Abstract
Random eigenvalues are the key elements in parallel analysis. When analyzing Likert-type data, is it necessary to convert the continuous random data to discrete type before estimating eigenvalues? The study compared the random eigenvalues obtained from continuous and categorized random data from two popular computer programs to be used as the basis for comparison in conducting parallel analysis on Likert-type data. Results indicated that categorized random data gave eigenvalues and number of factors similar to those obtained from continuous random data. It is suggested that when conducting parallel analysis on Likert-type data by the two programs, the conversion is unnecessary.
Original language | English |
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Pages (from-to) | 5367-5377 |
Number of pages | 11 |
Journal | Communications in Statistics: Simulation and Computation |
Volume | 46 |
Issue number | 7 |
DOIs | |
Publication status | Published - 2017 Aug 9 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modelling and Simulation