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研究方法

New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research

·580 字·2 分钟
Polihot 研究方法 Repeated Measures Survey Experiments Experimental Design Treatment Effects Precision
APSR — pp. 1-21 2026-04-24 Original New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research DIANA JORDAN, TRENT OLLERENSHAW, ANDREW TREXLER Abstract We re-examine recent influential claims that repeated measure experimental designs offer large precision gains without biasing treatment effect estimates in survey research. We test these claims by experimentally varying the design of six classic political science experiments across three distinct large samples of U.S. adults (total $ N=\mathrm{13,163} $ ). In contrast to prior evidence, we observe consistent attenuation of treatment effects in repeated measure designs. However, we show in simulations that this average design effect is small enough, and the precision gains large enough, that we recommend repeated measure designs for broad application—though (large-N) post-only designs may be preferable when research priorities include estimating the precise magnitude of a treatment effect. We additionally explore how several design considerations affect the bias-precision trade-off, such as within-subject versus between-groups designs, the relative separation of repeated measures within single surveys, and differences in respondent characteristics across sample types.

How Can Researchers Have Greater Policy Impact?

·669 字·2 分钟
Polihot 公共政策 研究方法 Policy Impact Research Utilization Contribution Analysis Evidence-Based Policymaking Research-Policy Interaction
PSJ — 2026-04-17 Original How Can Researchers Have Greater Policy Impact? Kizzy Gandy Abstract ABSTRACT Researchers seeking public policy impact lack consistent, coherent, and practical definitions, strategies, and measurement approaches. This article addresses these gaps through four questions using literature, practitioner expertise, and real‐world examples. What does it mean to have policy impact? Three levels of impact are defined: contributing to new policy conversations; shaping policy narrative direction; and influencing decisions that create, reform, or stop policies. How does research influence policy? Research and policy interact bi‐directionally and iteratively. Strategies to maximize the supply, demand, and co‐production of research in policymaking are operationalized for both individual researchers and research organizations. How can the impact of research on policy be evaluated? Contribution analysis is the most appropriate approach because it goes beyond simple correlations—revealing how and why evidence was used in policymaking, guiding future influencing strategies. How can researchers achieve greater policy impact? While each researcher and research organization should develop their own theory of change to inform an effective and testable impact strategy for their operating context, four generalizable principles are presented with a case study demonstration.

Heterogeneous Treatment Effects and Causal Mechanisms

·491 字·1 分钟
Polihot 研究方法 Causal Inference Heterogeneous Treatment Effects Causal Mechanisms Research Design Exclusion Assumptions
APSR — pp. 1-18 2026-04-06 Original Heterogeneous Treatment Effects and Causal Mechanisms JIAWEI FU, TARA SLOUGH Abstract The credibility revolution advances the use of research designs that permit the identification and estimation of causal effects. However, understanding which mechanisms produce measured causal effects remains a challenge. The dominant current approach to the quantitative evaluation of mechanisms relies on the detection of heterogeneous treatment effects (HTEs) with respect to pretreatment covariates. This article develops a framework to understand when the existence of such HTEs can support inferences about the activation of a mechanism. We show first that this design cannot provide evidence of mechanism activation without additional, generally implicit, exclusion assumptions. Further, even when these assumptions are satisfied, the presence of HTEs supports the inference that the mechanism is active but the absence of HTEs is generally uninformative about mechanism activation. We provide novel guidance for interpretation and research design in light of these findings.

Experiments in public administration research: contributions, challenges, and the road ahead

·450 字·1 分钟
Polihot 公共行政 研究方法 Experiments Public Administration Causal Inference Bibliometrics Quasi-Experiments
PMR — pp. 1-33 2026-03-30 Original Experiments in public administration research: contributions, challenges, and the road ahead Ricardo C. Gomes, Gustavo M. Tavares, Gustavo Mirapalheta Abstract Experiments are essential for testing theory and evaluating policy interventions as they uniquely enable causal inference. This study provides a primer on experimental and quasi-experimental methods and reviews their use in public administration research by analysing 1,143 articles through bibliometric and regression techniques. It focuses on laboratory, field, survey-based, and quasi/natural experiments. The findings reveal rapid growth in experimental research, particularly survey-based experiments, which now dominate the field. Key theoretical clusters, themes, and references are identified, and statistical analyses investigate the link between experiment type and citation counts. The study concludes with recommendations for advancing experimental research in public administration.