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What exactly is reliability of measurement? How can you be sure that your test results are not wrong?
In statistics and psychometrics, reliability refers to the overall consistency of a measurement. A measurement is considered to have high reliability if it produces similar results under consistent conditions. Experts point out: "This is a characteristic of a group of test scores related to random errors that may be embedded in the test scores during the measurement process." Simply put, the more reliable the measurement, the more accurate, repeatable and reliable the results. The higher the consistency.
"When a test procedure is repeated and the results are roughly the same for the same group of people, the measurement is considered to have high reliability."
There are several different categories of reliability of measurements. The first is the reliability between evaluators, that is, the consistency of the evaluators in measuring the target. In this case, if a patient presents with stomach pain and receives the same diagnosis from multiple doctors, the measure has good reliability. Second, test-retest reliability refers to the consistency of test scores across different test administrations. This includes internal consistency assessment, which evaluates the degree of agreement between test items. There are also various ways of mutual verification, for example, the reliability between methods and the reliability between forms.
Difference between reliability and validity
It is important to note that reliability is not the same as validity. A reliable measurement does not mean that it correctly measures the desired characteristic. For example, while there are many tests that reliably quantify specific abilities, they are not necessarily sufficient to predict job performance. At this point, reliability has some limitations on validity. A test that is not completely reliable cannot be completely valid. For example, if a scale always displays the weight of an object as 500 grams, even if the scale is reliable, it is obviously not effective because the displayed weight is not the actual weight.
“A completely reliable measurement is not necessarily valid, but a valid measurement is certainly reliable.”
Factors of measurement inconsistency
In practice, testing measures are never completely consistent. Theory of test reliability seeks to estimate the effect of inconsistency on measurement accuracy. The variation in test scores is generally influenced by two types of factors: stable factors, which are stable characteristics of individuals, and unstable factors, which are other factors in individuals or situations that may affect test scores. This may involve temporary factors such as health, fatigue, motivation, etc., and may also include interference from the test environment and clarity of instructions.
Methods to improve reliability
An important method for achieving high reliability is to conduct item analysis, which involves calculating the difficulty and discrimination index of the items. If some questions are too easy or difficult, or their discrimination is close to zero or negative, then these questions need to be replaced by more valid items to improve the reliability of the measurement. Reliability can often be improved through test clarity, test length, or other informal means.
Conclusion
Understanding the true nature of reliability and how to test it is critical when designing and implementing any measurement. This not only ensures the reliability of the test results, but also improves the overall validity of the test. If measurement is unreliable, then it will not achieve the desired effect. We should always reflect on whether we can find better ways to improve reliability from different measurement perspectives?
