Abstract
Topic set size design methods provide principles and procedures for test collection builders to decide on the number of topics to create. These methods can then help us keep improving the test collection design based on accumulated data. Simple Excel tools are available for such purposes. Post-hoc power analysis tools, available as simple R scripts, can help IR researchers examine the achieved power of a reported experiment and determine future sample sizes for ensuring high power. Thus, for example, underpowered user experiments can be detected, and a larger sample size can be proposed. If used appropriately, these Excel and R tools should be able to provide the IR community with better experimentation practices. The main objective of this tutorial is to let IR researchers familiarise themselves with these tools and understand the basic ideas behind them.
Original language | English |
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Title of host publication | ICTIR 2016 - Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval |
Publisher | Association for Computing Machinery, Inc |
Pages | 9-10 |
Number of pages | 2 |
ISBN (Electronic) | 9781450344975 |
DOIs | |
Publication status | Published - 2016 Sept 12 |
Event | 2016 ACM International Conference on the Theory of Information Retrieval, ICTIR 2016 - Newark, United States Duration: 2016 Sept 12 → 2016 Sept 16 |
Other
Other | 2016 ACM International Conference on the Theory of Information Retrieval, ICTIR 2016 |
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Country/Territory | United States |
City | Newark |
Period | 16/9/12 → 16/9/16 |
Keywords
- Effect sizes
- Experimental design
- Statistical power
- Statistical significance
- Test collections
- Variances
ASJC Scopus subject areas
- Information Systems
- Computer Science (miscellaneous)