These types of consistency are also known as-test-retest, internal, and inter-rater reliability. To evaluate reliability, analysts assess consistency over time, within the measurement instrument, and between different observers. Reliability relates to measurement consistency. Unreliable measurements typically cannot be valid. Measures have appropriate relationships to theories, similar measures, and different measures. Stability of results across time, between observers, within the test. Measurements reflect what they’re supposed to measure.

Similar measurements for the same person/item under the same conditions. validity is the topic for the rest of this post! How can you determine whether measurements are both valid and reliable? Assessing reliability vs. Just because you can measure the same object multiple times and get consistent values, it does not necessarily indicate that the measurements reflect the desired characteristic. If you’re assessing the psychological construct of conscientiousness, you need to confirm that the instrument poses questions that appraise this attribute rather than, say, obedience. Validity is a bigger concern in the social sciences, where you can measure elusive concepts such as positive outlook and self-esteem. You might have a biased bathroom scale if it tends to read too high or too low-but it still measures weight. Validity is a smaller concern for tangible measurements like height and weight.

Or do the measurements reflect something else? Does the instrument measure what it says it measures? It’s a question that addresses the appropriateness of the data rather than whether measurements are repeatable. Researchers need to consider whether they’re measuring what they think they’re measuring. This concept is a broader issue than reliability. Validity refers to whether the measurements reflect what they’re supposed to measure. When assessing studies, evaluate data collection methodologies and consider whether any issues undermine their reliability.

Reliability in research