Data considerations for Item Analysis

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

You should have at least two variables
You must have numeric data for at least two variables. Data can be continuous or discrete, and you must have at least two observations for each variable. Usually, the data are scores, such as test scores, or responses to a survey, such as Likert-scale responses.
The items should measure the same characteristic
The objective of an item analysis is to assess how consistently multiple items in a survey or test measure the same characteristic. For example, you might want to know whether the items on a test all measure reading comprehension, or whether questions on a survey all reflect customer satisfaction. Therefore, all the variables that you enter for the analysis should be reasonably expected to measure the same characteristic.
By using this site you agree to the use of cookies for analytics and personalized content.  Read our policy