Maximum Likelihood Estimation of the Log-Binomial Model

Details

• Personal Author:
  Deddens JA ; Petersen, Martin R.
• Description:
  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. [Description provided by NIOSH]
• Subjects:
  Occupational Health Safety
• Keywords:
  Analytical-methods Analytical-models Author Keywords: Log-binomial Model Mathematical-models Maximum Likelihood Models Parameter Space Samplers Sampling-methods
• ISSN:
  0361-0926
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Ohio ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DSHEFS - Division of Surveillance, Hazard Evaluations, and Field Studies
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  39
• Issue:
  5
• NIOSHTIC Number:
  nn:20036545
• Citation:
  Commun Stat Theory Methods 2010 Jan; 39(5):874-883
• Contact Point Address:
  Martin R. Petersen, HGO/NIOSH, DSHEFS, 4676 Columbia Parkway, Cincinnati, OH 45226
• Email:
  mrp1@one.net
• Federal Fiscal Year:
  2010
• NORA Priority Area:
  Mining ; Manufacturing
• Peer Reviewed:
  True
• Source Full Name:
  Communications in Statistics - Theory and Methods
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:a5578969995eeb40051e41286ab64ec1e9dbc4f44cc581eb8f31984d70e9d275a9cafbf00ca0533ff75e9d3f2c6cde6df490c506f412fd33899b7cabe4118aa7
• Download URL:
  https://stacks.cdc.gov/view/cdc/187918/cdc_187918_DS1.pdf
• File Type:
  [PDF - 91.82 KB ]