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Maximum likelihood estimation of the log-binomial model.
Commun Stat Theory Methods 2010 Jan; 39(5):874-883
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.
Analytical-methods; Analytical-models; Mathematical-models; Models; Samplers; Sampling-methods; Author Keywords: Log-binomial model; Maximum likelihood; Parameter space
Martin R. Petersen, HGO/NIOSH, DSHEFS, 4676 Columbia Parkway, Cincinnati, OH 45226
Issue of Publication
Communications in Statistics - Theory and Methods
Page last reviewed: September 2, 2020
Content source: National Institute for Occupational Safety and Health Education and Information Division