Censoring (Censored Observations)

Observations are referred to as censored when the dependent variable of interest represents the time to a terminal event, and the duration of the study is limited in time. Although the concept was developed in the biomedical research, censored observations may occur in a number of different areas of research. For example, in the social sciences we may study the "survival" of marriages, high school drop-out rates (time to drop-out), turnover in organizations, etc. In each case, by the end of the study period, some subjects probably will still be married, will not have dropped out, or will still be working at the same company; thus, those subjects represent censored observations.

In economics we may study the "survival" of new businesses or the "survival" times of products such as automobiles. In quality control research, it is common practice to study the "survival" of parts under stress (failure time analysis).

Data sets with censored observations can be analyzed via the Survival Analysis module or via the Weibull and Reliability/Failure Time Analysis options in the Process Analysis module; additional information about different types of censoring can also be found there.

See also, Type I and II Censoring, Single and Multiple Censoring and Left and Right Censoring.