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Bachhofer-Gupta-Sobel Memorial Symposium on
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Ajit Tamhane is Professor and
Chairman of Industrial Engineering & Management Sciences and
Professor of Statistics at Northwestern
University. He received his B.Tech. degree with honors in
Mechanical Engineering from I.I.T. Bombay, and his M.S. and Ph.D.
degrees in
Operations Research and Statistics from Cornell University.
Professor Tamhane has published about 75 papers in top statistical
journals on multiple comparisons with applications to clinical
trials, ranking and selection procedures, design of experiments
and
chemometrics. He has authored two books, edited a collection of
research papers, and is currently working on a text-book on design
of experiments to be published by Wiley. He is a fellow of the
American Statistical Association. |
Latent Class Analysis for Clustering Multivariate Correlated Bernoulli
Data
This paper gives an extension of latent class analysis for clustering
multivariate correlated Bernoulli data. Various models for such data
are compared and a choice among them is made. The EM algorithm is
employed to fit the model to the data and assign observations to the
clusters. The misclassification rate of our algorithm is compared via
simulation with that of a standard latent class analysis algorithm
which assumes independence among the Bernoulli responses. A criterion
is suggested for choosing the number of clusters. The proposed
algorithm is applied to two real data sets.
12th Annual Conference of the Forum for Interdisciplinary Mathematics (FIM XII)