A large-scale dataset of choice and response-time data in intertemporal choice

Area of Science:

• Behavioral Economics
• Cognitive Psychology
• Decision Science

Background:

• Intertemporal choice (ITC) research traditionally focuses on decisions, overlooking underlying cognitive processes.
• Process models of ITC require process data, such as response times (RTs), which have been underutilized.
• A growing need exists for comprehensive data to develop more sophisticated ITC theories.

Purpose of the Study:

• To present a large-scale, open-access dataset of intertemporal choices (ITC) and associated response times (RTs).
• To facilitate the development of advanced process models for understanding ITC.
• To create a continuously expanding database for ongoing research contributions.

Main Methods:

• Compiled data from 100 ITC studies, encompassing 11,852 subjects and 1,172,644 trials.
• Collected behavioral data (choices and response times).
• Gathered methodological and sample information, including task procedures and incentivization details.

Main Results:

• A substantial dataset combining ITC, RTs, and contextual information is now available.
• The dataset provides a foundation for exploring cognitive processes in decision-making.
• The ITC Database is structured for continuous growth and community contribution.

Conclusions:

• The presented dataset addresses a critical gap in ITC research by including response time data.
• This resource is expected to significantly contribute to the refinement of theories on intertemporal decision-making.
• The open and expanding nature of the ITC Database promotes collaborative advancement in the field.