This Article Free Full Text (Free PDF) Free References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Finch, H. Articles by Habing, B. Search for Related Content Social Bookmarking                   What's this?

Performance of DIMTEST- and NOHARM-Based Statistics for Testing Unidimensionality

Ball State University, whfinch{at}bsu.edu

Brian Habing

University of South Carolina

This Monte Carlo study compares the ability of the parametric bootstrap version of DIMTEST with three goodness-of-fit tests calculated from a fitted NOHARM model to detect violations of the assumption of unidimensionality in testing data. The effectiveness of the procedures was evaluated for different numbers of items, numbers of examinees, correlations between underlying ability dimensions, skewness of underlying ability distributions, and the presence or absence of a guessing parameter. In the absence of guessing, DIMTEST and the NOHARM-based statistics had similar power, with the ² statistic having a very low Type I error rate. In the presence of guessing, however, two of the NOHARM-based statistics had unacceptably high Type I error rates, while the third performed similarly to DIMTEST. Given this inflated error rate, the study compares the empirical powers after adjusting for the discrepancy in Type I error rates.

Key Words: Index terms: DIMTEST • NOHARM • item response theory • dimensionality • multidimensionality • unidimensionality

CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?