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Maximum likelihood estimation of the log-binomial model.

Authors
Petersen-MR; Deddens-JA
Source
Commun Stat Theory Methods 2010 Jan; 39(5):874-883
NIOSHTIC No.
20036545
Abstract
Maximum likelihood estimation of prevalence ratios using the log-binomial model is problematic when the estimates are on the boundary of the parameter space. When the model is correct, maximum likelihood is often the method of choice. The authors provide a theorem, formulas, and methodology for obtaining maximum likelihood estimators of the log-binomial model and their estimated standard errors when the solution is on the boundary of the parameter space. Examples are given to illustrate the method.
Keywords
Analytical-methods; Analytical-models; Mathematical-models; Models; Samplers; Sampling-methods; Author Keywords: Log-binomial model; Maximum likelihood; Parameter space
Contact
Martin R. Petersen, HGO/NIOSH, DSHEFS, 4676 Columbia Parkway, Cincinnati, OH 45226
CODEN
CSTMDC
Publication Date
20100101
Document Type
Journal Article
Email Address
mrp1@one.net
Fiscal Year
2010
NTIS Accession No.
NTIS Price
Issue of Publication
5
ISSN
0361-0926
NIOSH Division
DSHEFS
Priority Area
Mining; Manufacturing
Source Name
Communications in Statistics - Theory and Methods
State
OH
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