NDLI: An evaluation of k-nearest neighbour imputation using Likert data

Content Provider	IEEE Xplore Digital Library
Author	Jonsson, P. Wohlin, C.
Copyright Year	2004
Description	Author affiliation: Sch. of Eng., Blekinge Inst. of Technol., Ronneby, Sweden (Jonsson, P.; Wohlin, C.)
Abstract	Studies in many different fields of research suffer from the problem of missing data. With missing data, statistical tests will lose power, results may be biased, or analysis may not be feasible at all. There are several ways to handle the problem, for example through imputation. With imputation, missing values are replaced with estimated values according to an imputation method or model. In the k-nearest neighbour (k-NN) method, a case is imputed using values from the k most similar cases. In this paper, we present an evaluation of the k-NN method using Likert data in a software engineering context. We simulate the method with different values of k and for different percentages of missing data. Our findings indicate that it is feasible to use the k-NN method with Likert data. We suggest that a suitable value of k is approximately the square root of the number of complete cases. We also show that by relaxing the method rules with respect to selecting neighbours, the ability of the method remains high for large amounts of missing data without affecting the quality of the imputation.
Sponsorship	IEEE Comput. Soc. Tech. Council on Software Eng. (TCSE)
Starting Page	108
Ending Page	118
File Size	335509
Page Count	11
File Format	PDF
ISBN	0769521290
ISSN	15301435
DOI	10.1109/METRIC.2004.1357895
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Software engineering Testing Data engineering Power engineering and energy Artificial intelligence Machine learning Psychology Data analysis Performance evaluation Software architecture
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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