# In research design, what is the difference between reliability and validity?

The dependent variable should be operationally defined in measurable terms. As such they should be characterized as reliable and valid. Could someone clarify these concept?

## All Answers (4)

Fathi M Sherif· University of TripoliDeletedIn other words reliability refers to the consistency of the measure or the set of measures while validity refers to how properly the concept is defined by the measure(s).

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Rakesh Pandey· Banaras Hindu UniversityReliability refers to the consistency of the measure and this consistency may be gauged across time or the content of the measure. If we get the measurement using the same tool/measure across two points of time (separated by a defined time interval e.g., 1 day, 1 week, 1 month or any other time interval depending on the nature of the construct to be measured) and the results are consistent (e.g., a high correlation between the two measurements) then this reflects the temporal consistency of the measure. This aspect of reliability is also called test - retest reliability.

Another aspect of reliability is called internal consistency and it reflects that each and every element or component of the given measure are consistent or highly correlated with each other. If the measure happens to have a single component (item/scale) then this form of reliability can be measured by taking another measure of the same construct which is equivalent to the measure under consideration. The correlation between the original measure and the alternative equivalent measure reflects the internal consistency of the given measure. Sometimes this methodology of estimating internal consistency is referred to as "parallel/ alternative form reliability".

The overall reliability of a given measure depends on both the temporal consistency as well as internal consistency because some errors of measurement are inevitable because of temporal variations as well as variations in the content/sub-components of the measure.

Statistically, the reliability of a measure is the proportion of true variance to total variance or 1 minus the proportion of error variance.

On the other hand, the validity of a measure is the proportion of common variance to total variance. The total variance is the sum of common variance, specific variance and error variance and the sum of common and specific variance represents the amount of true variance. Thus, technically, the reliability is always the upper limit of the validity of the measure and validity will equal to reliability only when the specific variance of the measure is zero.

As Prof. Halkos have mentioned the validity of the measure reflects the extent to which it measures the construct for which it has been developed. To demonstrate this we generally take some external criterion reflecting the construct under consideration (say another measure of the same construct with demonstrated validity) and correlate it with given measure. The magnitude of squared correlation reflects the shared or common variance. higher the common variance higher is the validity of the measure.

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Shabeer p k· Tata Institute of Social Sciencesy with which your measure assesses the characteristics you are evaluating.

Validity: Check on whether your measure is actually measuring what you claim it is measuring.

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