Weighting Methods for Attrition in Choice-Based Panels

  • Ram M. Pendyala
  • Ryuichi Kitamura
Part of the Transportation Research, Economics and Policy book series (TRES)


A choice-based panel sample is one in which selected sample units, chosen on the basis of endogenous variable values, are repeatedly surveyed over time. Choice-based panel samples are subject to two forms of bias. The first arises from selective attrition. The second is a result of the choice-based nature of the sampling scheme itself. This chapter discusses weighting methods for choice-based panel samples which account for both kinds of bias, and enable us to draw inferences regarding the population. Panel samples are usually replenished with refreshments to maintain the size and representativeness of the panel. This chapter discusses weighting methods for refreshment samples, and briefly reviews sampling schemes that can be used for recruitment of new panel members. We demonstrate the application of these methods through a study of mode choice behavior in the Puget Sound Transportation Panel.


Choice Behavior Mode Choice Panel Survey Initial Choice Panel Sample 
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  1. Abdel-Aty, M. (1994) A New Approach to Route Choice Data Collection: Multiphase CATI Panel Surveys Using a GIS Data Base. Mimeograph.Google Scholar
  2. Amemiya, T. (1985) Advanced Econometrics. Harvard University Press, Cambridge, Massachusetts.Google Scholar
  3. Ben-Aiuva, M. and Lerman, S.R. (1985) Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, Cambridge, Massachusetts.Google Scholar
  4. Bollen, K.A. (1989) Structural Equations with Latent Variables. John Wiley Sons, New York.Google Scholar
  5. Brownstone, D. and Chu, X. (1997) Multiply-imputed sampling weights for consistent inference with panel attrition. Chapter Ten in this volume.Google Scholar
  6. Cossletr, S.R. (1981) Maximum likelihood estimator for choice-based samples. Econometrica, 49(5), 1289 - 1316.CrossRefGoogle Scholar
  7. Dwivedi, T. and Srivastava, K. (1978) Optimality of least squares in the seemingly unrelated regressions model. Journal of Econometrics, 7, 391 - 395.CrossRefGoogle Scholar
  8. Greene, W.H. (1990) Econometric Analysis. Macmillan Publishing Co., New York.Google Scholar
  9. Greene, W.H. (1990a) LIMDEP Version 5. 1. Econometric Software Inc., New York.Google Scholar
  10. Heckman, J. (1976) The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement, 5, 475 - 492.Google Scholar
  11. Hensher, D.A. (1989) An assessment of attrition in a multi-wave panel of households. In J. Hauer, et al. (eds.) Urban Dynamics and Spatial Choice Behavior. Kluwer Publishing, Dordrecht, 105 - 124.CrossRefGoogle Scholar
  12. Imbens, G. (1992) An efficient method of moments estimator for discrete choice models with choice-based sampling. Econometrica, 60(5), 1187 - 1214.CrossRefGoogle Scholar
  13. Krramura, R. (1990) Panel analysis in transportation planning: An overview. Transportation Research, 24A, 401 - 415.CrossRefGoogle Scholar
  14. Krramura, R. and Bovy, P.H.L. (1987) Analysis of attrition biases and trip reporting errors for panel data. Transportation Research, 21A, 287 - 302.Google Scholar
  15. Krramura, R. and Bunch, D.S. (1990) Heterogeneity and state dependence in household car ownership: A panel analysis using ordered-response probit models with error components. In M. Koshi (ed.) Transportation and Traffic Theory. Elsevier Science Publishers B.V., North Holland, 477 - 496.Google Scholar
  16. Krramura, R Pendyata, R.M. and Goudas, K.G. (1993) Weighting methods for choice-based panels with correlated attrition and initial choice. In C.F. Daganzo (ed.) Transportation and Traffic Theory. Elsevier Science Publishers B.V., North Holland, 275 - 294.Google Scholar
  17. Lancaster, T. and Imbens, G. (1990) Choice-based sampling of dynamic populations. In J. Hartog, G. Ridder, and J. Theeuwes (eds.) Panel Data and Labor Market Studies. Elsevier Science Publishers B.V., North Holland, 21 - 43.Google Scholar
  18. Maddai A., G.S. (1983) Limited Dependent and Qualitative Variables in Econometrics. Cambridge University Press. Cambridge, Massachusetts.Google Scholar
  19. Manskq, C.F. and Lerman, S.R. (1977) The estimation of choice probabilities from choice based samples. Econometrica, 45(8), 1977 - 1988.CrossRefGoogle Scholar
  20. Manski, C.F. and Mcfadden, D. (1981) Alternative estimators and sample designs for discrete choice analysis. In C.F. Manski and D.McFadden (eds.) Structural Analysis of Discrete Data. MIT Press, Cambridge, Massachusetts, 2 - 50.Google Scholar
  21. Murawwu, E. and Warrerson, W.T. (1990) Developing a household travel panel survey for the Puget Sound Region. Transportation Research Record, 1285, 40 - 46.Google Scholar
  22. Murakaml, E. and Watterson, W.T. (1992) The Puget Sound Transportation Panel after two waves. Transportation, 19(2), 141 - 158.CrossRefGoogle Scholar
  23. Nelson, F.D. (1984) Efficiency of the two-step estimator for models with endogenous sample selection. Journal of Econometrics, 24, 181 - 196.CrossRefGoogle Scholar
  24. Permyal A., R.M., Gouuas, K.G., Krramura, R. and Murakami, E. (1992) Development of weights for a choice-based panel sample with attrition. Transportation Research, 27A(6), 477 - 492.Google Scholar
  25. Bidder, G. (1990) Attrition in multi-wave panel data. In J. Hartog, et al. (eds.) Panel Data and Labor Market Studies. North Holland, Amsterdam, 45 - 69.Google Scholar
  26. Thtu, J.C. and Horowrrz, J.L. (1991) Estimating a destination choice model from a choice-based sample with limited information. Geographical Analysis, 23(4), 298 - 315.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Ram M. Pendyala
    • 1
  • Ryuichi Kitamura
    • 2
  1. 1.Department of Civil Engineering & MechanicsUniversity of South FloridaTampaUSA
  2. 2.Department of Transportation EngineeringKyoto UniversitySakyo-ku, Kyoto 606Japan

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