems, they rarely lead to the system’s collapse. Although these processes are widely understood, most studies of how exogenous shocks affect networks rely on simulated or observational data. Thus, little is known about how groups of real individuals respond to external attacks. In this article, we employ an experimental design in w…
Computer Science (15 works) · Mathematics (14 works) · Statistics (12 works) · Economics (10 works) · Artificial Intelligence (9 works) · Econometrics (9 works) · Law (8 works) · Political science (8 works) · Complex Network Analysis Techniques (7 works) · Electoral Systems and Political Participation (7 works)