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Journal of Transportation and Statistics Volume 9 Number 1

Journal of Transportation and Statistics - Volume 9, Number 1

Journal of Transportation and Statistics
Volume 9 Number 1

2006
ISSN 1094-8848

NOTE: The views presented in the articles in this journal are those of the authors and not necessarily the views of the Bureau of Transportation Statistics. All material contained in this journal is in the public domain and may be used and reprinted without special permission; citation as to sources is required.

Table of Contents File Formats
Entire Report
Editorial Board
Contributors
Front Matter
Letter from the Editor-in-Chief
Paper 1 - Impacts of Productivity Changes in Air Transportation on Profits, Prices, and Labor Compensation: 1990-2001 by Anthony D. Apostolides
Table 1 - Growth Rates of Labor Productivity in Transportation
Table 2 - Productivity and Profits in Air Transportation
Table 3 - Productivity and Prices in Air Transportation
Table 4 - Labor Compensation per Employee
Figure 1 - Labor Productivity in Air Transportation
Figure 2 - Labor Productivity in Transportation and the U.S. Business Sector
Figure 3 - Multifactor Productivity in Air Transportation and U.S. Business Sector
Appendix 1 - Growth of Multifactor Productivity in Air Transportation
Appendix 2 - Spearman Rank Correlation Coefficients
Appendix 3 - Prices in Air Transportation
Appendix 4
Appendix 5
Paper 2 - Speed as a Risk Factor in Serious Run-off-Road Crashes: Bayesian Case-Control Analysis with Case Speed Uncertainty by Gary A. Davis, Sujay Davuluri, and Jianping Pei
Table 1 - Posterior Means and Standard Deviations for the Speeds of the Case Vehicles, and the Measured Speeds for the Control Vehicles, for 10 Road Accident Research Unit Run-off Road Crashes
Table 2 - Posterior Means and Standard Deviations for the Speeds of the Case Vehicles, and Measured Speeds of the Control Vehicles, for 10 Minnesota Run-off Road Crashes
Table 3 - Bayesian Parameter Estimates and Goodness of Fit Measures for the Linear and Constrained Quadratic Models Applied to the Minnesota Data
Table 4 - Bayesian Parameter Estimates and Goodness of Fit Measures for Linear and Quadratic Models Applied to the RARU Data
Figure 1 - Contour Plot of Log Likelihood Function of Quadratic Model Fit to the Minnesota Data
Figure 2 - Matched Case Control Log Likelihood as a Function of b1 for Linear Model Fit to Road Accident Research Unit Data
Paper 3 - Speed Estimation for Air Quality Analysis by Huafeng Gong, Mei Chen, Jesse Mayes, and Rob Bostrom
Table 1 - Sample Data Summary
Table 2 - Speed Comparison Based on the 1997 Speed Study
Table 3 - Speed Comparison Based on the 2004 Christian Country Survey
Table 4 - Christian Country Speeds Comparison
Table 5 - Speed Comparison with Changes in Traffic Control Devices
Table 6 - Statewide Average Speeds by Area Type and Functional Class
Figure 1 - Estimating Average Effective Speed
Paper 4 - Measurement Errors in Poisson Regressions: A Simulation Study Based on Travel Frequency Data by Erling Häggström Lundevaller
Table 1 - Maximum Likelihood Estimates of the Model Assuming No Random Effects
Table 2 - The Bias Measure when Measurement Errors Exist in the Petrol Price Index
Table 3 - The Bias Measure when Measurement Error Exists in the Income Variable
Table 4 - Percentage of Rejected Replications with Different Levels of Effects and Measurement Error
Table 5 - Percentage of Rejected under Negatively Correlated Individual Effects and Different Levels of Individual Effects and Measurement Errors
Paper 5 - Measuring Variability in Urban Traffic Flow by Use of Principal Component Analysis by Theodore Tsekeris and Antony Stathopoulos
Table 1 - Values of MRE Resulting from the Reconstruction of a Typical Traffic Flow
Figure 1 - Illustration of the Greater Athens Area (GAA) Network and Configuration of the Location of Loop Detectors
Figure 2 - Graphical Representation of an Eigenflow and its Corresponding Principal Axis
Figure 3 - Number of Significant Eigenflows, in Terms of the Cumulative Density Function (CDF) of the Number of Entries in Each Row of the Principal Matrix that Exceed the Threshold and Histogram of Significant Eigenflows
Figure 4 - The Number of Significant Eigenflows with Respect to the Monthly Average Daily Traffic Flow Rate
Figure 5 - Plot of Singular Values for Traffic Flows and Normalized Traffic Flows
Figure 6 - Reconstruction of a Typical Traffic Flow Using 5 Principal Components and Statistical Analysis of the Reconstructed Traffic Flow
Figure 7 - Decomposition of a Typical Eigenflow by Use of Temporal Trend Thresholding and t-test Statistical Analysis of Structural Breaks and Outliers
Paper 6 - Frequency and Severity of Belgian Road Traffic Accidents Studied by State-Space Methods by Elke Hermans, Geert Wets, and Filip van den Bossche
Table 1 - Dependent and Independent Variables
Table 2 - Overview of the Significant Explanatory and Correction Variables for Each Dependent Variable
Figure 1 - Actual Monthly Accident and Casualty Observations: 1974-1999
Figure 2 - Residuals of the Model with Stochastic Trend, Deterministic Seasonal, and Explanatory Variables for the Four Dependent Variables
Figure 3 - Monthly Two-Year Ahead Predictions for the Four Dependent Variables
Reviewers for 2006
Index to Volume 9
Back Cover
Updated: Saturday, May 20, 2017