Imputation of missing categorical data by maximizing internal consistency
article
This paper suggests a method to supplant missing categorical data by "reasonable" replacements. These replacements will maximize the consistency of the completed data as measured by Guttman's squared correlation ratio. The text outlines a solution of the optimization problem, describes relationships with the relevant psychometric theory, and studies some properties of the method in detail. The main result is that the average correlation should be at least 0.50 before the method becomes practical. At that point, the technique gives reasonable results up to 10-15% missing data. © 1992 The Psychometric Society.
TNO Identifier
231968
ISSN
00333123
Source
Psychometrika, 57(4), pp. 567-580.
Pages
567-580
Files
To receive the publication files, please send an e-mail request to TNO Repository.