Erratum to: Spatial Trends and Factors Affecting Mercury Bioaccumulation in Freshwater Fishes of Washington State, USA

Fifteen of the 36 indigenous freshwater fishes of the Cape Province are endemic to this region and a further eight are endemic to the Republic of South Africa. A third of the species are listed in the South African Red Data Book - Fishes. The distribution and conservation status of each species, excluding eels, are described. The possible effect of environmental changes, such as farming and other forms of land use, exotics, mining, industrial development, human settlement and construction of dams, are discussed and conservation measures are proposed.

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Organizational factors affecting successful physician–system integration: A qualitative study of Washington State health executives

Health Care Management Review ◽

10.1097/hmr.0000000000000238 ◽

2019 ◽

Vol 46 (1) ◽

pp. 35-43 ◽

Cited By ~ 1

Author(s):

Ann M. Nguyen ◽

Christopher E. Johnson ◽

Suzanne J. Wood ◽

William L. Dowling

Keyword(s):

Qualitative Study ◽

System Integration ◽

Organizational Factors ◽

Washington State ◽

State Health ◽

Factors Affecting

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Evaluating Median Crossover Likelihoods with Clustered Accident Counts: An Empirical Inquiry Using the Random Effects Negative Binomial Model

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1635-06 ◽

1998 ◽

Vol 1635 (1) ◽

pp. 44-48 ◽

Cited By ~ 142

Author(s):

Venkataraman N. Shankar ◽

Richard B. Albin ◽

John C. Milton ◽

Fred L. Mannering

Keyword(s):

Random Effects ◽

Negative Binomial ◽

Mathematical Formulation ◽

Washington State ◽

Cross Sectional ◽

Factors Affecting ◽

Model Transferability ◽

Temporal Effects ◽

Empirical Inquiry ◽

Key Issues

Insights into plausible methodological frameworks specifically with respect to two key issues—(1) mathematical formulation of the underlying process affecting median crossover accidents and (2) the factors affecting median crossover frequencies in Washington State—are provided in this study. Random effects negative binomial (RENB) and the cross-sectional negative binomial (NB) models are examined. The specification comparisons indicate benefits from using the RENB model only when spatial and temporal effects are totally unobserved. When spatial and temporal effects are explicitly included, the NB model is statistically adequate, while the RENB model appears to lose its distributional advantage. Such findings might be artifacts of the median crossover accident dataset used in this study. While the NB model appears to be the superior model in the present case of median crossover accidents, the marginally inferior performance of the RENB model warrants further examination through application to regular accident types in light of its flexibility to incorporate temporal and cross-sectional variations simultaneously in panel counts. From a predictive standpoint, RENB offers advantages in terms of model transferability and updating.

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