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Validity

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# Validity - PowerPoint PPT Presentation

Validity. Notes Chapter 4. Overview. Validity and reliability are independent of each other Validity = Accuracy Reliability = Precision Marksman example Validity and reliability are continuous Errors in measurement are always either the result of

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### Validity

Notes Chapter 4

Overview
• Validity and reliability are independent of each other
• Validity = Accuracy
• Reliability = Precision
• Marksman example
• Validity and reliability are continuous
• Errors in measurement are always either the result of
• Systematic biasing of your scale (validity)
• Random error introduced by your scale (reliability)
Validity
• Four major types of experimental validity (Cook & Campbell, 1979)
• Statistical conclusion validity
• Internal validity
• External validity
• Construct validity
• Most concerned with when creating a scale
• Extent to which the measurements taken in a study properly represent the underlying theoretical construct
Construct Validity
• Measures the match between a variable representing a “true” measure of the construct and the scale responses
• Applies only when attempting to relate a scale to a theoretical construct
• May have validity for one purpose but not for another
Criterion Validity (continued)
• When there is an objectively correct way to measure an underlying construct your scale was designed to represent
• Demonstrate your scale is related to the correct measure
• When there is no objective measurement there is no single procedure to measure validity
• Build an argument for how to interpret the scale by demonstrating that measurements are consistent with the theoretical variable motivating the responses
Face Validity
• Items composing the scale are logically related to the underlying construct
• Scale “looks” appropriate
Convergent Validity
• Most important to demonstrate
• Shows that the responses to your scale are related to other measurements that are supposed to be affected by the same variable
• Assess it numerous ways
• Each time you demonstrate consistency with the underlying construct makes a more convincing argument that your scale provides an accurate representation of that construct
Divergent Validity
• Demonstrating that your scale is not related to measurements that represent different variables
• Shows that your scale is measuring a new concept
• Assess it at the same time as convergent validity
• Unclear whether the relation does not exist or your study lacked enough power to detect it
• If you show significant relations in your study, it makes the argument that the nonsignificant findings in your divergent validity are not due to faults in your study
Unique Utility
• Demonstrate that your scale does something beyond similar measures that already exist
• Shows that your scale can explain unique portions of the variance
• Can cause people to use or not use your scale
Final Points on Validity
• Validity and reliability are independent concepts but are related in important ways
• Difficult to determine validity of a highly unreliable scale
• Involve showing statistically significant relations between the scale and other measures
• Validity measures how successfully your scale matches onto the theory you propose
• Failure to validate the scale does not mean there is something wrong with your scale
• May indicate there is something wrong with the theory underlying the validation