Naoki Egami
Biographic Data
| ID | 4179869 |
|---|---|
| NAME | Naoki Egami |
| GIVEN NAMES | Naoki |
| FAMILY NAME | Egami |
| SIGNATURE | EGAMI N |
| AFFILIATIONS | Columbia University |
| ORCID | 0000-0002-5491-2174 |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 189 |
| AUTHOR COUNT | 9 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Designing multi‐site studies for external validity: Site selection via synthetic purposive sampling
Multi‐site/context studies have become popular strategies to address the most common and challenging external validity concerns about contexts. Under such studies, scholars conduct causal studies in each site and evaluate whether findings generalize across sites. Despite the potential, there has been little guidance on the fundamental research design question—how should we select sites for external validity? Existing approaches have challenges: r…
Placebo-Augmented Pica Design (Pica-2): Assessing the Influence of Foreign Propaganda
Correcting the Measurement Errors of AI-Assisted Labeling in Image Analysis Using Design-Based Supervised Learning
Generative artificial intelligence (AI) has shown incredible leaps in performance across data of a variety of modalities including texts, images, audio, and videos. This affords social scientists the ability to annotate variables of interest from unstructured media. While rapidly improving, these methods are far from perfect and, as we show, even ignoring the small amounts of error in high accuracy systems can lead to substantial bias and invalid…
Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs
While a difference-in-differences (DID) design was originally developed with one pre- and one posttreatment period, data from additional pretreatment periods are often available. How can researchers improve the DID design with such multiple pretreatment periods under what conditions? We first use potential outcomes to clarify three benefits of multiple pretreatment periods: (1) assessing the parallel trends assumption, (2) improving estimation ac…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution
Conjoint analysis has become popular among social scientists for measuring multidimensional preferences. When analyzing such experiments, researchers often focus on the average marginal component effect (AMCE), which represents the causal effect of a single profile attribute while averaging over the remaining attributes. What has been overlooked, however, is the fact that the AMCE critically relies upon the distribution of the other attributes us…
Hate Crimes and Gender Imbalances: Fears over Mate Competition and Violence against Refugees
As the number of refugees rises across the world, anti‐refugee violence has become a pressing concern. What explains the incidence and support of such hate crime? We argue that fears among native men that refugees pose a threat in the competition for female partners are a critical but understudied factor driving hate crime. Employing a comprehensive data set on the incidence of hate crime across Germany, we first demonstrate that hate crime rises…
Spillover Effects in the Presence of Unobserved Networks
When experimental subjects can interact with each other, the outcome of one individual may be affected by the treatment status of others. In many social science experiments, such spillover effects may occur through multiple networks, for example, through both online and offline face-to-face networks in a Twitter experiment. Thus, to understand how people use different networks, it is essential to estimate the spillover effect in each specific net…
Competing for Loyalists? How Party Positioning Affects Populist Radical Right Voting
As populist radical right parties muster increasing support in many democracies, an important question is how mainstream parties can recapture their voters. Focusing on Germany, we present original panel evidence that voters supporting the Alternative für Deutschland (AfD)—the country’s largest populist radical right party—resemble partisan loyalists with entrenched anti-establishment views, seemingly beyond recapture by mainstream parties. Yet t…
Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution
Conjoint analysis has become popular among social scientists for measuring multidimensional preferences. When analyzing such experiments, researchers often focus on the average marginal component effect (AMCE), which represents the causal effect of a single profile attribute while averaging over the remaining attributes. What has been overlooked, however, is the fact that the AMCE critically relies upon the distribution of the other attributes us…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Competing for Loyalists? How Party Positioning Affects Populist Radical Right Voting
As populist radical right parties muster increasing support in many democracies, an important question is how mainstream parties can recapture their voters. Focusing on Germany, we present original panel evidence that voters supporting the Alternative für Deutschland (AfD)—the country’s largest populist radical right party—resemble partisan loyalists with entrenched anti-establishment views, seemingly beyond recapture by mainstream parties. Yet t…
Hate Crimes and Gender Imbalances: Fears over Mate Competition and Violence against Refugees
As the number of refugees rises across the world, anti‐refugee violence has become a pressing concern. What explains the incidence and support of such hate crime? We argue that fears among native men that refugees pose a threat in the competition for female partners are a critical but understudied factor driving hate crime. Employing a comprehensive data set on the incidence of hate crime across Germany, we first demonstrate that hate crime rises…
Correcting the Measurement Errors of AI-Assisted Labeling in Image Analysis Using Design-Based Supervised Learning
