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Bayesian Adjustment of Anticipatory Covariates in Analyzing Retrospective Data

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  • GEBRENEGUS GHILAGABER
  • JOHAN KOSKINEN

Abstract

In retrospective surveys, records on important variables such as the respondent's educational level and social class refer to what is achieved by the date of the survey. Such variables are then used as covariates in investigations of behavior such as marriage and divorce in life segments that have occurred before the survey. To what extent can any change in the behavior be attributed to the misclassification of respondents across the various levels of the anticipatory variable? To what extent do they reflect real differences in the behavior across the levels? The connection is obtained by a Bayesian adjustment, by specifying a continuous-time Markov model for the incompletely observed time-varying anticipatory covariates, and by implementing standard Bayesian data augmentation techniques. The issues are illustrated by estimating effects of educational level on risks of divorce in a multiplicative piecewise-constant hazard model. Results show that ignoring the time-inconsistency of anticipatory variables may seriously plague the analyses because the relative risks across the anticipatory educational level are overestimated.

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  • Gebrenegus Ghilagaber & Johan Koskinen, 2009. "Bayesian Adjustment of Anticipatory Covariates in Analyzing Retrospective Data," Mathematical Population Studies, Taylor & Francis Journals, vol. 16(2), pages 105-130.
    • Handle: RePEc:taf:mpopst:v:16:y:2009:i:2:p:105-130
    DOI: 10.1080/08898480902790171
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    References listed on IDEAS

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    1. Jan M. Hoem & Michaela Kreyenfeld, 2006. "Anticipatory analysis and its alternatives in life-course research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(16), pages 461-484.
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    5. Jan M. Hoem & Michaela R. Kreyenfeld, 2006. "Anticipatory analysis and its alternatives in life-course research. Part 2: Marriage and first birth," MPIDR Working Papers WP-2006-007, Max Planck Institute for Demographic Research, Rostock, Germany.
    6. Jan M. Hoem & Michaela Kreyenfeld, 2006. "Anticipatory analysis and its alternatives in life-course research," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(17), pages 485-498.
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    1. Gebrenegus Ghilagaber & Rolf Larsson, 2023. "Adjustment of Anticipatory Covariates in Retrospective Surveys: An Expected Likelihood Approach," Stats, MDPI, vol. 6(4), pages 1-19, November.
    2. Pina-Sánchez Jose & Koskinen Johan & Plewis Ian, 2019. "Adjusting for Measurement Error in Retrospectively Reported Work Histories: An Analysis Using Swedish Register Data," Journal of Official Statistics, Sciendo, vol. 35(1), pages 203-229, March.

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