Effects of Omitting a Covariate in Poisson Models When the Data Are Balanced

Details

• Personal Author:
  Deddens JA ; Petersen, Martin R.
• Description:
  The authors show that for balanced data, the estimate of effects of interest and of their standard errors are unaffected when a covariate is removed from a multiplicative Poisson model. As they point out, this is not verified in the analogous linear model, nor in the logistic model. In the first case, only the estimated coefficients remain the same, while in the second case, both the estimated effects and their standard errors can change. [Description provided by NIOSH]
• Subjects:
  Coal Coal Mining Engineering Geology Mining Occupational Health Safety
• Keywords:
  Analytical Processes Author Keywords: Generalized Linear Model Maximum-likelihood Estimation Models Poisson Model Statistical Analysis
• ISSN:
  0319-5724
• 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:
  28
• Issue:
  2
• NIOSHTIC Number:
  nn:20020779
• Citation:
  Can J Stat 2000 Apr-Jun; 28(2):439-445
• Federal Fiscal Year:
  2000
• Peer Reviewed:
  True
• Source Full Name:
  The Canadian Journal of Statistics
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:cee40ab9dd832e574c377c27a173e609fd24508b78eb25f17b54308f8a23f56de463e3db8a2df3edc4cc778fe56481a77b35bffaeed1445395c3b4b2d9c64747
• Download URL:
  https://stacks.cdc.gov/view/cdc/198445/cdc_198445_DS1.pdf
• File Type:
  [PDF - 315.16 KB ]