How to Solve Discriminant Validity Issues?
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How to Solve Discriminant Validity Issues?
Understanding and Solving Discriminant Validity Issues.
We have now assessed the discriminant validity. However, a number of time scholars face issues in establishing discriminant validity. The two session specifically focus on how to solve discriminant validity issues.
Considerations before Collecting the Data
- Make sure to have adequate No. of Items in each scale/construct.
- There should be at least 4-6 items, since, in SEM items are deleted if they fail to load or due to cross-loading.
- Make sure that the Items/Statements are easy to understand.
- Make sure there is no overlap in the statements of different constructs.
How to Solve Discriminant Validity Problems?
To solve the discriminant validity issues, following steps may be undertaken
- Make sure to clean the data.
- Check for Standard Deviation in Responses. Standard Deviation value of Less than 0.25 mean that there is probability of respondent misconduct and the responses for the questions are almost similar.
- Assess cross-loading, if an item is loading well onto another construct instead of its own construct, that particular items shall be removed. For example, an item has loading over 0.70 on two constructs
- Check for Cross-loading, if an item is cross-loading, and the difference is less than .10, REMOVE the item(s).
- Check for low loadings, remove items that have low loadings (start with < 0.40).
- If the problem still persists,try collecting more data
- Combine the constructs that have lack of discriminant validity as they are measuring the same concept (This is appropriate for dimensions of the same construct).
- If problems still persist, dropping one (or more) independent variables (i.e., collinear variables that demonstrate insufficient discriminant validity) from the model may also help.
Reference
Farrell, A. M. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63(3), 324-327.