Data considerations for Simple Correspondence 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 two-way classification data
Simple correspondence analysis evaluates the relationships in a two-way classification. You can also use the analysis on three-way and four-way classification tables if you collapse the data into a two-way table when you perform the analysis. For more information, go to Combine variables for Simple Correspondence Analysis.
You can have raw data or data in a contingency table form
If you have raw categorical data, you usually have two classification columns in the worksheet, with each row representing an observation. You can also have up to two additional classification columns, which must be collapsed using the Combine sub-dialog box. If your data are in contingency table form, the worksheet columns contain integer frequencies of the category combinations. To see examples of each type of data, go to Enter your data for Simple Correspondence Analysis. You must delete rows with missing data from the worksheet before using this analysis.
You can use supplementary data
You might have additional or supplementary data in the same form as the main data set used for the analysis. These supplementary data could be further information from the same study, information from other studies, or target profiles. You can use the supplementary data to validate the components, often with a historical value or known standard. You can also explore the scores of auxiliary data, such as outliers that you remove from the analysis. Supplementary data appear in the output but do not affect the components.
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