Monday, June 11, 2012

Find out the differences between Test Validity and Test Reliability.


Test Validity vs. Test Reliability:

Whenever a test or other measuring device is used as part of the data collection process, the validity and reliability of that test is important.  Just as we would not use a math test to assess verbal skills, we would not want to use a measuring device for research that was not truly measuring what we purport it to measure.  After all, we are relying on the results to show support or a lack of support for our theory and if the data collection methods are erroneous, the data we analyze will also be erroneous.

Test Validity. 

Validity refers to the degree in which our test or other measuring device is truly measuring what we intended it to measure.
  • Construct Validity: Construct validity is the term given to a test that measures a construct accurately and there are different types of construct validity that we should be concerned with.  Three of these, concurrent validity, content validity, and predictive validity are discussed below. 
  • Concurrent Validity: Concurrent Validity refers to a measurement device’s ability to vary directly with a measure of the same construct or indirectly with a measure of an opposite construct.  It allows you to show that your test is valid by comparing it with an already valid test. 
  • Content Validity: Content validity is concerned with a test’s ability to include or represent all of the content of a particular construct. There is no easy way to determine content validity aside from expert opinion. 
  • Predictive Validity: In order for a test to be a valid screening device for some future behavior, it must have predictive validity. The GMAT is used to predict success in business school. The main concern with these and many other predictive measures is predictive validity because without it, they would be worthless.

Test Reliability.

Reliability is synonymous with the consistency of a test, survey, observation, or other measuring device.  Based on the inconsistency of this scale, any research relying on it would certainly be unreliable.
A reliability coefficient is often the statistic of choice in determining the reliability of a test.  This coefficient merely represents a correlation, which measures the intensity and direction of a relationship between two or more variables.

  • Test-Retest Reliability: Test-Retest reliability refers to the test’s consistency among different administrations.  To determine the coefficient for this type of reliability, the same test is given to a group of subjects on at least two separate occasions.  If the test is reliable, the scores that each student receives on the first administration should be similar to the scores on the second.  We would expect the relationship between the first and second administration to be a high positive correlation. 
  • Parallel Forms Reliability: One way to assure that memory effects do not occur is to use a different pre- and posttest.  In order for these two tests to be used in this manner, however, they must be parallel or equal in what they measure.  To determine parallel forms reliability, a reliability coefficient is calculated on the scores of the two measures taken by the same group of subjects.  Once again, we would expect a high and positive correlation is we are to say the two forms are parallel. 
  • Inter-Rater Reliability: Whenever observations of behavior are used as data in research, we want to assure that these observations are reliable. One way to determine this is to have two or more observers rate the same subjects and then correlate their observations.
Therefore we can now easily differentiate between these two terms “Test Validity” and “Test Reliability”.

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