Application: Impact of Sample Size on Interpretation

As we have demonstrated above, both sample size and subject to item ratio have an impact on the quality of your results. The larger the sample and subject to item ratio, the better. But if you have a smaller than desirable sample, your analysis might identify an incorrect factor structure, inaccurate classification of items, or unrepresentative factor loadings. Costello & Osborne (2005) examined the effect of sample size among the SDQ data. Now let’s review how differences in sample size could affect interpretation of the engineering and GDS data.
We will start by running an EFA on the entire sample of data. We will use the extraction methods, the number of factors, and the rotation methods ...

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