Dear all !
I'm working on historical data related to events and like to carry out a survival analysis. In the dataset there are typically some right censored data, when the individuals are still living. But there are also individuals with missing birth dates, which means that they are left censored.
While survival analysis with right or left censoring can be carried out in most professional statistic software, I found no solution to include right and left censoring in one survival analyis.
Does anyone have an idea?
Thanks
Yes, there are methods to handle both right and left censoring in survival analysis. Censoring occurs when the event of interest (e.g., death, failure) is not observed for some individuals within the study period. Right, censoring refers to cases where the event has not yet occurred by the end of the study, while left censoring occurs when the event occurred before the study started and is only known to have happened within a certain time frame.
In the presence of right and left censoring, you can use a statistical technique called interval-censored survival analysis. This approach takes into account the time intervals within which the event of interest occurred, rather than the precise event times. Interval-censored survival analysis allows for the estimation of survival probabilities and the comparison of survival curves when the event times are only known within certain intervals.
There are several methods available for interval-censored survival analysis, including:
The choice of method depends on the specific characteristics of your data and the assumptions you are willing to make. It is important to consider the underlying distribution of the event times, the nature of censoring, and the sample size.
Implementing interval-censored survival analysis typically requires specialized software or programming packages that offer appropriate functions or procedures for this type of analysis. Consult the documentation of statistical software packages such as R, SAS, or Stata, as they often provide specific functions for interval-censored survival analysis.
Remember to carefully interpret and report the results, acknowledging the presence of censoring and the methods used to handle it in your analysis.
There are certain important components to note when carrying out survival analysis. They include the starting time of the study, the ending time of the study, censoring, follow-up period, event of interest etc.
In this your study, I am sure you have specified the event of interest and I want to believe that is responsible for the right censored observations. Individuals with missing birth dates cannot be said to be left censored since missing birth dates cannot be the event of interest. There could be several events during the study period but there is need to specify only a particular event of interest before carrying out survival analysis. Also, all the individuals considered in the study must have a starting time.
Based on the explanation above, I will advise you consider the information of those individuals with missing birth dates as missing. You can delete the missing information and carry on your analysis with only the right censored data.
I hope this helps. Cheers!!!
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