Comparison of algorithms for replacing missing data in discriminant analysis
- 1 January 1992
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 21 (6) , 1567-1578
- https://doi.org/10.1080/03610929208830864
Abstract
We examined the impact of different methods for replacing missing data in discriminant analyses conducted on randomly generated samples from multivariate normal and non-normal distributions. The probabilities of correct classification were obtained for these discriminant analyses before and after randomly deleting data as well as after deleted data were replaced using: (1) variable means, (2) principal component projections, and (3) the EM algorithm. Populations compared were: (1) multivariate normal with covariance matrices ∑1=∑2, (2) multivariate normal with ∑1≠∑2 and (3) multivariate non-normal with ∑1=∑2. Differences in the probabilities of correct classification were most evident for populations with small Mahalanobis distances or high proportions of missing data. The three replacement methods performed similarly but all were better than non - replacement.Keywords
This publication has 10 references indexed in Scilit:
- On the Convergence Properties of the EM AlgorithmThe Annals of Statistics, 1983
- Maximum Likelihood from Incomplete Data Via the EM AlgorithmJournal of the Royal Statistical Society Series B: Statistical Methodology, 1977
- Alternative Approaches to Missing Values in Discriminant AnalysisJournal of the American Statistical Association, 1976
- The Treatment of Missing Values in Discriminant Analysis-1. The Sampling ExperimentJournal of the American Statistical Association, 1972
- The Effect of Unequal Variance-Covariance Matrices on Fisher's Linear Discriminant FunctionPublished by JSTOR ,1969
- On Expected Probabilities of Misclassification in Discriminant Analysis, Necessary Sample Size, and a Relation with the Multiple Correlation CoefficientPublished by JSTOR ,1968
- Estimation of Error Rates in Discriminant AnalysisTechnometrics, 1968
- The Robustness of Hotelling's T 2Journal of the American Statistical Association, 1967
- Probabilities of Correct Classification in Discriminant AnalysisPublished by JSTOR ,1966
- THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMSAnnals of Eugenics, 1936