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Exercise

Factorability check

In this exercise, you will implement the first step in the workflow of Exploratory Factor Analysis; namely to conduct a factorability check on a sample of 100 observations of the original SD3 dataset, presented in the last video, and determine whether you can potentially provide insights of hidden factors based on the dataset.

To complete this exercise, the sdt_sub_correl correlation object is available in your workspace. sdt_sub_correl has been calculated with the hetcor() function of the polycor package and contains the actual correlation matrix in one of its attributes, the correlations attribute. The sdt_sub dataframe, the sample of the SD3 dataset based on which sdt_sub_correl was computed, is also loaded for you and you can access it at any time in the console.

Instructions
100 XP
  • Get to know the sdt_sub_correl correlation object by exploring its structure.
  • Extract the actual correlation matrix of sdt_sub_correl from its correlations attribute and store it to sdt_polychoric.
  • The next two lines involve the factorability check on the correlation matrix sdt_polychoric with Bartlett-sphericity test and the KMO index respectively.