A 0-1 Quadratic Programme for the Case of Missing Data in Regression
Abstract
Multivariate statistical analysis techniques including regression analysis compose a popular toolset for analysing survey data, but the techniques require a complete dataset with no missing values. Unfortunately, most survey datasets contain missing values. These missing values must be resolved in some manner before regression analysis can take place. We present a quadratic programming methodology for eliminating non-responses from a survey dataset. Copyright © 2014 Inderscience Enterprises Ltd.
Recommended Citation
B. K. Smith et al., "A 0-1 Quadratic Programme for the Case of Missing Data in Regression," International Journal of Data Analysis Techniques and Strategies, vol. 6, no. 1, pp. 94 - 104, Inderscience, Jan 2014.
The definitive version is available at https://doi.org/10.1504/IJDATS.2014.059016
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Missing Data; QP; Quadratic Programme; Regression Analysis; Survey Research
International Standard Serial Number (ISSN)
1755-8069; 1755-8050
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Inderscience, All rights reserved.
Publication Date
01 Jan 2014
