Template:Right Censored: Difference between revisions
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The most common case of censoring is what is referred to as ''right censored data'', or ''suspended data''. In the case of life data, these data sets are composed of units that did not fail. For example, if we tested five units and only three had failed by the end of the test, we would have suspended data (or right censored data) for the two unfailed units. The term ''right censored'' implies that the event of interest (i.e. the time-to-failure) is to the right of our data point. In other words, if the units were to keep on operating, the failure would occur at some time after our data point (or to the right on the time scale). | The most common case of censoring is what is referred to as ''right censored data'', or ''suspended data''. In the case of life data, these data sets are composed of units that did not fail. For example, if we tested five units and only three had failed by the end of the test, we would have suspended data (or right censored data) for the two unfailed units. The term ''right censored'' implies that the event of interest (i.e. the time-to-failure) is to the right of our data point. In other words, if the units were to keep on operating, the failure would occur at some time after our data point (or to the right on the time scale). | ||
[[Image: | [[Image:right censoring.png|center|400px|Graphical representation of right censored data.]] | ||
Revision as of 15:57, 13 March 2012
Right Censored (Suspended)
The most common case of censoring is what is referred to as right censored data, or suspended data. In the case of life data, these data sets are composed of units that did not fail. For example, if we tested five units and only three had failed by the end of the test, we would have suspended data (or right censored data) for the two unfailed units. The term right censored implies that the event of interest (i.e. the time-to-failure) is to the right of our data point. In other words, if the units were to keep on operating, the failure would occur at some time after our data point (or to the right on the time scale).
