Here is a differentiation of reliability and validity as applied to the preparation of research instruments.
One of the most difficult parts in research writing is when the instrument’s psychometric properties are scrutinized or questioned by your panel of examiners. Psychometric properties may sound new to you, but they are not actually new.
In simple words, psychometric properties refer to the reliability and validity of the instrument. So, what is the difference between the two?
Reliability refers to the consistency while validity refers to the test results’ accuracy. An instrument should accurately and dependably measure what it ought to measure. Its reliability can help you have a valid assessment; its validity can make you confident in making a prediction.
How can you say that your instrument is reliable? Although there are many types of reliability tests, what is more usually looked at is the internal consistency of the test. When presenting the results of your research, your panel of examiners might look for the results of the Cronbach’s alpha or the Kuder-Richardson Formula 20 computations. If you cannot do the analysis by yourself, you may ask a statistician to help you process and analyze data using a reliable statistical software application.
But if your intention is to determine the inter-correlations of the items in the instrument and if these items measure the same construct, Cronbach’s alpha is suggested. According to David Kingsbury, a construct is the behavior or outcome a researcher seeks to measure in the study. This is often revealed by the independent variable.
When the inter-correlations of the items increase, the Cronbach’s alpha generally increases as well. The table below shows the range of values of Cronbach’s alpha and the corresponding descriptions on internal consistency.
(Note: The description is not officially cited and taken only from Wikipedia, but you may confer with your statistician and your panel of examiners. If the value of alpha is less than .05, the items are considered poor and must be omitted).
There are many types of validity measures. One of the most commonly used is the construct validity. Thus, the construct or the independent variable must be accurately defined.
To illustrate, if the independent variable is the school principals’ leadership style, the sub-scales of that construct are the types of leadership style such as authoritative, delegative and participative.
The construct validity would determine if the items being used in the instrument have good validity measures using factor analysis and each sub-scale has a good inter-item correlation using Bivariate Correlation. The items are considered good if the p-value is less than 0.05.
1. Kingsbury, D. (2012). How to validate a research instrument. Retrieved October 16, 2013, from http://www.ehow.com/how_2277596_validate-research-instrument.html
2. Grindstaff, T. (n.d.). The reliability & validity of psychological tests. Retrieved October 16, 2013, from http://www.ehow.com/facts_7282618_reliability-validity-psychological-tests.html
3. Renata, R. (2013). The real difference between reliability and validity. http://www.ehow.com/info_8481668_real-difference-between-reliability-validity.html
4. Cronbach’s alpha. Retrieved October 17, 2013, from http://en.wikipedia.org/wiki/Cronbach%27s_alpha
© 2013 October 17 M. G. Alvior