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http://hdl.handle.net/1942/338
Title: | Obtaining the maximum likelihood estimates in incomplete R x C contingency tables using a Poisson generalized linear model | Authors: | Lipsitz, Stuart R. Parzen, Michael MOLENBERGHS, Geert |
Issue Date: | 1998 | Source: | Journal of Computational and Graphical Statistics, 7(3). p. 356-376 | Abstract: | This article describes estimation of the cell probabilities in an R x C contingency table with ignorable missing data. Popular methods for maximizing the incomplete data likelihood are the EM-algorithm and the Newton--Raphson algorithm. Both of these methods require some modification of existing statistical software to get the MLEs of the cell probabilities as well as the variance estimates. We make the connection between the multinomial and Poisson likelihoods to show that the MLEs can be obtained in any generalized linear models program without additional programming or iteration loops. | Keywords: | EM-algorithm; ignorable missing data; Newton-Raphson algorithm; offset | Document URI: | http://hdl.handle.net/1942/338 | DOI: | 10.2307/1390709 | ISI #: | 000076008800007 | Rights: | (c) 1998 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America | Type: | Journal Contribution | Validations: | ecoom 1999 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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lipsitz.pdf | Published version | 99.06 kB | Adobe PDF | View/Open |
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