Generative artificial intelligence (AI) has shown incredible leaps in performance across data of a variety of modalities including texts, images, audio, and videos. This affords social scientists the ability to annotate variables of interest from unstructured media. While rapidly improving, these methods are far from perfect and, as we show, even ignoring the small amounts of error in high accuracy systems can lead to substantial bias and invalid…
Spillover Effects in the Presence of Unobserved Networks
When experimental subjects can interact with each other, the outcome of one individual may be affected by the treatment status of others. In many social science experiments, such spillover effects may occur through multiple networks, for example, through both online and offline face-to-face networks in a Twitter experiment. Thus, to understand how people use different networks, it is essential to estimate the spillover effect in each specific net…
Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs
While a difference-in-differences (DID) design was originally developed with one pre- and one posttreatment period, data from additional pretreatment periods are often available. How can researchers improve the DID design with such multiple pretreatment periods under what conditions? We first use potential outcomes to clarify three benefits of multiple pretreatment periods: (1) assessing the parallel trends assumption, (2) improving estimation ac…
Placebo-Augmented Pica Design (Pica-2): Assessing the Influence of Foreign Propaganda
Spillover Effects in the Presence of Unobserved Networks
When experimental subjects can interact with each other, the outcome of one individual may be affected by the treatment status of others. In many social science experiments, such spillover effects may occur through multiple networks, for example, through both online and offline face-to-face networks in a Twitter experiment. Thus, to understand how people use different networks, it is essential to estimate the spillover effect in each specific net…
Competing for Loyalists? How Party Positioning Affects Populist Radical Right Voting
As populist radical right parties muster increasing support in many democracies, an important question is how mainstream parties can recapture their voters. Focusing on Germany, we present original panel evidence that voters supporting the Alternative für Deutschland (AfD)—the country’s largest populist radical right party—resemble partisan loyalists with entrenched anti-establishment views, seemingly beyond recapture by mainstream parties. Yet t…
Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution
Conjoint analysis has become popular among social scientists for measuring multidimensional preferences. When analyzing such experiments, researchers often focus on the average marginal component effect (AMCE), which represents the causal effect of a single profile attribute while averaging over the remaining attributes. What has been overlooked, however, is the fact that the AMCE critically relies upon the distribution of the other attributes us…
Hate Crimes and Gender Imbalances: Fears over Mate Competition and Violence against Refugees
As the number of refugees rises across the world, anti‐refugee violence has become a pressing concern. What explains the incidence and support of such hate crime? We argue that fears among native men that refugees pose a threat in the competition for female partners are a critical but understudied factor driving hate crime. Employing a comprehensive data set on the incidence of hate crime across Germany, we first demonstrate that hate crime rises…
Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs
While a difference-in-differences (DID) design was originally developed with one pre- and one posttreatment period, data from additional pretreatment periods are often available. How can researchers improve the DID design with such multiple pretreatment periods under what conditions? We first use potential outcomes to clarify three benefits of multiple pretreatment periods: (1) assessing the parallel trends assumption, (2) improving estimation ac…
Elements of External Validity: Framework, Design, and Analysis
The external validity of causal findings is a focus of long-standing debates in the social sciences. Although the issue has been extensively studied at the conceptual level, in practice few empirical studies include an explicit analysis that is directed toward externally valid inferences. In this article, we make three contributions to improve empirical approaches for external validity. First, we propose a formal framework that encompasses four d…
Placebo-Augmented Pica Design (Pica-2): Assessing the Influence of Foreign Propaganda
Correcting the Measurement Errors of AI-Assisted Labeling in Image Analysis Using Design-Based Supervised Learning
Generative artificial intelligence (AI) has shown incredible leaps in performance across data of a variety of modalities including texts, images, audio, and videos. This affords social scientists the ability to annotate variables of interest from unstructured media. While rapidly improving, these methods are far from perfect and, as we show, even ignoring the small amounts of error in high accuracy systems can lead to substantial bias and invalid…
Designing multi‐site studies for external validity: Site selection via synthetic purposive sampling
Multi‐site/context studies have become popular strategies to address the most common and challenging external validity concerns about contexts. Under such studies, scholars conduct causal studies in each site and evaluate whether findings generalize across sites. Despite the potential, there has been little guidance on the fundamental research design question—how should we select sites for external validity? Existing approaches have challenges: r…
Computer Science (5 works) · Mathematics (4 works) · Statistics (4 works) · Advanced Causal Inference Techniques (3 works) · Econometrics (3 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Economic and Environmental Valuation (2 works) · Electoral Systems and Political Participation (2 works) · Estimator (2 works)