Assessing reliability

Defining Reliability

Reliability refers to the consistency, dependability, or repeatability of research findings.
It is crucial in research as it can affect the validity of the results. If a study is not reliable, it’s doubtful that the results are valid.
Reliability is concerned with consistency of measurements - if the same procedure is repeated under the same conditions, the results should be the same.

Test-retest reliability deals with the consistency of a participant’s performance over time. If the same test is given to the same participant on two different occasions, the scores should be highly correlated.
Internal consistency reliability looks at the extent to which tests or procedures assessing the same characteristic or construct produce similar results.
Split-half reliability involves splitting a test into two, and examining whether a person’s score on one half of the test correlates with their score on the other half.
Inter-rater or inter-observer reliability assesses the degree of agreement between two or more raters or observers. If several people are coding or scoring the same behaviour or event, there should be a high degree of agreement between them.

To assess test-retest reliability, the same test is administered to the same participants at two points in time. A correlation coefficient is then calculated to determine the relationship between the two sets of scores.
Internal consistency is typically measured with Cronbach’s alpha. This statistic provides an average value of the correlations between all items in a test.
To assess split-half reliability, the test is divided into two halves and the scores for each half are compared. They should be as close to 1.0 as possible.
Inter-rater reliability can be assessed using a variety of statistical measures like the Kappa statistic. A higher value suggests greater consistency in ratings.

Ensuring clear operational definitions and providing clear and detailed instructions can help improve reliability.
Using standardized procedures and keeping conditions the same for all participants can enhance reliability.
Avoiding vague or ambiguous questions in questionnaires can improve both reliability and validity.
Regular training and monitoring of observers can help reduce observer bias and improve inter-rater reliability.
Long tests are generally more reliable than short ones as they provide more opportunity for consistent responses compared with chance.