Categorical missing data imputation for software cost estimation by multinomial logistic regression

Journal of Systems and Software

Volumn 79, Issue 3, 2006, Pages 404-414

  Sentas, Panagiotis ^a   Angelis, Lefteris ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Cost estimation; Imputation; Missing data; Multinomial logistic regression; Software effort prediction

Indexed keywords

COSTS; DATABASE SYSTEMS; ESTIMATION; LOGISTICS; MATHEMATICAL MODELS; REGRESSION ANALYSIS;

COST ESTIMATION; IMPUTATION; MISSING DATA; MULTINOMIAL LOGISTIC REGRESSION; SOFTWARE EFFORT PREDICTION;

DATA REDUCTION;

EID: 33644682829     PISSN: 01641212     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jss.2005.02.026     Document Type: Article

References (19)

1. A.A. Afifi, and R.M. Elashoff Missing observations in multivariate statistics: review of the literature J. Am. Statist. Assoc. 61 1966 595 604
2. Angelis, L., Stamelos, I., Morisio, M., 2001. Building a software cost estimation model based on categorical data. In: Proceedings of the 7th IEEE International Software Metrics Symposium, pp. 4-15.
3. L. Briand, V. Basili, and W. Thomas A pattern recognition approach for software engineering data analysis IEEE Trans. Software Eng. 18 11 1992 931 942
4. Cartwright, M.H., Shepperd, M.J., Song, Q., 2003. Dealing with missing software project data. In: Proc. METRICS, pp. 154-165.
5. A.P. Dempster, N.M. Laird, and D.B. Rubin Maximum likelihood from incomplete data via the EM algorithm (with discussion) J. Roy. Statist. Soc. B 39 1977 1 38
6. K.E. Emam, and A. Birk Validating the ISO/IEC 15504 measure of software requirements analysis process capability IEEE Trans. Software Eng. 26 6 2000 541 566
7. T. Foss, E. Stensurd, B. Kitchenham, and I. Myrtveit A simulation study of the model evaluation criterion MMRE IEEE Trans. Software Eng. 29 11 2003 985 995
8. H.O. Hartley, and R.R. Hocking The analysis of incomplete data Biometrics 27 1971 783 808
9. D.W. Hosmer, and S. Lemeshow Applied logistic regression 1989 Wiley New York
10. ISBSG Data Disk, Release 7, June 2001.
11. R. Jeffery, M. Ruhe, and I. Wieczorek A comparative study of two software development cost modelling techniques using multi-organizational and company-specific data Inform. Software Technol. 42 2000 1009 1016
12. R.J.A. Little, and D.B. Rubin Incomplete data Encycl. Statist. Sci. 4 1983 46 53
13. R.J.A. Little, and D.B. Rubin Statistical analysis with missing data second ed. 2002 Wiley New York
14. K. Maxwell Applied statistics for software managers 2002 Prentice-Hall New Jersey
15. I. Myrtveit, E. Stensrud, and U. Olsson Analyzing data sets with missing data: an empirical evaluation of imputation methods and likelihood-based methods IEEE Trans. Software Eng. 27 11 2001 999 1013
16. P. Sentas, L. Angelis, I. Stamelos, and G. Bleris Software productivity and effort prediction with ordinal regression Inform. Software Technol. 47 1 2005 17 29
17. M.J. Shepperd, and C. Schofield Estimating software project effort using analogies IEEE Trans. Software Eng. 23 1997 736 743
18. Song, Q., Shepperd, M., 2003. A short note on safest default missingness mechanism assumptions, ESERG Technical Report TR02-07, Bournemouth University. Available from: 〈 dec.Bournemouth.ac.uk/ESERG/TechnicalReports.html 〉.
19. K. Strike, K.E. Emam, and N. Madhavji Software cost estimation with incomplete data IEEE Trans. Software Eng. 27 10 2001 890 908