Steps in validating research instruments

When we think about the reliability of these variables, we want to know how stable or constant they are.This assumption, that the variable you are measuring is stable or constant, is central to the concept of reliability.This will increase the consistency/stability of the measurement procedure.Most of what you have done up until now has been theoretical.The error reflects conditions that result in the score that we are measuring not reflecting the true score, but a variation on the actual score (e.g., a person whose true score on an IQ test should be 76 out of 100 gets 74 one day, but 79 the next, with the difference in the scores between the two days reflecting the error component).

Also consider how the data collection and data methods are described, and what types of analyses of the data are recommended.Therefore, the score measured (e.g., 0-100 in an exam) for a given variable consists of the true score plus error.The true score is the actual score that would reliably reflect the measurement (e.g., for a person) on a given construct (e.g., a score of 76 out of 100 in an IQ test actually reflects the intelligence of the person taking the test; if that person took another IQ test the next day, we would expect them to get 76 out of 100 again, assuming that we are only seeing that person's true score and not any error).Some variables are more stable (constant) than others; that is, some change significantly, whilst others are reasonably constant.However, the measurement procedure that is used to measure a variable introduces some amount/degree of error, whether small or large.

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