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Example input data sets

Usage

data(exidata)

data(extran1)

data(extran2)

data(extran3)

data(exTheoph)

data(exBoot)

Details

  • exidata holds individual-level parameters and other data items, one per row

  • extran1 is a "condensed" data set

  • extran2 is a full dataset

  • extran3 is a full dataset with parameters

  • exTheoph is the theophylline data set, ready for input into mrgsolve

  • exBoot a set of bootstrap parameter estimates

Examples


mod <- mrgsolve::house() %>% update(end=240) %>% Req(CP)

## Full data set
data(exTheoph)
out <- mod %>% data_set(exTheoph) %>% mrgsim
out
#> Model:  housemodel 
#> Dim:    132 x 3 
#> Time:   0 to 24.65 
#> ID:     12 
#>     ID time      CP
#> 1:   1 0.00 0.00000
#> 2:   1 0.25 0.04552
#> 3:   1 0.57 0.08624
#> 4:   1 1.12 0.12643
#> 5:   1 2.02 0.15072
#> 6:   1 3.82 0.15121
#> 7:   1 5.10 0.14348
#> 8:   1 7.03 0.13101
plot(out)


## Condensed: mrgsolve fills in the observations
data(extran1)
out <- mod %>% data_set(extran1) %>% mrgsim
out
#> Model:  housemodel 
#> Dim:    4814 x 3 
#> Time:   0 to 240 
#> ID:     5 
#>     ID time    CP
#> 1:   1 0.00  0.00
#> 2:   1 0.00  0.00
#> 3:   1 0.25 12.87
#> 4:   1 0.50 22.25
#> 5:   1 0.75 29.04
#> 6:   1 1.00 33.91
#> 7:   1 1.25 37.37
#> 8:   1 1.50 39.78
plot(out)


## Add a parameter to the data set
stopifnot(require(dplyr))
#> Loading required package: dplyr
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
data <- extran1 %>% distinct(ID) %>% select(ID) %>%
  mutate(CL=exp(log(1.5) + rnorm(nrow(.), 0,sqrt(0.1)))) %>%
  left_join(extran1,.)
#> Joining, by = "ID"
  
data
#>   ID  amt cmt time addl ii rate evid       CL
#> 1  1 1000   1    0    3 24    0    1 1.240031
#> 2  2 1000   2    0    0  0   20    1 1.139219
#> 3  3 1000   1    0    0  0    0    1 2.040717
#> 4  3  500   1   24    0  0    0    1 2.040717
#> 5  3  500   1   48    0  0    0    1 2.040717
#> 6  3 1000   1   72    0  0    0    1 2.040717
#> 7  4 2000   2    0    2 48  100    1 1.464033
#> 8  5 1000   1    0    0  0    0    1 1.388181
#> 9  5 5000   1   24    0  0   60    1 1.388181

out <- mod %>% data_set(data) %>% carry_out(CL) %>%  mrgsim
out
#> Model:  housemodel 
#> Dim:    4814 x 4 
#> Time:   0 to 240 
#> ID:     5 
#>     ID time   CL    CP
#> 1:   1 0.00 1.24  0.00
#> 2:   1 0.00 1.24  0.00
#> 3:   1 0.25 1.24 12.85
#> 4:   1 0.50 1.24 22.18
#> 5:   1 0.75 1.24 28.89
#> 6:   1 1.00 1.24 33.67
#> 7:   1 1.25 1.24 37.03
#> 8:   1 1.50 1.24 39.33
plot(out)


## idata
data(exidata)
out <- mod %>% idata_set(exidata) %>% ev(amt=100,ii=24,addl=10) %>% mrgsim
plot(out, CP~time|ID)