Censored and Truncated Data

Frederick J. Boehmke

Both censored and truncated data involve a lack of information about a random variable and occur in the context of quantitative analysis of data, when one is using that variable either to estimate a population mean (or other population parameters) or as the dependent variable in a regression analysis. The key distinction between them is whether one has information about missing values. With censored data, one observes some information about the missing data, either in the form of a range of values that they might fall into or in the form of the knowledge that they are missing. With truncated data, one has no information about the existence or value of missing observations. The difference in the structure of information for two types of data determines how one approaches censored or truncated data, whether in the context of a single random variable or as a dependent variable in a regression ...

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