I have a dataset with quarterly data, and among the individuals I am studying, there are those who experience the event of interest, or right-censored ones (i.e., those who disappear from the study after their last quarter of observation without any further data provided in the future, or live until the end of the study period by providing data until the last day of the study period). For those who experience the event, I have a record of the last quarter of observation prior to the event date (for example, individual X dies on 04/15/2010, and their last recorded observation is on 03/31/2010).

The study period starts on 03/31/2001 for all individuals and ends on 06/30/2010.

The current dataset is structured as follows:

Every row represents the reporting date of data, which is the date of each quarter (e.g., 03/31/2001, 06/30/2001, etc.).
Each column represents a time-dependent variable, recording the value of that variable for each quarter corresponding to the existence of every individual in the study period.
My question is: how can I transform this data from a longitudinal format to a counting process format?

I tried to follow the instructions in this document, but the example mentioned in the beginning assumes that the end of the study period has no record of data, which is not the case for my dataset.

Thank you in advance for your assistance.