Revised Modified Parallel Analysis (RMPA) for the Construction of UnidimensionalItem Pools

摘要

Modified Parallel Analysis (MPA) is a heuristic method for assessing approximateunidimensionality of item pools. It compares the second eigenvalue of the observed correlation matrix with the corresponding eigenvalue extracted from a parallel matrix generated by a unidimensional and locally independent model. Revised Modified Parallel Analysis (RMPA) generalizes MPA and alleviates some of its technical limitations. An important and useful feature is a new method for eliminating items which violate the test's unidimensionality. This is achieved by eliminating items, one at a time to determine their contribution to the matrices' eigenvalues. We propose a test for detecting item with larger impact in the observed data set, and eliminating them. The new method was tested in several simulations in which unidimensional item pools were contaminated by various proportions of items from a secondary pool. The results indicate that RMPA does an excellent job in detecting low (10%) and moderate (25%) levels of contamination, but fails in cases of maximal (50%) contamination. Parallel Analysis, Dimensionality, Gapping. Unidimensionality, Item Pools.