Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Evidence of the Presence of Bias in Subjective Metrics: Analysis Within a Family of Experiments
Year:2014
Research Areas
  • Information technology and adata processing
Information
Abstract
Context: Measurement is crucial and important to empirical software engineering. Although reliability and validity are two important properties warranting consideration in measurement processes, they may be influenced by random or systematic error (bias) depending on which metric is used. Aim: Check whether, the simple subjective metrics used in empirical software engineering studies are prone to bias. Method: Comparison of the reliability of a family of empirical studies on requirements elicitation that explore the same phenomenon using different design types and objective and subjective metrics. Results: The objectively measured variables (experience and knowledge) tend to achieve more reliable results, whereas subjective metrics using Likert scales (expertise and familiarity) tend to be influenced by systematic error or bias. Conclusions: Studies that predominantly use variables measured subjectively, like opinion polls or expert opinion acquisition.
International
Si
Congress
EASE 2014: International Conference on Evaluation and Assessment in Software Engineering
960
Place
London, UK
Reviewers
Si
ISBN/ISSN
978-1-4503-2476-2
10.1145/2601248.2601291
Start Date
13/05/2014
End Date
14/05/2014
From page
1
To page
4
Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE 2014)
Participants
  • Autor: Alejandrina Maria Aranda Lopez King (UPM)
  • Autor: Oscar Dieste Tubio (UPM)
  • Autor: Natalia Juristo Juzgado (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ingeniería del Software
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software
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