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AbstractAlthough strategies exist to measure actors' efforts to set policy, media, and lawmaking agendas, political scientists lack a method for identifying and accurately measuring another form of agenda setting that lies under the surface anytime two people talk. Within interactions, such as debates, deliberations, and discussions, actors can set the agenda by shifting others' attention to their preferred topics. In this article, I use a topic model that locates where topic shifts occur within an interaction in order to measure the relative agenda‐setting power of actors. Validation exercises show that the model accurately identifies topic shifts and infers coherent topics. Three empirical applications also validate the agenda‐setting measure within different political settings: U.S. presidential debates, in‐person deliberations, and online discussions. These applications show that successfully setting the agenda can shape an interaction's outcomes, demonstrating the importance of continued research on this form of agenda setting.

The goal of this Element is to provide a detailed introduction to adaptive inventories, an approach to making surveys adjust to respondents' answers dynamically. This method can help survey researchers measure important latent traits or attitudes accurately while minimizing the number of questions respondents must answer. The Element provides both a theoretical overview of the method and a suite of tools and tricks for integrating it into the normal survey process. It also provides practical advice and direction on how to calibrate, evaluate, and field adaptive batteries using example batteries that measure variety of latent traits of interest to survey researchers across the social sciences.

Abstract
One of the most difficult tasks facing survey researchers is balancing the imperative to keep surveys short with the need to measure important concepts accurately. Not only are long batteries prohibitively expensive but lengthy surveys can also lead to less informative answers from respondents. Yet, scholars often wish to measure traits that require a multi-item battery. To resolve these contradicting constraints, we propose the use of adaptive inventories. This approach uses computerized adaptive testing methods to minimize the number of questions each respondent must answer while maximizing the accuracy of the resulting measurement. We provide evidence supporting the utility of adaptive inventories through an empirically informed simulation study, an experimental study, and a detailed case study using data from the 2016 American National Election Study (ANES) Pilot. The simulation and experiment illustrate the superior performance of adaptive inventories relative to fixed-reduced batteries in terms of precision and accuracy. The ANES analysis serves as an illustration of how adaptive inventories can be developed and fielded and also validates an adaptive inventory with a nationally representative sample. Critically, we provide extensive software tools that allow researchers to incorporate adaptive inventories into their own surveys.