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Logistic Regression Models for Binary Panel Data with Attrition

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  • Garrett M. Fitzmaurice
  • Anthony F. Heath
  • Peter Clifford

Abstract

We discuss ways of analysing panel data when the response is binary and there is attrition or drop‐out. In general, informative or non‐ignorable drop‐out models are non‐identifiable and arbitrary constraints on the drop‐out model must be imposed before carrying out a statistical analysis. The problem is particularly acute when predictors as well as response variables are lost by attrition. We describe a likelihood‐based method for dealing with the drop‐out process in this difficult case and show how the effect of non‐identifiability can be reduced by importing additional data from a cross‐sectional survey of the same population. The methods are primarily motivated by data from the 1987–92 British Election Panel Study and the 1992 British Election Study.

Suggested Citation

  • Garrett M. Fitzmaurice & Anthony F. Heath & Peter Clifford, 1996. "Logistic Regression Models for Binary Panel Data with Attrition," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 249-263, March.
    • Handle: RePEc:bla:jorssa:v:159:y:1996:i:2:p:249-263
    DOI: 10.2307/2983172
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    Cited by:

    1. Andrew M. Jones & Xander Koolman & Nigel Rice, 2006. "Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 543-569, July.
    2. Jolene Birmingham & Garrett M. Fitzmaurice, 2002. "A Pattern-Mixture Model for Longitudinal Binary Responses with Nonignorable Nonresponse," Biometrics, The International Biometric Society, vol. 58(4), pages 989-996, December.
    3. Janet Tsin-Yee Leung, 2021. "Overparenting, Parent-Child Conflict and Anxiety among Chinese Adolescents: A Cross-Lagged Panel Study," IJERPH, MDPI, vol. 18(22), pages 1-14, November.

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