Document Type

Article

Publication Date

10-24-2013

Publication Title

Optimal Data Analysis

Volume

2

Issue

2

Pages

69-70

Publisher Name

Optimal Data Analysis LLC

Abstract

Attributes measured on a categorical response scale are common in the literature. Categorical scales for attributes such as, for example, political affiliation, ethnic origin, marital status, state of residence, or diagnosis may consist of many qualitative response categories. Such disorganized variables rarely appear in multivariable models: some effects are missed in analysis due to inadequate statistical power for the many categories, and some findings are dismissed due to inability of the investigator to recognize the dimension(s) underlying segmented categories. This research note recommends that such multi-categorical attributes are replaced by a new set of attributes created via content analysis. In this approach observations are scored on new dimensions all theoretically motivated to predict the class variable. The methodology is illustrated using a hypothetical example in the field of investment realty.

Comments

Author Posting © Optimal Data Analysis LLC, 2013. This article is posted here by permission of Optimal Data Analysis LLC for personal use, not for redistribution. The article was published in Optimal Data Analysis, Volume 2, September 2013, https://odajournal.files.wordpress.com/2019/01/v2.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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