Literature DB >> 19290770

To sum or not to sum: taxometric analysis with ordered categorical assessment items.

Glenn D Walters1, John Ruscio.   

Abstract

Meehl's taxometric method has been shown to differentiate between categorical and dimensional data, but there are many ways to implement taxometric procedures. When analyzing the ordered categorical data typically provided by assessment instruments, summing items to form input indicators has been a popular practice for more than 20 years. A Monte Carlo study compared the accuracy of taxometric analyses implemented in the traditional way (without summing items) and taxometric analyses implemented with the summed-input method. These analyses generated no support for the summed-input method, which substantially reduced discriminating power for 2 of the 3 procedures studied. Accuracy was highest when 5 or more indicators and 4 or more ordered categories were used. Findings from the simulation study were then used to help interpret the results for taxometric analyses of antisocial personality disorder criteria with real research data. In this example, the traditional method yielded clearer results than the summed-input method. Implications for the use and further study of the taxometric method in assessment research are discussed. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Mesh:

Year:  2009        PMID: 19290770     DOI: 10.1037/a0015010

Source DB:  PubMed          Journal:  Psychol Assess        ISSN: 1040-3590


  11 in total

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8.  Taxometric analysis of DSM-IV and DSM-5 alcohol use disorders.

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9.  Performing Taxometric Analysis to Distinguish Categorical and Dimensional Variables.

Authors:  John Ruscio; Ayelet Meron Ruscio; Lauren M Carney
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