What is reliability in research?

A brief introduction to reliability

For more best practices see our method overview

Definition of reliability

Reliability is the degree, to which the measurement instruments are consistent (Guba, 1981; Frambach et al. (2013)). Reliability is a prerequisite to statistical conclusion validity since, without reliable and repeatable measurements, inferences about the correlation between the independent and dependent variable become invalid. Measures improving the reliability of measurements include an increased number of measurements and better training of raters applying the measurement (Shadish et al., 2002).
Decoration image for reliability in qualitative research
The other dimensions of research rigor that correspond to reliability are:On our page on rigor you can get an overview for judging whether these are the dimensions to evaluate for your research or if (for qualitative research) you should use framework of trustworthiness instead.

Strategies to improve reliability

Ensuring reliability in research requires deliberate planning and strategic execution. You can enhance the consistency and stability of your measurements and assessments by adopting the strategies presented in the following.
  • Test-Retest Reliability: Conduct the same measurement on the same subjects at different time intervals to ensure consistent results.
  • Inter-Rater Reliability: Provide clear guidelines, training, and calibration to ensure consistent conclusions when multiple raters are involved.
  • Parallel Forms Reliability: Use multiple versions of the same test and compare results to counteract practice effects or memorization.
  • Internal Consistency Reliability: Assess the closeness of relationship between items in a measurement scale using techniques like Cronbach's alpha.

Conclusion on reliability

Reliability is a cornerstone of rigorous research and ensures the validity of your findings. By employing strategies such as test-retest reliability, inter-rater reliability, parallel forms reliability, and internal consistency reliability, you can ensure that your measurements and assessments remain consistent and dependable across different contexts.
Reliability ensures that the research's validity is upheld over time and across different conditions. Just as a structure requires a solid foundation to stand tall, research findings require reliability to maintain their integrity in the face of scrutiny and application.

We use cookies for a number of purposes, including analytics and performance, functionality and advertising. Learn more about QDAcity use of cookies.