Exam 18: Exploratory Factor Analysis

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A top way of determining the number of factors to retain is generating a random set of cases that have a similar number of items to your target data set. You then compare the magnitude of eigen values in your random data set to the magnitude of eigen values in your real data set to see at what point the random data has larger values than the real data set. This technique is called _____.

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B

Which is the ratio of cases to items that is recommended as a minimum sample size within Shultz, Whitney, and Zickar (2021)? 

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What are strategies that can be used in exploratory factor analysis to help improve interpretability?

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First off, theory and common sense should guide results. You should have a large enough sample size relative to number of items to provide stable results. You should use parallel analysis (along with common sense) to choose the number of factors to interpret. And you should use a rotation to improve interpretability. Items that do not load on factors or cross-load significantly on factors should be thrown out.

Explain the main steps and decisions that need to be made when conducting an EFA.

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What is the graphical technique that can be used to identify the number of factors to retain from an exploratory factor analysis?

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The regression between the item score and the underlying factors is called a(n) ______.

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When should exploratory factor analysis be used compared to confirmatory factor analysis?

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If you want to discover what the underlying structure is in your test, Shultz, Whitney, and Zickar (2021) recommend using the following technique?

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Shultz, Whitney, and Zickar (2021) recommend an oblique rotation over an orthogonal rotation. Explain the differences between the two and explain their rationale.

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In exploratory factor analysis, what is the term that refers to the variance in an item that is not shared with any other items?

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Oblique rotations have ______ factors, whereas orthogonal rotations result in ___ factors.

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Which of the following practices do Shultz, Whitney, and Zickar (2021) recommend with respect to exploratory factor analysis?

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How should exploratory factor analysis be used in scale development?

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What is the mathematical procedure that is used in exploratory factory analysis that is designed to choose an interpretable factor pattern matrix?

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Which of the following techniques uses linear combinations of observed items to determine a test's structure?

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