IQReventTable objects represent event tables that can be passed to simulation functions (such as sim_IQRmodel). Essentially, they are data frames with a define set of columns and certain requirements. These columns code for doses and/or regression parameters.
IQReventTable( data, regression = NULL, abs0inputs = NULL, abs0Tk0param = NULL, FLAGfixDoseOverlap = FALSE )
data.frame with the following columns: ID, TIME, ADM, AMT, TINF or RATE, ADDL and II, additional regression parameter columns defined by the user. ADDL and II will be handled by expansion. RATE can be present if TINF is not present. If neither RATE nor TINF is present, TINF=0 will be assumed. TIME is the only required column. ADM and AMT will be set to NA is not provided.
Vector with names of regression parameters (need to be present as columns in "data")
numeric vector with numbers of inputs (ADM) that are of type ABSORPTION0. If this argument is set also abs0Tk0param needs to be defined
character vector with names of regression parameters that should be used as 0-order infusion time (by updating TINF). The regression parameters for these values are kept in the event table. Ordering has to be as in abs0inputs
If TRUE then ensure non-overlapping dosing intervals if these occur by re-defining the dosing events. If FALSE (default) in case of overlapping dose intervals, error is issued.
An IQReventTable object with the following columns: ID, TIME, ADM, AMT, TINF (+ all defined regression parameters). The IQReventTable will be sorted by ID, TIME, ADM
Event tables are essentially data frames with the following minimum set of columns: ID, TIME, ADM, AMT, TINF. ID codes the unique subject ID and is present even if only a single subject is simulated. TIME is the time of dosing, ADM is the number of the dosing (INPUT"number"), AMT is the amount of dosing, and TINF is the dose administration time. Note that TINF=0 will be exchanged to TINF=0.0001. Additional columns can be present in event tables and from these regression parameters can be selected. Matching with model parameters will be done by name of parameter and regression parameter column, which need to be identical (case-sensitive).