JSM 2005 - Toronto

Abstract #303115

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 140
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: General Methodology
Abstract - #303115
Title: Suggested Sample-Size-to-Variable Ratios for Discriminant Analysis
Author(s): Mercedes Schneider*+ and Holmes Finch
Companies: Ball State University and Ball State University
Address: Dept of Ed Psyc, Muncie, IN, 47306, United States
Keywords: discriminant analysis ; structure coefficients ; sample size ; effect size
Abstract:

The discriminant analysis (DA) literature includes a number of suggestions for minimum sample size based upon the number of p continuous variables in the analysis, including sample-size-to-variable (N:p) ratios of 20:1, 10:1, and "between these two." It appears no simulation research has tested any of these N:p guidelines. Furthermore, none of the above suggestions considers the influences of p-variable intercorrelation and effect size upon suggested N:p ratios. This two-group simulation study tests the above three N:p suggestions, where the "in-between" ratio is set as 15:1. The number of p variables per vector ranges from 2 to 5, variable intercorrelation is set at five levels, ranging from minimal (rho = .00 - .20) to high (rho = .81 - .99). Three levels of effect size are examined: 0 (no effect), .5 (medium effect), and .8 (large effect). Finally, two types of structure coefficients (SCs) are compared: within-matrix and total-matrix. The outcome is the proportion of SCs conforming to the criteria that an SC value > .3 indicates an influential p variable. For a given cell, if the proportion of SCs > .3 equals or exceeds .8, the N:p criteria is judged useful.


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