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Consequences of measurement error for inference in cross-lagged panel design—the example of the reciprocal causal relationship between subjective health and socio-economic status


  • Hannes Kröger
  • Rasmus Hoffmann
  • Eduwin Pakpahan


type="main" xml:id="rssa12129-abs-0001"> We discuss the problem of random measurement error in two variables when using a cross-lagged panel design. We apply the problem to the question of the causal direction between socio-economic status and subjective health, known also as health selection versus social causation. We plot the bias of the ratio between the social causation and the health selection coefficient as a function of the degree of measurement error in subjective health and socio-economic status for different scenarios which might occur in practice. Using simulated data we give an example of a Bayesian model for the treatment of measurement error that relies on external information about the degree of measurement error.

Suggested Citation

  • Hannes Kröger & Rasmus Hoffmann & Eduwin Pakpahan, 2016. "Consequences of measurement error for inference in cross-lagged panel design—the example of the reciprocal causal relationship between subjective health and socio-economic status," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 607-628, February.
  • Handle: RePEc:bla:jorssa:v:179:y:2016:i:2:p:607-628

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