R: Combining event tables

etRbind {RxODE} | R Documentation

## Combining event tables

### Description

Combining event tables

### Usage

    etRbind(..., samples = c("use", "clear"), waitII = c("smart", "+ii"),
      id = c("merge", "unique"))

    ## S3 method for class 'rxEt'
    rbind(..., deparse.level = 1)

### Arguments

`...` | The event tables and optionally time between event tables, called waiting times in this help document.
`samples` | How to handle samples when repeating an event table. The options are: "clear" Clear sampling records before combining the datasets "use" Use the sampling records when combining the datasets
`waitII` | This determines how waiting times between events are handled. The options are: `"smart"` This "smart" handling of waiting times is the default option. In this case, if the waiting time is above the last observed inter-dose interval in the first combined event table, then the actual time between doses is given by the wait time. If it is smaller than the last observed inter-dose interval, the time between event tables is given by the inter-dose interval + the waiting time between event tables. `"+ii"` In this case, the wait time is added to the inter-dose interval no matter the length of the wait time or inter-dose interval
`id` | This is how rbind will handle IDs. There are two different types of options: merge with `id="merge"`, the IDs are merged together, overlapping IDs would be merged into a single event table. unique with `id="unique"`, the IDs will be renumbered so that the IDs in all the event tables are not overlapping.
`deparse.level` | The `deparse.level` of a traditional `rbind` is ignored.

### Value

An event table

### Author(s)

Matthew L Fidler

Matthew L Fidler, Wenping Wang

### References

Wang W, Hallow K, James D (2015). "A Tutorial on RxODE: Simulating Differential Equation Pharmacometric Models in R." CPT: Pharmacometrics \& Systems Pharmacology, 5(1), 3-10. ISSN 2163-8306, <URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728294/>.

### See Also

`eventTable`, `add.sampling`, `add.dosing`, `et`, `etRep`, `etRbind`, `RxODE`

### Examples

    ## Model from RxODE tutorial
    mod1 <-RxODE({
        KA=2.94E-01;
        CL=1.86E+01;
        V2=4.02E+01;
        Q=1.05E+01;
        V3=2.97E+02;
        Kin=1;
        Kout=1;
        EC50=200;
        C2 = centr/V2;
        C3 = peri/V3;
        d/dt(depot) =-KA*depot;
        d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
        d/dt(peri)  =                    Q*C2 - Q*C3;
        d/dt(eff)  = Kin - Kout*(1-C2/(EC50+C2))*eff;
    });

    ## These are making the more complex regimens of the RxODE tutorial

    ## bid for 5 days
    bid <- et(timeUnits="hr") %>%
           et(amt=10000,ii=12,until=set_units(5, "days"))

    ## qd for 5 days
    qd <- et(timeUnits="hr") %>%
          et(amt=20000,ii=24,until=set_units(5, "days"))

    ## bid for 5 days followed by qd for 5 days

    et <- seq(bid,qd) %>% et(seq(0,11*24,length.out=100));

    bidQd <- rxSolve(mod1, et)

    plot(bidQd, C2)

    ## Now Infusion for 5 days followed by oral for 5 days

    ##  note you can dose to a named compartment instead of using the compartment number
    infusion <- et(timeUnits = "hr") %>%
          et(amt=10000, rate=5000, ii=24, until=set_units(5, "days"), cmt="centr")

    qd <- et(timeUnits = "hr") %>% et(amt=10000, ii=24, until=set_units(5, "days"), cmt="depot")

    et <- seq(infusion,qd)

    infusionQd <- rxSolve(mod1, et)

    plot(infusionQd, C2)

    ## 2wk-on, 1wk-off

    qd <- et(timeUnits = "hr") %>% et(amt=10000, ii=24, until=set_units(2, "weeks"), cmt="depot")

    et <- seq(qd, set_units(1,"weeks"), qd) %>%
         add.sampling(set_units(seq(0, 5.5,by=0.005),weeks))

    wkOnOff <- rxSolve(mod1, et)

    plot(wkOnOff, C2)

    ## You can also repeat the cycle easily with the rep function

    qd <-et(timeUnits = "hr") %>% et(amt=10000, ii=24, until=set_units(2, "weeks"), cmt="depot")

    et <- etRep(qd, times=4, wait=set_units(1,"weeks")) %>%
         add.sampling(set_units(seq(0, 12.5,by=0.005),weeks))

    repCycle4 <- rxSolve(mod1, et)

    plot(repCycle4, C2)

[Package RxODE version 0.9.1-8 Index]