Item Analysis using Excel and SPSS (Item Discrimination and Corrected Item-total Correlation Method)

How to perform item analysis using MS Excel and SPSS.
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This video demonstrates how to carry out item analysis using MS Excel and SPSS. It includes item discrimination for dichotomous scale data, item discrimination for Likert scale data, and corrected item-total correlation method.

Item analysis refers to statistical methods used for selecting items for inclusion in a psychological test.
After watching this video, you'll be able to compute the item discrimination index for dichotomous data and for Likert data (using Microsoft Excel). It will also help you to carry out item analysis with the help of the corrected item-total correlation method (using IBM-SPSS).


CAUTION! PLEASE READ BEFORE PROCEEDING
One more suggestion from my side, please use 0 to 4 scores for the Likert scale when you enter data in the Excel sheet. This will give you more accurate values compared to the scores entered with values 1 to 5.
For example, by using 1 to 5 scores, if you have an upper group mean as 5 and a lower group mean as 1, this is 100% discrimination, so your item discrimination value should be 1. But with this formula, it will be 5 minus 1 and the result divided by 5, that is 4 divided by 5 which equals .80 which is not an accurate value.
This problem can be solved if you use a 0 to 4 rating for 5 point Likert scale. In this case, with reference to the earlier example, your upper group mean will be 4 instead of 5 and your lower group mean will be 0 instead of 1. This will give you 4 minus 0, which is 4, and 4 will be divided by the maximum score possible on one item which is 4. Therefore, 4 divided by 4 will equal 1.0, which is a 100% item discrimination value!

Hope this helps you. All the best 👍


In this video (key moments):
00:00 – Item discrimination for dichotomous data using Excel
10:37 – Item discrimination for Likert data using Excel
17:18 – Corrected item-total correlation method (can be used in case of dichotomous or Likert data) using SPSS
28:13 – Interpretation and closing remarks


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