Abstract
The subject-specific data from a longitudinal study consist of a string of numbers. These numbers represent a series of empirical measurements. Calculations are performed on these strings of numbers and causal inferences are drawn. For example, an investigator might conclude that the analysis provides strong evidence for “a direct effect of AZT on the survival of AIDS patients controlling for the intermediate variable - therapy with aerosolized pentamidine.” The nature of the relationship between the sentence expressing these causal conclusions and the computer calculations performed on the strings of numbers has been obscure. Since the computer algorithms are well-defined mathematical objects, it is important to provide formal mathematical definitions for the English sentences expressing the investigator’s causal inferences.
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Robins, J.M. (1997). Causal Inference from Complex Longitudinal Data. In: Berkane, M. (eds) Latent Variable Modeling and Applications to Causality. Lecture Notes in Statistics, vol 120. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1842-5_4
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DOI: https://doi.org/10.1007/978-1-4612-1842-5_4
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