Estimating the Same Quantities from Different Levels of Data: Time Dependence and Aggregation Bias in Event Process Models (1997)
| Citations: | 3 - 0 self |
BibTeX
@MISC{Alt97estimatingthe,
author = {James E. Alt and Gary King and Curtis S. Signorino},
title = {Estimating the Same Quantities from Different Levels of Data: Time Dependence and Aggregation Bias in Event Process Models},
year = {1997}
}
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Abstract
Binary, count, and duration data all code for discrete events occurring at points in time. Although a single data generation process can produce any of these three data types, the statistical literature is not very helpful in providing methods to estimate parameters of the same process from each. In fact, only a single theoretical process exists for which known statistical methods can estimate the same parameters --- and it is generally limited to count and duration data. The result is that seemingly trivial decisions about which level of data to use can have important consequences for substantive interpretations. We describe the theoretical event process for which results exist, based on time-independence. We also derive a new set of models for a time-dependent process and compare their predictions to those of a commonly used model. Any hope of avoiding the more serious problems of aggregation bias in events data is contingent on first deriving a much wider arsenal of statistical mode...
