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Full-Text Articles in Cognition and Perception
Attribute-Based Choice, Francine W. Goh, Jeffrey R. Stevens
Attribute-Based Choice, Francine W. Goh, Jeffrey R. Stevens
Jeffrey Stevens Publications
Alternative-based approaches to decision making generate overall values for each option in a choice set by processing information within options before comparing options to arrive at a decision. By contrast, attribute-based approaches compare attributes (such as monetary cost and time delay to receipt of a reward) across options and use these attribute comparisons to make a decision. Because they compare attributes, they may not use all available information to make a choice, which categorizes many of them as heuristics. Choice data have suggested that attribute-based models can better predict choice compared to alternative-based models in some situations (e.g., when there …
Exercise Shifts Hypothetical Food Choices Toward Greater Amounts And More Immediate Consumption, Karsten Koehler, Safiya E. Beckford, Elise Thayer, Alexandra R. Martin, Julie B. Boron, Jeffrey R. Stevens
Exercise Shifts Hypothetical Food Choices Toward Greater Amounts And More Immediate Consumption, Karsten Koehler, Safiya E. Beckford, Elise Thayer, Alexandra R. Martin, Julie B. Boron, Jeffrey R. Stevens
Jeffrey Stevens Publications
Although exercise modulates appetite regulation and food intake, it remains poorly understood how exercise impacts decision-making about food. The purpose of the present study was to assess the impact of an acute exercise bout on hypothetical choices related to the amount and timing of food intake. Forty-one healthy participants (22.0 ± 2.6 years; 23.7 ± 2.5 kg/m 2 , 56% female) completed 45 min of aerobic exercise and a resting control condition in randomized order. Food amount preferences and intertemporal food preferences (preference for immediate vs. delayed consumption) were assessed using electronic questionnaires with visual food cues. Compared to rest, …
Improving Measurements Of Similarity Judgments With Machine-Learning Algorithms, Jeffrey R. Stevens, Alexis Polzkill Saltzman, Tanner Rasmussen, Leen-Kiat Soh
Improving Measurements Of Similarity Judgments With Machine-Learning Algorithms, Jeffrey R. Stevens, Alexis Polzkill Saltzman, Tanner Rasmussen, Leen-Kiat Soh
Jeffrey Stevens Publications
Intertemporal choices involve assessing options with different reward amounts available at different time delays. The similarity approach to intertemporal choice focuses on judging how similar amounts and delays are. Yet we do not fully understand the cognitive process of how these judgments are made. Here, we use machine-learning algorithms to predict similarity judgments to (1) investigate which algorithms best predict these judgments, (2) assess which predictors are most useful in predicting participants’ judgments, and (3) determine the minimum number of judgments required to accurately predict future judgments. We applied eight algorithms to similarity judgments for reward amount and time delay …
Excluder: An R Package That Checks For Exclusion Criteria In Online Data, Jeffrey R. Stevens
Excluder: An R Package That Checks For Exclusion Criteria In Online Data, Jeffrey R. Stevens
Jeffrey Stevens Publications
Collecting survey data online can result in low-quality data. Survey participants may not complete the survey, may complete the survey too quickly or slowly, may not reside in the country they claim, or may use unacceptable screen types. Also, online surveys are plagued by automated bots attempting to complete the surveys while offering worthless data. Researchers collecting online data may want to check their data for these and other potential criteria to exclude problematic data entries. The excluder package uses three main function types to mark, check, and exclude data based on seven different exclusion criteria.