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ERIC Number: EJ809795
Record Type: Journal
Publication Date: 2008-Jul
Pages: 27
Abstractor: As Provided
Reference Count: 21
ISSN: ISSN-0027-3171
Simulating Multivariate Nonnormal Data Using an Iterative Algorithm
Ruscio, John; Kaczetow, Walter
Multivariate Behavioral Research, v43 n3 p355-381 Jul 2008
Simulating multivariate nonnormal data with specified correlation matrices is difficult. One especially popular method is Vale and Maurelli's (1983) extension of Fleishman's (1978) polynomial transformation technique to multivariate applications. This requires the specification of distributional moments and the calculation of an intermediate correlation matrix such that when data are transformed, the target correlation matrix is reproduced. We present an alternative technique that involves sampling data from specified population distributions and identifying the intermediate correlation matrix through an iterative, trial-and-error process. We provide R program code to implement this technique and show that it can generate data under a wide range of conditions (e.g., with empirical samples, with discrete rather than continuous data, when distributional moments are undefined or outside the boundary conditions of other techniques). This approach could be useful in many contexts, especially Monte Carlo studies of multivariate statistics. (Contains 5 tables, 3 figures and 2 footnotes.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A